run_all.py

if __name__ == '__main__':
    # the subdirectory for my project you may need to change this
    base_dir = "./BollingerBot/"  
    img_dir = base_dir + "imgs/"
    tickers = pd.read_csv(base_dir + "sp500tickers.csv")["symbol"].tolist()
    end_dt = datetime.datetime.today()
    start_dt = datetime.datetime(end_dt.year - 1, end_dt.month, end_dt.day)
    api = YahooFinanceAPI(Interval.DAILY)

    progress_count = 1
    results_dict = {
        "ticker": [],
        "profit": [],
        "avg_return": [],
        "start_price": []
    }
    for ticker in tickers:
        print("Processing ticker symbol {} ({} out of {}).".format(ticker.upper(), progress_count, len(tickers)))
        try:
            # fetch the data
            data = api.get_ticker_data(ticker, start_dt, end_dt)
        except:
            # don't care if we can't
            progress_count += 1
            continue

        data['ma'] = get_sma(data["Close"], 20) # get 20-period SMA
        data['upper'], data['lower'] = get_bollinger_bands(data['Close'], data['ma'], 20)

        # plot the bands + close price
        data['Close'][20:].plot(label='close', color='darkcyan')
        data['ma'].plot(label='mid', linestyle='--', linewidth='0.9', color='darkturquoise')
        data['upper'].plot(label='upper', linestyle='--', linewidth='1.1', color='indianred')
        data['lower'].plot(label='lower', linestyle='--', linewidth='1.1', color='lightgreen')

        # determine trades, calculate profit, and store results
        trades = get_buy_sell_points(data)
        avg_return, profit = calculate_profits(trades, ticker, base_dir)
        results_dict["ticker"].append(ticker.upper())
        results_dict["profit"].append(profit)
        results_dict["avg_return"].append(avg_return)
        results_dict["start_price"].append(data.loc[0]["Close"])

        print("Average return per trade: {}\t\tTotal profit trading one share: {}".format(avg_return, profit))

        # plot the trades and make the graph prettier
        plt.scatter(trades["buy_indices"], trades["buy_prices"], marker="^", color="darkgreen", s=100, label="buy")
        plt.scatter(trades["sell_indices"], trades["sell_prices"], marker="v", color="darkred", s=100, label="sell")
        plt.title("Bollinger Bands w/ Trades for {}".format(ticker.upper()))
        plt.legend(loc='upper left')
        plt.savefig(img_dir + "{}_plot.png".format(ticker.upper()))
        #plt.show()
        plt.clf()
        progress_count += 1
    
    # export the results to CSV
    results_df = pd.DataFrame.from_dict(results_dict)
    results_df.to_csv(base_dir + "results.dat", index=False)