ChaoZhang
概述
该策略名为“OBV金字塔”,基于OBV指标设计开仓策略,并采用金字塔加仓方式,在趋势出现后,分批多次加仓,追踪趋势进行获利。
策略原理
该策略使用OBV指标判断趋势方向。OBV指标基于成交量变化判断价格趋势,成交量的变化反映市场参与者的态度。当OBV上穿0轴表示买盘力道增强,多头趋势形成;当OBV下穿0轴表示卖盘力道增强,空头趋势形成。
该策略通过判断OBV是否上穿0轴,来确认多头趋势的形成。在多头趋势形成时,设定金字塔式加仓规则,最多可加仓7次。通过追踪趋势进行获利,设置止盈止损退出机制。
优势分析
该策略最大优势是能捕捉趋势,通过金字塔加仓方式追踪趋势运行,获利潜力大。另外,策略风险控制到位,有止盈止损设置。
具体来说,优势主要体现在:
1. 使用OBV判断趋势方向准确;
2. 金字塔加仓方式能够追踪趋势获利;
3. 设置止盈止损能控制风险;
4. 策略逻辑简单清晰易于理解。
风险分析
该策略主要风险来自两方面:
- OBV判断失误,造成错失良机或错误建仓;
- 加仓过多,风险扩大。
对应解决方法: 1. 优化OBV参数,确保判断准确; 2. 适当控制加仓次数,确保风险可控。
优化方向
该策略主要可优化方向:
- OBV参数优化,提高判断准确率;
- 加仓次数和金额优化;
- 止盈止损点位优化;
- 结合其他指标判断,避免OBV单一判断风险。
优化这些内容后,可以使策略更稳定、更可控、更具备扩展性。
总结
该策略整体来说非常实用。它使用OBV指标判断趋势方向,然后通过金字塔加仓追踪趋势运行。策略逻辑简洁清晰,易于理解和回测。有一定的实战运用价值。通过对参数、止盈止损、加仓方式等的深入优化,策略效果能够得到进一步提升,值得进一步研究。
策略源码
/*backtest
start: 2023-11-07 00:00:00
end: 2023-12-07 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © RafaelZioni
//@version=4
strategy(title = " OBV Pyr", overlay = true, pyramiding=5,initial_capital = 10000, default_qty_type= strategy.percent_of_equity, default_qty_value = 20, calc_on_order_fills=false, slippage=0,commission_type=strategy.commission.percent,commission_value=0.075)
strat_dir_input = input(title="Strategy Direction", defval="long", options=["long", "short", "all"])
strat_dir_value = strat_dir_input == "long" ? strategy.direction.long : strat_dir_input == "short" ? strategy.direction.short : strategy.direction.all
strategy.risk.allow_entry_in(strat_dir_value)
//
fastLength = input(250, title="Fast filter length ", minval=1)
slowLength = input(500,title="Slow filter length", minval=1)
source=close
v1=ema(source,fastLength)
v2=ema(source,slowLength)
//
filter=true
src = close
LengthOBV = input(20)
nv = change(src) > 0 ? volume : change(src) < 0 ? -volume : 0*volume
c = cum(nv)
c_tb = c - sma(c,LengthOBV)
// Conditions
longCond = crossover(c_tb,0)
//shortCond =crossunder(cnv_tb,0)
//
longsignal = (v1 > v2 or filter == false ) and longCond
//shortsignal = (v1 < v2 or filter == false ) and shortCond
//set take profit
ProfitTarget_Percent = input(3)
Profit_Ticks = close * (ProfitTarget_Percent / 100) / syminfo.mintick
//set take profit
LossTarget_Percent = input(10)
Loss_Ticks = close * (LossTarget_Percent / 100) / syminfo.mintick
////Order Placing
//
strategy.entry("Entry 1", strategy.long, when=strategy.opentrades == 0 and longsignal)
//
strategy.entry("Entry 2", strategy.long, when=strategy.opentrades == 1 and longsignal)
//
strategy.entry("Entry 3", strategy.long, when=strategy.opentrades == 2 and longsignal)
//
strategy.entry("Entry 4", strategy.long, when=strategy.opentrades == 3 and longsignal)
//
strategy.entry("Entry 5", strategy.long, when=strategy.opentrades == 4 and longsignal)
//
strategy.entry("Entry 6", strategy.long, when=strategy.opentrades == 5 and longsignal)
//
strategy.entry("Entry 7", strategy.long, when=strategy.opentrades == 6 and longsignal)
//
//
//
if strategy.position_size > 0
strategy.exit(id="Exit 1", from_entry="Entry 1", profit=Profit_Ticks, loss=Loss_Ticks)
strategy.exit(id="Exit 2", from_entry="Entry 2", profit=Profit_Ticks, loss=Loss_Ticks)
strategy.exit(id="Exit 3", from_entry="Entry 3", profit=Profit_Ticks, loss=Loss_Ticks)
strategy.exit(id="Exit 4", from_entry="Entry 4", profit=Profit_Ticks, loss=Loss_Ticks)
strategy.exit(id="Exit 5", from_entry="Entry 5", profit=Profit_Ticks, loss=Loss_Ticks)
strategy.exit(id="Exit 6", from_entry="Entry 6", profit=Profit_Ticks, loss=Loss_Ticks)
strategy.exit(id="Exit 7", from_entry="Entry 7", profit=Profit_Ticks, loss=Loss_Ticks)