Commit f8d7bd1

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style: format code with autopep8

Format code with autopep8 This commit fixes the style issues introduced in faf42a4 according to the output from Autopep8. Details: None

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Algorithmic Trading Simulation
- algorithmic_trading_simulation.py

1 file changed

+19

-10

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`‎Algorithmic Trading Simulation/algorithmic_trading_simulation.py‎`

Lines changed: 19 additions & 10 deletions

Original file line number	Diff line number	Diff line change
`@@ -16,19 +16,25 @@`
`16`	`16`	`df.set_index('Date', inplace=True)`
`17`	`17`
`18`	`18`	`# Example trading strategy`
	`19`	`+`
	`20`	`+`
`19`	`21`	`def simple_moving_average_strategy(data, short_window, long_window):`
`20`	`22`	`signals = pd.DataFrame(index=data.index)`
`21`	`23`	`signals['Signal'] = 0.0`
`22`		`-`
`23`		`- signals['Short_MA'] = data['Close'].rolling(window=short_window, min_periods=1, center=False).mean()`
`24`		`- signals['Long_MA'] = data['Close'].rolling(window=long_window, min_periods=1, center=False).mean()`
`25`		`-`
`26`		`- signals['Signal'][short_window:] = np.where(signals['Short_MA'][short_window:] > signals['Long_MA'][short_window:], 1.0, 0.0)`
`27`		`-`
	`24`	`+`
	`25`	`+ signals['Short_MA'] = data['Close'].rolling(`
	`26`	`+ window=short_window, min_periods=1, center=False).mean()`
	`27`	`+ signals['Long_MA'] = data['Close'].rolling(`
	`28`	`+ window=long_window, min_periods=1, center=False).mean()`
	`29`	`+`
	`30`	`+ signals['Signal'][short_window:] = np.where(`
	`31`	`+ signals['Short_MA'][short_window:] > signals['Long_MA'][short_window:], 1.0, 0.0)`
	`32`	`+`
`28`	`33`	`signals['Positions'] = signals['Signal'].diff()`
`29`		`-`
	`34`	`+`
`30`	`35`	`return signals`
`31`	`36`
	`37`	`+`
`32`	`38`	`# Define strategy parameters`
`33`	`39`	`short_window = 10`
`34`	`40`	`long_window = 50`
`@@ -45,8 +51,10 @@ def simple_moving_average_strategy(data, short_window, long_window):`
`45`	`51`	`portfolio_value = []`
`46`	`52`	`for index, row in signals.iterrows():`
`47`	`53`	`if row['Positions'] == 1:`
`48`		`- max_position_size = (risk_per_trade * initial_portfolio_value) / (row['Close'] - row['Low'])`
`49`		`- position = min(max_position_size, initial_portfolio_value / row['Close'])`
	`54`	`+ max_position_size = (`
	`55`	`+ risk_per_trade * initial_portfolio_value) / (row['Close'] - row['Low'])`
	`56`	`+ position = min(max_position_size,`
	`57`	`+ initial_portfolio_value / row['Close'])`
`50`	`58`	`initial_portfolio_value -= position * row['Close']`
`51`	`59`	`elif row['Positions'] == -1:`
`52`	`60`	`initial_portfolio_value += position * row['Close']`
`@@ -66,7 +74,8 @@ def simple_moving_average_strategy(data, short_window, long_window):`
`66`	`74`	`plt.title('Price Data and Moving Averages')`
`67`	`75`
`68`	`76`	`plt.subplot(2, 1, 2)`
`69`		`-plt.plot(signals.index, signals['PortfolioValue'], label='Portfolio Value', linestyle='--', color='green')`
	`77`	`+plt.plot(signals.index, signals['PortfolioValue'],`
	`78`	`+ label='Portfolio Value', linestyle='--', color='green')`
`70`	`79`	`plt.legend()`
`71`	`80`	`plt.title('Portfolio Value')`
`72`	`81`

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`‎Algorithmic Trading Simulation/algorithmic_trading_simulation.py‎`

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