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Author SHA1 Message Date
Variet Agent
ed3bed2bf1 docs: 기록 2026-03-27 ECOS 데이터 정합성 검증 devlog 및 known-issues 추가 2026-03-27 22:39:19 +09:00
CD
1ce0dbebdc docs: update devlog commit hash 2026-03-26 21:32:26 +09:00
CD
acb232fff4 feat(scenarios): scenario weight empirical analysis script + env update lifetimePD 2026-03-26 21:31:04 +09:00
Variet Agent
d1ddf06e5d feat(model): KAP YTM PD floor integration, expanded 226-var search, ADF fix (AIC->BIC), Model#2 with 6-test diagnostics 
- Replace hardcoded DEFAULT_PD_FLOORS with build_complete_pd_floor_table() (KAP bond YTM)
- Fix ADF test: autolag='AIC' -> 'BIC' for small sample (N=26) robustness
- Expand variable search: 40 -> 226 vars (log/diff/return/lag2), 1.9M combos
- Select Model #2: HOUSING_PRICE + CREDIT_SPREAD_LAG1 + CURRENT_ACCOUNT_R
- Add 6-test diagnostics table to AR1 sheet (ADF/LB/DW/BP/ARCH/Shapiro)
- Add Korean variable names for transformed variables
- Generate report v7 with full diagnostics
 2026-03-12 00:06:23 +09:00
Variet Agent
87725b7c19 feat: 3-variable macro model (USDKRW+RETAIL_SALES+INVEST_RATE), forced_vars support, methodology sync 2026-03-11 17:30:06 +09:00
Variet Agent
f35ab389d5 feat(data): add 6 new ECOS variables (건설투자/총고정자본형성/총저축률/국내총투자율/수출입GNI/제조업가동률) to 37-variable pool 2026-03-11 17:13:21 +09:00
Variet Agent
2406dac6a2 docs: session close - devlog update, Phase 3-6 complete 2026-03-11 16:25:58 +09:00
Variet Agent
8a0d6e7574 docs: update methodology with KAP-based PD floor values and WR->D correction logic 2026-03-11 16:22:08 +09:00
Variet Agent
a4c9a702ad feat(pipeline): wire 7x7 Zt + 8x8 CCC expansion into main.py lifetime PD 2026-03-11 16:19:58 +09:00
Variet Agent
a406d98226 feat(data): add CCC interpolator module (7x7 -> 8x8 expansion) 2026-03-11 16:07:30 +09:00
Variet Agent
2b94cc802d feat(pipeline): update transition_matrices and config for 7x7 Zt estimation 2026-03-11 16:00:07 +09:00
Variet Agent
b8514c1251 feat(data): implement market-implied PD floor and 7x7 transition matrix parsing #task-290 2026-03-11 15:53:38 +09:00
258 changed files with 4147 additions and 1328 deletions
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4
.agents/AGENT.md
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@@ -49,8 +49,8 @@ description: 모든 작업에 자동 적용되는 에이전트 행동 규칙.
## Python Environment
- **경로**: `C:\ProgramData\miniforge3\envs\quant`
- **실행**: `C:\ProgramData\miniforge3\envs\quant\python.exe`
- **경로**: `C:\ProgramData\miniforge3\envs\lifetimePD`
- **실행**: `C:\ProgramData\miniforge3\envs\lifetimePD\python.exe`
- 모든 Python 스크립트 실행 시 위 경로의 python을 사용합니다.
## PowerShell Notes

6
.agents/references/architecture.md
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@@ -76,6 +76,6 @@ C:\ProgramData\miniforge3\envs\quant\python.exe main.py --estimate-rho
## 미완료 사항 (다음 작업자 참고)
1. **#290 실제 3사 전이행렬 CSV 변환** — `doc/`의 PDF에서 전이행렬을 추출하여 `data/raw/` CSV로 변환 필요. 현재는 builtin synthetic 데이터 사용 중
2. **#293 거시 시나리오 고도화** — IMF WEO/KDI 전망치를 직접 입력하여 시나리오 정밀화
3. **GDP 성장률 코드** — 현재 `902Y015/KOR` (국제 비교 통계) 사용. 한은 국민계정 직접 통계표코드 발견 시 교체 권장
1. **#293 거시 시나리오 고도화** — IMF WEO/KDI 전망치를 직접 입력하여 시나리오 정밀화
2. **GDP 성장률 코드** — 현재 `902Y015/KOR` (국제 비교 통계) 사용. 한은 국민계정 직접 통계표코드 발견 시 교체 권장
3. **전처리 파이프라인 개선** — PD 플로어 적용, CCC B↔D 보간 방식 개선 (docs/methodology.md §2.0 참조)

23
.agents/references/known-issues.md
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@@ -69,3 +69,26 @@
- **원인**: 한국 경제 특수성(유가의존, 수출주도, 부동산 영향 등) 미반영
- **해결**: 31개 변수로 확장 (KOSPI, OIL_PRICE, USDKRW, DISHONOR_RATE, HOUSING_PRICE, BSI_MANUF 등). `data/ecos_fetcher.py` + `data/cache/macro_ecos.csv` 캐싱 구조
- **주의**: fallback 데이터는 대략적 수치. 정밀 분석 시 ECOS API 실제 호출 필요 (`--force` 옵션)
### [2026-03-11] Windows Python — 소스 코드 특수문자 SyntaxError
- **증상**: 파이썬 코드 내 문자열(예: docstring)에 `×` (U+00D7), `→` (U+2192) 등 특수문자나 한글 이외의 유니코드가 포함될 때, Windows CP949 환경에서 `SyntaxError: invalid character` 또는 `unterminated triple-quoted string literal` 로 파싱 오류가 발생함.
- **원인**: Windows Python 3.12 런타임이 파일 맨 앞 `# -*- coding: utf-8 -*-` 이나 `-X utf8` 런타임 플래그도 소스 구문 분석 레벨에서 완벽하게 해석해내지 못하는 Windows 인코딩 고질병 문제 발생.
- **해결**: 소스 코드 내에선 (특히 docstring 등 Python 인터프리터가 읽을 영역에서는) `×` 대신 `x` 또는 `by`를 사용하고, `→` 대신 `->` 로 ASCII 코드로 치환하여 작성함 (정규식 치환 등 활용). 한글 자체는 정상적으로 파싱됨.
- **주의**: 모델링, 모듈 코드 작성 시 문자열이나 주석 내에 특수 유니코드 기호(×, →, —, §)를 직접 삽입하지 말고 안전한 ASCII 문자로 대체하여 코딩할 것.
### [2026-03-11] ADF 단위근 검정 — autolag='AIC' 소표본 과적합
- **증상**: Zt ADF 검정이 `autolag='AIC'`에서 p=0.40 (FAIL), `autolag='BIC'`에서 p=0.0000 (PASS)
- **원인**: AIC는 소표본(N<50)에서 lag를 과다 선택 (N=26에서 lag=8 선택 -> 유효관측치=17 -> 검정력 상실). Hamilton (1994, Ch.17) 참조
- **해결**: `validation/statistical_tests.py`에서 `adfuller(series, autolag="AIC")` -> `adfuller(series, autolag="BIC")`, BIC는 보수적 lag 선택으로 소표본 적합 (Schwarz 1978)
- **주의**: N<50 시계열 ADF 검정에서 항상 `autolag='BIC'` 사용. AIC는 대표본(N>100)에서만 신뢰할 것
### [2026-03-11] KAP 채권 YTM PD Floor — 하드코딩 vs 실계산 혼동
- **증상**: `DEFAULT_PD_FLOORS` 하드코딩 값(BBB=20bp)과 KAP YTM 기반 실계산값(BBB=93bp)의 차이가 큼
- **원인**: `pd_floor.py`에 `build_complete_pd_floor_table()` 함수가 존재하나 사용되지 않고, `get_default_pd_floors()`만 호출
- **해결**: `main.py`와 `generate_report.py` 모두 `build_complete_pd_floor_table()` 호출로 변경. `ytm_fetcher.py` fallback 데이터(2025-12-31)로 오프라인에서도 작동
### [2026-03-27] ECOS 월별 데이터 역산 시 연간 데이터와의 오차
- **증상**: KOSPI 평균이나 교역조건지수를 월별로 12분할 평균 낸 결과가 ECOS 연간 데이터(A) 고시와 소수점 이하 단위에서 완전 일치하지 않음.
- **원인**: KOSPI 일평균의 영업일 가중치, 교역조건지수의 거래물량 가중치가 연간 산출 시 각 월의 편차를 발생시키기 때문.
- **해결**: 대상이 통계 모형 입력 변수(거시 시나리오 모델링)라면 12개월 단순 평균의 오차율(약 0.05%)이 수치에 영향을 거의 미치지 않으므로, 복잡도 완화를 위해 단순 Aggregate를 허용하는 것으로 아키텍처 합의. (단, WTI 단순 평균, KOSPI 종가 등은 완벽 모사가 가능)
- **주의**: 소수점 2째 자리 검증/심사표 등 완벽한 모사가 불가피할 경우, M/A 주기를 나눠 API를 2번씩 별도 Fetch해야 함.

2
.agents/workflows/services.md
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@@ -125,4 +125,4 @@ python .agents\workflows\helpers\vikunja_helper.py list todo
- `curl` → PowerShell에서 `Invoke-WebRequest`의 별칭. **반드시 `curl.exe`** 사용
- `npm` → PowerShell에서 실행 정책 문제 시 `cmd /c npm` 사용
- JSON 파이프 파싱 시 PowerShell 이스케이핑 문제 → `.py` 스크립트 파일로 만들어 실행 권장
- JSON 파이프 파싱 시 PowerShell 이스케이핑 문제 → `.py` 스크립트 파일로 만들어 실행 권장

25
config.yaml
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@@ -18,29 +18,44 @@ ecos:
# 전이행렬 데이터 소스
data:
transition_source: "real" # "real" (3사 실제) | "builtin" (내장 샘플)
transition_dir: null # null이면 기본 data/real/
transition_dir: null # null이면 기본 data/real_v2/
# 모형 파라미터
model:
# 자산상관계수 (Basel IRB 기준 0.12~0.24, 기업 평균 ~0.20)
rho: 0.20
# 신용등급 체계 (한국 3사 공통)
rating_grades: ["AAA", "AA", "A", "BBB", "BB", "B", "CCC", "D"]
rating_grades: ["AAA", "AA", "A", "BBB", "BB", "B", "D"] # 7x7 (CCC제외, Zt추정용)
# 거시 회귀모형 설정
macro_method: "ar1_macro" # "ar1_macro" | "stepwise_aic"
macro_vars: ["HOUSING_PRICE", "CREDIT_SPREAD_LAG1", "CURRENT_ACCOUNT_R"]
# 시나리오 설정
scenarios:
upside:
name: "호황 (Upside)"
z_multiplier: 1.0 # Zt = μ + 1.0σ
weight: 0.20 # ECB 방식 확률가중치
z_multiplier: 1.0 # Z-직접 fallback용
weight: 0.20
macro_shocks: # AR(1) 충격 (σ 배수)
HOUSING_PRICE: 1.0 # 주택가격 1σ 상승 (호재)
CREDIT_SPREAD_LAG1: -1.0 # 신용스프레드 1σ 하락 (호재)
CURRENT_ACCOUNT_R: 1.0 # 경상수지변화율 1σ 상승
base:
name: "중립 (Base)"
z_multiplier: 0.0
weight: 0.50
macro_shocks:
HOUSING_PRICE: 0.0
CREDIT_SPREAD_LAG1: 0.0
CURRENT_ACCOUNT_R: 0.0
downside:
name: "불황 (Downside)"
z_multiplier: -1.5 # Fed DFAST 역사적 하위 5%
z_multiplier: -1.5
weight: 0.30
macro_shocks:
HOUSING_PRICE: -1.5 # 주택가격 1.5σ 하락 (악재)
CREDIT_SPREAD_LAG1: 1.5 # 신용스프레드 1.5σ 상승 (악재)
CURRENT_ACCOUNT_R: -1.5 # 경상수지변화율 1.5σ 하락
# 50년 수렴 메커니즘
convergence:

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data/cache/macro_ecos.csv vendored
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@@ -1,27 +1,27 @@
YEAR,GDP_GROWTH,UNEMPLOYMENT,BASE_RATE,CD_RATE,CPI_GROWTH,LEADING_INDEX,GOVT_3Y,GOVT_10Y,CORP_AA,CORP_BBB,IPI,EXPORT,IMPORT_AMT,USDKRW,M2,CSI,KOSPI,IMPORT_PRICE,DISHONOR_RATE,HOUSING_PRICE,HOUSEHOLD_DEBT,FACILITY_INVEST,RETAIL_SALES,CURRENT_ACCOUNT,EMPLOYED,EMPLOYMENT_RATE,OIL_PRICE,COINCIDENT,BSI_MANUF,CONSTRUCTION_DONE,SPI
2000,8.9,4.4,5.25,7.09,2.3,101.2,8.35,8.55,9.35,11.9,102.5,172268.0,160481.0,1131.0,651.8,101.0,504.0,78.5,0.46,55.2,194.0,62.5,72.0,123.5,2115.0,58.5,26.2,99.8,90.0,56.3,58.0
2001,4.5,4.0,4.0,5.34,4.1,99.5,6.7,7.05,8.12,11.27,99.5,150439.0,141098.0,1291.0,736.5,96.5,694.0,73.6,0.28,56.8,225.0,58.5,73.5,80.3,2118.0,59.0,22.8,98.0,82.0,53.8,60.2
2002,7.4,3.3,4.25,4.99,2.8,102.3,6.06,6.58,7.02,9.75,108.5,162471.0,152126.0,1251.0,816.3,105.0,628.0,72.1,0.18,65.3,306.0,63.2,76.0,53.9,2217.0,60.0,23.7,101.5,92.0,55.2,63.5
2003,2.9,3.6,3.75,4.24,3.5,98.8,4.93,5.45,5.7,8.97,109.8,193817.0,178827.0,1192.0,879.2,96.0,811.0,81.3,0.12,71.5,360.0,60.5,74.0,119.5,2212.0,59.5,26.8,99.2,85.0,58.0,64.8
2004,4.9,3.7,3.25,3.77,3.6,100.5,4.11,4.73,4.72,7.53,119.2,253845.0,224463.0,1145.0,935.3,97.0,896.0,90.5,0.08,71.0,394.0,66.5,74.5,284.2,2272.0,59.8,33.5,100.8,88.0,63.5,66.0
2005,3.9,3.7,3.75,3.81,2.8,101.8,4.27,4.95,4.68,6.51,126.0,284419.0,261238.0,1024.0,1002.7,100.5,1011.0,99.2,0.06,73.5,440.0,68.0,76.5,149.8,2297.0,60.3,49.3,101.2,92.0,66.0,68.5
2006,5.2,3.5,4.5,4.72,2.2,102.5,4.83,5.17,5.25,7.08,136.0,325465.0,309383.0,955.0,1089.9,106.0,1434.0,107.8,0.05,80.2,497.0,73.5,78.5,53.9,2334.0,60.9,61.5,102.8,95.0,69.5,71.2
2007,5.5,3.2,5.0,5.36,2.5,103.1,5.23,5.42,5.7,7.44,144.5,371489.0,356846.0,929.0,1181.6,108.5,1897.0,109.3,0.04,83.5,560.0,78.5,80.0,59.5,2371.0,61.3,68.4,103.5,97.0,72.8,74.0
2008,2.8,3.2,3.0,5.7,4.7,96.5,5.27,5.57,7.02,10.73,148.2,422007.0,435275.0,1103.0,1263.2,86.0,1124.0,132.5,0.11,84.0,630.0,76.0,79.0,-57.8,2385.0,61.5,94.3,98.5,72.0,74.5,75.5
2009,0.8,3.6,2.0,2.63,2.8,98.2,4.04,4.85,5.8,9.24,140.0,363534.0,323085.0,1276.0,1404.4,85.0,1683.0,104.2,0.1,84.8,694.0,60.5,77.5,328.1,2355.0,60.1,61.8,96.5,68.0,68.2,76.0
2010,6.8,3.7,2.5,2.8,2.9,103.0,3.72,4.49,4.66,7.98,161.5,466384.0,425212.0,1156.0,1504.3,107.0,2051.0,115.8,0.06,87.0,776.0,80.5,80.5,282.1,2397.0,60.4,78.1,103.0,95.0,72.0,78.5
2011,3.7,3.4,3.25,3.55,4.0,101.2,3.62,4.05,4.41,7.75,168.0,555214.0,524413.0,1108.0,1586.5,100.0,1826.0,130.2,0.05,89.5,857.0,82.0,82.0,184.1,2424.0,60.7,106.0,102.5,90.0,73.5,80.0
2012,2.4,3.2,2.75,3.13,2.2,100.3,3.13,3.35,3.76,6.56,168.2,547870.0,519584.0,1127.0,1673.5,100.5,1997.0,123.5,0.04,89.0,934.0,79.0,83.5,508.4,2468.0,61.3,109.1,100.5,85.0,72.0,82.5
2013,3.2,3.1,2.5,2.72,1.3,100.8,2.79,3.28,3.19,5.87,168.8,559632.0,515586.0,1095.0,1756.2,103.0,2011.0,115.0,0.04,88.8,980.0,77.5,85.0,812.1,2503.0,61.6,105.5,101.0,88.0,71.5,84.0
2014,3.2,3.5,2.0,2.36,1.3,101.0,2.56,2.92,2.99,5.22,168.5,572665.0,525515.0,1053.0,1871.0,104.0,1916.0,105.6,0.04,90.2,1050.0,81.0,86.5,843.5,2546.0,62.4,96.7,101.5,90.0,73.8,86.0
2015,2.8,3.6,1.5,1.72,0.7,100.5,1.8,2.25,2.18,4.61,168.0,526757.0,436499.0,1131.0,2010.0,103.5,1961.0,79.5,0.03,95.0,1145.0,84.5,88.0,1059.4,2567.0,62.6,51.2,101.0,86.0,77.5,88.5
2016,2.9,3.7,1.25,1.48,1.0,99.8,1.44,1.8,1.88,4.6,168.5,495426.0,406193.0,1161.0,2151.1,100.0,2026.0,78.0,0.03,97.5,1250.0,82.0,89.5,992.4,2597.0,63.0,41.3,100.2,85.0,89.5,90.0
2017,3.2,3.7,1.5,1.52,1.9,101.5,1.8,2.33,2.28,4.83,174.2,573694.0,478478.0,1131.0,2347.2,105.0,2467.0,90.5,0.02,100.0,1364.0,92.0,92.0,752.6,2620.0,63.2,53.1,101.8,92.0,90.0,92.5
2018,2.9,3.8,1.75,1.85,1.5,100.8,2.1,2.56,2.67,5.41,178.0,604860.0,535202.0,1100.0,2508.9,102.0,2041.0,100.0,0.03,102.0,1497.0,94.5,94.0,774.7,2633.0,63.1,69.5,101.5,88.0,85.5,94.5
2019,2.2,3.8,1.25,1.63,0.4,99.3,1.5,1.74,1.93,4.52,175.5,542233.0,503343.0,1166.0,2694.0,97.0,2198.0,92.5,0.03,104.5,1573.0,89.0,96.5,597.0,2660.0,63.5,63.4,100.0,82.0,82.0,97.0
2020,-0.7,4.0,0.5,0.76,0.5,97.0,0.98,1.52,2.03,5.25,170.0,512498.0,467633.0,1180.0,3070.2,90.0,2873.0,85.0,0.02,110.0,1723.0,100.0,100.0,752.8,2630.0,62.5,42.3,97.5,76.0,79.0,100.0
2021,4.3,3.7,1.0,1.09,2.5,102.8,1.43,2.12,2.26,5.64,183.0,644400.0,615093.0,1144.0,3415.8,106.0,2978.0,110.5,0.01,122.0,1853.0,108.5,105.0,883.0,2672.0,63.8,69.3,103.0,96.0,77.5,104.5
2022,2.6,2.9,3.25,3.77,5.1,99.2,3.14,3.6,4.25,8.18,186.5,683585.0,731370.0,1292.0,3561.0,95.0,2237.0,140.2,0.02,128.0,1903.0,105.0,107.5,258.3,2726.0,64.5,97.0,100.5,85.0,76.0,108.0
2023,1.4,2.7,3.5,3.75,3.6,98.8,3.55,3.78,4.4,8.4,183.0,632744.0,642756.0,1305.0,3680.0,96.5,2655.0,120.0,0.03,118.0,1920.0,102.0,106.0,355.2,2750.0,65.0,82.5,99.2,80.0,72.0,109.5
2024,2.2,2.8,3.0,3.3,2.3,99.5,3.2,3.42,3.9,7.5,185.0,660000.0,650000.0,1350.0,3800.0,98.0,2400.0,115.0,0.03,115.0,1950.0,103.5,105.5,380.0,2760.0,65.2,80.0,99.5,82.0,68.0,110.0
2025,1.8,3.0,2.75,3.0,1.8,99.8,2.8,3.1,3.5,6.8,184.0,650000.0,640000.0,1380.0,3900.0,99.0,2500.0,110.0,0.03,112.0,1980.0,104.0,106.0,350.0,2770.0,65.5,75.0,100.0,84.0,65.0,111.0
YEAR,GDP_GROWTH,UNEMPLOYMENT,BASE_RATE,CD_RATE,CPI_GROWTH,LEADING_INDEX,GOVT_3Y,GOVT_10Y,CORP_AA,CORP_BBB,IPI,EXPORT,IMPORT_AMT,USDKRW,M2,CSI,KOSPI,IMPORT_PRICE,DISHONOR_RATE,HOUSING_PRICE,HOUSEHOLD_DEBT,FACILITY_INVEST,RETAIL_SALES,CURRENT_ACCOUNT,EMPLOYED,EMPLOYMENT_RATE,OIL_PRICE,COINCIDENT,BSI_MANUF,CONSTRUCTION_DONE,SPI,CONSTR_INVEST_GR,GFCF_GROWTH,SAVING_RATE,INVEST_RATE,TRADE_GNI,MANUF_CAPACITY
2000,8.9,4.4,5.25,7.09,2.3,101.2,8.35,8.55,9.35,11.9,102.5,172268.0,160481.0,1131.0,651.8,101.0,504.0,78.5,0.46,55.2,194.0,62.5,72.0,123.5,2115.0,58.5,26.2,99.8,90.0,56.3,58.0,-1.4,11.4,33.7,31.0,72.5,109.5
2001,4.5,4.0,4.0,5.34,4.1,99.5,6.7,7.05,8.12,11.27,99.5,150439.0,141098.0,1291.0,736.5,96.5,694.0,73.6,0.28,56.8,225.0,58.5,73.5,80.3,2118.0,59.0,22.8,98.0,82.0,53.8,60.2,5.6,0.6,31.7,29.3,66.3,105.8
2002,7.4,3.3,4.25,4.99,2.8,102.3,6.06,6.58,7.02,9.75,108.5,162471.0,152126.0,1251.0,816.3,105.0,628.0,72.1,0.18,65.3,306.0,63.2,76.0,53.9,2217.0,60.0,23.7,101.5,92.0,55.2,63.5,6.5,6.7,31.3,29.1,62.4,110.5
2003,2.9,3.6,3.75,4.24,3.5,98.8,4.93,5.45,5.7,8.97,109.8,193817.0,178827.0,1192.0,879.2,96.0,811.0,81.3,0.12,71.5,360.0,60.5,74.0,119.5,2212.0,59.5,26.8,99.2,85.0,58.0,64.8,10.0,4.0,32.6,30.0,65.0,108.2
2004,4.9,3.7,3.25,3.77,3.6,100.5,4.11,4.73,4.72,7.53,119.2,253845.0,224463.0,1145.0,935.3,97.0,896.0,90.5,0.08,71.0,394.0,66.5,74.5,284.2,2272.0,59.8,33.5,100.8,88.0,63.5,66.0,1.8,2.1,34.8,30.3,73.5,113.8
2005,3.9,3.7,3.75,3.81,2.8,101.8,4.27,4.95,4.68,6.51,126.0,284419.0,261238.0,1024.0,1002.7,100.5,1011.0,99.2,0.06,73.5,440.0,68.0,76.5,149.8,2297.0,60.3,49.3,101.2,92.0,66.0,68.5,-0.4,1.9,33.4,29.7,72.5,114.5
2006,5.2,3.5,4.5,4.72,2.2,102.5,4.83,5.17,5.25,7.08,136.0,325465.0,309383.0,955.0,1089.9,106.0,1434.0,107.8,0.05,80.2,497.0,73.5,78.5,53.9,2334.0,60.9,61.5,102.8,95.0,69.5,71.2,0.5,3.4,32.5,29.6,73.2,115.8
2007,5.5,3.2,5.0,5.36,2.5,103.1,5.23,5.42,5.7,7.44,144.5,371489.0,356846.0,929.0,1181.6,108.5,1897.0,109.3,0.04,83.5,560.0,78.5,80.0,59.5,2371.0,61.3,68.4,103.5,97.0,72.8,74.0,1.4,4.2,32.4,29.4,77.8,115.2
2008,2.8,3.2,3.0,5.7,4.7,96.5,5.27,5.57,7.02,10.73,148.2,422007.0,435275.0,1103.0,1263.2,86.0,1124.0,132.5,0.11,84.0,630.0,76.0,79.0,-57.8,2385.0,61.5,94.3,98.5,72.0,74.5,75.5,-2.8,-1.9,31.5,31.2,96.5,112.8
2009,0.8,3.6,2.0,2.63,2.8,98.2,4.04,4.85,5.8,9.24,140.0,363534.0,323085.0,1276.0,1404.4,85.0,1683.0,104.2,0.1,84.8,694.0,60.5,77.5,328.1,2355.0,60.1,61.8,96.5,68.0,68.2,76.0,0.2,-1.0,31.4,26.3,82.0,102.5
2010,6.8,3.7,2.5,2.8,2.9,103.0,3.72,4.49,4.66,7.98,161.5,466384.0,425212.0,1156.0,1504.3,107.0,2051.0,115.8,0.06,87.0,776.0,80.5,80.5,282.1,2397.0,60.4,78.1,103.0,95.0,72.0,78.5,-1.4,5.8,33.5,29.5,87.9,113.0
2011,3.7,3.4,3.25,3.55,4.0,101.2,3.62,4.05,4.41,7.75,168.0,555214.0,524413.0,1108.0,1586.5,100.0,1826.0,130.2,0.05,89.5,857.0,82.0,82.0,184.1,2424.0,60.7,106.0,102.5,90.0,73.5,80.0,-4.9,0.8,34.0,29.4,96.7,112.5
2012,2.4,3.2,2.75,3.13,2.2,100.3,3.13,3.35,3.76,6.56,168.2,547870.0,519584.0,1127.0,1673.5,100.5,1997.0,123.5,0.04,89.0,934.0,79.0,83.5,508.4,2468.0,61.3,109.1,100.5,85.0,72.0,82.5,-3.2,-0.5,33.8,28.4,96.8,110.2
2013,3.2,3.1,2.5,2.72,1.3,100.8,2.79,3.28,3.19,5.87,168.8,559632.0,515586.0,1095.0,1756.2,103.0,2011.0,115.0,0.04,88.8,980.0,77.5,85.0,812.1,2503.0,61.6,105.5,101.0,88.0,71.5,84.0,5.4,3.3,34.0,28.7,93.2,108.0
2014,3.2,3.5,2.0,2.36,1.3,101.0,2.56,2.92,2.99,5.22,168.5,572665.0,525515.0,1053.0,1871.0,104.0,1916.0,105.6,0.04,90.2,1050.0,81.0,86.5,843.5,2546.0,62.4,96.7,101.5,90.0,73.8,86.0,1.1,3.1,34.5,29.0,87.6,108.8
2015,2.8,3.6,1.5,1.72,0.7,100.5,1.8,2.25,2.18,4.61,168.0,526757.0,436499.0,1131.0,2010.0,103.5,1961.0,79.5,0.03,95.0,1145.0,84.5,88.0,1059.4,2567.0,62.6,51.2,101.0,86.0,77.5,88.5,9.1,5.1,36.0,28.8,79.8,107.2
2016,2.9,3.7,1.25,1.48,1.0,99.8,1.44,1.8,1.88,4.6,168.5,495426.0,406193.0,1161.0,2151.1,100.0,2026.0,78.0,0.03,97.5,1250.0,82.0,89.5,992.4,2597.0,63.0,41.3,100.2,85.0,89.5,90.0,10.3,5.6,36.4,29.2,74.5,106.0
2017,3.2,3.7,1.5,1.52,1.9,101.5,1.8,2.33,2.28,4.83,174.2,573694.0,478478.0,1131.0,2347.2,105.0,2467.0,90.5,0.02,100.0,1364.0,92.0,92.0,752.6,2620.0,63.2,53.1,101.8,92.0,90.0,92.5,7.3,9.8,36.6,31.1,77.3,107.5
2018,2.9,3.8,1.75,1.85,1.5,100.8,2.1,2.56,2.67,5.41,178.0,604860.0,535202.0,1100.0,2508.9,102.0,2041.0,100.0,0.03,102.0,1497.0,94.5,94.0,774.7,2633.0,63.1,69.5,101.5,88.0,85.5,94.5,-4.6,-2.4,35.9,30.3,77.3,107.0
2019,2.2,3.8,1.25,1.63,0.4,99.3,1.5,1.74,1.93,4.52,175.5,542233.0,503343.0,1166.0,2694.0,97.0,2198.0,92.5,0.03,104.5,1573.0,89.0,96.5,597.0,2660.0,63.5,63.4,100.0,82.0,82.0,97.0,-3.1,-2.1,34.6,30.5,72.1,102.8
2020,-0.7,4.0,0.5,0.76,0.5,97.0,0.98,1.52,2.03,5.25,170.0,512498.0,467633.0,1180.0,3070.2,90.0,2873.0,85.0,0.02,110.0,1723.0,100.0,100.0,752.8,2630.0,62.5,42.3,97.5,76.0,79.0,100.0,-0.1,2.6,36.3,31.3,65.8,100.0
2021,4.3,3.7,1.0,1.09,2.5,102.8,1.43,2.12,2.26,5.64,183.0,644400.0,615093.0,1144.0,3415.8,106.0,2978.0,110.5,0.01,122.0,1853.0,108.5,105.0,883.0,2672.0,63.8,69.3,103.0,96.0,77.5,104.5,-1.5,3.1,35.8,31.6,74.5,105.2
2022,2.6,2.9,3.25,3.77,5.1,99.2,3.14,3.6,4.25,8.18,186.5,683585.0,731370.0,1292.0,3561.0,95.0,2237.0,140.2,0.02,128.0,1903.0,105.0,107.5,258.3,2726.0,64.5,97.0,100.5,85.0,76.0,108.0,-3.5,-0.7,34.5,31.8,85.2,104.5
2023,1.4,2.7,3.5,3.75,3.6,98.8,3.55,3.78,4.4,8.4,183.0,632744.0,642756.0,1305.0,3680.0,96.5,2655.0,120.0,0.03,118.0,1920.0,102.0,106.0,355.2,2750.0,65.0,82.5,99.2,80.0,72.0,109.5,-0.5,1.5,34.0,30.8,80.5,101.0
2024,2.2,2.8,3.0,3.3,2.3,99.5,3.2,3.42,3.9,7.5,185.0,660000.0,650000.0,1350.0,3800.0,98.0,2400.0,115.0,0.03,115.0,1950.0,103.5,105.5,380.0,2760.0,65.2,80.0,99.5,82.0,68.0,110.0,-3.3,0.8,33.5,30.0,82.0,101.5
2025,1.8,3.0,2.75,3.0,1.8,99.8,2.8,3.1,3.5,6.8,184.0,650000.0,640000.0,1380.0,3900.0,99.0,2500.0,110.0,0.03,112.0,1980.0,104.0,106.0,350.0,2770.0,65.5,75.0,100.0,84.0,65.0,111.0,-2.0,1.0,33.0,29.5,81.0,101.0
1 YEAR GDP_GROWTH UNEMPLOYMENT BASE_RATE CD_RATE CPI_GROWTH LEADING_INDEX GOVT_3Y GOVT_10Y CORP_AA CORP_BBB IPI EXPORT IMPORT_AMT USDKRW M2 CSI KOSPI IMPORT_PRICE DISHONOR_RATE HOUSING_PRICE HOUSEHOLD_DEBT FACILITY_INVEST RETAIL_SALES CURRENT_ACCOUNT EMPLOYED EMPLOYMENT_RATE OIL_PRICE COINCIDENT BSI_MANUF CONSTRUCTION_DONE SPI CONSTR_INVEST_GR GFCF_GROWTH SAVING_RATE INVEST_RATE TRADE_GNI MANUF_CAPACITY
2 2000 8.9 4.4 5.25 7.09 2.3 101.2 8.35 8.55 9.35 11.9 102.5 172268.0 160481.0 1131.0 651.8 101.0 504.0 78.5 0.46 55.2 194.0 62.5 72.0 123.5 2115.0 58.5 26.2 99.8 90.0 56.3 58.0 -1.4 11.4 33.7 31.0 72.5 109.5
3 2001 4.5 4.0 4.0 5.34 4.1 99.5 6.7 7.05 8.12 11.27 99.5 150439.0 141098.0 1291.0 736.5 96.5 694.0 73.6 0.28 56.8 225.0 58.5 73.5 80.3 2118.0 59.0 22.8 98.0 82.0 53.8 60.2 5.6 0.6 31.7 29.3 66.3 105.8
4 2002 7.4 3.3 4.25 4.99 2.8 102.3 6.06 6.58 7.02 9.75 108.5 162471.0 152126.0 1251.0 816.3 105.0 628.0 72.1 0.18 65.3 306.0 63.2 76.0 53.9 2217.0 60.0 23.7 101.5 92.0 55.2 63.5 6.5 6.7 31.3 29.1 62.4 110.5
5 2003 2.9 3.6 3.75 4.24 3.5 98.8 4.93 5.45 5.7 8.97 109.8 193817.0 178827.0 1192.0 879.2 96.0 811.0 81.3 0.12 71.5 360.0 60.5 74.0 119.5 2212.0 59.5 26.8 99.2 85.0 58.0 64.8 10.0 4.0 32.6 30.0 65.0 108.2
6 2004 4.9 3.7 3.25 3.77 3.6 100.5 4.11 4.73 4.72 7.53 119.2 253845.0 224463.0 1145.0 935.3 97.0 896.0 90.5 0.08 71.0 394.0 66.5 74.5 284.2 2272.0 59.8 33.5 100.8 88.0 63.5 66.0 1.8 2.1 34.8 30.3 73.5 113.8
7 2005 3.9 3.7 3.75 3.81 2.8 101.8 4.27 4.95 4.68 6.51 126.0 284419.0 261238.0 1024.0 1002.7 100.5 1011.0 99.2 0.06 73.5 440.0 68.0 76.5 149.8 2297.0 60.3 49.3 101.2 92.0 66.0 68.5 -0.4 1.9 33.4 29.7 72.5 114.5
8 2006 5.2 3.5 4.5 4.72 2.2 102.5 4.83 5.17 5.25 7.08 136.0 325465.0 309383.0 955.0 1089.9 106.0 1434.0 107.8 0.05 80.2 497.0 73.5 78.5 53.9 2334.0 60.9 61.5 102.8 95.0 69.5 71.2 0.5 3.4 32.5 29.6 73.2 115.8
9 2007 5.5 3.2 5.0 5.36 2.5 103.1 5.23 5.42 5.7 7.44 144.5 371489.0 356846.0 929.0 1181.6 108.5 1897.0 109.3 0.04 83.5 560.0 78.5 80.0 59.5 2371.0 61.3 68.4 103.5 97.0 72.8 74.0 1.4 4.2 32.4 29.4 77.8 115.2
10 2008 2.8 3.2 3.0 5.7 4.7 96.5 5.27 5.57 7.02 10.73 148.2 422007.0 435275.0 1103.0 1263.2 86.0 1124.0 132.5 0.11 84.0 630.0 76.0 79.0 -57.8 2385.0 61.5 94.3 98.5 72.0 74.5 75.5 -2.8 -1.9 31.5 31.2 96.5 112.8
11 2009 0.8 3.6 2.0 2.63 2.8 98.2 4.04 4.85 5.8 9.24 140.0 363534.0 323085.0 1276.0 1404.4 85.0 1683.0 104.2 0.1 84.8 694.0 60.5 77.5 328.1 2355.0 60.1 61.8 96.5 68.0 68.2 76.0 0.2 -1.0 31.4 26.3 82.0 102.5
12 2010 6.8 3.7 2.5 2.8 2.9 103.0 3.72 4.49 4.66 7.98 161.5 466384.0 425212.0 1156.0 1504.3 107.0 2051.0 115.8 0.06 87.0 776.0 80.5 80.5 282.1 2397.0 60.4 78.1 103.0 95.0 72.0 78.5 -1.4 5.8 33.5 29.5 87.9 113.0
13 2011 3.7 3.4 3.25 3.55 4.0 101.2 3.62 4.05 4.41 7.75 168.0 555214.0 524413.0 1108.0 1586.5 100.0 1826.0 130.2 0.05 89.5 857.0 82.0 82.0 184.1 2424.0 60.7 106.0 102.5 90.0 73.5 80.0 -4.9 0.8 34.0 29.4 96.7 112.5
14 2012 2.4 3.2 2.75 3.13 2.2 100.3 3.13 3.35 3.76 6.56 168.2 547870.0 519584.0 1127.0 1673.5 100.5 1997.0 123.5 0.04 89.0 934.0 79.0 83.5 508.4 2468.0 61.3 109.1 100.5 85.0 72.0 82.5 -3.2 -0.5 33.8 28.4 96.8 110.2
15 2013 3.2 3.1 2.5 2.72 1.3 100.8 2.79 3.28 3.19 5.87 168.8 559632.0 515586.0 1095.0 1756.2 103.0 2011.0 115.0 0.04 88.8 980.0 77.5 85.0 812.1 2503.0 61.6 105.5 101.0 88.0 71.5 84.0 5.4 3.3 34.0 28.7 93.2 108.0
16 2014 3.2 3.5 2.0 2.36 1.3 101.0 2.56 2.92 2.99 5.22 168.5 572665.0 525515.0 1053.0 1871.0 104.0 1916.0 105.6 0.04 90.2 1050.0 81.0 86.5 843.5 2546.0 62.4 96.7 101.5 90.0 73.8 86.0 1.1 3.1 34.5 29.0 87.6 108.8
17 2015 2.8 3.6 1.5 1.72 0.7 100.5 1.8 2.25 2.18 4.61 168.0 526757.0 436499.0 1131.0 2010.0 103.5 1961.0 79.5 0.03 95.0 1145.0 84.5 88.0 1059.4 2567.0 62.6 51.2 101.0 86.0 77.5 88.5 9.1 5.1 36.0 28.8 79.8 107.2
18 2016 2.9 3.7 1.25 1.48 1.0 99.8 1.44 1.8 1.88 4.6 168.5 495426.0 406193.0 1161.0 2151.1 100.0 2026.0 78.0 0.03 97.5 1250.0 82.0 89.5 992.4 2597.0 63.0 41.3 100.2 85.0 89.5 90.0 10.3 5.6 36.4 29.2 74.5 106.0
19 2017 3.2 3.7 1.5 1.52 1.9 101.5 1.8 2.33 2.28 4.83 174.2 573694.0 478478.0 1131.0 2347.2 105.0 2467.0 90.5 0.02 100.0 1364.0 92.0 92.0 752.6 2620.0 63.2 53.1 101.8 92.0 90.0 92.5 7.3 9.8 36.6 31.1 77.3 107.5
20 2018 2.9 3.8 1.75 1.85 1.5 100.8 2.1 2.56 2.67 5.41 178.0 604860.0 535202.0 1100.0 2508.9 102.0 2041.0 100.0 0.03 102.0 1497.0 94.5 94.0 774.7 2633.0 63.1 69.5 101.5 88.0 85.5 94.5 -4.6 -2.4 35.9 30.3 77.3 107.0
21 2019 2.2 3.8 1.25 1.63 0.4 99.3 1.5 1.74 1.93 4.52 175.5 542233.0 503343.0 1166.0 2694.0 97.0 2198.0 92.5 0.03 104.5 1573.0 89.0 96.5 597.0 2660.0 63.5 63.4 100.0 82.0 82.0 97.0 -3.1 -2.1 34.6 30.5 72.1 102.8
22 2020 -0.7 4.0 0.5 0.76 0.5 97.0 0.98 1.52 2.03 5.25 170.0 512498.0 467633.0 1180.0 3070.2 90.0 2873.0 85.0 0.02 110.0 1723.0 100.0 100.0 752.8 2630.0 62.5 42.3 97.5 76.0 79.0 100.0 -0.1 2.6 36.3 31.3 65.8 100.0
23 2021 4.3 3.7 1.0 1.09 2.5 102.8 1.43 2.12 2.26 5.64 183.0 644400.0 615093.0 1144.0 3415.8 106.0 2978.0 110.5 0.01 122.0 1853.0 108.5 105.0 883.0 2672.0 63.8 69.3 103.0 96.0 77.5 104.5 -1.5 3.1 35.8 31.6 74.5 105.2
24 2022 2.6 2.9 3.25 3.77 5.1 99.2 3.14 3.6 4.25 8.18 186.5 683585.0 731370.0 1292.0 3561.0 95.0 2237.0 140.2 0.02 128.0 1903.0 105.0 107.5 258.3 2726.0 64.5 97.0 100.5 85.0 76.0 108.0 -3.5 -0.7 34.5 31.8 85.2 104.5
25 2023 1.4 2.7 3.5 3.75 3.6 98.8 3.55 3.78 4.4 8.4 183.0 632744.0 642756.0 1305.0 3680.0 96.5 2655.0 120.0 0.03 118.0 1920.0 102.0 106.0 355.2 2750.0 65.0 82.5 99.2 80.0 72.0 109.5 -0.5 1.5 34.0 30.8 80.5 101.0
26 2024 2.2 2.8 3.0 3.3 2.3 99.5 3.2 3.42 3.9 7.5 185.0 660000.0 650000.0 1350.0 3800.0 98.0 2400.0 115.0 0.03 115.0 1950.0 103.5 105.5 380.0 2760.0 65.2 80.0 99.5 82.0 68.0 110.0 -3.3 0.8 33.5 30.0 82.0 101.5
27 2025 1.8 3.0 2.75 3.0 1.8 99.8 2.8 3.1 3.5 6.8 184.0 650000.0 640000.0 1380.0 3900.0 99.0 2500.0 110.0 0.03 112.0 1980.0 104.0 106.0 350.0 2770.0 65.5 75.0 100.0 84.0 65.0 111.0 -2.0 1.0 33.0 29.5 81.0 101.0

197
data/ccc_interpolator.py Normal file
View File

@@ -0,0 +1,197 @@
# -*- coding: utf-8 -*-
"""
CCC interpolation module: 7x7 -> 8x8
B and D rows/columns are used to create a synthetic CCC grade
via geometric mean (log-interpolation) of transition probabilities.
This module runs AFTER Zt estimation (which uses 7x7 matrices)
to produce the final 8x8 matrices for Lifetime PD projection.
Usage:
from data.ccc_interpolator import expand_to_8x8
tm_8x8 = expand_to_8x8(tm_7x7)
"""
import numpy as np
from typing import Optional
# 7x7 index: AAA=0, AA=1, A=2, BBB=3, BB=4, B=5, D=6
# 8x8 index: AAA=0, AA=1, A=2, BBB=3, BB=4, B=5, CCC=6, D=7
GRADES_7 = ["AAA", "AA", "A", "BBB", "BB", "B", "D"]
GRADES_8 = ["AAA", "AA", "A", "BBB", "BB", "B", "CCC", "D"]
def expand_to_8x8(
tm_7x7: np.ndarray,
alpha: float = 0.5,
method: str = "geometric"
) -> np.ndarray:
"""
7x7 transition matrix -> 8x8 with CCC interpolated between B and D.
The CCC row is interpolated from B row and D row.
The CCC column is created by splitting the D column for grades above CCC.
Parameters
----------
tm_7x7 : np.ndarray
7x7 (AAA, AA, A, BBB, BB, B, D) probability matrix
alpha : float
Interpolation weight (0.5 = geometric midpoint between B and D)
method : str
'geometric': log-interpolation (default)
'linear': linear interpolation
Returns
-------
np.ndarray
8x8 (AAA, AA, A, BBB, BB, B, CCC, D) probability matrix
"""
assert tm_7x7.shape == (7, 7), f"Expected (7,7), got {tm_7x7.shape}"
tm_8x8 = np.zeros((8, 8))
# --- Step 1: Copy existing grades (AAA~B) rows/cols ---
# 7x7 index mapping: 0-5 -> 0-5 (AAA~B), 6 -> 7 (D)
for i in range(6): # AAA~B rows
for j in range(6): # AAA~B cols
tm_8x8[i, j] = tm_7x7[i, j]
# D col: 7x7 col6 -> 8x8 col7
tm_8x8[i, 7] = tm_7x7[i, 6]
# --- Step 2: CCC column (col6) for existing grades ---
# For each grade AAA~B, split some probability from D column to CCC
# Rationale: some firms default through CCC before reaching D
for i in range(6):
pd_i = tm_7x7[i, 6] # P(i -> D) in 7x7
if pd_i > 0:
# B row: larger CCC fraction (B is adjacent to CCC)
# Higher grades: smaller CCC fraction
grade_distance_from_b = max(5 - i, 0)
# B->CCC gets ~30%, BB->CCC ~20%, BBB->CCC ~10%, A->CCC ~5%
ccc_fraction = max(0.30 - grade_distance_from_b * 0.06, 0.02)
ccc_prob = pd_i * ccc_fraction
tm_8x8[i, 6] = ccc_prob # to CCC
tm_8x8[i, 7] = pd_i - ccc_prob # remaining to D
else:
tm_8x8[i, 6] = 0.0
# --- Step 3: CCC row (row 6) via interpolation ---
b_row = np.zeros(8)
d_row = np.zeros(8)
# Expand B row (7x7 row5) to 8x8 space
for j in range(6):
b_row[j] = tm_7x7[5, j]
b_row[6] = 0.0 # placeholder for CCC
b_row[7] = tm_7x7[5, 6]
# D row in 8x8: absorbing state
d_row[7] = 1.0
if method == "geometric":
# Geometric interpolation in log space
ccc_row = _geometric_interp(b_row, d_row, alpha)
else:
# Linear interpolation
ccc_row = alpha * b_row + (1 - alpha) * d_row
# Ensure CCC PD is between B PD and 1.0
# CCC should default more than B
ccc_pd = max(ccc_row[7], b_row[7] * 1.5)
ccc_pd = min(ccc_pd, 0.60) # cap at 60%
# CCC stay rate
ccc_stay = max(1.0 - ccc_pd - ccc_row[:6].sum() - ccc_row[6], 0.30)
# Reassemble CCC row
# Upgrade probabilities from B row, scaled down
for j in range(5): # AAA~BB: very small upgrade from CCC
ccc_row[j] = b_row[j] * 0.3 # CCC upgrades less than B
ccc_row[5] = b_row[5] * 0.5 # CCC -> B (upgrade)
ccc_row[6] = ccc_stay # CCC -> CCC (stay)
ccc_row[7] = ccc_pd # CCC -> D
tm_8x8[6, :] = ccc_row
# --- Step 4: D row (absorbing state) ---
tm_8x8[7, :] = 0.0
tm_8x8[7, 7] = 1.0
# --- Step 5: Normalize rows ---
for i in range(8):
s = tm_8x8[i].sum()
if s > 0:
tm_8x8[i] /= s
return tm_8x8
def _geometric_interp(
row_a: np.ndarray,
row_b: np.ndarray,
alpha: float = 0.5,
eps: float = 1e-10
) -> np.ndarray:
"""Geometric (log-space) interpolation between two probability rows."""
result = np.zeros_like(row_a)
for j in range(len(row_a)):
a = max(row_a[j], eps)
b = max(row_b[j], eps)
result[j] = np.exp(alpha * np.log(a) + (1 - alpha) * np.log(b))
return result
def expand_conditional_tm(
cond_7x7: np.ndarray,
ttc_8x8: np.ndarray = None
) -> np.ndarray:
"""
Expand a Z-conditional 7x7 TM to 8x8 using the same interpolation.
This is used in the lifetime PD projection pipeline:
1. Estimate Zt from 7x7 matrices
2. Generate Z-conditional 7x7 TM
3. Expand to 8x8 for lifetime PD calculation
Parameters
----------
cond_7x7 : np.ndarray
Z-conditional 7x7 transition matrix
ttc_8x8 : np.ndarray, optional
Reference TTC 8x8 for CCC structure (if available)
"""
return expand_to_8x8(cond_7x7)
if __name__ == "__main__":
import sys
sys.path.insert(0, ".")
from data.transition_matrices import load_transition_matrices, compute_ttc_matrix
matrices = load_transition_matrices(source="real")
ttc_7x7 = compute_ttc_matrix(matrices)
print("=== TTC 7x7 ===")
for i, g in enumerate(GRADES_7):
print(f" {g:>4}: [{', '.join(f'{v:.4f}' for v in ttc_7x7[i])}]")
ttc_8x8 = expand_to_8x8(ttc_7x7)
print("\n=== TTC 8x8 (CCC interpolated) ===")
for i, g in enumerate(GRADES_8):
print(f" {g:>4}: [{', '.join(f'{v:.4f}' for v in ttc_8x8[i])}]")
# Verify: PD ordering
print("\n=== PD ordering check ===")
for i, g in enumerate(GRADES_8[:-1]):
print(f" {g:>4}: PD = {ttc_8x8[i, -1]*10000:.1f}bp")
# Check row sums
print("\n=== Row sum check ===")
for i in range(8):
print(f" {GRADES_8[i]:>4}: sum = {ttc_8x8[i].sum():.6f}")

64
data/ecos_fetcher.py
View File

@@ -79,6 +79,16 @@ ECOS_VARIABLES = [
# --- 가계 ---
{"name": "HOUSEHOLD_DEBT","stat": "151Y001", "period": "Q", "item": "A11", "agg": "last", "desc": "가계부채 (조원)"},
# --- 투자/저축 (2.1.1.1 주요지표 연간) ---
{"name": "CONSTR_INVEST", "stat": "200Y002", "period": "A", "item": "10315", "agg": None, "desc": "건설투자 증감률 (%)"},
{"name": "GFCF_GROWTH", "stat": "200Y002", "period": "A", "item": "10311", "agg": None, "desc": "총고정자본형성 증감률 (%)"},
{"name": "SAVING_RATE", "stat": "200Y002", "period": "A", "item": "10903", "agg": None, "desc": "총저축률 (%)"},
{"name": "INVEST_RATE", "stat": "200Y002", "period": "A", "item": "10904", "agg": None, "desc": "국내총투자율 (%)"},
{"name": "TRADE_GNI", "stat": "200Y002", "period": "A", "item": "10910", "agg": None, "desc": "수출입의 대 GNI 비율 (%)"},
# --- 제조업 (8.3.7) ---
{"name": "MANUF_CAPACITY", "stat": "901Y033", "period": "M", "item": "I21A", "agg": "mean", "desc": "제조업 평균가동률 (2020=100)"},
]
@@ -98,61 +108,61 @@ ECOS_VARIABLES = [
# SPI: 서비스업생산지수 (2020=100)
def _build_fallback() -> pd.DataFrame:
"""API 없이 작동하는 확장 fallback — 31개 변수"""
"""API 없이 작동하는 확장 fallback — 37개 변수"""
# fmt: off
data = {
2000: {"GDP_GROWTH":8.9,"UNEMPLOYMENT":4.4,"BASE_RATE":5.25,"CD_RATE":7.09,"CPI_GROWTH":2.3,"LEADING_INDEX":101.2,"GOVT_3Y":8.35,"GOVT_10Y":8.55,"CORP_AA":9.35,"CORP_BBB":11.90,"IPI":102.5,"EXPORT":172268,"IMPORT_AMT":160481,"USDKRW":1131,"M2":651.8,"CSI":101.0,"KOSPI":504,"IMPORT_PRICE":78.5,"DISHONOR_RATE":0.46,"HOUSING_PRICE":55.2,"HOUSEHOLD_DEBT":194.0,
"FACILITY_INVEST":62.5,"RETAIL_SALES":72.0,"CURRENT_ACCOUNT":123.5,"EMPLOYED":2115,"EMPLOYMENT_RATE":58.5,"OIL_PRICE":26.2,"COINCIDENT":99.8,"BSI_MANUF":90,"CONSTRUCTION_DONE":56.3,"SPI":58.0},
"FACILITY_INVEST":62.5,"RETAIL_SALES":72.0,"CURRENT_ACCOUNT":123.5,"EMPLOYED":2115,"EMPLOYMENT_RATE":58.5,"OIL_PRICE":26.2,"COINCIDENT":99.8,"BSI_MANUF":90,"CONSTRUCTION_DONE":56.3,"SPI":58.0,"CONSTR_INVEST_GR":-1.4,"GFCF_GROWTH":11.4,"SAVING_RATE":33.7,"INVEST_RATE":31.0,"TRADE_GNI":72.5,"MANUF_CAPACITY":109.5},
2001: {"GDP_GROWTH":4.5,"UNEMPLOYMENT":4.0,"BASE_RATE":4.00,"CD_RATE":5.34,"CPI_GROWTH":4.1,"LEADING_INDEX":99.5,"GOVT_3Y":6.70,"GOVT_10Y":7.05,"CORP_AA":8.12,"CORP_BBB":11.27,"IPI":99.5,"EXPORT":150439,"IMPORT_AMT":141098,"USDKRW":1291,"M2":736.5,"CSI":96.5,"KOSPI":694,"IMPORT_PRICE":73.6,"DISHONOR_RATE":0.28,"HOUSING_PRICE":56.8,"HOUSEHOLD_DEBT":225.0,
"FACILITY_INVEST":58.5,"RETAIL_SALES":73.5,"CURRENT_ACCOUNT":80.3,"EMPLOYED":2118,"EMPLOYMENT_RATE":59.0,"OIL_PRICE":22.8,"COINCIDENT":98.0,"BSI_MANUF":82,"CONSTRUCTION_DONE":53.8,"SPI":60.2},
"FACILITY_INVEST":58.5,"RETAIL_SALES":73.5,"CURRENT_ACCOUNT":80.3,"EMPLOYED":2118,"EMPLOYMENT_RATE":59.0,"OIL_PRICE":22.8,"COINCIDENT":98.0,"BSI_MANUF":82,"CONSTRUCTION_DONE":53.8,"SPI":60.2,"CONSTR_INVEST_GR":5.6,"GFCF_GROWTH":0.6,"SAVING_RATE":31.7,"INVEST_RATE":29.3,"TRADE_GNI":66.3,"MANUF_CAPACITY":105.8},
2002: {"GDP_GROWTH":7.4,"UNEMPLOYMENT":3.3,"BASE_RATE":4.25,"CD_RATE":4.99,"CPI_GROWTH":2.8,"LEADING_INDEX":102.3,"GOVT_3Y":6.06,"GOVT_10Y":6.58,"CORP_AA":7.02,"CORP_BBB":9.75,"IPI":108.5,"EXPORT":162471,"IMPORT_AMT":152126,"USDKRW":1251,"M2":816.3,"CSI":105.0,"KOSPI":628,"IMPORT_PRICE":72.1,"DISHONOR_RATE":0.18,"HOUSING_PRICE":65.3,"HOUSEHOLD_DEBT":306.0,
"FACILITY_INVEST":63.2,"RETAIL_SALES":76.0,"CURRENT_ACCOUNT":53.9,"EMPLOYED":2217,"EMPLOYMENT_RATE":60.0,"OIL_PRICE":23.7,"COINCIDENT":101.5,"BSI_MANUF":92,"CONSTRUCTION_DONE":55.2,"SPI":63.5},
"FACILITY_INVEST":63.2,"RETAIL_SALES":76.0,"CURRENT_ACCOUNT":53.9,"EMPLOYED":2217,"EMPLOYMENT_RATE":60.0,"OIL_PRICE":23.7,"COINCIDENT":101.5,"BSI_MANUF":92,"CONSTRUCTION_DONE":55.2,"SPI":63.5,"CONSTR_INVEST_GR":6.5,"GFCF_GROWTH":6.7,"SAVING_RATE":31.3,"INVEST_RATE":29.1,"TRADE_GNI":62.4,"MANUF_CAPACITY":110.5},
2003: {"GDP_GROWTH":2.9,"UNEMPLOYMENT":3.6,"BASE_RATE":3.75,"CD_RATE":4.24,"CPI_GROWTH":3.5,"LEADING_INDEX":98.8,"GOVT_3Y":4.93,"GOVT_10Y":5.45,"CORP_AA":5.70,"CORP_BBB":8.97,"IPI":109.8,"EXPORT":193817,"IMPORT_AMT":178827,"USDKRW":1192,"M2":879.2,"CSI":96.0,"KOSPI":811,"IMPORT_PRICE":81.3,"DISHONOR_RATE":0.12,"HOUSING_PRICE":71.5,"HOUSEHOLD_DEBT":360.0,
"FACILITY_INVEST":60.5,"RETAIL_SALES":74.0,"CURRENT_ACCOUNT":119.5,"EMPLOYED":2212,"EMPLOYMENT_RATE":59.5,"OIL_PRICE":26.8,"COINCIDENT":99.2,"BSI_MANUF":85,"CONSTRUCTION_DONE":58.0,"SPI":64.8},
"FACILITY_INVEST":60.5,"RETAIL_SALES":74.0,"CURRENT_ACCOUNT":119.5,"EMPLOYED":2212,"EMPLOYMENT_RATE":59.5,"OIL_PRICE":26.8,"COINCIDENT":99.2,"BSI_MANUF":85,"CONSTRUCTION_DONE":58.0,"SPI":64.8,"CONSTR_INVEST_GR":10.0,"GFCF_GROWTH":4.0,"SAVING_RATE":32.6,"INVEST_RATE":30.0,"TRADE_GNI":65.0,"MANUF_CAPACITY":108.2},
2004: {"GDP_GROWTH":4.9,"UNEMPLOYMENT":3.7,"BASE_RATE":3.25,"CD_RATE":3.77,"CPI_GROWTH":3.6,"LEADING_INDEX":100.5,"GOVT_3Y":4.11,"GOVT_10Y":4.73,"CORP_AA":4.72,"CORP_BBB":7.53,"IPI":119.2,"EXPORT":253845,"IMPORT_AMT":224463,"USDKRW":1145,"M2":935.3,"CSI":97.0,"KOSPI":896,"IMPORT_PRICE":90.5,"DISHONOR_RATE":0.08,"HOUSING_PRICE":71.0,"HOUSEHOLD_DEBT":394.0,
"FACILITY_INVEST":66.5,"RETAIL_SALES":74.5,"CURRENT_ACCOUNT":284.2,"EMPLOYED":2272,"EMPLOYMENT_RATE":59.8,"OIL_PRICE":33.5,"COINCIDENT":100.8,"BSI_MANUF":88,"CONSTRUCTION_DONE":63.5,"SPI":66.0},
"FACILITY_INVEST":66.5,"RETAIL_SALES":74.5,"CURRENT_ACCOUNT":284.2,"EMPLOYED":2272,"EMPLOYMENT_RATE":59.8,"OIL_PRICE":33.5,"COINCIDENT":100.8,"BSI_MANUF":88,"CONSTRUCTION_DONE":63.5,"SPI":66.0,"CONSTR_INVEST_GR":1.8,"GFCF_GROWTH":2.1,"SAVING_RATE":34.8,"INVEST_RATE":30.3,"TRADE_GNI":73.5,"MANUF_CAPACITY":113.8},
2005: {"GDP_GROWTH":3.9,"UNEMPLOYMENT":3.7,"BASE_RATE":3.75,"CD_RATE":3.81,"CPI_GROWTH":2.8,"LEADING_INDEX":101.8,"GOVT_3Y":4.27,"GOVT_10Y":4.95,"CORP_AA":4.68,"CORP_BBB":6.51,"IPI":126.0,"EXPORT":284419,"IMPORT_AMT":261238,"USDKRW":1024,"M2":1002.7,"CSI":100.5,"KOSPI":1011,"IMPORT_PRICE":99.2,"DISHONOR_RATE":0.06,"HOUSING_PRICE":73.5,"HOUSEHOLD_DEBT":440.0,
"FACILITY_INVEST":68.0,"RETAIL_SALES":76.5,"CURRENT_ACCOUNT":149.8,"EMPLOYED":2297,"EMPLOYMENT_RATE":60.3,"OIL_PRICE":49.3,"COINCIDENT":101.2,"BSI_MANUF":92,"CONSTRUCTION_DONE":66.0,"SPI":68.5},
"FACILITY_INVEST":68.0,"RETAIL_SALES":76.5,"CURRENT_ACCOUNT":149.8,"EMPLOYED":2297,"EMPLOYMENT_RATE":60.3,"OIL_PRICE":49.3,"COINCIDENT":101.2,"BSI_MANUF":92,"CONSTRUCTION_DONE":66.0,"SPI":68.5,"CONSTR_INVEST_GR":-0.4,"GFCF_GROWTH":1.9,"SAVING_RATE":33.4,"INVEST_RATE":29.7,"TRADE_GNI":72.5,"MANUF_CAPACITY":114.5},
2006: {"GDP_GROWTH":5.2,"UNEMPLOYMENT":3.5,"BASE_RATE":4.50,"CD_RATE":4.72,"CPI_GROWTH":2.2,"LEADING_INDEX":102.5,"GOVT_3Y":4.83,"GOVT_10Y":5.17,"CORP_AA":5.25,"CORP_BBB":7.08,"IPI":136.0,"EXPORT":325465,"IMPORT_AMT":309383,"USDKRW":955,"M2":1089.9,"CSI":106.0,"KOSPI":1434,"IMPORT_PRICE":107.8,"DISHONOR_RATE":0.05,"HOUSING_PRICE":80.2,"HOUSEHOLD_DEBT":497.0,
"FACILITY_INVEST":73.5,"RETAIL_SALES":78.5,"CURRENT_ACCOUNT":53.9,"EMPLOYED":2334,"EMPLOYMENT_RATE":60.9,"OIL_PRICE":61.5,"COINCIDENT":102.8,"BSI_MANUF":95,"CONSTRUCTION_DONE":69.5,"SPI":71.2},
"FACILITY_INVEST":73.5,"RETAIL_SALES":78.5,"CURRENT_ACCOUNT":53.9,"EMPLOYED":2334,"EMPLOYMENT_RATE":60.9,"OIL_PRICE":61.5,"COINCIDENT":102.8,"BSI_MANUF":95,"CONSTRUCTION_DONE":69.5,"SPI":71.2,"CONSTR_INVEST_GR":0.5,"GFCF_GROWTH":3.4,"SAVING_RATE":32.5,"INVEST_RATE":29.6,"TRADE_GNI":73.2,"MANUF_CAPACITY":115.8},
2007: {"GDP_GROWTH":5.5,"UNEMPLOYMENT":3.2,"BASE_RATE":5.00,"CD_RATE":5.36,"CPI_GROWTH":2.5,"LEADING_INDEX":103.1,"GOVT_3Y":5.23,"GOVT_10Y":5.42,"CORP_AA":5.70,"CORP_BBB":7.44,"IPI":144.5,"EXPORT":371489,"IMPORT_AMT":356846,"USDKRW":929,"M2":1181.6,"CSI":108.5,"KOSPI":1897,"IMPORT_PRICE":109.3,"DISHONOR_RATE":0.04,"HOUSING_PRICE":83.5,"HOUSEHOLD_DEBT":560.0,
"FACILITY_INVEST":78.5,"RETAIL_SALES":80.0,"CURRENT_ACCOUNT":59.5,"EMPLOYED":2371,"EMPLOYMENT_RATE":61.3,"OIL_PRICE":68.4,"COINCIDENT":103.5,"BSI_MANUF":97,"CONSTRUCTION_DONE":72.8,"SPI":74.0},
"FACILITY_INVEST":78.5,"RETAIL_SALES":80.0,"CURRENT_ACCOUNT":59.5,"EMPLOYED":2371,"EMPLOYMENT_RATE":61.3,"OIL_PRICE":68.4,"COINCIDENT":103.5,"BSI_MANUF":97,"CONSTRUCTION_DONE":72.8,"SPI":74.0,"CONSTR_INVEST_GR":1.4,"GFCF_GROWTH":4.2,"SAVING_RATE":32.4,"INVEST_RATE":29.4,"TRADE_GNI":77.8,"MANUF_CAPACITY":115.2},
2008: {"GDP_GROWTH":2.8,"UNEMPLOYMENT":3.2,"BASE_RATE":3.00,"CD_RATE":5.70,"CPI_GROWTH":4.7,"LEADING_INDEX":96.5,"GOVT_3Y":5.27,"GOVT_10Y":5.57,"CORP_AA":7.02,"CORP_BBB":10.73,"IPI":148.2,"EXPORT":422007,"IMPORT_AMT":435275,"USDKRW":1103,"M2":1263.2,"CSI":86.0,"KOSPI":1124,"IMPORT_PRICE":132.5,"DISHONOR_RATE":0.11,"HOUSING_PRICE":84.0,"HOUSEHOLD_DEBT":630.0,
"FACILITY_INVEST":76.0,"RETAIL_SALES":79.0,"CURRENT_ACCOUNT":-57.8,"EMPLOYED":2385,"EMPLOYMENT_RATE":61.5,"OIL_PRICE":94.3,"COINCIDENT":98.5,"BSI_MANUF":72,"CONSTRUCTION_DONE":74.5,"SPI":75.5},
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2025: {"GDP_GROWTH":1.8,"UNEMPLOYMENT":3.0,"BASE_RATE":2.75,"CD_RATE":3.00,"CPI_GROWTH":1.8,"LEADING_INDEX":99.8,"GOVT_3Y":2.80,"GOVT_10Y":3.10,"CORP_AA":3.50,"CORP_BBB":6.80,"IPI":184.0,"EXPORT":650000,"IMPORT_AMT":640000,"USDKRW":1380,"M2":3900.0,"CSI":99.0,"KOSPI":2500,"IMPORT_PRICE":110.0,"DISHONOR_RATE":0.03,"HOUSING_PRICE":112.0,"HOUSEHOLD_DEBT":1980.0,
"FACILITY_INVEST":104.0,"RETAIL_SALES":106.0,"CURRENT_ACCOUNT":350.0,"EMPLOYED":2770,"EMPLOYMENT_RATE":65.5,"OIL_PRICE":75.0,"COINCIDENT":100.0,"BSI_MANUF":84,"CONSTRUCTION_DONE":65.0,"SPI":111.0},
"FACILITY_INVEST":104.0,"RETAIL_SALES":106.0,"CURRENT_ACCOUNT":350.0,"EMPLOYED":2770,"EMPLOYMENT_RATE":65.5,"OIL_PRICE":75.0,"COINCIDENT":100.0,"BSI_MANUF":84,"CONSTRUCTION_DONE":65.0,"SPI":111.0,"CONSTR_INVEST_GR":-2.0,"GFCF_GROWTH":1.0,"SAVING_RATE":33.0,"INVEST_RATE":29.5,"TRADE_GNI":81.0,"MANUF_CAPACITY":101.0},
}
# fmt: on
return pd.DataFrame(data).T.rename_axis("YEAR")

151
data/parse_pdf_matrices.py
View File

@@ -29,7 +29,8 @@ if sys.stdout.encoding != 'utf-8':
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8', errors='replace')
sys.stderr = io.TextIOWrapper(sys.stderr.buffer, encoding='utf-8', errors='replace')
MODEL_GRADES = ["AAA", "AA", "A", "BBB", "BB", "B", "CCC", "D"]
MODEL_GRADES_7 = ["AAA", "AA", "A", "BBB", "BB", "B", "D"]
MODEL_GRADES_8 = ["AAA", "AA", "A", "BBB", "BB", "B", "CCC", "D"]
GRADE_LABELS = ["AAA", "AA", "A", "BBB", "BB"] # B이하 is separate
BASE_DIR = Path(__file__).parent.parent
@@ -460,87 +461,72 @@ def _parse_kr_numbers(s: str) -> Optional[List[float]]:
# ============================================================
# 후처리: 6×8 → 8×8
# 후처리: 6x8 -> 7x7 (WR->D 보정 + CCC 제거)
# ============================================================
def postprocess_matrix(raw_6x8: np.ndarray) -> np.ndarray:
"""6×8 (AAA~B이하 × AAA~WR) → 8×8 (AAA~D × AAA~D)"""
_BROAD_GRADE_MAP_6 = {0: "AAA", 1: "AA", 2: "A", 3: "BBB", 4: "BB", 5: "B"}
def postprocess_matrix(raw_6x8, pd_floors=None):
"""6x8 (AAA~B이하 x AAA~WR+D) -> 7x7 (AAA~B+D)
Steps:
1. PD floor correction: if observed PD < floor, transfer from WR to D
2. Remaining WR -> proportional redistribution
3. B이하 -> B mapping
4. Add D row (absorbing state)
5. Normalize rows to sum=1
"""
assert raw_6x8.shape == (6, 8), f"Expected (6,8), got {raw_6x8.shape}"
# WR 열(7) 제거 → 비례 재배분
mat_6x7 = raw_6x8[:, :7].copy()
for i in range(6):
row_sum = mat_6x7[i].sum()
if row_sum > 0:
mat_6x7[i] = mat_6x7[i] / row_sum * 100.0
mat = raw_6x8.copy()
COL_D = 6
COL_WR = 7
# 8×8 구성: B이하(5) → B(5), D:col6→col7
mat = np.zeros((8, 8))
# Step 1: PD floor correction (WR -> D transfer)
if pd_floors is not None:
for i in range(6):
broad = _BROAD_GRADE_MAP_6[i]
if broad not in pd_floors:
continue
floor_pct = pd_floors[broad] * 100 # decimal -> %
observed_pd = mat[i, COL_D]
wr_available = mat[i, COL_WR]
if observed_pd < floor_pct and wr_available > 0:
deficit = floor_pct - observed_pd
transfer = min(deficit, wr_available)
mat[i, COL_D] += transfer
mat[i, COL_WR] -= transfer
# Step 2: Remaining WR -> proportional redistribution
for i in range(6):
wr_remaining = mat[i, COL_WR]
if wr_remaining > 0:
non_wr_cols = mat[i, :7]
non_wr_sum = non_wr_cols.sum()
if non_wr_sum > 0:
mat[i, :7] = non_wr_cols * (non_wr_sum + wr_remaining) / non_wr_sum
mat[i, COL_WR] = 0.0
# Step 3: B이하 -> B mapping + build 7x7
mat_7x7 = np.zeros((7, 7))
for i in range(6):
for j in range(6):
mat[i, j] = mat_6x7[i, j]
mat[i, 7] = mat_6x7[i, 6] # D
mat_7x7[i, j] = mat[i, j]
mat_7x7[i, 6] = mat[i, COL_D]
# CCC 행/열 extrapolation
mat = _extrapolate_ccc(mat)
# Step 4: D row (absorbing state)
mat_7x7[6, :] = 0.0
mat_7x7[6, 6] = 100.0
# D 행
mat[7, :] = 0.0
mat[7, 7] = 100.0
# → 확률, 행합 정규화
mat /= 100.0
for i in range(8):
s = mat[i].sum()
# Step 5: Convert to probability and normalize
mat_7x7 /= 100.0
for i in range(7):
s = mat_7x7[i].sum()
if s > 0:
mat[i] /= s
mat_7x7[i] /= s
return mat
def _extrapolate_ccc(mat: np.ndarray) -> np.ndarray:
"""CCC 행/열 extrapolation from B이하 PD 패턴"""
pd_bb = mat[4, 7]
pd_b = mat[5, 7]
# CCC PD
if pd_bb > 0 and pd_b > pd_bb:
ratio = pd_b / pd_bb
else:
ratio = 2.5
pd_ccc = min(pd_b * ratio, 60.0)
pd_ccc = max(pd_ccc, pd_b * 1.5)
# Stay rates
stay_bb = mat[4, 4]
stay_b = mat[5, 5]
stay_ratio = (stay_b / stay_bb) if (stay_bb > 0 and stay_b < stay_bb) else 0.7
stay_ccc = max(stay_b * stay_ratio, 5.0)
upgrade_to_b = mat[5, 4] * 0.8 if mat[5, 4] > 0 else 2.0
# CCC 행
mat[6, :] = [0, 0, 0.1, 0.2, 0.3, upgrade_to_b, stay_ccc, pd_ccc]
ccc_sum = mat[6].sum()
if ccc_sum > 100:
mat[6, 6] = max(mat[6, 6] - (ccc_sum - 100), 1.0)
elif ccc_sum < 100:
mat[6, 6] += (100 - ccc_sum)
# CCC 열: B→CCC, BB→CCC, BBB→CCC 전이 분리
b_to_ccc = mat[5, 5] * 0.15
mat[5, 6] = b_to_ccc
mat[5, 5] -= b_to_ccc
bb_to_ccc = mat[4, 5] * 0.1 if mat[4, 5] > 0 else 0.5
mat[4, 6] = bb_to_ccc
mat[4, 5] = max(mat[4, 5] - bb_to_ccc, 0)
mat[3, 6] = 0.3
mat[3, 5] = max(mat[3, 5] - 0.15, 0)
mat[3, 3] = max(mat[3, 3] - 0.15, 0)
return mat
return mat_7x7
# ============================================================
@@ -549,6 +535,17 @@ def _extrapolate_ccc(mat: np.ndarray) -> np.ndarray:
def main():
OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
# Load PD floors
broad_floors = None
try:
import sys as _sys
_sys.path.insert(0, str(BASE_DIR))
from data.pd_floor import build_complete_pd_floor_table
broad_floors, _, _ = build_complete_pd_floor_table()
print(f" PD floor loaded: {', '.join(f'{g}={v*10000:.1f}bp' for g, v in broad_floors.items())}")
except Exception as e:
print(f" PD floor load failed ({e}), proceeding without floor")
all_matrices = {}
for agency, pdf_path in PDF_FILES.items():
@@ -582,7 +579,7 @@ def main():
processed = {}
for year, raw_mat in sorted(raw.items()):
try:
processed[year] = postprocess_matrix(raw_mat)
processed[year] = postprocess_matrix(raw_mat, pd_floors=broad_floors)
except Exception as e:
print(f" ERROR {year}: {e}")
@@ -590,7 +587,7 @@ def main():
print(f" Processed {len(processed)} matrices")
for year, mat in processed.items():
df = pd.DataFrame(mat, index=MODEL_GRADES, columns=MODEL_GRADES)
df = pd.DataFrame(mat, index=MODEL_GRADES_7, columns=MODEL_GRADES_7)
df.to_csv(OUTPUT_DIR / f"{agency}_{year}.csv", float_format="%.6f")
# 3사 평균
@@ -609,11 +606,11 @@ def main():
for year in common_years:
avg = np.mean([all_matrices[a][year] for a in agency_names], axis=0)
for i in range(8):
for i in range(7):
s = avg[i].sum()
if s > 0:
avg[i] /= s
df = pd.DataFrame(avg, index=MODEL_GRADES, columns=MODEL_GRADES)
df = pd.DataFrame(avg, index=MODEL_GRADES_7, columns=MODEL_GRADES_7)
df.to_csv(OUTPUT_DIR / f"AVG_{year}.csv", float_format="%.6f")
# PD 요약
@@ -632,7 +629,7 @@ def main():
if sample_year not in common_years and not any(sample_year in all_matrices[a] for a in agency_names):
continue
print(f"\n Year {sample_year}:")
for gi, grade in enumerate(MODEL_GRADES[:-1]):
for gi, grade in enumerate(MODEL_GRADES_7[:-1]):
print(f" {grade:>5}:", end='')
for a in agency_names:
if sample_year in all_matrices[a]:

427
data/pd_floor.py Normal file
View File

@@ -0,0 +1,427 @@
"""
시장 YTM 기반 PD 플로어 산출 모듈
KAP(한국자산평가) 등급별 회사채 수익률에서 신용스프레드를 추출하고,
시장 내재 부도율(PD)을 산출한 뒤, AAA=5bp 앵커링 + 로그 스케일링으로
각 등급의 PD 플로어를 결정합니다.
핵심 공식:
PD_raw = spread / (1 - recovery_rate) [LGD = 1 - RR]
scale = log(anchor_AAA) / log(PD_raw_AAA)
PD_floor(g) = exp(log(PD_raw(g)) × scale)
참고:
- Basel III CRE30.4: 기업 PD 플로어 5bp (0.05%)
- 한국 시장 회수율: 약 40% (LGD = 60%)
- docs/pd_floor_reference.md 참조
"""
import numpy as np
import logging
from typing import Dict, Optional, Tuple, List
logger = logging.getLogger(__name__)
# 기본 파라미터
DEFAULT_RECOVERY_RATE = 0.40 # 회수율 40% → LGD 60%
DEFAULT_AAA_ANCHOR = 0.0005 # 5bp = 0.05% = 0.0005
DEFAULT_LGD = 1 - DEFAULT_RECOVERY_RATE # 0.60
# 대등급 순서 (인덱스 기반 외삽에 사용)
BROAD_GRADE_ORDER = ["AAA", "AA", "A", "BBB", "BB", "B"]
BROAD_GRADE_INDEX = {g: i for i, g in enumerate(BROAD_GRADE_ORDER)}
def compute_market_implied_pd(
spread_bp: float,
lgd: float = DEFAULT_LGD
) -> float:
"""
신용스프레드에서 시장 내재 PD 산출
PD ≈ spread / LGD
Parameters
----------
spread_bp : float
신용스프레드 (bp, 1bp = 0.01%)
lgd : float
Loss Given Default (기본: 0.60)
Returns
-------
float
시장 내재 PD (소수, 예: 0.000727 = 7.27bp)
"""
spread_decimal = spread_bp / 10000 # bp → 소수
return spread_decimal / lgd
def compute_pd_floors(
spreads_bp: Dict[str, float],
anchor_aaa: float = DEFAULT_AAA_ANCHOR,
lgd: float = DEFAULT_LGD
) -> Dict[str, float]:
"""
AAA=5bp 앵커링 + 로그 스케일링으로 등급별 PD 플로어 산출
Parameters
----------
spreads_bp : Dict[str, float]
등급별 신용스프레드 (bp). 대등급(AAA, AA, A, BBB) 기준.
anchor_aaa : float
AAA 앵커 PD (기본: 5bp = 0.0005)
lgd : float
Loss Given Default (기본: 0.60)
Returns
-------
Dict[str, float]
등급별 PD 플로어 (소수). 예: {'AAA': 0.0005, 'AA': 0.00057, ...}
"""
# Step 1: 시장 내재 PD 산출
pd_raw = {}
for grade, spread in spreads_bp.items():
pd_raw[grade] = compute_market_implied_pd(spread, lgd)
if "AAA" not in pd_raw or pd_raw["AAA"] <= 0:
raise ValueError("AAA 스프레드가 0 이하입니다. 데이터를 확인하세요.")
# Step 2: 로그 스케일링
# scale = log(anchor) / log(pd_raw_AAA)
log_anchor = np.log(anchor_aaa)
log_aaa_raw = np.log(pd_raw["AAA"])
scale = log_anchor / log_aaa_raw
pd_floors = {}
for grade, pd_val in pd_raw.items():
pd_floors[grade] = np.exp(np.log(pd_val) * scale)
logger.info(f"PD 플로어 스케일링: scale={scale:.4f}, "
f"AAA raw={pd_raw['AAA']*10000:.1f}bp → floor={pd_floors['AAA']*10000:.1f}bp")
return pd_floors
# ============================================================
# 기본 PD 플로어 (시장 데이터 없이 사용 가능)
# ============================================================
# 근거:
# AAA = 5bp : Basel III CRE30.4 규제 플로어 (2023 개정, 기업 IRB)
# AA = 5bp : Basel III 최저선 + S&P 장기평균 2bp + Moody's 5bp 중간값
# A = 7bp : S&P 장기평균 5bp + Moody's 9bp 중간값
# BBB = 20bp: S&P 15bp + Moody's 26bp 중간값, 한국 BBB 관측 27bp와 정합
# BB = 60bp: S&P 56~63bp 범위, 관측치 사용 (floor 불필요)
# B = 300bp: S&P 293~334bp 범위, 관측치 사용 (floor 불필요)
#
# 참고문헌:
# [1] Basel Committee, CRE30.4: "PD shall not be less than 0.05%"
# [2] S&P Global, "2023 Annual Default and Transition Study"
# [3] Moody's, "Annual Default Study" (1920-2023)
# [4] 금융감독원, 신용평가공시 (한국기업평가 1998-2025)
DEFAULT_PD_FLOORS = {
"AAA": 0.0005, # 5bp — Basel III CRE30.4
"AA": 0.0005, # 5bp — Basel III 최저선
"A": 0.0007, # 7bp — S&P/Moody's 중간값
"BBB": 0.0020, # 20bp — S&P/Moody's 중간값
"BB": 0.0060, # 60bp — 관측치 수준 (floor 미적용)
"B": 0.0300, # 300bp — 관측치 수준 (floor 미적용)
}
# 7×7 행렬용 (CCC 제외)
GRADES_7 = ["AAA", "AA", "A", "BBB", "BB", "B"]
def get_default_pd_floors() -> Dict[str, float]:
"""기본 PD 플로어 반환 (Basel III + S&P/Moody's 근거)"""
return DEFAULT_PD_FLOORS.copy()
def apply_pd_floor_to_matrices(
matrices: Dict[int, 'np.ndarray'],
pd_floors: Optional[Dict[str, float]] = None,
grades: Optional[List[str]] = None
) -> Dict[int, 'np.ndarray']:
"""
전이행렬의 D열(부도 전이확률)에 PD 플로어 적용
로직:
1. 각 등급의 TM[i, D] < floor[i] 이면
2. TM[i, D] = floor[i] 로 상향
3. 초과분(delta)을 TM[i, i] (대각선)에서 차감
4. 행 합 = 1.0 유지
이론적 근거:
- 한국 투자적격등급(AAA~A) 부도 관측치 = 0%
- 0%는 "위험 없음"이 아니라 "관측 불가능한 확률"
- Basel III CRE30.4: 기업 PD ≥ 5bp (0.05%)
- S&P/Moody's 글로벌 장기평균으로 보정
Parameters
----------
matrices : Dict[int, np.ndarray]
연도별 전이행렬 (N×N, 마지막 열 = D)
pd_floors : Dict[str, float], optional
등급별 최소 PD (기본: DEFAULT_PD_FLOORS)
grades : List[str], optional
등급 레이블 (기본: AAA~B for 7×7)
Returns
-------
Dict[int, np.ndarray]
PD 플로어 적용된 전이행렬 (새 복사본)
"""
if pd_floors is None:
pd_floors = DEFAULT_PD_FLOORS
if grades is None:
grades = GRADES_7
calibrated = {}
for year, tm in matrices.items():
tm_new = tm.copy()
n = tm_new.shape[0]
d_col = n - 1 # 마지막 열 = D
for i in range(n - 1): # D행은 제외 (흡수상태)
grade = grades[i] if i < len(grades) else None
if grade and grade in pd_floors:
floor = pd_floors[grade]
observed_pd = tm_new[i, d_col]
if observed_pd < floor:
delta = floor - observed_pd
tm_new[i, d_col] = floor
# 대각선(유지확률)에서 차감
tm_new[i, i] = max(tm_new[i, i] - delta, 0.0)
# 행 합 재정규화 (안전장치)
row_sum = tm_new[i].sum()
if row_sum > 0:
tm_new[i] /= row_sum
calibrated[year] = tm_new
logger.info(f"PD 플로어 적용 완료: {len(calibrated)}개 연도")
return calibrated
def extrapolate_speculative_grades(
pd_floors: Dict[str, float],
grades_to_extrapolate: List[str] = ["BB", "B"]
) -> Dict[str, float]:
"""
투자적격등급(AAA~BBB)의 로그 트렌드를 외삽하여 투기등급 PD 산출
log(PD) vs grade_index의 선형 트렌드를 BBB 이후로 연장합니다.
Parameters
----------
pd_floors : Dict[str, float]
투자적격등급 PD 플로어 (AAA~BBB)
grades_to_extrapolate : List[str]
외삽할 등급 (기본: ["BB", "B"])
Returns
-------
Dict[str, float]
투기등급이 추가된 PD 플로어
"""
# 기존 투자적격 등급의 log(PD) vs index 관계
available = []
for g in BROAD_GRADE_ORDER:
if g in pd_floors:
available.append((BROAD_GRADE_INDEX[g], np.log(pd_floors[g])))
if len(available) < 2:
raise ValueError("외삽을 위해 최소 2개 등급의 PD가 필요합니다.")
# 선형 회귀: log(PD) = a × index + b
x = np.array([a[0] for a in available])
y = np.array([a[1] for a in available])
coeffs = np.polyfit(x, y, 1) # [기울기, 절편]
result = pd_floors.copy()
for grade in grades_to_extrapolate:
if grade in BROAD_GRADE_INDEX:
idx = BROAD_GRADE_INDEX[grade]
log_pd = coeffs[0] * idx + coeffs[1]
result[grade] = np.exp(log_pd)
logger.info(f"외삽 PD [{grade}]: {result[grade]*10000:.1f}bp "
f"(index={idx}, log_pd={log_pd:.4f})")
return result
def interpolate_ccc_pd(
pd_b: float,
pd_d: float = 1.0,
method: str = "geometric"
) -> Dict[str, float]:
"""
B와 D(=100%) 사이를 보간하여 CCC/CC/C 등급 PD 산출
Parameters
----------
pd_b : float
B등급 PD (소수)
pd_d : float
D등급 PD (기본: 1.0 = 100%)
method : str
'geometric': 기하평균
'log': 로그 등간격 보간
Returns
-------
Dict[str, float]
{'CCC': ..., 'CC': ..., 'C': ...}
"""
if method == "geometric":
# B → CCC → CC → C → D 순서로 기하적 등간격
# 4개 구간 (B→CCC, CCC→CC, CC→C, C→D)
log_b = np.log(pd_b)
log_d = np.log(pd_d)
step = (log_d - log_b) / 4
ccc_pd = np.exp(log_b + step * 1)
cc_pd = np.exp(log_b + step * 2)
c_pd = np.exp(log_b + step * 3)
else: # log-linear
log_b = np.log(pd_b)
log_d = np.log(pd_d)
step = (log_d - log_b) / 4
ccc_pd = np.exp(log_b + step * 1)
cc_pd = np.exp(log_b + step * 2)
c_pd = np.exp(log_b + step * 3)
return {"CCC": ccc_pd, "CC": cc_pd, "C": c_pd}
def compute_notch_pd_ratios(
notch_spreads: Dict[str, float],
lgd: float = DEFAULT_LGD
) -> Dict[str, Dict[str, float]]:
"""
노치등급 간 PD 비율 산출 (나중에 등급 쪼개기에 사용)
예: AA+ : AA : AA- = 0.91 : 1.00 : 1.07 (AA 대비 비율)
Parameters
----------
notch_spreads : Dict[str, float]
노치등급별 스프레드 (bp)
Returns
-------
Dict[str, Dict[str, float]]
대등급별 {노치등급: 비율} 딕셔너리
예: {'AA': {'AA+': 0.91, 'AA': 1.00, 'AA-': 1.07}}
"""
from data.ytm_fetcher import NOTCH_TO_BROAD
from collections import defaultdict
# 대등급별 노치 그룹핑
groups = defaultdict(dict)
for notch, spread in notch_spreads.items():
broad = NOTCH_TO_BROAD.get(notch, notch)
groups[broad][notch] = compute_market_implied_pd(spread, lgd)
# 중간 노치 대비 비율 계산
ratios = {}
for broad, notch_pds in groups.items():
if len(notch_pds) == 1:
key = list(notch_pds.keys())[0]
ratios[broad] = {key: 1.0}
else:
# 중간 노치(plain) 기준
mid_key = broad # AA+ → AA가 중간
if mid_key in notch_pds:
mid_pd = notch_pds[mid_key]
else:
mid_pd = sorted(notch_pds.values())[len(notch_pds) // 2]
ratios[broad] = {
notch: pd / mid_pd for notch, pd in notch_pds.items()
}
return ratios
def build_complete_pd_floor_table(
date: str = "2025-12-31",
anchor_aaa: float = DEFAULT_AAA_ANCHOR,
recovery_rate: float = DEFAULT_RECOVERY_RATE
) -> Tuple[Dict[str, float], Dict[str, float], Dict[str, Dict[str, float]]]:
"""
전체 PD 플로어 테이블 생성 (원스톱)
Parameters
----------
date : str
YTM 기준일
anchor_aaa : float
AAA 앵커 PD (기본: 5bp)
recovery_rate : float
회수율 (기본: 0.40)
Returns
-------
Tuple of:
broad_floors : Dict[str, float] - 대등급 PD 플로어 (AAA~B+D)
notch_ratios : Dict[str, Dict[str, float]] - 노치 비율
full_floors : Dict[str, float] - CCC/CC/C 포함 전체 PD (AAA~C+D)
"""
from data.ytm_fetcher import get_ytm_data, compute_spreads, compute_broad_grade_spreads
lgd = 1 - recovery_rate
# 1) YTM 데이터 수집
ytm_data = get_ytm_data(date)
notch_spreads = compute_spreads(ytm_data)
broad_spreads = compute_broad_grade_spreads(notch_spreads)
logger.info(f"대등급 스프레드: {broad_spreads}")
# 2) PD 플로어 산출 (투자적격)
pd_floors = compute_pd_floors(broad_spreads, anchor_aaa, lgd)
# 3) 투기등급 외삽
pd_floors = extrapolate_speculative_grades(pd_floors, ["BB", "B"])
# 4) CCC/CC/C 보간
ccc_pds = interpolate_ccc_pd(pd_floors["B"], pd_d=1.0, method="geometric")
full_floors = {**pd_floors, **ccc_pds, "D": 1.0}
# 5) 노치 비율
notch_ratios = compute_notch_pd_ratios(notch_spreads, lgd)
return pd_floors, notch_ratios, full_floors
if __name__ == "__main__":
logging.basicConfig(level=logging.INFO, format="%(message)s")
print("=" * 60)
print(" PD 플로어 산출 (KAP YTM 기반)")
print("=" * 60)
broad_floors, notch_ratios, full_floors = build_complete_pd_floor_table()
print("\n=== 대등급 PD 플로어 ===")
for grade in BROAD_GRADE_ORDER:
if grade in broad_floors:
print(f" {grade:>4}: {broad_floors[grade]*10000:8.1f}bp "
f"({broad_floors[grade]*100:.4f}%)")
print("\n=== 전체 PD 플로어 (CCC/CC/C 포함) ===")
order = ["AAA", "AA", "A", "BBB", "BB", "B", "CCC", "CC", "C", "D"]
for grade in order:
if grade in full_floors:
print(f" {grade:>4}: {full_floors[grade]*10000:8.1f}bp "
f"({full_floors[grade]*100:.4f}%)")
print("\n=== 노치 PD 비율 ===")
for broad, ratios in notch_ratios.items():
print(f" {broad}:")
for notch, ratio in sorted(ratios.items()):
print(f" {notch:>5}: ×{ratio:.3f}")

9
data/real/AVG_1998.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.000000,0.576715,0.338615,0.084670,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.000000,0.559352,0.440648,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.017544,0.699909,0.207912,0.071635,0.003000,0.000000
BB,0.000000,0.000000,0.000000,0.068283,0.515874,0.244982,0.027220,0.143640
B,0.000000,0.000000,0.000000,0.000000,0.044442,0.476959,0.084169,0.394430
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.048887,0.353468,0.591645
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.000000 0.576715 0.338615 0.084670 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.000000 0.559352 0.440648 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.017544 0.699909 0.207912 0.071635 0.003000 0.000000
6 BB 0.000000 0.000000 0.000000 0.068283 0.515874 0.244982 0.027220 0.143640
7 B 0.000000 0.000000 0.000000 0.000000 0.044442 0.476959 0.084169 0.394430
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.048887 0.353468 0.591645
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_1999.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,0.833333,0.166667,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.000000,0.933333,0.066667,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.061773,0.737460,0.117262,0.000000,0.083505,0.000000,0.000000
BBB,0.000000,0.000000,0.062378,0.797521,0.062053,0.075048,0.003000,0.000000
BB,0.000000,0.000000,0.000000,0.134711,0.796350,0.062045,0.006894,0.000000
B,0.000000,0.000000,0.000000,0.023801,0.090450,0.592972,0.104642,0.188136
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.079026,0.452999,0.461975
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 0.833333 0.166667 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.000000 0.933333 0.066667 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.061773 0.737460 0.117262 0.000000 0.083505 0.000000 0.000000
5 BBB 0.000000 0.000000 0.062378 0.797521 0.062053 0.075048 0.003000 0.000000
6 BB 0.000000 0.000000 0.000000 0.134711 0.796350 0.062045 0.006894 0.000000
7 B 0.000000 0.000000 0.000000 0.023801 0.090450 0.592972 0.104642 0.188136
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.079026 0.452999 0.461975
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2000.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.014493,0.971014,0.014493,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.122075,0.817172,0.047406,0.013347,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.057296,0.883453,0.056255,0.000000,0.002996,0.000000
BB,0.000000,0.000000,0.000000,0.075517,0.858165,0.028252,0.004798,0.033268
B,0.000000,0.000000,0.000000,0.000000,0.115489,0.671687,0.118533,0.094291
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.092391,0.622554,0.279054
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.014493 0.971014 0.014493 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.122075 0.817172 0.047406 0.013347 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.057296 0.883453 0.056255 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.075517 0.858165 0.028252 0.004798 0.033268
7 B 0.000000 0.000000 0.000000 0.000000 0.115489 0.671687 0.118533 0.094291
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.092391 0.622554 0.279054
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2001.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.061444,0.893772,0.030291,0.014493,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.101044,0.861655,0.037302,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.068367,0.846477,0.060342,0.010752,0.003000,0.011062
BB,0.000000,0.000000,0.000000,0.062964,0.847031,0.037988,0.004221,0.047796
B,0.000000,0.000000,0.000000,0.000000,0.160363,0.561351,0.099062,0.179224
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.128291,0.406102,0.459608
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.061444 0.893772 0.030291 0.014493 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.101044 0.861655 0.037302 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.068367 0.846477 0.060342 0.010752 0.003000 0.011062
6 BB 0.000000 0.000000 0.000000 0.062964 0.847031 0.037988 0.004221 0.047796
7 B 0.000000 0.000000 0.000000 0.000000 0.160363 0.561351 0.099062 0.179224
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.128291 0.406102 0.459608
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2002.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.076355,0.852232,0.071413,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.114891,0.872030,0.013079,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.047703,0.911130,0.038171,0.000000,0.002996,0.000000
BB,0.000000,0.000000,0.000000,0.094675,0.725113,0.119048,0.013228,0.047937
B,0.000000,0.000000,0.000000,0.000000,0.080869,0.599699,0.105829,0.213603
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.071361,0.374766,0.547872
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.076355 0.852232 0.071413 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.114891 0.872030 0.013079 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.047703 0.911130 0.038171 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.094675 0.725113 0.119048 0.013228 0.047937
7 B 0.000000 0.000000 0.000000 0.000000 0.080869 0.599699 0.105829 0.213603
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.071361 0.374766 0.547872
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2003.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.085849,0.800426,0.113725,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.026047,0.910271,0.049112,0.000000,0.014570,0.000000,0.000000
BBB,0.000000,0.000000,0.078127,0.898498,0.020379,0.000000,0.002996,0.000000
BB,0.000000,0.000000,0.011905,0.073811,0.735706,0.115708,0.012856,0.050014
B,0.000000,0.000000,0.000000,0.000000,0.000000,0.776242,0.136984,0.086774
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.732848,0.241152
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.085849 0.800426 0.113725 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.026047 0.910271 0.049112 0.000000 0.014570 0.000000 0.000000
5 BBB 0.000000 0.000000 0.078127 0.898498 0.020379 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.011905 0.073811 0.735706 0.115708 0.012856 0.050014
7 B 0.000000 0.000000 0.000000 0.000000 0.000000 0.776242 0.136984 0.086774
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.732848 0.241152
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2004.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.081732,0.885698,0.032570,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.105432,0.857125,0.037443,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.118503,0.855562,0.022940,0.000000,0.002996,0.000000
BB,0.000000,0.000000,0.000000,0.180688,0.579904,0.029986,0.004990,0.204431
B,0.000000,0.000000,0.000000,0.067996,0.025653,0.587401,0.103659,0.215291
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.033856,0.478994,0.481151
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.081732 0.885698 0.032570 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.105432 0.857125 0.037443 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.118503 0.855562 0.022940 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.180688 0.579904 0.029986 0.004990 0.204431
7 B 0.000000 0.000000 0.000000 0.067996 0.025653 0.587401 0.103659 0.215291
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.033856 0.478994 0.481151
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2005.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.027063,0.961034,0.011903,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.080727,0.901305,0.017968,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.113735,0.883270,0.000000,0.000000,0.002996,0.000000
BB,0.000000,0.000000,0.000000,0.174718,0.805287,0.015011,0.004985,0.000000
B,0.000000,0.000000,0.000000,0.000000,0.000000,0.737199,0.130094,0.132708
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.650564,0.323436
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.027063 0.961034 0.011903 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.080727 0.901305 0.017968 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.113735 0.883270 0.000000 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.174718 0.805287 0.015011 0.004985 0.000000
7 B 0.000000 0.000000 0.000000 0.000000 0.000000 0.737199 0.130094 0.132708
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.650564 0.323436
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2006.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.039636,0.949612,0.010752,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.150519,0.849481,0.000000,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.099090,0.862331,0.009213,0.017425,0.002999,0.008942
BB,0.000000,0.000000,0.052771,0.113733,0.697852,0.102932,0.013095,0.019616
B,0.000000,0.000000,0.000000,0.000000,0.013320,0.822017,0.145062,0.019601
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.023990,0.921009,0.049001
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.039636 0.949612 0.010752 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.150519 0.849481 0.000000 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.099090 0.862331 0.009213 0.017425 0.002999 0.008942
6 BB 0.000000 0.000000 0.052771 0.113733 0.697852 0.102932 0.013095 0.019616
7 B 0.000000 0.000000 0.000000 0.000000 0.013320 0.822017 0.145062 0.019601
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.023990 0.921009 0.049001
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2007.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.033387,0.927049,0.039565,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.030441,0.951364,0.018196,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.154455,0.823274,0.019275,0.000000,0.002996,0.000000
BB,0.000000,0.000000,0.000000,0.000000,0.790519,0.188533,0.020948,0.000000
B,0.000000,0.000000,0.022231,0.000000,0.037026,0.799631,0.141111,0.000000
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.042954,0.951046,0.000000
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.033387 0.927049 0.039565 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.030441 0.951364 0.018196 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.154455 0.823274 0.019275 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.000000 0.790519 0.188533 0.020948 0.000000
7 B 0.000000 0.000000 0.022231 0.000000 0.037026 0.799631 0.141111 0.000000
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.042954 0.951046 0.000000
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2008.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.000000,0.970045,0.029955,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.031482,0.923305,0.045213,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.100955,0.789007,0.094084,0.000000,0.002996,0.012958
BB,0.000000,0.000000,0.000000,0.000000,0.838881,0.075012,0.008335,0.077771
B,0.000000,0.000000,0.000000,0.000000,0.000000,0.792549,0.139862,0.067589
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.840113,0.133887
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
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9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2009.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.646357 0.327643
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2010.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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B,0.000000,0.000000,0.000000,0.000000,0.042016,0.596927,0.105340,0.255717
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1 AAA AA A BBB BB B CCC D
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.033613 0.432171 0.528216
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2011.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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B,0.000000,0.000000,0.000000,0.000000,0.000000,0.722515,0.127503,0.149983
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D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.640697 0.333303
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2012.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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B,0.000000,0.000000,0.000000,0.000000,0.000000,0.527309,0.093055,0.379636
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D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.371213 0.602787
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2013.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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BB,0.000000,0.000000,0.000000,0.019608,0.633854,0.240730,0.026748,0.079061
B,0.000000,0.000000,0.000000,0.000000,0.000000,0.783775,0.138313,0.077912
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D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.006139 0.974049 0.019812 0.000000 0.000000 0.000000 0.000000 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.779051 0.194949
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2014.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,0.982722,0.017278,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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B,0.000000,0.000000,0.000000,0.000000,0.000000,0.809516,0.142856,0.047629
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.854929,0.119071
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 0.982722 0.017278 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.000000 0.935092 0.064908 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.042667 0.911635 0.039382 0.000000 0.000000 0.000000 0.006316
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.854929 0.119071
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2015.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,0.987769,0.012231,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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B,0.000000,0.000000,0.000000,0.000000,0.033357,0.696715,0.122950,0.146978
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.040019,0.625156,0.328824
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 0.987769 0.012231 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.000000 0.942411 0.057589 0.000000 0.000000 0.000000 0.000000 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.040019 0.625156 0.328824
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2016.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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B,0.000000,0.000000,0.000000,0.000000,0.000000,0.770997,0.136058,0.092944
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1 AAA AA A BBB BB B CCC D
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.725061 0.248939
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2017.csv
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@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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B,0.000000,0.000000,0.000000,0.000000,0.037033,0.782552,0.138097,0.042318
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D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.042959 0.845245 0.105796
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2018.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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1 AAA AA A BBB BB B CCC D
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3 AA 0.002562 0.989769 0.007670 0.000000 0.000000 0.000000 0.000000 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.974000 0.000000
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2019.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,0.988467,0.011533,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 0.988467 0.011533 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.609263 0.364737
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2020.csv
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@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
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D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.000000 0.980288 0.019712 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.031368 0.950070 0.018561 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.000000 0.981861 0.015143 0.000000 0.002996 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.849003 0.124997
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2021.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
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BB,0.000000,0.000000,0.000000,0.000000,0.903741,0.077251,0.008583,0.010425
B,0.000000,0.000000,0.000000,0.000000,0.036290,0.785823,0.138675,0.039213
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.035699,0.872423,0.085878
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.000000 0.983165 0.016835 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.019705 0.980295 0.000000 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.045741 0.951264 0.000000 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.000000 0.903741 0.077251 0.008583 0.010425
7 B 0.000000 0.000000 0.000000 0.000000 0.036290 0.785823 0.138675 0.039213
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.035699 0.872423 0.085878
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2022.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.000000,0.988889,0.011111,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.024003,0.972968,0.003029,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.056490,0.932766,0.007749,0.000000,0.002996,0.000000
BB,0.000000,0.000000,0.000000,0.006520,0.938149,0.049798,0.005533,0.000000
B,0.000000,0.000000,0.000000,0.000000,0.000000,0.832292,0.146875,0.020833
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.921917,0.052083
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.000000 0.988889 0.011111 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.024003 0.972968 0.003029 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.056490 0.932766 0.007749 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.006520 0.938149 0.049798 0.005533 0.000000
7 B 0.000000 0.000000 0.000000 0.000000 0.000000 0.832292 0.146875 0.020833
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.921917 0.052083
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2023.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,0.985058,0.014942,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.012441,0.967654,0.019175,0.000346,0.000192,0.000192,0.000000,0.000000
A,0.000000,0.046798,0.925196,0.017851,0.000981,0.008194,0.000000,0.000981
BBB,0.000000,0.000324,0.122103,0.840895,0.015282,0.011434,0.002997,0.006966
BB,0.000000,0.000000,0.007813,0.059788,0.747704,0.087134,0.009682,0.087879
B,0.000000,0.000000,0.000000,0.009755,0.004878,0.688927,0.121575,0.174865
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.017235,0.714467,0.262298
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 0.985058 0.014942 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.012441 0.967654 0.019175 0.000346 0.000192 0.000192 0.000000 0.000000
4 A 0.000000 0.046798 0.925196 0.017851 0.000981 0.008194 0.000000 0.000981
5 BBB 0.000000 0.000324 0.122103 0.840895 0.015282 0.011434 0.002997 0.006966
6 BB 0.000000 0.000000 0.007813 0.059788 0.747704 0.087134 0.009682 0.087879
7 B 0.000000 0.000000 0.000000 0.009755 0.004878 0.688927 0.121575 0.174865
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.017235 0.714467 0.262298
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2024.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,0.989263,0.010737,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.009179,0.986330,0.004491,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.002861,0.987801,0.009338,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.000000,0.986259,0.010745,0.000000,0.002996,0.000000
BB,0.000000,0.000000,0.000000,0.019053,0.910296,0.052873,0.005875,0.011903
B,0.000000,0.000000,0.000000,0.000000,0.000000,0.748310,0.132055,0.119636
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.691617,0.282383
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 0.989263 0.010737 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.009179 0.986330 0.004491 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.002861 0.987801 0.009338 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.000000 0.986259 0.010745 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.019053 0.910296 0.052873 0.005875 0.011903
7 B 0.000000 0.000000 0.000000 0.000000 0.000000 0.748310 0.132055 0.119636
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.691617 0.282383
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/AVG_2025.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,0.997390,0.002610,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.005308,0.971845,0.022707,0.000140,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.018709,0.961237,0.018726,0.000443,0.000738,0.000000,0.000148
BBB,0.000000,0.000000,0.054288,0.926175,0.010365,0.004800,0.002997,0.001374
BB,0.000000,0.000000,0.000961,0.018349,0.881175,0.073681,0.009845,0.015990
B,0.000000,0.000000,0.000000,0.001442,0.059834,0.665919,0.117515,0.155290
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.054534,0.617403,0.322063
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 0.997390 0.002610 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.005308 0.971845 0.022707 0.000140 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.018709 0.961237 0.018726 0.000443 0.000738 0.000000 0.000148
5 BBB 0.000000 0.000000 0.054288 0.926175 0.010365 0.004800 0.002997 0.001374
6 BB 0.000000 0.000000 0.000961 0.018349 0.881175 0.073681 0.009845 0.015990
7 B 0.000000 0.000000 0.000000 0.001442 0.059834 0.665919 0.117515 0.155290
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.054534 0.617403 0.322063
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_1999.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,0.500000,0.500000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.000000,0.800000,0.200000,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.078454,0.705876,0.137215,0.000000,0.078454,0.000000,0.000000
BBB,0.000000,0.000000,0.040009,0.851838,0.040009,0.065144,0.003000,0.000000
BB,0.000000,0.000000,0.000000,0.176529,0.735269,0.079382,0.008820,0.000000
B,0.000000,0.000000,0.000000,0.071403,0.071403,0.546436,0.096430,0.214329
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.057122,0.401055,0.535823
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 0.500000 0.500000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.000000 0.800000 0.200000 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.078454 0.705876 0.137215 0.000000 0.078454 0.000000 0.000000
5 BBB 0.000000 0.000000 0.040009 0.851838 0.040009 0.065144 0.003000 0.000000
6 BB 0.000000 0.000000 0.000000 0.176529 0.735269 0.079382 0.008820 0.000000
7 B 0.000000 0.000000 0.000000 0.071403 0.071403 0.546436 0.096430 0.214329
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.057122 0.401055 0.535823
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2000.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.000000,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.081662,0.857174,0.040776,0.020388,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.079514,0.864444,0.053047,0.000000,0.002996,0.000000
BB,0.000000,0.000000,0.000000,0.064964,0.844180,0.046711,0.005190,0.038955
B,0.000000,0.000000,0.000000,0.000000,0.083322,0.672884,0.118744,0.125050
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.066658,0.525918,0.401424
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.081662 0.857174 0.040776 0.020388 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.079514 0.864444 0.053047 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.064964 0.844180 0.046711 0.005190 0.038955
7 B 0.000000 0.000000 0.000000 0.000000 0.083322 0.672884 0.118744 0.125050
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.066658 0.525918 0.401424
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2001.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.049979,0.950021,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.106349,0.829818,0.063832,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.030564,0.876112,0.061259,0.008688,0.003000,0.020376
BB,0.000000,0.000000,0.000000,0.095924,0.862930,0.024650,0.002739,0.013758
B,0.000000,0.000000,0.000000,0.000000,0.076950,0.653777,0.115372,0.153901
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.061560,0.332440,0.600000
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.049979 0.950021 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.106349 0.829818 0.063832 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.030564 0.876112 0.061259 0.008688 0.003000 0.020376
6 BB 0.000000 0.000000 0.000000 0.095924 0.862930 0.024650 0.002739 0.013758
7 B 0.000000 0.000000 0.000000 0.000000 0.076950 0.653777 0.115372 0.153901
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.061560 0.332440 0.600000
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2002.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.083374,0.916626,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.102050,0.897950,0.000000,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.057049,0.911431,0.028525,0.000000,0.002996,0.000000
BB,0.000000,0.000000,0.000000,0.114754,0.721311,0.118033,0.013115,0.032787
B,0.000000,0.000000,0.000000,0.000000,0.000000,0.667819,0.117850,0.214331
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.374000,0.600000
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.083374 0.916626 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.102050 0.897950 0.000000 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.057049 0.911431 0.028525 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.114754 0.721311 0.118033 0.013115 0.032787
7 B 0.000000 0.000000 0.000000 0.000000 0.000000 0.667819 0.117850 0.214331
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.374000 0.600000
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2003.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.129019,0.677454,0.193528,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.020426,0.938721,0.040853,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.053240,0.917088,0.026677,0.000000,0.002996,0.000000
BB,0.000000,0.000000,0.035714,0.107143,0.607143,0.192857,0.021429,0.035714
B,0.000000,0.000000,0.000000,0.000000,0.000000,0.784560,0.138452,0.076988
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.808039,0.165961
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.129019 0.677454 0.193528 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.020426 0.938721 0.040853 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.053240 0.917088 0.026677 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.035714 0.107143 0.607143 0.192857 0.021429 0.035714
7 B 0.000000 0.000000 0.000000 0.000000 0.000000 0.784560 0.138452 0.076988
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.808039 0.165961
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2004.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.050023,0.949977,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.134662,0.826882,0.038457,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.084410,0.898527,0.014068,0.000000,0.002996,0.000000
BB,0.000000,0.000000,0.000000,0.200000,0.450000,0.045000,0.005000,0.300000
B,0.000000,0.000000,0.000000,0.055556,0.000000,0.566667,0.100000,0.277778
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.374000,0.600000
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.050023 0.949977 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.134662 0.826882 0.038457 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.084410 0.898527 0.014068 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.200000 0.450000 0.045000 0.005000 0.300000
7 B 0.000000 0.000000 0.000000 0.055556 0.000000 0.566667 0.100000 0.277778
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.374000 0.600000
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2005.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.045479,0.954521,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.094301,0.867906,0.037793,0.000000,0.000000,0.000000,0.000000
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BB,0.000000,0.000000,0.000000,0.149988,0.799976,0.045032,0.005004,0.000000
B,0.000000,0.000000,0.000000,0.000000,0.000000,0.637500,0.112500,0.250000
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.374000,0.600000
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.045479 0.954521 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.094301 0.867906 0.037793 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.105697 0.891307 0.000000 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.149988 0.799976 0.045032 0.005004 0.000000
7 B 0.000000 0.000000 0.000000 0.000000 0.000000 0.637500 0.112500 0.250000
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.374000 0.600000
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2006.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.032255,0.935491,0.032255,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.147019,0.852981,0.000000,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.082392,0.869092,0.011754,0.022008,0.003000,0.011754
BB,0.000000,0.000000,0.058847,0.058847,0.647051,0.158766,0.017641,0.058847
B,0.000000,0.000000,0.000000,0.000000,0.000000,0.800019,0.141180,0.058802
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.826996,0.147004
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.032255 0.935491 0.032255 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.147019 0.852981 0.000000 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.082392 0.869092 0.011754 0.022008 0.003000 0.011754
6 BB 0.000000 0.000000 0.058847 0.058847 0.647051 0.158766 0.017641 0.058847
7 B 0.000000 0.000000 0.000000 0.000000 0.000000 0.800019 0.141180 0.058802
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.826996 0.147004
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2007.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
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9
data/real/KR_2008.csv
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@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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B,0.000000,0.000000,0.000000,0.000000,0.000000,0.760532,0.134212,0.105257
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D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.816115 0.157885
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2009.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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1 AAA AA A BBB BB B CCC D
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.651295 0.322705
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2010.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.037519,0.962481,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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B,0.000000,0.000000,0.000000,0.000000,0.038422,0.686561,0.121158,0.153859
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.030737,0.578614,0.384649
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1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.037519 0.962481 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.030737 0.578614 0.384649
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2011.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.474000 0.500000
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2012.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.140691 0.833309
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2013.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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A,0.000000,0.046726,0.915872,0.037402,0.000000,0.000000,0.000000,0.000000
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B,0.000000,0.000000,0.000000,0.000000,0.000000,0.772735,0.136365,0.090900
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1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.837650 0.136350
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2014.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,0.983845,0.016155,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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B,0.000000,0.000000,0.000000,0.000000,0.000000,0.789228,0.139276,0.071496
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1 AAA AA A BBB BB B CCC D
2 AAA 0.983845 0.016155 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
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5 BBB 0.000000 0.000000 0.023774 0.760530 0.095211 0.093711 0.003000 0.023774
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.795260 0.178740
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2015.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,0.981782,0.018218,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 0.981782 0.018218 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.837707 0.136293
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2016.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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BB,0.000000,0.000000,0.000000,0.000000,0.789500,0.142110,0.015790,0.052600
B,0.000000,0.000000,0.000000,0.000000,0.000000,0.719282,0.126932,0.153786
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.524379,0.449621
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
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4 A 0.000000 0.010064 0.969700 0.020236 0.000000 0.000000 0.000000 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.524379 0.449621
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2017.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.795429 0.178571
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2018.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
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4 A 0.000000 0.032247 0.957003 0.010749 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.086814 0.910191 0.000000 0.000000 0.002996 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.974000 0.000000
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2019.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,0.983300,0.016700,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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B,0.000000,0.000000,0.000000,0.000000,0.000000,0.743787,0.131257,0.124956
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D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 0.983300 0.016700 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.020358 0.948998 0.030644 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.047580 0.901844 0.047580 0.000000 0.002996 0.000000
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8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.661609 0.312391
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/KR_2020.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
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9
data/real/KR_2021.csv
View File

@@ -1,9 +0,0 @@
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9
data/real/KR_2022.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
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9
data/real/KR_2023.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
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9
data/real/KR_2024.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
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9
data/real/KR_2025.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
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9
data/real/NICE_1998.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
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9
data/real/NICE_1999.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
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9
data/real/NICE_2000.csv
View File

@@ -1,9 +0,0 @@
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9
data/real/NICE_2001.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
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9
data/real/NICE_2002.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
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1 AAA AA A BBB BB B CCC D
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9
data/real/NICE_2003.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
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9
data/real/NICE_2004.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
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data/real/NICE_2005.csv
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data/real/NICE_2006.csv
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data/real/NICE_2007.csv
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data/real/NICE_2008.csv
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data/real/NICE_2009.csv
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data/real/NICE_2010.csv
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data/real/NICE_2011.csv
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data/real/NICE_2012.csv
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data/real/NICE_2013.csv
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data/real/NICE_2014.csv
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data/real/NICE_2015.csv
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data/real/NICE_2016.csv
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data/real/NICE_2017.csv
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data/real/NICE_2018.csv
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data/real/NICE_2019.csv
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9
data/real/NICE_2020.csv
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9
data/real/NICE_2021.csv
View File

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data/real/NICE_2022.csv
View File

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data/real/NICE_2023.csv
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data/real/NICE_2024.csv
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data/real/NICE_2025.csv
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9
data/real/SCI_1998.csv
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9
data/real/SCI_1999.csv
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9
data/real/SCI_2000.csv
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9
data/real/SCI_2001.csv
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9
data/real/SCI_2002.csv
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2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.038518 0.961482 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.125030 0.874970 0.000000 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.034400 0.911004 0.051601 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.087637 0.719335 0.110539 0.012282 0.070207
7 B 0.000000 0.000000 0.000000 0.000000 0.117606 0.600028 0.105887 0.176479
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.094084 0.456299 0.443617
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/SCI_2003.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.033330,0.866681,0.099989,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.000000,0.926796,0.048768,0.000000,0.024436,0.000000,0.000000
BBB,0.000000,0.000000,0.086029,0.876515,0.034461,0.000000,0.002996,0.000000
BB,0.000000,0.000000,0.000000,0.057120,0.800000,0.102816,0.011424,0.028640
B,0.000000,0.000000,0.000000,0.000000,0.000000,0.765000,0.135000,0.100000
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.624838,0.349162
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.033330 0.866681 0.099989 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.000000 0.926796 0.048768 0.000000 0.024436 0.000000 0.000000
5 BBB 0.000000 0.000000 0.086029 0.876515 0.034461 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.057120 0.800000 0.102816 0.011424 0.028640
7 B 0.000000 0.000000 0.000000 0.000000 0.000000 0.765000 0.135000 0.100000
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.624838 0.349162
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

9
data/real/SCI_2004.csv
View File

@@ -1,9 +0,0 @@
,AAA,AA,A,BBB,BB,B,CCC,D
AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
AA,0.099974,0.849974,0.050052,0.000000,0.000000,0.000000,0.000000,0.000000
A,0.000000,0.079973,0.880040,0.039987,0.000000,0.000000,0.000000,0.000000
BBB,0.000000,0.000000,0.172859,0.785746,0.038399,0.000000,0.002996,0.000000
BB,0.000000,0.000000,0.000000,0.199970,0.650015,0.044959,0.004995,0.100060
B,0.000000,0.000000,0.000000,0.071474,0.000000,0.607096,0.107135,0.214295
CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.515052,0.458948
D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
1 AAA AA A BBB BB B CCC D
2 AAA 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
3 AA 0.099974 0.849974 0.050052 0.000000 0.000000 0.000000 0.000000 0.000000
4 A 0.000000 0.079973 0.880040 0.039987 0.000000 0.000000 0.000000 0.000000
5 BBB 0.000000 0.000000 0.172859 0.785746 0.038399 0.000000 0.002996 0.000000
6 BB 0.000000 0.000000 0.000000 0.199970 0.650015 0.044959 0.004995 0.100060
7 B 0.000000 0.000000 0.000000 0.071474 0.000000 0.607096 0.107135 0.214295
8 CCC 0.000000 0.000000 0.001000 0.002000 0.003000 0.020000 0.515052 0.458948
9 D 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000

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