184 lines
6.1 KiB
Markdown
184 lines
6.1 KiB
Markdown
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> Name
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基于历史数据的动态支撑阻力策略Dynamic-Support-and-Resistance-Strategy-Based-on-Historical-Data
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> Author
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ChaoZhang
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> Strategy Description
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[trans]
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## 概述
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本策略基于历史高点、低点和收盘价的动态计算,得到支撑阻力位,并以此进行交易信号生成。该策略适用于中长线持仓,可以有效利用市场中的支撑阻力进行获利。
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## 策略原理
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1. 计算上一周期的最高价、最低价和收盘价的平均值,得到基准点PP。
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2. 计算3条支撑线:S1 = 2*PP - 最高价;S2 = PP - (R1-S1); S3 = 最低价 - 2*(最高价-PP)。
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3. 计算3条阻力线:R1 = 2*PP - 最低价;R2 = PP + (R1-S1); R3 = 最高价 + 2*(PP-最低价)。
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4. 当价格上穿阻力线时,做多;当价格下穿支撑线时,做空。
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## 优势分析
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1. 基于历史数据计算的支撑阻力位变化动态,能够实时捕捉市场结构。
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2. 多层级的支撑阻力设定,可以进行风险管理优化。
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3. 简单直观的交易信号和止损方式。
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## 风险分析
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1. 在高波动行情中,历史数据提供的参考价位可能会失效。
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2. 多空仓位之间的切换需要考虑交易成本。
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3. 需要确保数据质量,避免计算错误。
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## 优化方向
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1. 可以考虑引入更多历史数据的参考,如百日线等。
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2. 优化仓位管理,如基于波动率调整仓位比例。
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3. 增加止损策略,如跟踪止损或资金管理止损。
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## 总结
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本策略基于历史支撑阻力概念,提供多层级的参考价位。策略简单直接,适合中长线持仓获利。同时也需要注意高波动市场的风险,以及交易成本的控制。通过进一步优化,可以使策略在复杂环境中依然稳定运行。
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## Overview
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This strategy dynamically calculates support and resistance levels based on historical high, low and close prices, and generates trading signals accordingly. It is suitable for medium-to-long-term positions and can effectively utilize support and resistance levels in the market for profit.
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## Strategy Logic
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1. Calculate the average of previous period's high, low and close prices as the pivot point (PP).
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2. Calculate 3 support lines: S1 = 2*PP - highest price; S2 = PP - (R1-S1); S3 = lowest price - 2*(highest price - PP).
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3. Calculate 3 resistance lines: R1 = 2*PP - lowest price; R2 = PP + (R1-S1); R3 = highest price + 2*(PP - lowest price).
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4. Take long position when price breaks through resistance lines, take short position when price breaks through support lines.
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## Advantage Analysis
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1. The dynamic support and resistance levels based on historical data can capture market structure changes timely.
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2. The multi-layer support and resistance settings allow better risk management optimization.
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3. Simple and intuitive trading signals and stop loss mechanism.
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## Risk Analysis
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1. The reference price levels provided by historical data may become invalid in high volatility scenarios.
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2. The switching between long and short positions should consider trading cost.
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3. Data quality needs to ensured to avoid calculation errors.
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## Optimization Directions
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1. Consider incorporating more historical data references like 100-day moving average etc.
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2. Optimize position sizing, e.g. adjust position size based on volatility.
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3. Add stop loss strategies like trailing stop loss or risk-based stop loss.
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## Summary
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This strategy provides multi-layer support and resistance reference price levels based on history. It has simple and straightforward logic suitable for medium-to-long-term positions. Meanwhile, risks under high volatility market and trading costs should be monitored. Further optimizations can make the strategy robust under complex environments.
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[/trans]
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> Strategy Arguments
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|Argument|Default|Description|
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|----|----|----|
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|v_input_1|D|Resolution|
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|v_input_2|0|Sell from : R1|R2|R3|
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|v_input_3|0|Buy from : S1|S2|S3|
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|v_input_4|true|width|
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|v_input_5|false|Trade reverse|
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> Source (PineScript)
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``` pinescript
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/*backtest
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start: 2023-10-28 00:00:00
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end: 2023-11-27 00:00:00
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period: 1h
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basePeriod: 15m
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exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
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*/
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//@version=4
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////////////////////////////////////////////////////////////
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// Copyright by HPotter v1.0 09/06/2020
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// Pivot points simply took the high, low, and closing price from the previous period and
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// divided by 3 to find the pivot. From this pivot, traders would then base their
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// calculations for three support, and three resistance levels. The calculation for the most
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// basic flavor of pivot points, known as ‘floor-trader pivots’, along with their support and
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// resistance levels.
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//
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// WARNING:
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// - For purpose educate only
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// - This script to change bars colors.
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////////////////////////////////////////////////////////////
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strategy(title="Pivot Point V2", shorttitle="Pivot Point V2", overlay = true)
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res = input(title="Resolution", type=input.resolution, defval="D")
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SellFrom = input(title="Sell from ", defval="R1", options=["R1", "R2", "R3"])
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BuyFrom = input(title="Buy from ", defval="S1", options=["S1", "S2", "S3"])
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width = input(1, minval=1)
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reverse = input(false, title="Trade reverse")
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xHigh = security(syminfo.tickerid,res, high)
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xLow = security(syminfo.tickerid,res, low)
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xClose = security(syminfo.tickerid,res, close)
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vPP = (xHigh+xLow+xClose) / 3
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vS1 = 2*vPP - xHigh
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vR1 = 2*vPP-xLow
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vS2 = vPP - (vR1 - vS1)
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vR2 = vPP + (vR1 - vS1)
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vS3 = xLow - 2 * (xHigh - vPP)
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vR3 = xHigh + 2 * (vPP - xLow)
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pos = 0
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S = iff(BuyFrom == "S1", vS1,
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iff(BuyFrom == "S2", vS2,
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iff(BuyFrom == "S3", vS3,0)))
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B = iff(SellFrom == "R1", vR1,
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iff(SellFrom == "R2", vR2,
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iff(SellFrom == "R3", vR3,0)))
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pos := iff(close > B, 1,
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iff(close < S, -1, nz(pos[1], 0)))
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possig = iff(reverse and pos == 1, -1,
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iff(reverse and pos == -1 , 1, pos))
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if (possig == 1)
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strategy.entry("Long", strategy.long)
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if (possig == -1)
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strategy.entry("Short", strategy.short)
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if (possig == 0)
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strategy.close_all()
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barcolor(possig == -1 ? #b50404: possig == 1 ? #079605 : #0536b3 )
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```
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> Detail
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https://www.fmz.com/strategy/433589
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> Last Modified
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2023-11-28 17:04:16
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