[Ratimbum] BloodEmperor

stable
By Rob in Trading Bots Published November 2022 👁 2,577 views 💬 2 comments ★ Staff Pick

Description

This is a short scalper based on a very rough approximation of the following conditions: - Open MACD & EMA200 on 5 min timeframe - Condition 1: price must trade below EMA200 - Condition 2: MACD is above 0 line - Condition 3: Blue line crosses orange line If someone has the time to fully implement all conditions in Code Editor, please post it here after :) We all need a little help after FTX. MA settings should be set to EMA = 200 and SMA =9 (SMA should track price and not be distant) MACD Signal should be MacD - Zero Cross (Please check the settings screenshot ;) ) This bot will not function well in a change of trend. This is a bear market scalper and the weights of the indicators will make it hard for it to produce longs.
HaasScript
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

2 Comments

Sign in to leave a comment.

E
ehi.pluto over 3 years ago

Do you think it can be made faster? So that it works on 5 minute chart with multiple positions opened and closed within an hour when possible?
Apart from the question about this bot, my purpose would be to find a Scalping Bot on 1/5 minute chart, which creates a single position and exits from it based on some data such as EMA 60, EMA 100 and EMA 150, wanting also STC and Trend Trading Strategy.
I am quite inexperienced so I don't know if it is feasible and safe as a thing, understanding the risk of this kind of trading.

P
PragueQuantTrader over 3 years ago

Thanks for script, I create code version (it's isn't 1:1), but I believe that everybody can easy tweak the code by yourself.

-- Author: PragueQuantTrader
stopLossValue = Input('StopLoss', 3)
takeProfitValue = Input('Profit', 5)

close = ClosePrices()
high = HighPrices()
low = LowPrices()

signalMacd = SignalWeight(EasyMACD(1), 2)
signalRSI = SignalWeight(CC_EasyVolumeRSI(2),2)
signalMA = SignalWeight(EasyMA(0),2)

signal = GetWeightedConsensusSignal(3,3,1, signalMacd, signalRSI, signalMA)

indicatorContainer = IndicatorContainer(signal)
indicatorSignal = indicatorContainer[1]

safeties = SafetyContainer(StopLoss(stopLossValue)) -- StopLoss(stopLossValue) TakeProfit(takeProfitValue)

-- Insurances
insurances = InsuranceContainer() -- OvercomeFeeCosts() TradeOnlySideways()

-- Trade Bot
TradeBotContainer(safeties, indicatorSignal, insurances)