initial commit

2026-05-26 12:43:47 +02:00
commit b43fbe2170
20 changed files with 1619 additions and 0 deletions
@@ -0,0 +1,103 @@
+import os
+from datetime import datetime
+
+
+class Config:
+    # Data settings
+    DATA_DIR = os.path.join(os.path.dirname(__file__), "data")
+    RAW_DATA_DIR = os.path.join(DATA_DIR, "raw")
+    PROCESSED_DATA_DIR = os.path.join(DATA_DIR, "processed")
+    EXTERNAL_DATA_DIR = os.path.join(DATA_DIR, "external")
+
+    # Ensure directories exist
+    os.makedirs(RAW_DATA_DIR, exist_ok=True)
+    os.makedirs(PROCESSED_DATA_DIR, exist_ok=True)
+    os.makedirs(EXTERNAL_DATA_DIR, exist_ok=True)
+
+    # Stock universe settings
+    INITIAL_TICKERS = [
+        "AAPL",
+        "MSFT",
+        "GOOGL",
+        "AMZN",
+        "META",
+        "TSLA",
+        "NVDA",
+        "JPM",
+        "V",
+        "WMT",
+        "PG",
+        "DIS",
+        "NFLX",
+        "ADBE",
+        "PYPL",
+        "INTC",
+        "CSCO",
+        "PEP",
+        "KO",
+        "XOM",
+    ]
+    INDEX_TICKER = "^GSPC"  # S&P 500
+    DELISTED_TICKERS_FILE = os.path.join(EXTERNAL_DATA_DIR, "delisted_stocks.csv")
+
+    # Date settings
+    START_DATE = "2010-01-01"
+    END_DATE = datetime.now().strftime("%Y-%m-%d")
+    TRAIN_END_DATE = "2020-12-31"
+    VAL_END_DATE = "2021-12-31"
+
+    # Model settings
+    MODEL_DIR = os.path.join(os.path.dirname(__file__), "models")
+    os.makedirs(MODEL_DIR, exist_ok=True)
+    MODEL_NAME = "stock_gnn"
+    HIDDEN_CHANNELS = 64
+    NUM_HEADS = 8
+    DROPOUT = 0.6
+    LEARNING_RATE = 0.001
+    EPOCHS = 100
+    BATCH_SIZE = 32
+    LOOKBACK_WINDOW = 30  # Days for feature calculation
+
+    # Backtesting settings
+    INITIAL_CAPITAL = 100000
+    TRANSACTION_COST = 0.001  # 0.1% per trade
+
+    # Evaluation settings
+    BENCHMARK_TICKER = "^GSPC"
+
+    # News data settings
+    NEWS_API_KEY = "your_news_api_key"  # For NewsAPI or similar
+    NEWS_SOURCES = ["reuters", "bloomberg", "financial-times", "wsj"]
+    NEWS_CATEGORIES = ["business", "financial", "economy"]
+    NEWS_LOOKBACK_DAYS = 7  # Number of days to look back for news
+
+    # Social media settings
+    TWITTER_BEARER_TOKEN = "your_twitter_bearer_token"
+    REDDIT_CLIENT_ID = "your_reddit_client_id"
+    REDDIT_CLIENT_SECRET = "your_reddit_client_secret"
+    SOCIAL_MEDIA_LOOKBACK_DAYS = 3  # Number of days to look back for social media
+
+    # Sentiment analysis settings
+    SENTIMENT_MODEL = "vader"  # 'vader', 'finbert', or 'custom'
+    FINBERT_MODEL_PATH = "yiyanghkust/finbert-tone"  # HuggingFace model path
+
+    # Alternative data features
+    NEWS_FEATURES = [
+        "sentiment_score",
+        "mention_count",
+        "positive_score",
+        "negative_score",
+    ]
+    SOCIAL_FEATURES = [
+        "twitter_sentiment",
+        "reddit_sentiment",
+        "twitter_volume",
+        "reddit_volume",
+    ]
+    ALTERNATIVE_DATA_WEIGHT = 0.3  # Weight for alternative data in final prediction
+
+    # Database settings for alternative data
+    ALTERNATIVE_DATA_DB = os.path.join(DATA_DIR, "alternative_data.db")
+
+
+config = Config()