Oscillation Spectrum Moving Average Trading Strategy

Author: ChaoZhang, Date: 2024-01-25 14:19:27
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Overview

This strategy is based on the spectrum moving average, generating trading signals through the golden cross and death cross of the fast and slow moving averages. The spectrum moving average covers a variety of types from simple moving average to oscillating moving average, which can be freely combined through parameter adjustment for strong adaptability.

Strategy Principle

This strategy uses a variant moving average function that can generate 12 different types of moving averages. The basic principle is to calculate two moving average lines, the fast line (Close MA) and the slow line (Open MA). When the fast line crosses above the slow line, a buy signal is generated. When the fast line crosses below the slow line, a sell signal is generated. Stop loss and take profit parameters are also set to achieve automatic stop loss and take profit.

The key logic is to generate two moving average lines through the variant function: `closeSeries = variant(basisType, close, basisLen, offsetSigma, offsetALMA)` and `openSeries = variant(basisType, open, basisLen, offsetSigma, offsetALMA)`. The variant function encapsulates calculation methods for 12 different types of moving averages. Users can freely select the type through the basisType parameter. This implements the combination of spectrum moving averages.

The basic logic for generating trading signals is: `longCond = xlong` and `shortCond = xshort`. That means when the fast line crosses above the slow line, long position is taken, and when the fast line crosses below the slow line, short position is taken.

The entry rule is to go long or go short when the longCond or shortCond condition is met. The exit rule is to close the position for stop loss or take profit when the price movement reaches the preset stop loss/profit points.

The biggest advantage of this strategy is that it can freely combine a variety of different types of moving averages. It is indefinite which types of moving averages are best suited for different markets and timeframes. This strategy provides powerful customizability. Users can determine the optimal parameter combination through repeated testing, thereby formulating the best solution for the specific market.

Another advantage is that the strategy logic is simple and clear, but provides powerful functionality. It is easy for users to understand and use this strategy. At the same time, the abundant input parameters also provide sufficient optimization space for advanced users.

Risk Analysis

The biggest risk with this strategy is that the spectrum moving average itself has a certain degree of lagging. Abnormal price breakthroughs may cause larger losses. In addition, improper parameter selection may also lead to excessive trading frequency or redundant signals.

To reduce the risk, it is recommended to use other indicators to determine the validity of signals and avoid false breakouts. In addition, parameter optimization and backtesting are also essential to find the best parameter combination through repeated testing. In live trading, the position sizing should be appropriately reduced to control single loss.

Optimization Directions

The main optimization directions for this strategy include:

1. Test more types of moving average combinations to find the best combination
2. Add filters to avoid false signals, such as combining trading volume indicators, etc.
3. Optimize the length parameters of the moving averages to find the optimal parameters
4. Optimize position sizing, stop loss and take profit parameters
5. Try different products and timeframes

By optimizing in these directions above, the live trading performance of the strategy can be continuously improved.

Summary

This trading strategy implements high flexibility based on the spectrum moving average. It provides powerful customizability for users to freely choose and combine different types of moving averages. The strategy logic is simple and clear, easy to use, and also offers abundant optimization space. Through parameter optimization and risk control, this strategy can adapt to different market environments and obtain steady returns. It is an efficient and flexible trend tracking strategy.

```/*backtest
start: 2023-01-18 00:00:00
end: 2024-01-24 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
//

strategy(title="Long/Short", shorttitle="Banana Maker", overlay=true, pyramiding=0, default_qty_type=strategy.percent_of_equity, default_qty_value=100, calc_on_every_tick=false)

// === INPUTS ===
useRes = input(defval=true, title="Use Alternate Resolution?")
intRes = input(defval=7, title="Multiplier for Alernate Resolution")
stratRes = timeframe.ismonthly ? tostring(timeframe.multiplier * intRes, "###M") :
timeframe.isweekly ? tostring(timeframe.multiplier * intRes, "###W") :
timeframe.isdaily ? tostring(timeframe.multiplier * intRes, "###D") :
timeframe.isintraday ? tostring(timeframe.multiplier * intRes, "####") : '60'
basisType = input(defval="DEMA", title="MA Type: ", options=["SMA", "EMA", "DEMA", "TEMA", "WMA", "VWMA", "SMMA", "HullMA", "LSMA", "ALMA", "SSMA", "TMA"])
basisLen = input(defval=8, title="MA Period", minval=1)
offsetSigma = input(defval=6, title="Offset for LSMA / Sigma for ALMA", minval=0)
offsetALMA = input(defval=0.85, title="Offset for ALMA", minval=0, step=0.01)
scolor = input(false, title="Show coloured Bars to indicate Trend?")
delayOffset = input(defval=0, title="Delay Open/Close MA (Forces Non-Repainting)", minval=0, step=1)
tradeType = input("BOTH", title="What trades should be taken : ", options=["LONG", "SHORT", "BOTH", "NONE"])
// === /INPUTS ===

// Constants colours that include fully non-transparent option.
green100 = #008000FF
red100 = #FF0000FF
blue100 = #0000FFFF
aqua100 = #00FFFFFF
darkred100 = #8B0000FF
gray100 = #808080FF

// === BASE FUNCTIONS ===
variant(type, src, len, offSig, offALMA) =>
v1 = sma(src, len)  // Simple
v2 = ema(src, len)  // Exponential
v3 = 2 * v2 - ema(v2, len)  // Double Exponential
v4 = 3 * (v2 - ema(v2, len)) + ema(ema(v2, len), len)  // Triple Exponential
v5 = wma(src, len)  // Weighted
v6 = vwma(src, len)  // Volume Weighted
v7 = 0.0
sma_1 = sma(src, len)  // Smoothed
v7 := na(v7[1]) ? sma_1 : (v7[1] * (len - 1) + src) / len
v8 = wma(2 * wma(src, len / 2) - wma(src, len), round(sqrt(len)))  // Hull
v9 = linreg(src, len, offSig)  // Least Squares
v10 = alma(src, len, offALMA, offSig)  // Arnaud Legoux
v11 = sma(v1, len)  // Triangular (extreme smooth)
// SuperSmoother filter
// © 2013  John F. Ehlers
a1 = exp(-1.414 * 3.14159 / len)
b1 = 2 * a1 * cos(1.414 * 3.14159 / len)
c2 = b1
c3 = -a1 * a1
c1 = 1 - c2 - c3
v12 = 0.0
v12 := c1 * (src + nz(src[1])) / 2 + c2 * nz(v12[1]) + c3 * nz(v12[2])
type == "EMA" ? v2 : type == "DEMA" ? v3 :
type == "TEMA" ? v4 : type == "WMA" ? v5 : type == "VWMA" ? v6 :
type == "SMMA" ? v7 : type == "HullMA" ? v8 : type == "LSMA" ? v9 :
type == "ALMA" ? v10 : type == "TMA" ? v11 : type == "SSMA" ? v12 : v1

// security wrapper for repeat calls* NEEDS REFINEMENT- backtesting this shows repaint. need new wrapper
reso(exp, use, res) =>
use ? security_1 : exp

// === /BASE FUNCTIONS ===

// === SERIES SETUP ===
closeSeries = variant(basisType, close[delayOffset], basisLen, offsetSigma, offsetALMA)
openSeries = variant(basisType, open[delayOffset], basisLen, offsetSigma, offsetALMA)
// === /SERIES ===

// === PLOTTING ===

// alt resulution
closeSeriesAlt = reso(closeSeries, useRes, stratRes)
openSeriesAlt = reso(openSeries, useRes, stratRes)
//
trendColour = closeSeriesAlt > openSeriesAlt ? color.green : color.red
bcolour = closeSeries > openSeriesAlt ? lime100 : red100
barcolor(scolor ? bcolour : na, title="Bar Colours")
closeP = plot(closeSeriesAlt, title="Close Series", color=trendColour, linewidth=0, style=plot.style_line, transp=1)
openP = plot(openSeriesAlt, title="Open Series", color=trendColour, linewidth=0, style=plot.style_line, transp=1)
fill(closeP, openP, color=trendColour, transp=80)

// === /PLOTTING ===
//

//

xlong = crossover(closeSeriesAlt, openSeriesAlt)
xshort = crossunder(closeSeriesAlt, openSeriesAlt)
longCond = xlong  // alternative: longCond[1]? false : (xlong or xlong[1]) and close>closeSeriesAlt and close>=open
shortCond = xshort  // alternative: shortCond[1]? false : (xshort or xshort[1]) and close<closeSeriesAlt and close<=open

// === /ALERT conditions. needs work in study mode. the banana maker is the study script.
// Create alert for cross, shunt back 1 if source is not 'open', this should prevent repaint issue.
//shunt = RSIsrc == open ? 0 : 1
//shunt = 0
// show only when alert condition is met and bar closed.

//Repaint city, study mode will help but wont trigger the alerts

// === STRATEGY ===
// stop loss
slPoints = input(defval=0, title="Initial Stop Loss Points (zero to disable)", minval=0)
tpPoints = input(defval=0, title="Initial Target Profit Points (zero for disable)", minval=0)
// Include bar limiting algorithm
ebar = input(defval=1000, title="Number of Bars for Back Testing", minval=0)
dummy = input(false, title="- SET to ZERO for Daily or Longer Timeframes")
//
// Calculate how many mars since last bar
tdays = (timenow - time) / 60000.0  // number of minutes since last bar
tdays := timeframe.ismonthly ? tdays / 1440.0 / 5.0 / 4.3 / timeframe.multiplier :
timeframe.isweekly ? tdays / 1440.0 / 5.0 / timeframe.multiplier :
timeframe.isdaily ? tdays / 1440.0 / timeframe.multiplier :
tdays / timeframe.multiplier  // number of bars since last bar
//
//set up exit parameters
TP = tpPoints > 0 ? tpPoints : na
SL = slPoints > 0 ? slPoints : na

// Make sure we are within the bar range, Set up entries and exit conditions
if (ebar == 0 or tdays <= ebar) and tradeType != "NONE"
strategy.entry("long", strategy.long, when=longCond == true and tradeType != "SHORT")
strategy.entry("short", strategy.short, when=shortCond == true and tradeType != "LONG")
strategy.close("long", when=shortCond == true and tradeType == "LONG")
strategy.close("short", when=longCond == true and tradeType == "SHORT")
strategy.exit("XL", from_entry="long", profit=TP, loss=SL)
strategy.exit("XS", from_entry="short", profit=TP, loss=SL)

// === /STRATEGY ===
// eof

```
template: strategy.tpl:40:21: executing "strategy.tpl" at <.api.GetStrategyListByName>: wrong number of args for GetStrategyListByName: want 7 got 6