This is a simple quantitative strategy that uses the Money Flow Index to identify “big sharks” in the market. It is suitable for the 5-minute timeframe and is mainly used for cryptocurrency trading.
The strategy uses a 3-period Money Flow Index with an overbought level set at 100 and an oversold level set at 0. The strategy waits for the Money Flow Index to reach overbought levels, indicating the presence of “big sharks” in the market. If price holds up on the first two overbought occurrences of the Money Flow Index for the day, it is considered a bullish entry signal.
A long entry is taken when Money Flow Index = 100 and next candle is a bullish candle with short wicks. The stop loss is set below the low of the trading day and profit is taken within 60 minutes after entry.
The logic above can be used in a mirrored fashion to take short entries as well.
Using Money Flow Index can effectively identify accumulation behavior by “big sharks” in the market, stocks with continuation potential.
Candlestick filters help confirm stronger breakouts, avoiding many false breaks.
The SMA filter avoids buying into declining trends, effectively reducing risk.
60-minute time-based exits quickly lock in profits, reducing drawdowns.
Money Flow Index may generate false signals, leading to unnecessary losses. Parameters can be adjusted or additional filters added.
60-minute exits may be too aggressive for high volatility stocks. Profit taking time or moving stop loss can be optimized.
Major macro events are not considered which can impact markets. Strategy should be paused until markets stabilize.
Test different parameter combinations like MFI length, SMA periods etc.
Add other indicators like Bollinger Bands, RSI to improve signal accuracy.
Test widening stops to allow larger profit targets.
Develop versions for other timeframes like 15 or 30 minutes based on same principles.
The strategy is simple and easy to understand, aligning with the classic approach of tracking “big sharks”. Key overbought/oversold levels combined with candlestick filters remove noise. The SMA filter further enhances robustness.
The 60-minute timeframe allows fast profits but also introduces higher risk. Overall an insightful strategy template for exploration and optimization, providing a blueprint for systematic development.
/*backtest start: 2024-01-15 00:00:00 end: 2024-01-22 00:00:00 period: 1m basePeriod: 1m 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/ // From "Crypto Day Trading Strategy" PDF file. // * I'm using a SMA filter to avoid buying when the price is declining. Time frame was better at 15 min according to my test. // 1 - Apply the 3 period Money Flow Index indicator to the 5 minute chart, using 0 and 100 as our oversold and overbought boundaries // 2 - Wait for the MFI to reach overbought levels, that indicates the presence of "big sharks" in the market. Price needs to hold up // the first two MFI overbought occurrences of the day to be considered as a bullish entry signal.* // 3 - We buy when the MFI = 100 and the next candle is a bullish candle with short wicks. // 4 - We place our Stop Loss below the low of the trading day and we Take Profit during the first 60 minutes after taking the trade. // The logic above can be used in a mirrored fashion to take short entries, this is a custom parameter that can be modified from // the strategy Inputs panel. // © tweakerID //@version=4 strategy("Money Flow Index 5 min Strategy", overlay=true ) direction = input(0, title = "Strategy Direction", type=input.integer, minval=-1, maxval=1) strategy.risk.allow_entry_in(direction == 0 ? strategy.direction.all : (direction < 0 ? strategy.direction.short : strategy.direction.long)) /////////////////////// STRATEGY INPUTS //////////////////////////////////////// title1=input(true, "-----------------Strategy Inputs-------------------") i_MFI = input(3, title="MFI Length") OB=input(100, title="Overbought Level") OS=input(0, title="Oversold Level") barsizeThreshold=input(.5, step=.05, minval=.1, maxval=1, title="Bar Body Size, 1=No Wicks") i_MAFilter = input(true, title="Use MA Trend Filter") i_MALen = input(80, title="MA Length") i_timedexit=input(false, title="Use 60 minutes exit rule") short=input(true, title="Use Mirrored logic for Shorts") /////////////////////// BACKTESTER ///////////////////////////////////////////// title2=input(true, "-----------------General Inputs-------------------") // Backtester General Inputs i_SL=input(true, title="Use Stop Loss and Take Profit") i_SLType=input(defval="Strategy Stop", title="Type Of Stop", options=["Strategy Stop", "Swing Lo/Hi", "ATR Stop"]) i_SPL=input(defval=10, title="Swing Point Lookback") i_PercIncrement=input(defval=3, step=.1, title="Swing Point SL Perc Increment")*0.01 i_ATR = input(14, title="ATR Length") i_ATRMult = input(5, step=.1, title="ATR Multiple") i_TPRRR = input(2.2, step=.1, title="Take Profit Risk Reward Ratio") TS=input(false, title="Trailing Stop") // Bought and Sold Boolean Signal bought = strategy.position_size > strategy.position_size[1] or strategy.position_size < strategy.position_size[1] // Price Action Stop and Take Profit LL=(lowest(i_SPL))*(1-i_PercIncrement) HH=(highest(i_SPL))*(1+i_PercIncrement) LL_price = valuewhen(bought, LL, 0) HH_price = valuewhen(bought, HH, 0) entry_LL_price = strategy.position_size > 0 ? LL_price : na entry_HH_price = strategy.position_size < 0 ? HH_price : na tp=strategy.position_avg_price + (strategy.position_avg_price - entry_LL_price)*i_TPRRR stp=strategy.position_avg_price - (entry_HH_price - strategy.position_avg_price)*i_TPRRR // ATR Stop ATR=atr(i_ATR)*i_ATRMult ATRLong = ohlc4 - ATR ATRShort = ohlc4 + ATR ATRLongStop = valuewhen(bought, ATRLong, 0) ATRShortStop = valuewhen(bought, ATRShort, 0) LongSL_ATR_price = strategy.position_size > 0 ? ATRLongStop : na ShortSL_ATR_price = strategy.position_size < 0 ? ATRShortStop : na ATRtp=strategy.position_avg_price + (strategy.position_avg_price - LongSL_ATR_price)*i_TPRRR ATRstp=strategy.position_avg_price - (ShortSL_ATR_price - strategy.position_avg_price)*i_TPRRR // Strategy Stop DayStart = time == timestamp("UTC", year, month, dayofmonth, 0, 0, 0) plot(DayStart ? 1e9 : na, style=plot.style_columns, color=color.silver, transp=80, title="Trade Day Start") float LongStop = valuewhen(DayStart,low,0)*(1-i_PercIncrement) float ShortStop = valuewhen(DayStart,high,0)*(1+i_PercIncrement) float StratTP = strategy.position_avg_price + (strategy.position_avg_price - LongStop)*i_TPRRR float StratSTP = strategy.position_avg_price - (ShortStop - strategy.position_avg_price)*i_TPRRR /////////////////////// STRATEGY LOGIC ///////////////////////////////////////// MFI=mfi(close,i_MFI) barsize=high-low barbodysize=close>open?(open-close)*-1:(open-close) shortwicksbar=barbodysize>barsize*barsizeThreshold SMA=sma(close, i_MALen) MAFilter=close > SMA timesinceentry=(time - valuewhen(bought, time, 0)) / 60000 timedexit=timesinceentry == 60 BUY = MFI[1] == OB and close > open and shortwicksbar and (i_MAFilter ? MAFilter : true) bool SELL = na if short SELL := MFI[1] == OS and close < open and shortwicksbar and (i_MAFilter ? not MAFilter : true) //Debugging Plots plot(timesinceentry, transp=100, title="Time Since Entry") //Trading Inputs DPR=input(true, "Allow Direct Position Reverse") reverse=input(false, "Reverse Trades") // Entries if reverse if not DPR strategy.entry("long", strategy.long, when=SELL and strategy.position_size == 0) strategy.entry("short", strategy.short, when=BUY and strategy.position_size == 0) else strategy.entry("long", strategy.long, when=SELL) strategy.entry("short", strategy.short, when=BUY) else if not DPR strategy.entry("long", strategy.long, when=BUY and strategy.position_size == 0) strategy.entry("short", strategy.short, when=SELL and strategy.position_size == 0) else strategy.entry("long", strategy.long, when=BUY) strategy.entry("short", strategy.short, when=SELL) if i_timedexit strategy.close_all(when=timedexit) SL= i_SLType == "Swing Lo/Hi" ? entry_LL_price : i_SLType == "ATR Stop" ? LongSL_ATR_price : LongStop SSL= i_SLType == "Swing Lo/Hi" ? entry_HH_price : i_SLType == "ATR Stop" ? ShortSL_ATR_price : ShortStop TP= i_SLType == "Swing Lo/Hi" ? tp : i_SLType == "ATR Stop" ? ATRtp : StratTP STP= i_SLType == "Swing Lo/Hi" ? stp : i_SLType == "ATR Stop" ? ATRstp : StratSTP //TrailingStop dif=(valuewhen(strategy.position_size>0 and strategy.position_size[1]<=0, high,0)) -strategy.position_avg_price trailOffset = strategy.position_avg_price - SL var tstop = float(na) if strategy.position_size > 0 tstop := high- trailOffset - dif if tstop<tstop[1] tstop:=tstop[1] else tstop := na StrailOffset = SSL - strategy.position_avg_price var Ststop = float(na) Sdif=strategy.position_avg_price-(valuewhen(strategy.position_size<0 and strategy.position_size[1]>=0, low,0)) if strategy.position_size < 0 Ststop := low+ StrailOffset + Sdif if Ststop>Ststop[1] Ststop:=Ststop[1] else Ststop := na strategy.exit("TP & SL", "long", limit=TP, stop=TS? tstop : SL, when=i_SL) strategy.exit("TP & SL", "short", limit=STP, stop=TS? Ststop : SSL, when=i_SL) /////////////////////// PLOTS ////////////////////////////////////////////////// plot(i_SL and strategy.position_size > 0 and not TS ? SL : i_SL and strategy.position_size > 0 and TS ? tstop : na , title='SL', style=plot.style_cross, color=color.red) plot(i_SL and strategy.position_size < 0 and not TS ? SSL : i_SL and strategy.position_size < 0 and TS ? Ststop : na , title='SSL', style=plot.style_cross, color=color.red) plot(i_SL and strategy.position_size > 0 ? TP : na, title='TP', style=plot.style_cross, color=color.green) plot(i_SL and strategy.position_size < 0 ? STP : na, title='STP', style=plot.style_cross, color=color.green) // Draw price action setup arrows plotshape(BUY ? 1 : na, style=shape.triangleup, location=location.belowbar, color=color.green, title="Bullish Setup", size=size.auto) plotshape(SELL ? 1 : na, style=shape.triangledown, location=location.abovebar, color=color.red, title="Bearish Setup", size=size.auto)