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The Price Channel Robot White Box Strategy is a simple mechanical trading strategy based on the price channel indicator. It uses the upper and lower limits of the price channel to determine entry and exit points. The strategy goes long on uptrend and goes short on downtrend.

The core logic of the Price Channel Robot White Box Strategy is:

- Use highest and lowest functions to calculate the highest high and lowest low of recent len bars, defined as upper and lower limits of the price channel
- Calculate middle price of price channel: (highest high + lowest low) / 2
- Go long when price breaks above the upper limit of price channel
- Go short when price breaks below the lower limit of price channel
- Close position when price pulls back to the middle price of price channel

The strategy also has some configurable parameters:

- Price channel length len: default 50 bars
- Trade direction: long, short can be configured separately
- Trade size: default 100% of account equity
- Stop loss: option to use middle price as stop loss
- Trading hours: only trade within configured date range

By adjusting these parameters, the strategy can be better adapted to different products and market environments.

The Price Channel Robot White Box Strategy has the following advantages:

- Simple logic, easy to understand and implement
- Make full use of price channel indicator to determine trend and reversal
- Highly configurable parameters for better adaptability
- Built-in stop loss mechanism to limit losses
- Support time filter to avoid impacts of major events

In summary, it is a simple yet practical trend following strategy, which can achieve decent results after parameter tuning.

The Price Channel Robot White Box Strategy also has some risks:

- Price channel indicator is sensitive to parameter len, independent testing and optimization needed for different timeframes and products
- Tracking stop loss has risk of being stopped out prematurely, stop loss distance needs adjustment based on market volatility
- Excessive meaningless trades during range-bound and sideways markets, increasing transaction costs and slippage

To reduce these risks, optimization needs to be done in the following aspects:

- Use Walk Forward Analysis to auto optimize parameters
- Add buffer zone to stop loss price to avoid being stopped out
- Add trend filter to avoid trading in sideways market

There is room for further optimization of the Price Channel Robot White Box Strategy:

- Add judgement of higher timeframe trend to avoid counter trend trading
- Use price spread between correlated products to set parameters and utilize arbitrage opportunities
- Add random buffer to stop loss price to reduce chance of stopped out
- Dynamically adjust price channel parameter len based on market volatility
- Train agent with deep learning methods to optimize strategy for specific products

These optimization techniques could help further improve the stability and profitability of the strategy.

The Price Channel Robot White Box Strategy is a simple yet practical trend following strategy. It identifies trend direction and reversal points using the price channel indicator to make trading decisions. The strategy is easy to understand and implement, and can achieve decent returns after parameter tuning. There are also certain risks that need to be mitigated through optimizing parameters and stop loss. Overall, the strategy has broad application prospects and optimization potential, worth exploring and practicing.

/*backtest start: 2023-02-21 00:00:00 end: 2024-02-27 00:00:00 period: 1d basePeriod: 1h exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //Noro //@version=4 strategy(title = "Robot WhiteBox Channel", shorttitle = "Robot WhiteBox Channel", overlay = true, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, pyramiding = 0, commission_value = 0.1) //Settings needlong = input(true, defval = true, title = "Long") needshort = input(true, defval = true, title = "Short") needstop = input(true, defval = true, title = "Stop-loss") lotsize = input(100, defval = 100, minval = 1, maxval = 10000, title = "Lot, %") len = input(50, minval = 1, title = "Price Channel Length") showll = input(true, defval = true, title = "Show lines") showbg = input(false, defval = false, title = "Show Background") fromyear = input(1900, defval = 1900, minval = 1900, maxval = 2100, title = "From Year") toyear = input(2100, defval = 2100, minval = 1900, maxval = 2100, title = "To Year") frommonth = input(01, defval = 01, minval = 01, maxval = 12, title = "From Month") tomonth = input(12, defval = 12, minval = 01, maxval = 12, title = "To Month") fromday = input(01, defval = 01, minval = 01, maxval = 31, title = "From day") today = input(31, defval = 31, minval = 01, maxval = 31, title = "To day") //Price Channel h = highest(high, len) l = lowest(low, len) center = (h + l) / 2 //Lines pccol = showll ? color.black : na slcol = showll ? color.red : na plot(h, offset = 1, color = pccol) plot(center, offset = 1, color = slcol) plot(l, offset = 1, color = pccol) //Background size = strategy.position_size bgcol = showbg == false ? na : size > 0 ? color.lime : size < 0 ? color.red : na bgcolor(bgcol, transp = 70) //Trading truetime = time > timestamp(fromyear, frommonth, fromday, 00, 00) and time < timestamp(toyear, tomonth, today, 23, 59) lot = 0.0 lot := size != size[1] ? strategy.equity / close * lotsize / 100 : lot[1] if h > 0 strategy.entry("Long", strategy.long, needlong == false ? 0 : lot, stop = h, when = strategy.position_size <= 0 and truetime) strategy.entry("Short", strategy.short, needshort == false ? 0 : lot, stop = l, when = strategy.position_size >= 0 and truetime) strategy.entry("S Stop", strategy.long, 0, stop = center, when = strategy.position_size[1] <= 0 and needstop) strategy.entry("L Stop", strategy.short, 0, stop = center, when = strategy.position_size[1] >= 0 and needstop) if time > timestamp(toyear, tomonth, today, 23, 59) strategy.close_all() strategy.cancel("Long") strategy.cancel("Short")

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