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The Trading Muse
Приєднався 10 тра 2021
The Trading Muse is about understanding how markets move. Trading strategies are backtested and other analyses are done. However, the information provided is only for general and educational purposes only. Nothing in this channel is investment or trading advice. I am not a registered broker-dealer or registered investment adviser.
92% Win Rate: Parabolic SAR + EMA Trading Strategy Backtested with Bitcoin 5 Minute Data
Parabolic stop and reverse (PSAR) is a widely used technical indicator. In this video I backtest and optimize PSAR and EMA trading strategy using historical 5 minute data for Bitcoin. This time I wanted to find a high win rate so the optimization is based on that. The results show a 92% win rate. But how about the return rate?
Переглядів: 1 711
Відео
Classic MACD + EMA + ATR Trading Strategy Tested with EURUSD for Over 20 Years 5 Minute Candles
Переглядів 1,2 тис.3 роки тому
The classic MACD EMA ATR Trading Strategy for scalping is back tested with Forex EURUSD pair. The data for five minute candles spans over 20 years and is tested over 14500 times. The ATR multiples are optimized based on System Quality Number (SQN).
How to use Stop loss and Take Profit for Backtesting module in Python
Переглядів 2,2 тис.3 роки тому
Backtesting module in python is one of the simpler frameworks for doing back tests. In this video I show how to use stop loss and take profit both as a fixed percentage and as multiples of Average True Range (ATR) in the back tests of your trading strategies.
Morning Star Candle Stick Pattern Trading Strategy Back Tested with Bitcoin 5 Minute Data
Переглядів 3953 роки тому
The morning star candle stick pattern can imply a change in the direction of a downtrend, from bearish to bullish. In this video I use python and TALib pattern recognition methods to backtest a trading strategy using only the morning star as the entry signal. The backtest data is Bitcoin 5 minute candles between 2012 and 2021.
RSI + EMA Trading Strategy Backtested with Bitcoin 5 Minute Historical Data
Переглядів 6413 роки тому
Using historical Bitcoin data the RSI and triple EMA trading strategy is tested for 5 minute candles. The strategy uses two fast EMA crossovers which are found from optimization. The stop loss and take profit targets are also obtained from the optimization with python. The results of the optimizations, the heatmap, an example trade and the python code using Backtesting.py is provided. Remember ...
90% Win Rate: Bollinger Bands + EMA Trading Strategy Backtested with Bitcoin 5 Minute Data
Переглядів 6 тис.3 роки тому
Bollinger Bands is a widely used technical indicator. In this video I backtest and optimize Bollinger Bands and EMA Trading strategy using historical 5 minute data for Bitcoin. This time I wanted to find a high win rate so the optimization is based on that. The results show a 90% win rate. But how about the return rate?
BB %B + AO + ADX + EMA Trading Strategy Tested with Ethereum 5 Minute Historical Data 2980 Times
Переглядів 7163 роки тому
Inspired by Trade Pro's video I backtested a trading strategy involving the Bollinger Bands %B indicator Awesome Oscillator ADX EMA indicators. The results with original strategy did not look good although win rate was OK, which are shown in the video. So I optimized the stop loss and take profit targets, those results look much better. I used five minute historical Ethereum price data for the ...
Best Simple Moving Average Period for Bitcoin Daily Trades
Переглядів 6363 роки тому
In this video the classic Simple Moving Average (SMA) crossover trading strategy is optimized with backtesting module in python and backtested with historical Bitcoin daily data in tradingview. - We first look at golden cross and death cross (50 and 200 day simple moving averages) results - Then using the optimized results we test the SMA crossover strategy with Bitcoin daily data. You will fin...
Stochastic RSI + Triple EMA + ATR Trading Strategy Tested over 2000 times with Bitcoin Hourly Data
Переглядів 3,4 тис.3 роки тому
Trade Pro's video claimed that Stochastic RSI Triple EMA ATR stop loss and take profit values used as a trading strategy performed very well. I wanted to test this assertion and see how it played out with Bitcoin hourly data. In this video I will first describe the strategy, then backtest it with almost 10 years of Bitcoin historical price data. I would like to remind that this is not trading o...
Which Day of Week is the best to trade Bitcoin? Monday or Sunday? How about weekdays and weekends?
Переглядів 3323 роки тому
Which days of the week do Bitcoin make biggest gains and losses? Is there a best day of week to trade it? How about weekdays or weekends, is there a difference? In this video I explore these questions using descriptive and inferential statistics. The R code is available at thetradingmuse.com/is-there-a-best-day-of-week-to-buy-or-sell-bitcoin/
MACD and EMA Trading Strategy Back Tested with Bitcoin 5 Minute Chart: Does it work? (Full results)
Переглядів 4,8 тис.3 роки тому
Trade Pro's video claimed that MACD EMA trading strategy performed very well. I wanted to test his assertion and see how it played out with Bitcoin. In this video you will find the backtest results with last 12 months data. Then I optimized the strategy to see if it works better. Afterwards I checked the optimized strategy against another time frame. You will not only learn about this trading s...
Stochastic+SMA+WMA Trading Strategy for Bitcoin 5 Minute Chart: Backtesting Results of 612 Trades
Переглядів 4,1 тис.3 роки тому
Inspired by Trade Pro's video I backtested Stochastic(14) and SMA(5) and WMA(144) trading strategy entry signals using Bitcoin 5 minute historical price data . In this video I describe the strategy in detail, give examples of trades, backtest it, then optimize the exit conditions. Very interesting results for two distinct time periods, the last one including 612 trades. The optimized parameters...
Backtesting.py SMA Crossover Strategy Example with Bitcoin: Using Python to Optimize Parameters
Переглядів 5 тис.3 роки тому
Want to learn how to do backtests with python? This video presents a Backtesting.py example. Through the video: 1. We will first install backtesting.py. 2. Then we will discuss the conceptual basis of Simple Moving Average Crossover Strategy (SMA). 3. Afterwards we will write the code together in python. 4. Then run the code. 5. Finally interpret the results. Backtesting is similar to Backtrade...
Great Video! Can you simultaneously do a backtesting on all 4 symbols like for example EURUSD and SPUSD so if I buy on SP500 on 2011-01-07 and sell on 2011-01- 10 then in the next buy this program will recheck the opportunity in EURUSD and SPUSD and automatically matches the buying signal and then buy that stock after 2011-01-10 in this way we can have a full return on investment 😀
Would you share the code?
How to make sure that Buy & Hold Return strategy and your strategy start at the same time?
You set the start and end date for the data, and use the same data set for both strategies.
@@thetradingmuse1384 Yes but if the strategy implies moving averages with n period, the strategy will start at n period after the start date. The buy and hold strategy will start at the start date. That's a problem.
You should post links for getting your code, like most do?
How do I set a stop-limit in backtesting.py
This is using small data, what do I do if I want to load large data(10gb) in chunks?
man, this is by far, the best channel to learn how to backtest strategies on UA-cam!!, PLEASE keep on uploading videos, they are really helpful
That's the plan!
@@thetradingmuse1384 Cool! Congrats for such a nice work!
How to use backtesting.py without talib?
You may want to check out kernc.github.io/backtesting.py/ for the examples. You can use other libraries too, talib is written in C and is fast.
@@thetradingmuse1384 The backtesting.py document is weak. There are a few examples.
I noticed that if you have a position and meets the buy criteria again, the system will sell off the current position first (decided by system) and buy again. Is the observation of the behavior correct?
In this strategy if SMA(short) crosses over SMA(long) then a buy signal is produced. This does not happen again unless the reverse happens first, SMA(long) crosses over SMA(short). So because you cannot get a buy signal when you already bought, the system keeps the position until the sell signal is produced, SMA(long) crosses over SMA(short).
Great work... Nicely explained.. Can you please make one for intraday . Like closing the existing position at the end of the day. is there a built in function for that??
There isn't a built in function to do this, but it can be done. Noted. I will make a video on that.
Hey, love your content! Could you share the source code for your videos? It would be nice to experiment with them.
Sure. I thought people did not watch the code part.
man can u please do 30m or 60m charts
Sure.
What is the actual strategy and the optimal settings for it?
The actual strategy is explained in the video. Optimization was based on win rate.
Can't know how I stopmed onto this. All in all GREAT clip 🥇. I also watched those rather similar from mStarTutorials and kinda wonder how you guys create these vids. MStar Tutorials also had cool information about similiar make money online things on his channel.
In Which timeframe do you backtest this strategy?
5 minute candles.
Backtesting library used here? How to add this candlestick entry criteria in Backtesting lib? Which function method can be used to optimize Exit ,SL & trail SL ?
The library is backtesting.py. I have an introduction video ua-cam.com/video/gdrSo1Yclys/v-deo.html
@@thetradingmuse1384 How to use two or three indicator for better entry or exit in Backtesting lib & use ATR as trailing SL for trailing ? MA cross method in docs is not showing this.
I'll do several videos showing these.
Hi, I think 7% stop-loss is a bit far from real trading. We can only take 1~2.5% risk. I see max drawdown is -85%, it is effectively blowing up the account. Did the drawdown happens in the early years? maybe bitcoin in its early years doesn't worth trading because the price doesn't move much?
I use all data available, Bitcoin is widely volatile. In the backtests, the best return percentages are always with high stop loss and take profit. In most cases the entry signals are accurate, it is the exit that matters.
Thank you very much for your analysis and help , your content is really priceless . Can you also make another video explaining how to write this method in python ?
Yes, soon
From where i can get these code.
I added the code here thetradingmuse.com/how-to-find-the-best-sma-crossover-trading-strategy-for-bitcoin-using-daily-data/ Enjoy!
How did you backtest the strategy since 2011 and what is the name of the trading platform, thanks
I dug the data from the web. May not be completely accurate. The backtests are done with Backtesting package in python.
nice vid!! The value in the heat map is the win rate?
Yes it is.
Nice!! I don't get what do you store in heatmap variable at line 51? What is that \ at the end? I am new in python
Heatmap stores the heatmap, the calculated values for different combinations of the parameters. \ just means the statement continues on the following line.
Do the opposite and win %40 percent gain :)
Merhaba python ile bot kodlama ve bactest yapabilmeyi profesyonel bir kanaldan öğrenmek istiyorum udemy üzerinden vs öneride bulunabilir misiniz?
udemy'de "python backtesting" diye aratırsanız birkaç ders çıkıyor. İnceleyebilirsiniz, ben kendim bakmadım.
@@thetradingmuse1384 sizin bu şekilde bir eğitim seriniz olacak mı?
would you optimize the parameters of indicators, such as, the period of EMAs? And it would better to change position size to keep the risk within a certain range. This way, you would not have one big trade dominating the profit.
In future videos I might do that. Thanks for the suggestion.
looks overfitted. if the heat map has a region of yellow (not a thin line), the result would look reasonable.
It probably is overfitted.
Thx alot for the good work. I hope other videos will come near soon. About the strategy, first results was awful as you said. But after optimization it is awesome. Do you thing that your optimization parameters are overfited? Did you check any other date section ( such as 01.01.2021 to 01.06.2021 etc) any acceptable results for other period or time frame? Did you applied Monte Carlo or walk-forward analysis on it? BR.
I have not checked for other time intervals. These results are probably overfitted.
It seems a Turkish voice
Hello. Have you tried in different time frames? Like 1h chart, 30m and so on? Also for other coins? Imo a strategy cannot be designed just for 1 coin and 1 time frame, otherwise it’s not a strategy it’s just an indicator
I haven't looked at other timeframes and other coins. Obviously different optimized periods will emerge.
So from what i understand is, in the optimized version your stop loss would be 4% and take profit 6% in Long positions, stop loss 1% and take profit 9% in short positions right ?
Yes.
thanks for this
You're welcome
SL and TP levels are incorrect. SL is last swing with an TP of 1.5R or 2 R.
Yes. The SL and TP are absolute in the backtest here, not from the last swing.
Are you testing this with tick data?
Not tick data. I'm using hourly OHLC in this video.
Turk musun aga? :) aksanin oyle gibi
%100
bunu yazmaya gelmiştim hahaha
Yeah, a promising strategy with a 25% win rate.... good luck with that
I an a membrer of Trade Pro’s community on Discord and I am also a supporter of his Patreon. As you will hear in his videos, he is sharing ideas on possible strategies to test for people to further develop into a full strategy. We are doing countless test with different configurations of strategies to find optimal parameters for any assets before deploying any of them in live trading. Many members are automating strategies with many ideas which are further tweaked over time to make sure parameters are optimised for CURRENT market conditions to avoid overfitting.
Good video and well explained however, watching the Trade Pro video in the link he takes long trades when the Stoch RSI and Signal line cross from below the 50 level and short trades when they cross down from above the 50 level. You seem to have it the other way round. Is this just a typo or do you have different entry criteria for the Stoch RSI?
The strategy is the same as Trade Pro. It seems to be a typo.
4:08 shows 15 M chart and not 5M? The risk is 1 percent and reward is 2 percent but at what level are you setting the Stop Loss?
Yes the chart is downsampled it's not showing 5 minutes. Stop loss is 1% and take profit is 2%.
This was one of the greatest videos of trading strategies, please do more videos like that with different strategies.
Will do.
please make a video on how to backtest and optimise a strategy in detail. that will be very helpful. keep posting content like this. great work 👍
Noted
Thanks for sharing this.
Thanks for listening
Hocam selam aksandan kaptim boyle devam icerikler gayet guzel!
Will do.
I would look into setting a SL at x% away from last high or low swing. A 1% stop loss right now means something much different than 1% meant in a flat market. You can also look into ATR for stop loss and TP. But i would look into a high low swing script, set SL x% away from last swing, then find a TP of 2:1 risk reward.
We can try both stop loss and take profit approaches, in another video.
Hey! Nice video! I Subscribed! I know a little python, but I'm fairly new to coding, and I would love to run this test my self. Can you tell me what I do after i copy the code into python? What now? Thanks!
You need the data first. Then you run the script via command line using "python script.py" or "python3 script.py".
Bu abi %100 Türk
%100
Good stuff, man, keep going
Thanks, will do!
@@thetradingmuse1384 btw what's your thoughts about ninja trader strategies scripting features, have you used it? Or you just prefer python
I like seeing the bowels of the programming so I prefer python.
Do you have an email or some way that we can get in contact?
This would be the best way to contact me: thetradingmuse.com/contact/
Are you on discord?
Not yet.
How do I get in contact with you?
Through this form you can contact me: thetradingmuse.com/contact/