What is ctx.stop_trailing for?

[edtechre]

What is ctx.stop_trailing for?

[none2003]

Hi @edtechre

I tried your code, but it still doesn't work, no trade happens.
So I made some changes to your code based on my understanding of ATR Trailing Stop.
I list code below, in case anyone needs it.

def exec_fn(ctx: ExecContext):
    if ctx.long_pos():
        stop = ctx.session.setdefault(
            "stop",
            ctx.close[-1] - ctx.indicator("atr_100")[-1] * 2
        )
        stop = max(
            stop,
            ctx.close[-1] - ctx.indicator("atr_100")[-1] * 2,
        )
        if ctx.low[-1] <= stop:
            ctx.sell_all_shares()
            del ctx.session["stop"]
        else:
            ctx.session["stop"] = stop
    elif ctx.short_pos():
        stop = ctx.session.setdefault(
            "stop",
            ctx.close[-1] + ctx.indicator("atr_100")[-1] * 2
        )
        stop = min(
            stop,
            ctx.close[-1] + ctx.indicator("atr_100")[-1] * 2,
        )
        if ctx.high[-1] >= stop:
            ctx.cover_all_shares()
            del ctx.session["stop"]
        else:
            ctx.session["stop"] = stop
    else:
        # some buy/long or sell/short code here
        pass

[edtechre]

Hi @none2003,

The field stop_trailing will behave just like stop_trailing_pct, except the units are set in absolute price points.

The reason the code isn't working is that the stop is created when the entry is created (i.e., ctx.buy_shares) and cannot be updated afterwards because each stop only applies to its associated entry.

To support your case of dynamically updating the stop, I can add support for setting a Callable that would return the points amount based on the current context (e.g., ATR).

In the meantime, you can determine if a stop is hit by checking ctx.long_pos() and ctx.high. Additionally, you can then update and save the stop threshold in ctx.session to achieve the trailing behavior.

[edtechre]

After considering this further, I have come to the conclusion that introducing support for dynamic stop values using Callables would make the API confusing. The desired behavior can already be achieved using the execution function. Because stop thresholds are intended to be static, I have implemented checks to prevent your example from failing silently. Instead, it will now throw an error.

To achieve what you are after, you can reference this code:

import pybroker as pyb
import talib

def exec_fn(ctx):
    if ctx.long_pos():
        stop = ctx.session.setdefault(
            "stop",
            ctx.high[-1] - ctx.indicator("atr_100")[-1] * 2
        )
        if ctx.low[-1] <= stop:
            ctx.sell_all_shares()
            del ctx.session["stop"]
        else:
            ctx.session["stop"] = max(
                stop,
                ctx.high[-1] - ctx.indicator("atr_100")[-1] * 2, 
            )
    else:
        ctx.buy_shares = ctx.calc_target_shares(1)
    
atr_100 = pyb.indicator("atr_100", lambda data: talib.ATR(data.high, data.low, data.close, timeperiod=100))
strategy.clear_executions()
strategy.add_execution(exec_fn, ['TSLA'], indicators=atr_100)
result = strategy.backtest(warmup=100)

Let me know if you need anything else!

[edtechre]

Whether a trade is made is going to depend on the data you're using for the backtest. My example uses the daily high price instead of close for updating the stop, and it placed trades for my dataset. But glad you have something working, thanks for sharing!

[none2003]

After considering this further, I have come to the conclusion that introducing support for dynamic stop values using Callables would make the API confusing. The desired behavior can already be achieved using the execution function. Because stop thresholds are intended to be static, I have implemented checks to prevent your example from failing silently. Instead, it will now throw an error.

To achieve what you are after, you can reference this code:

import pybroker as pyb
import talib

def exec_fn(ctx):
    if ctx.long_pos():
        stop = ctx.session.setdefault(
            "stop",
            ctx.high[-1] - ctx.indicator("atr_100")[-1] * 2
        )
        if ctx.low[-1] <= stop:
            ctx.sell_all_shares()
            del ctx.session["stop"]
        else:
            ctx.session["stop"] = max(
                stop,
                ctx.high[-1] - ctx.indicator("atr_100")[-1] * 2, 
            )
    else:
        ctx.buy_shares = ctx.calc_target_shares(1)
    
atr_100 = pyb.indicator("atr_100", lambda data: talib.ATR(data.high, data.low, data.close, timeperiod=100))
strategy.clear_executions()
strategy.add_execution(exec_fn, ['TSLA'], indicators=atr_100)
result = strategy.backtest(warmup=100)

Let me know if you need anything else!

@edtechre,

I have a question about the timing of the trailing stop trigger in pyb. If ctx.buy_shares is executed along with ctx.stop_trailing_pct.

My understanding is that pyb calculates a stop loss level for each bar, so question 1, this stop loss level is calculated based on what price minus stop_trailing_pct? high[-1]?

Once the price of a bar falls below this stop level, then the stop loss will be triggered, so question 2, which of the ohlc specifically falls below the stop level and triggers the stop loss?

Question 3, after the stop is triggered, is the timing for the order to be fulfilled at the moment it is triggered, or at the next bar? This is related to the code you provided above, in your code, the trailing stop order will be fulfilled at the next bar, rather than at the moment stop loss was trigged.

Question 4, if it is at the next bar, which of the ohlc will be the price to fulfill tailing stop order?