PnL Ratio - long short¶

Market sentiment is high when everyone is profit on paper, and vice versa. Can we use this as an indicator to trade?

Comment¶

When there is a long bear market in the time series, the long short strategy will usually benefit in that period. However, in reality a trader cannot predict a bull or bear market from happening, not to mention how long it will last. Moreover, short selling is high risk because the volatility is usually higher in the bear market, especially during the panic selling period.

Data¶

In [1]:

from btbox import *
from pandas import Series

In [2]:

SYMBOL = 'QQQ'
START = '2001-01-01'
WINDOW = 365
INTERVAL = 5

In [3]:

dfs = {SYMBOL: import_yahoo_csv(f'../../_data_/{SYMBOL}_bar1d.csv')}

Benchmark¶

In [4]:

class BM_AllInAndForget(Strategy):

    def initial(self, b: Broker):
        b.portfolio.trade_target_weight(SYMBOL, 1)


class BM_KeepAtHalf(Strategy):

    @interval(INTERVAL)
    def step(self, b: Broker):
        b.portfolio.trade_target_weight(SYMBOL, 0.5)

Indicator¶

In [5]:

def pnl_ratio(win: Series) -> float:
    pnlr = win.rank(pct=True)
    return pnlr[-1]

Strategy¶

In [6]:

def ST_LongShortPnL(min, max):

    offset = max - min

    class ST(Strategy):
        name = f'ST_LongShortPnl_range[{min},{max}]'

        @interval(INTERVAL)
        def step(self, b: Broker):
            win = b.market.get_close_window(SYMBOL)
            pnlr = pnl_ratio(win)
            weight = min + offset * pnlr
            b.portfolio.trade_target_weight(SYMBOL, weight)
            self.journal.mark(weight, 'weight')

    return ST

Backtest¶

In [7]:

bt = create_backtest(
    [
        BM_AllInAndForget,
        BM_KeepAtHalf,
        ST_LongShortPnL(0, 1),
        ST_LongShortPnL(-0.2, 1),
        ST_LongShortPnL(-0.2, 1.5),
        ST_LongShortPnL(-0.5, 1.5),
    ],
    dfs,
    start=START,
    window=WINDOW,
)

In [8]:

results = bt.run()

Dashboard¶

In [9]:

results.dashboard_pretty()

Out[9]:

	return	cagr	mu	sigma	mdd	duration	sharpe	calmar
BM_AllInAndForget	522.9%	8.71%	11.54%	25.33%	-70.40%	624 days 00:00	0.456	0.164
BM_KeepAtHalf	188.1%	4.95%	5.62%	12.61%	-43.48%	624 days 00:00	0.446	0.129
ST_LongShortPnl_range[0,1]	544.0%	8.87%	9.53%	14.38%	-25.57%	26 days 00:00	0.663	0.373
ST_LongShortPnl_range[-0.2,1]	507.9%	8.59%	9.21%	13.98%	-24.97%	26 days 00:00	0.659	0.369
ST_LongShortPnl_range[-0.2,1.5]	1,242.7%	12.59%	14.08%	21.12%	-36.07%	26 days 00:00	0.667	0.390
ST_LongShortPnl_range[-0.5,1.5]	1,102.2%	12.02%	13.64%	21.39%	-35.24%	26 days 00:00	0.638	0.387

Equity Curve¶

In [10]:

results.plot(log_y=True)

Evaluation¶

In [11]:

results['ST_LongShortPnl_range[-0.2,1.5]'].journals['weight'].ffill.plot_line_under_price(SYMBOL)