.py

# Fade if price closes outside of running 1h % change (w/2h ema)... closes after 15m.
close_time = 1
pct_change = 4
smoothing = 8

results = []
for ticker in tqdm(sp):
    
    data = pd.read_json(json.load(open('./{}/{}.json'.format(data_path, ticker), 'r')))

    # Setting up for pybacktest
    ohlc = data.rename(columns={'open': 'O', 'high': 'H', 'low': 'L', 'close': 'C', 'volume': 'V'})
    ohlc = hb_lb(ohlc, pct_change, smoothing)
    buy, cover, sell, short = get_signals(close_time)

    bt = pybacktest.Backtest(locals(), 'MR pct_period: {}, close_time: {}, ticker: {}'.format(pct_change, close_time, ticker))

    e = pd.concat([
        bt.trades,
        bt.equity
    ], axis=1)

    # Allocating capital equally between symbols (using fractional share amounts)
    e['shares'] = e.apply(lambda x: capital/len(sp)/x['price'], axis=1)
    e['change'] = e[0] * e['shares']

    results.append({
        'ticker': ticker,
        'trades': e
    })