Moving Average Crossover Mehrperiodenstrategie
ChaoZhang
Überblick
Die Strategie basiert auf einem Kreuzungssystem von Moving Averages, bei dem die Kauf- und Verkaufsmomente anhand von Moving Averages mit unterschiedlichen Perioden golden cross und death cross beurteilt werden. Die Strategie kombiniert gleichzeitig Trend-Tracking-Stopps, Stop-Loss-Stopps und andere Funktionen, um Gewinne zu erzielen und Risiken zu vermeiden.
Strategieprinzip
Die Strategie verwendet zwei Arten von Moving Averages, die schnelle und die langsame Linie. Die schnelle Linie ist kürzer und zeigt den kurzfristigen Trend an. Die langsame Linie ist länger und zeigt den langfristigen Trend.
In den Codes sind die Schnelllinie ma1 und die Langlinie ma2. Ma1 und ma2 bieten verschiedene Arten von Moving Averages wie SMA, EMA usw. und verschiedene Periodenparameter. Ma1 steht für kurzfristige Trends mit kürzeren Perioden; ma2 für langfristige Trends mit längeren Perioden.
Wenn ma1 Goldfork ma2 ist, erzeugt Long-Signal, machen Sie mehr; wenn ma1 Dead-Fork ma2 ist, erzeugt Short-Signal, machen Sie leer. Wenn der tatsächliche Handel, kann in Kombination mit Trend-Tracking-Stopp-Loss, Stop-Stopp-Loss und andere Funktionen, um Gewinn zu sperren und Risiken zu vermeiden.
Analyse der Stärken
Diese Strategie hat folgende Vorteile:
Die Strategie ist einfach, klar und leicht zu verstehen und umzusetzen.
Flexible Wahl von Moving Averages mit verschiedenen Typen und Parametern, die für verschiedene Marktumgebungen geeignet sind
Mehrzeit- und langfristige Trends sind dabei zu erfassen und zu vermeiden, dass sie verfehlt werden.
Die Bedingungen für die Eröffnung von Positionen können individuell angepasst werden und die Häufigkeit des Handels wird streng kontrolliert.
Sie können Stop-Loss-Bedingungen einstellen, um Risiken effektiv zu kontrollieren.
Trend-Tracking-Stopp-Loss kann hinzugefügt werden, um den Gewinn zu verfolgen.
Optimierbare Parameter, um die Strategie stabiler und zuverlässiger zu machen.
Risikoanalyse
Die Strategie birgt auch folgende Risiken:
Die doppelte Moving Average-Kreuzung selbst ist zurückgeblieben und könnte die beste Zeit für eine Preisumkehr verpassen.
Die falsche Einstellung der Moving-Average-Periode kann zu weiteren Falschsignalen führen.
Die Gefahr, dass ein Unfall schneller umschlägt und die Schäden verringert werden, ist groß.
Bei einem Trend ist die Wahrscheinlichkeit höher, dass der Preis länger auf der Seite der Durchschnittslinie bleibt.
Die Optimierung der Parameter ist nicht korrekt und könnte zu optimiert sein für bestimmte Zeiträume.
Entsprechende Risikomanagementmaßnahmen:
In Kombination mit anderen Indikatoren filtert das Signal, um falsche Durchbrüche zu vermeiden.
Die Zyklus-Einstellungen folgen dem Trend-Trading-Prinzip und testen Optimierungsparameter.
Die Risikokontrolle muss vorsichtig sein und die Stop-Loss-Position sollte vernünftig eingestellt werden.
Die Kosten für die geduldige Wartezeit.
Testparameter für die Robustheit in verschiedenen Marktumgebungen.
Optimierungsrichtung
Diese Strategie kann optimiert werden durch:
Testung von weiteren Arten von Moving Averages, wie beispielsweise gewogenen Moving Averages.
Erhöhen Sie die dynamischen Zyklen, die auf der Volatilität basieren, und passen Sie die Durchschnittsparameter an die Marktveränderungen an.
Strategische Einstiegsvoraussetzungen können mit Zeit oder grundlegenden Filtern ausgewählt werden, um die Fehlerquote zu verringern.
Die Ausstiegsbedingungen können dynamische Stop-Loss-Bedingungen festlegen, wobei die Stop-Loss-Bedingungen entsprechend der Schwankungen des Marktes angepasst werden.
Es kann ein System zur Parameteroptimierung eingerichtet werden, um eine historische Rückverfolgung der Strategie mit Parameteroptimierungen zu ermöglichen.
Die Einführung von Machine Learning-Algorithmen zur Optimierung von Parametern und Filtersignalen durch KI.
Zusammenfassen
Die Moving-Average-Cross-Multi-Cycle-Strategie ist klar und einfach zu verstehen. Die Strategie erfasst Trends durch schnelle und langsame Durchschnittslinie-Cross, eine eher klassische Trendverfolgungsstrategie. Die Strategie kann durch die Auswahl geeigneter Parameter, die Optimierung der Einstiegs- und Ausstiegslogik und die strenge Risikokontrolle zu einem stabilen Gewinn führen.
/*backtest
start: 2023-09-08 00:00:00
end: 2023-10-08 00:00:00
period: 4h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=3
// The majority of this script I took from the Autoview website. There are some typos in the original that I've fixed, some things I've added, things I will add, and I'm tired pulling my strategy code out and uploading this to pastebin for people.
// DISCLAIMER: I am not a financial advisor, this is not financial advice, do not use this code without first doing your own research, etc, etc, it's not my fault when you lose your house.
strategy("Moving Averages Cross - MTF - Strategy", "MA Cross", overlay=true, pyramiding=0, initial_capital=100000, currency=currency.USD, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, commission_type=strategy.commission.percent, commission_value=0.1)
bgcolor ( color=black, transp=40, title='Blackground', editable=true)
///////////////////////////////////////////////
//* Backtesting Period Selector | Component *//
///////////////////////////////////////////////
//* https://www.tradingview.com/script/eCC1cvxQ-Backtesting-Period-Selector-Component *//
//* https://www.tradingview.com/u/pbergden/ *//
//* Modifications made *//
testStartYear = input(2018, "Backtest Start Year")
testStartMonth = input(1, "Backtest Start Month")
testStartDay = input(1, "Backtest Start Day")
testPeriodStart = timestamp(testStartYear,testStartMonth,testStartDay,00,00)
testStopYear = input(9999, "Backtest Stop Year")
testStopMonth = input(12, "Backtest Stop Month")
testStopDay = input(31, "Backtest Stop Day")
testPeriodStop = timestamp(testStopYear,testStopMonth,testStopDay,0,0)
testPeriod() => true
/////////////////////////////////////
//* Put your strategy logic below *//
/////////////////////////////////////
sp1 = input("----", title="--------Moving Average 1----------", options=["----"])
maUseRes1 = input(defval = false, title = "Use Different Resolution?")
//maReso1 = input(defval = "60", title = "Set Resolution", type = resolution)
maReso1 = input(defval='60', title = "Set Resolution Minutes")
maType1 = input("EMA", title="MA", options=["SMA", "EMA", "DEMA", "TEMA", "WMA", "VWMA", "SMMA", "Hull", "LSMA", "ALMA"])
maSource1 = input(defval = close, title = "Source")
maLength1 = input(defval = 15, title = "Period", minval = 1)
lsmaOffset1 = input(defval = 1, title = "Least Squares (LSMA) Only - Offset Value", minval = 0)
almaOffset1 = input(defval = 0.85, title = "Arnaud Legoux (ALMA) Only - Offset Value", minval = 0, step = 0.01)
almaSigma1 = input(defval = 6, title = "Arnaud Legoux (ALMA) Only - Sigma Value", minval = 0)
sp2 = input("----", title="--------Moving Average 2----------", options=["----"])
maUseRes2 = input(defval = false, title = "Use Different Resolution?")
//maReso2 = input(defval = "60", title = "Set Resolution", type = resolution)
maReso2 = input(defval='60', title = "Set Resolution Minutes")
maType2 = input("EMA", title="MA", options=["SMA", "EMA", "DEMA", "TEMA", "WMA", "VWMA", "SMMA", "Hull", "LSMA", "ALMA"])
maSource2 = input(defval = close, title = "Source")
maLength2 = input(defval = 30, title = "Period", minval = 1)
lsmaOffset2 = input(defval = 1, title = "Least Squares (LSMA) Only - Offset Value", minval = 0)
almaOffset2 = input(defval = 0.85, title = "Arnaud Legoux (ALMA) Only - Offset Value", minval = 0, step = 0.01)
almaSigma2 = input(defval = 6, title = "Arnaud Legoux (ALMA) Only - Sigma Value", minval = 0)
//Function from @JayRogers thank you man awesome work
variant(type, src, len, lsmaOffset, almaOffset, almaSigma) =>
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 = na(v5[1]) ? sma(src, len) : (v5[1] * (len - 1) + src) / len // Smoothed
v8 = wma(2 * wma(src, len / 2) - wma(src, len), round(sqrt(len))) // Hull
v9 = linreg(src, len, lsmaOffset) // Least Squares
v10 = alma(src, len, almaOffset, almaSigma) // Arnaud Legoux
type=="EMA"?v2 : type=="DEMA"?v3 : type=="TEMA"?v4 : type=="WMA"?v5 : type=="VWMA"?v6 : type=="SMMA"?v7 : type=="Hull"?v8 : type=="LSMA"?v9 : type=="ALMA"?v10 : v1
//Different resolution function
reso(exp, res, use) => use ? security(tickerid, res, exp) : exp
ma1 = reso(variant(maType1, maSource1, maLength1, lsmaOffset1, almaOffset1, almaSigma1), maReso1, maUseRes1)
ma2 = reso(variant(maType2, maSource2, maLength2, lsmaOffset2, almaOffset2, almaSigma2), maReso2, maUseRes2)
plotma1 = plot(ma1, color=green, tranps=50, linewidth = 2 )
plotma2 = plot(ma2, color=red, tranps=50, linewidth = 2 )
// Long/Short Logic
longLogic = crossover(ma1,ma2) ? 1 : 0
shortLogic = crossunder(ma1,ma2) ? 1 : 0
//////////////////////////
//* Strategy Component *//
//////////////////////////
isLong = input(false, "Longs Only")
isShort = input(false, "Shorts Only")
isFlip = input(false, "Flip the Opens")
long = longLogic
short = shortLogic
if isFlip
long := shortLogic
short := longLogic
else
long := longLogic
short := shortLogic
if isLong
long := long
short := na
if isShort
long := na
short := short
////////////////////////////////
//======[ Signal Count ]======//
////////////////////////////////
sectionLongs = 0
sectionLongs := nz(sectionLongs[1])
sectionShorts = 0
sectionShorts := nz(sectionShorts[1])
if long
sectionLongs := sectionLongs + 1
sectionShorts := 0
if short
sectionLongs := 0
sectionShorts := sectionShorts + 1
//////////////////////////////
//======[ Pyramiding ]======//
//////////////////////////////
pyrl = input(1, "Pyramiding less than") // If your count is less than this number
pyre = input(0, "Pyramiding equal to") // If your count is equal to this number
pyrg = input(1000000, "Pyramiding greater than") // If your count is greater than this number
longCondition = long and sectionLongs <= pyrl or long and sectionLongs >= pyrg or long and sectionLongs == pyre ? 1 : 0
shortCondition = short and sectionShorts <= pyrl or short and sectionShorts >= pyrg or short and sectionShorts == pyre ? 1 : 0
////////////////////////////////
//======[ Entry Prices ]======//
////////////////////////////////
last_open_longCondition = na
last_open_shortCondition = na
last_open_longCondition := longCondition ? close : nz(last_open_longCondition[1])
last_open_shortCondition := shortCondition ? close : nz(last_open_shortCondition[1])
////////////////////////////////////
//======[ Open Order Count ]======//
////////////////////////////////////
sectionLongConditions = 0
sectionLongConditions := nz(sectionLongConditions[1])
sectionShortConditions = 0
sectionShortConditions := nz(sectionShortConditions[1])
if longCondition
sectionLongConditions := sectionLongConditions + 1
sectionShortConditions := 0
if shortCondition
sectionLongConditions := 0
sectionShortConditions := sectionShortConditions + 1
///////////////////////////////////////////////
//======[ Position Check (long/short) ]======//
///////////////////////////////////////////////
last_longCondition = na
last_shortCondition = na
last_longCondition := longCondition ? time : nz(last_longCondition[1])
last_shortCondition := shortCondition ? time : nz(last_shortCondition[1])
in_longCondition = last_longCondition > last_shortCondition
in_shortCondition = last_shortCondition > last_longCondition
/////////////////////////////////////
//======[ Position Averages ]======//
/////////////////////////////////////
totalLongs = 0.0
totalLongs := nz(totalLongs[1])
totalShorts = 0.0
totalShorts := nz(totalShorts[1])
averageLongs = 0.0
averageLongs := nz(averageLongs[1])
averageShorts = 0.0
averageShorts := nz(averageShorts[1])
if longCondition
totalLongs := totalLongs + last_open_longCondition
totalShorts := 0.0
if shortCondition
totalLongs := 0.0
totalShorts := totalShorts + last_open_shortCondition
averageLongs := totalLongs / sectionLongConditions
averageShorts := totalShorts / sectionShortConditions
/////////////////////////////////
//======[ Trailing Stop ]======//
/////////////////////////////////
isTS = input(false, "Trailing Stop")
tsi = input(1000, "Activate Trailing Stop Price (%). Divided by 100 (1 = 0.01%)") / 100
ts = input(575, "Trailing Stop (%). Divided by 100 (1 = 0.01%)") / 100
last_high = na
last_low = na
last_high_short = na
last_low_short = na
last_high := not in_longCondition ? na : in_longCondition and (na(last_high[1]) or high > nz(last_high[1])) ? high : nz(last_high[1])
last_high_short := not in_shortCondition ? na : in_shortCondition and (na(last_high[1]) or high > nz(last_high[1])) ? high : nz(last_high[1])
last_low := not in_shortCondition ? na : in_shortCondition and (na(last_low[1]) or low < nz(last_low[1])) ? low : nz(last_low[1])
last_low_short := not in_longCondition ? na : in_longCondition and (na(last_low[1]) or low < nz(last_low[1])) ? low : nz(last_low[1])
long_ts = isTS and not na(last_high) and low <= last_high - last_high / 100 * ts and longCondition == 0 and last_high >= averageLongs + averageLongs / 100 * tsi
short_ts = isTS and not na(last_low) and high >= last_low + last_low / 100 * ts and shortCondition == 0 and last_low <= averageShorts - averageShorts/ 100 * tsi
///////////////////////////////
//======[ Take Profit ]======//
///////////////////////////////
isTP = input(false, "Take Profit")
tp = input(300, "Take Profit (%). Divided by 100 (1 = 0.01%)") / 100
long_tp = isTP and close > averageLongs + averageLongs / 100 * tp and not longCondition
short_tp = isTP and close < averageShorts - averageShorts / 100 * tp and not shortCondition
/////////////////////////////
//======[ Stop Loss ]======//
/////////////////////////////
isSL = input(false, "Stop Loss")
sl = input(575, "Stop Loss (%). Divided by 100 (1 = 0.01%)") / 100
long_sl = isSL and close < averageLongs - averageLongs / 100 * sl and longCondition == 0
short_sl = isSL and close > averageShorts + averageShorts / 100 * sl and shortCondition == 0
/////////////////////////////////
//======[ Close Signals ]======//
/////////////////////////////////
longClose = long_tp or long_sl or long_ts ? 1 : 0
shortClose = short_tp or short_sl or short_ts ? 1: 0
///////////////////////////////
//======[ Plot Colors ]======//
///////////////////////////////
longCloseCol = na
shortCloseCol = na
longCloseCol := long_tp ? purple : long_sl ? maroon : long_ts ? blue : longCloseCol[1]
shortCloseCol := short_tp ? purple : short_sl ? maroon : short_ts ? blue : shortCloseCol[1]
tpColor = isTP and in_longCondition ? purple : isTP and in_shortCondition ? purple : white
slColor = isSL and in_longCondition ? red : isSL and in_shortCondition ? red : white
//////////////////////////////////
//======[ Strategy Plots ]======//
//////////////////////////////////
// Comment out these lines to use alerts
plot(isTS and in_longCondition ? averageLongs + averageLongs / 100 * tsi : na, "Long Trailing Activate", blue, style=3, linewidth=2)
plot(isTS and in_longCondition and last_high >= averageLongs + averageLongs / 100 * tsi ? last_high - last_high / 100 * ts : na, "Long Trailing", fuchsia, style=2, linewidth=3)
plot(isTS and in_shortCondition ? averageShorts - averageShorts/ 100 * tsi : na, "Short Trailing Activate", blue, style=3, linewidth=2)
plot(isTS and in_shortCondition and last_low <= averageShorts - averageShorts/ 100 * tsi ? last_low + last_low / 100 * ts : na, "Short Trailing", fuchsia, style=2, linewidth=3)
plot(isTP and in_longCondition and last_high < averageLongs + averageLongs / 100 * tp ? averageLongs + averageLongs / 100 * tp : na, "Long TP", tpColor, style=3, linewidth=2)
plot(isTP and in_shortCondition and last_low > averageShorts - averageShorts / 100 * tp ? averageShorts - averageShorts / 100 * tp : na, "Short TP", tpColor, style=3, linewidth=2)
plot(isSL and in_longCondition and last_low_short > averageLongs - averageLongs / 100 * sl ? averageLongs - averageLongs / 100 * sl : na, "Long SL", slColor, style=3, linewidth=2)
plot(isSL and in_shortCondition and last_high_short < averageShorts + averageShorts / 100 * sl ? averageShorts + averageShorts / 100 * sl : na, "Short SL", slColor, style=3, linewidth=2)
///////////////////////////////
//======[ Alert Plots ]======//
///////////////////////////////
// Uncomment to use Alerts, or the new Signal Plots, but not both
// Old Signal Plots
//plot(longCondition, "Long", green)
//plot(shortCondition, "Short", red)
//plot(longClose, "Long Close", longCloseCol)
//plot(shortClose, "Short Close", shortCloseCol)
// Uncomment for your alerts
//alertcondition(condition=longCondition, title="Long", message="")
//alertcondition(condition=shortCondition, title="Short", message="")
//alertcondition(condition=longClose, title="Long Close", message="")
//alertcondition(condition=shortClose, title="Short Close", message="")
///////////////////////////////////
//======[ Reset Variables ]======//
///////////////////////////////////
if longClose or not in_longCondition
averageLongs := 0
totalLongs := 0.0
sectionLongs := 0
sectionLongConditions := 0
if shortClose or not in_shortCondition
averageShorts := 0
totalShorts := 0.0
sectionShorts := 0
sectionShortConditions := 0
////////////////////////////////////////////
//======[ Strategy Entry and Exits ]======//
////////////////////////////////////////////
// Comment out to use alerts
if testPeriod()
strategy.entry("Long", 1, when=longCondition)
strategy.entry("Short", 0, when=shortCondition)
strategy.close("Long", when=longClose)
strategy.close("Short", when=shortClose)