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import yfinance |
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stocks = ['ARM', 'META', 'SPY', 'TSLA'] |
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data = yfinance.download(stocks, |
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'2024-04-01', |
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'2024-05-09')['Close'] |
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returns = data.pct_change() |
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returns.head() |
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returns = returns.dropna() |
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returns.head() |
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average_daily_returns = returns.mean() |
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print(average_daily_returns) |
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standard_deviation_daily_returns = returns.std() |
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print(standard_deviation_daily_returns) |
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import numpy |
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weights = numpy.array([0.25, 0.25, 0.25, 0.25]) |
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covariance_matrix = (returns.cov())*250 |
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expected_portfolio_performace = numpy.sum(average_daily_returns * weights) |
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print(expected_portfolio_performance) |
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returns['Portfolio Returns'] = returns.dot(weights) |
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returns.head() |
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daily_cumulative_returns = (1+returns).cumprod() |
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print(daily_cumulative_returns) |
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daily_cumulative_returns.tail() |
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