multi-stock-testing-strategies.py

import yfinance as yfinance
import pandas as data_frame
import numpy as numerical

def retrieve_stock_data(symbol, begin_date, finish_date):
    """
    Obtain historical stock data from Yahoo Finance.
    """
    historical_data = yfinance.download(symbol, start=begin_date, end=finish_date)
    return historical_data

def compute_returns(historical_data, time_frames):
    """
    Compute returns for specified time frames.
    """
    outcome = {}
    for time_frame in time_frames:
        # Compute returns for the given time frame
        historical_data[f'returns_{time_frame}'] = historical_data['Adj Close'].pct_change(periods=time_frame).shift(-time_frame)
        # Add to outcome dictionary
        outcome[time_frame] = historical_data[f'returns_{time_frame}']
    return outcome

def evaluate_strategies(symbols, begin_date, finish_date, intervals):
    """
    Evaluate different investment strategies and compute potential returns across multiple symbols.
    """
    for symbol in symbols:
        print(f"Evaluating {symbol}...")
        try:
            # Retrieve stock data
            historical_data = retrieve_stock_data(symbol, begin_date, finish_date)
            
            # Compute returns
            outcomes = compute_returns(historical_data, intervals)
            
            # Display summary statistics for each interval
            for interval, returns_data in outcomes.items():
                print(f"Investment strategy for {symbol}: Hold for {interval} days")
                print(returns_data.describe())
                print("\n")
        except Exception as error:
            print(f"Failed to evaluate {symbol} due to: {error}")

# Specify tickers for evaluation
symbols = ['AAPL', 'MSFT', 'GOOGL', 'META']  # Update with real symbols

# Set analysis period
begin_date = '2010-01-01'
finish_date = '2023-01-01'

# Define intervals for holding in days (from 2 weeks to 5 years)
intervals = [14, 28, 60, 180, 365, 730, 1095, 1460, 1825]

evaluate_strategies(symbols, begin_date, finish_date, intervals)