57 lines
2.1 KiB
Python
57 lines
2.1 KiB
Python
import sqlite3
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import pandas as pd
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conn = sqlite3.connect('C:/Users/Variet-Worker/Desktop/climate_risk/data/climate_risk.db')
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cur = conn.cursor()
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# Drop if exists
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cur.execute("DROP TABLE IF EXISTS firm_reference_data")
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# Create table
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cur.execute("""
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CREATE TABLE firm_reference_data (
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asset_code TEXT PRIMARY KEY,
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asset_name TEXT,
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ksic_code TEXT,
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gics_sector TEXT,
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credit_rating TEXT
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)
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""")
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# Reference Data based on actual benchmark entities
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ref_data = [
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# Ticker, Name, KSIC, GICS, Rating
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('005930.KS', 'Samsung Electronics', 'C', 'Information Technology', 'AA-'),
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('000660.KS', 'SK Hynix', 'C', 'Information Technology', 'A'),
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('005380.KS', 'Hyundai Motor', 'C', 'Consumer Discretionary', 'A+'),
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('035420.KS', 'NAVER', 'J', 'Communication Services', 'AA-'),
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('051910.KS', 'LG Chem', 'C', 'Materials', 'A+'),
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('105560.KS', 'KB Financial', 'K', 'Financials', 'AAA'),
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('055550.KS', 'Shinhan Financial', 'K', 'Financials', 'AAA'),
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('032830.KS', 'Samsung Life', 'K', 'Financials', 'AAA'),
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('015760.KS', 'KEPCO', 'D', 'Utilities', 'AAA'), # Using D for Utilities logic mapping
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('KS200', 'KOSPI 200 Index', 'C', 'Index', 'AA'), # Approximate proxy
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('HSCEI', 'HSCEI Index', 'K', 'Index', 'A'),
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('SPX', 'S&P 500 Index', 'C', 'Index', 'AA'),
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('USDKRW', 'USD/KRW FX', 'FX', 'Currency', 'AAA'),
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('XAUUSD', 'Gold/USD', 'CM', 'Commodity', 'AAA'),
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('KTB_10Y', 'Korea Treasury Bond 10Y', 'GOV', 'Sovereign', 'AA'),
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('KR103501G000', 'Korea Treasury Bond 3Y (03125-2606)', 'GOV', 'Sovereign', 'AA'),
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('KR600538012C', 'Hyundai Motor 316-1 Unsecured', 'C', 'Corporate Bond', 'A+'),
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('KR600593000A', 'Samsung Elec 1st Unsecured', 'C', 'Corporate Bond', 'AA-'),
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('KR610556011B', 'KB Financial 2024-1 Bank Debenture', 'K', 'Corporate Bond', 'AAA'),
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('CD91D', 'KRW CD 91D', 'GOV', 'Rate', 'AAA'),
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('SOFR', 'USD SOFR', 'GOV', 'Rate', 'AAA'),
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]
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for row in ref_data:
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cur.execute("INSERT INTO firm_reference_data VALUES (?, ?, ?, ?, ?)", row)
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conn.commit()
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df = pd.read_sql("SELECT * FROM firm_reference_data", conn)
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print("Firm Reference Data generated:")
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print(df.to_markdown())
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conn.close()
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