ChaoZhang
概述
该策略基于前一交易日的最高价进行操作,属于趋势跟踪类型策略。它会在突破前一交易日的最高价时开多仓,即使当天有多次突破也会重复开仓。
策略原理
使用LucF函数避免回测时偷看最新K线。
判断是否是新交易日开盘。记录当天最高价max_today和最低价min_today。
比较当前最高价high和max_today,更新max_today。
比较当前最低价low和min_today,更新min_today。
画出前一交易日的最高价和最低价。
设置突破前一交易日最高价时的开仓点,可以在最高价上添加一定幅度的GAP以延迟或提前入场。
设置止损比例sl和止盈比例tp。
当价格突破前一交易日最高价时开多仓。
设置止损点和止盈点。
可以选择是否开启追踪止损,设置启动追踪止损的最低要求、追踪止损的距离。
可以选择关闭时是否判断EMA状态。
优势分析
这是一个相对简单的趋势跟踪策略,具有如下优势:
策略信号简单明确,易于实现。
利用前一交易日最高价的突破形成的趋势确认信号,可以有效过滤震荡市场的噪音。
可以通过GAP参数调节进场的灵敏度。
整体风险可控,止损清晰。
可以选择是否使用追踪止损来锁定更多利润。
可以结合EMA判断来避免死叉时被套。
风险分析
该策略也存在一些风险需要注意:
突破失败可能造成损失,需要合理设置止损价位。
突破有效性依赖于市场处于趋势状态,震荡市场中容易被套。
追踪止损如果设置不当可能过于灵敏,被价格小幅调整止损。
EMA判断如果参数选择不当也可能过于灵敏或迟钝。
需要关注和优化的变量较多,如GAP、止损幅度、追踪止损设置等。
优化方向
可以从以下几个方面继续优化该策略:
将止损从固定值调整为ATR或趋势的动态止损。
增加通过标准差过滤来判断突破有效性。
增加基于波动率的条件来避免震荡行情的无效突破。
优化EMA参数,使得判断更稳定和准确。
优化追踪止损的参数,使其更符合市场波动的幅度。
测试不同品种的参数健壮性。
增加动态调整仓位大小的机制。
总结
该策略整体较为简单实用,属于典型的趋势跟踪策略,以前一交易日最高价的突破作为信号来追踪趋势,风险控制主要依靠止损来实现。通过合理的参数优化,可以使策略在趋势行情中获得较好的效果。但需要注意控制止损策略和过滤条件,避免在震荡行情中被套。该策略可以作为趋势跟踪策略的基础框架进行拓展优化。
策略源码
/*backtest
start: 2023-09-30 00:00:00
end: 2023-10-07 00:00:00
period: 15m
basePeriod: 5m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
// This source code is subject to the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
// © TheSocialCryptoClub
//@version=5
strategy("Yesterday's High", overlay=true, pyramiding = 1,
initial_capital=10000,
default_qty_type=strategy.percent_of_equity, default_qty_value=10,
slippage=1, backtest_fill_limits_assumption=1, use_bar_magnifier=true,
commission_type=strategy.commission.percent, commission_value=0.075
)
// -----------------------------------------------------------------------------
// ROC Filter
// -----------------------------------------------------------------------------
// f_security function by LucF for PineCoders available here: https://www.tradingview.com/script/cyPWY96u-How-to-avoid-repainting-when-using-security-PineCoders-FAQ/
f_security(_sym, _res, _src, _rep) => request.security(_sym, _res, _src[not _rep and barstate.isrealtime ? 1 : 0])[_rep or barstate.isrealtime ? 0 : 1]
high_daily = f_security(syminfo.tickerid, "D", high, false)
roc_enable = input.bool(false, "", group="ROC Filter from CloseD", inline="roc")
roc_threshold = input.float(1, "Treshold", step=0.5, group="ROC Filter from CloseD", inline="roc")
closed = f_security(syminfo.tickerid,"1D",close, false)
roc_filter= roc_enable ? (close-closed)/closed*100 > roc_threshold : true
// -----------------------------------------------------------------------------
// Trigger Point
// -----------------------------------------------------------------------------
open_session = ta.change(time('D'))
price_session = ta.valuewhen(open_session, open, 0)
tf_session = timeframe.multiplier <= 60
bgcolor(open_session and tf_session ?color.new(color.blue,80):na, title = "Session")
first_bar = 0
if open_session
first_bar := bar_index
var max_today = 0.0
var min_today = 0.0
var high_daily1 = 0.0
var low_daily1 = 0.0
var today_open = 0.0
if first_bar
high_daily1 := max_today
low_daily1 := min_today
today_open := open
max_today := high
min_today := low
if high >= max_today
max_today := high
if low < min_today
min_today := low
same_day = today_open == today_open[1]
plot( timeframe.multiplier <= 240 and same_day ? high_daily1 : na, color= color.yellow , style=plot.style_linebr, linewidth=1, title='High line')
plot( timeframe.multiplier <= 240 and same_day ? low_daily1 : na, color= #E8000D , style=plot.style_linebr, linewidth=1, title='Low line')
// -----------------------------------------------------------------------------
// Strategy settings
// -----------------------------------------------------------------------------
Gap = input.float(1,"Gap%", step=0.5, tooltip="Gap di entrata su entry_price -n anticipa entrata, con +n posticipa entrata", group = "Entry")
Gap2 = (high_daily1 * Gap)/100
sl = input.float(3, "Stop-loss", step= 0.5, group = "Entry")
tp = input.float(9, "Take-profit", step= 0.5, group = "Entry")
stop_loss_price = strategy.position_avg_price * (1-sl/100)
take_price = strategy.position_avg_price * (1+tp/100)
sl_trl = input.float(2, "Trailing-stop", step = 0.5, tooltip = "Attiva trailing stop dopo che ha raggiunto...",group = "Trailing Stop Settings")//group = "Trailing Stop Settings")
Atrl= input.float(1, "Offset Trailing", step=0.5,tooltip = "Distanza dal prezzo", group = "Trailing Stop Settings")
stop_trl_price_cond = sl_trl * high/syminfo.mintick/100
stop_trl_price_offset_cond = Atrl * high/syminfo.mintick/100
stop_tick = sl * high/syminfo.mintick/100
profit_tick = tp * high/syminfo.mintick/100
mess_buy = "buy"
mess_sell = "sell"
// -----------------------------------------------------------------------------
// Entry - Exit - Close
// -----------------------------------------------------------------------------
if close < high_daily1 and roc_filter
strategy.entry("Entry", strategy.long, stop = high_daily1 + (Gap2), alert_message = mess_buy)
ts_n = input.bool(true, "Trailing-stop", tooltip = "Attiva o disattiva trailing-stop", group = "Trailing Stop Settings")
close_ema = input.bool(false, "Close EMA", tooltip = "Attiva o disattiva chiusura su EMA", group = "Trailing Stop Settings")
len1 = input.int(10, "EMA length", step=1, group = "Trailing Stop Settings")
ma1 = ta.ema(close, len1)
plot(ma1, title='EMA', color=color.new(color.yellow, 0))
if ts_n == true
strategy.exit("Trailing-Stop","Entry",loss= stop_tick, stop= stop_loss_price, limit= take_price, trail_points = stop_trl_price_cond, trail_offset = stop_trl_price_offset_cond, comment_loss="Stop-Loss!!",comment_profit ="CASH!!", comment_trailing = "TRL-Stop!!", alert_message = mess_sell)
else
strategy.exit("TP-SL", "Entry",loss= stop_tick, stop=stop_loss_price, limit= take_price, comment_loss= "Stop-loss!!!", comment_profit = "CASH!!", alert_message = mess_sell)
if close_ema == true and ta.crossunder(close,ma1)
strategy.close("Entry",comment = "Close" , alert_message = mess_sell)