This is an amazingly good tutorial and you, Chad, are an amazingly good teacher/guide. You don't make things more complicated than they are. You stay on track.
Perfect course! The best out there by far. What I still don't get is how to replace a sl or tp if a certain event happens. For example I would like to move my stop loss up if a take profit of another order was hit.
You can access the trades with self.trades and you can adjust the stop loss and take profit by doing for example for trade in self.trades: trade.sl=NEW_VALUE
Great video Chad. I really appreciate you taking the time. I'm three months into learning Python and stock investing and I was able to follow along this entire video.
I am watching your tutorial over the others because your using VIM as your editor :) This shows the commitment of a person to learn beyond what is required Awesome work and thank you for the wonderful tutorial !
This is the best tutorial on backtesting iN RUclips.. a quick question. How do I for loop through different strategy classes for running tests in backtesting.py
Thank you for another Great video. I really do Love your video and channel, so much information on topics where there is hardly any information elsewhere ✌️. BTW, could you post in the description a pros and cons table comparing VectorBT vs. Backtesting.py or perhaps you can make a short 5 min video comparing the differences and highlighting the use cases.
Hi Chad, Thank you for the good video. If I had known this video first, I could have saved a lot of time. But I was able to get a lot of ideas from watching this video. Thanks once again.
Very interresting and clever explanation about backtesting. I'm looking since a few months for readable and understandable content about backtesting, and .. I just found it now :) Thanks for that. I'm more "crypto market" oriented, and more scalping strategy interrested (I don't have so much time to trade :'( ) Thanks for this video, and waiting for the next ones. PS : I modified this message and deleted my "request" about developping a BOT, it is in your blog ;)
Chad, I really appreciate your content, very well explained, you are an excellent teacher and your content is incredible! thanks again! I will study all the content on your channel!
Thank u… By the way, I like your contents a lot because of your exclusive content, as well as your deep and soothing voice, With that British accent :) so because of that, I can normally watch an hour-long video with no boring
Hello, by default is doing size of units, how will be possible to make sizes with decimals, for example always enter with 0.95 of equity in ethereum, should be units with decimals
Very good tutorial. I have some problems to install TA-LIB on my Win11 computer, because of the Python version that I have (3.11). I solved this by creating an environment with Python 3.10.
Good tutorial and introduction of this backtest library! Thanks. One last question: Would you bet your real money on strategies that you have tested with this library?
22:00 when we did optimization over a much larger set of configs, we maximized the return and the sharp ratio improved as well. Why is it a bad thing. Please explain =) THanks
There is a way to do it. By using for loop, where you will be able to test multiple tickers and even multiple timeframe. (if this is what you mean, it's easy to do it especially with this library, compare to freqTrade)
@@damienong1462 No, that's not what I meant. Looping just runs a sequential series of separate tests. What I'm talking about involves trading multiple instruments as a single strategy.
Maybe cover trailing stop in a future video? Or can you replace an open order to sell with a new order that you want instead? For example a trailing stop % from the average price, not the close?
Hi Chad, this is a wonderful tutorial. Very well explained with the right context.I need help with the date column from a CSV file. python is not reading it as DateTime format but instead, it is reading it as an object. Not able to solve it, and because which not getting Sharpe and other ratios.
Hi @@ChadThackray, I am observing that my entries and exits are delayed by two candles not sure why it is happening. Send you an email with the python code and data file. Thanks
EDIT SOLVED: Downgrading bokeh to 2.4.3 solved the plotting issue I am unable to see the plotting using Jupyter notebooks. I've looked through the issue tracker and the fixes didn't work(or I couldn't figure out how to downgrade Python to 3.7). Any ideas?
Hi Chad, thanks for the detailed tutorial! Is it possible to backtest mulit-asset strategies using this API i.e. say option straddle strategy, or say buying a stock and shorting an index at the same time if a signal is generated? Otherwise this would be really limited long/short strategies only and not dollar/delta neutral strategies.
noob question here, what is that screen at 5:10 when you type "from backtesting import Backtest, Strategy" ? i successfully downloaded python, and my 'pip install backtest' in the CMD window worked, but where do i go to get what you have at 5:10? what screen is that? thx!
I'm using vim here as my text editor on the command line. You might want to use something like visual studio code or pycharm or similar program, which will do the same thing
Hi Chad! I hope you are doing really well. Thanks for this amazing tutorial! Do you know if it's possible to do live trading with a strategy developed using this library?
Chad's course is amazing. Sorry if not the place to answer, but I happen to be working on a video to try to easily convert to Interactive Brokers live trading so eventually check out my video in maybe a week or so lol.
Great video sir. Quick question. Delving deeper into algorithmic trading, I’ve found that mere backtesting isn’t sufficient and processes like out-of-sample backtesting, Sample parameter optimization, walk-forward optimization and Monte Carlo Simulation are viltal to creating a solid system. Question is: how do you conduct these tests with Python?
You are correct. There are many videos here on youtube that will teach you how to do these other tests. Some of those topics I've covered myself on this channel
How to write a strategy in backteting like : input data to backtest is one-minute chart, logic : get High and Low of 2 PM (5 minute candle), and then if current close > high buy order with target 20points , if current close < low sell with tartget of 20 points. Thanks
Hey Chad great work, i have a question. If i have a dictionary of dataframes for 50 stocks. All of the dataframes have the same start and end date. So how can i run a backtest over all of them instead of running the backtest only one a single dataframe?
Great video, very informative. I am just having one problem while applying the multitimeframe strategy. If resample_apply is done on an indicator which takes more than one inputs, it is giving all sorts of errors.
There is df.droplevel(axis=0, level=2) to drop "rsi_window" index level. That would be more reasonable to use instead of grouping and using meaningless .mean method.
In the tutorial, there is example to resample from daily to weekly data such as: self.weekly_rsi = resample_apply("W-FRI", talib.RSI, self.data.Close, self.rsi_window). However for future contract such as MNQ, its session opening time is not exactly in the same day (using Eastern Time as base). For example MNQ's monday session starts trading from Sunday 6PM ET until Monday 5PM ET. Than for the above case, how do you define "session", "daily" and "weekly" resample? Thank you so much!
hi there. I would like use Bollinger Bands and consider "lenght" and "stdev" as variables to be used within the optimization function. have you got some solving answer?!??!?! pllsssssss
Hi Chad, how confident are you to deploy a strategy after backtesting it? As in is there a strategy that is as profitable as/reflects the backtest without too many discrepancies? If not till what extent can we trust the backtest stats?
Thank you for the detailed explanation. I have a question, what's the difference between ''' crossover(self.daily_rsi, self.upper_bound) ''' and ''' self.daily_rsi [-1] > self.upper_bound ''' It would be helpful for the explanation :) Thanks first!
btw, I want to ask: ''' self.buy(sl = 0.95 * price) ''' Does that mean if the order is less than 95% of the price, the order will be sold? Or if the order is bought when the price is 95% of the current price?
I am new to python and was just curious what you're using to write your code in? I couldn't make it out when you said it in the beginning but would like to use the same platform
Yep! You can get it from the stats. So you have something like: output = bt.run() curve = output._equity_curve If you look it's just under all the other stats like sharpe, etc. You get a nice pandas df you can plot to your heart's content
If I run a backtest using moving averages with n periods, the dataframe will contain Nan values for the first n1 periods. So the strategy will actually not be backtested at the start date I initially set up. But it will compare with a buy and hold return strategy using the correct dataframe. So the comparison is actually not correct. What would be the fix?
@@sChaikovsky This will not solve the issue. Let's say my dataframe starts on January 1, 2015. Whether I add "if len(self.data) < self.n2" or not, the SMA cross strategy will start in n2 periods after January 1, 2015. But when I run output, the start period of the buy and hold strategy will still be January 1, 2015. So the periods for both strategies will not be the same.
@@borism4849 then you need to create backtesting library by yourself. Their backtesting library will start from the first date on your input data frame. I think instead of caring so much about NA values, you should focus on finding the best strategy with optimized parameters. NA values period is where no tradings took place, so your money still be the same. If you care so much about NA values, why don’t you prepare everything (e.g. 2 sma values into your data frame) first. Then in init() function you don’t need to perform anything, just type only “pass”. But by doing this, you will not be able to use their optimize function anymore I think. Nothing in this world cannot answer for all of what you need, you need to create it by yourself. I create everything by myself too. I just use everything on the internet as the guideline.
Great tutorial! I have a question. Why is my stats not calculating any of the Ratios or Volatility, there is multiple trades and everything else is displayed. Ratios and Volatility are NaN values.
Hi Chad, is there any possibility to extend the _trades dataframe with for example the stop loss and take profit? Or any other trade attribute like a specific trade enty criteria? This would be very helpful to analyse which trades working and which are not working.
Hi Chad @ 1:15 you said it doesn’t try to integrate with a broker does that mean i can only backtest and optimise i cant trade with it via api or whatever. I’m a python beginner
is there any other forex backtesting library, because I am having an issue regarding order size, leverage, lot size which are bit different than stock or crypto market...It would be very helpful. Thank you
Can you use a ML algorithm as part of your strategy? (ML algorithm will be trained on data to say buy, sell, or hold?) Thanks for the video! You're awesome
Great Video! Can you simultaneously do a backtesting on all 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 😀
Thanks for the video. Many questions and queries come to me. How to code a stop loss and take profit as a percentage of the purchasing power? Is there bibliography of online courses regarding this backtesting library?
I was thinking in collecting the last n candles live with the broker api and run the backtesting strategy, every time that a new candle is added, the backstesting strategy is run again and place an order (or close one) according to the last row of generated dataframe. Ugly? yes, not the best performance? yes. But since I will be using 1 minutes candles, it doesn't have to be fast. @@ChadThackray
Hi Chad, I am interested in running the backtesting with multiple threads in gpu-process. Could you please help to talk more about how to run it with GPU?
great video however I have a complex indicator which I am struggling to backtest. Do you have any strategies that you have built which are complex for example VIX/VVIX correlation?
Hi Chad, thank you for this video. I think that backtesting.py is not supported anymore because there are allot of errors when trying to run even a basic installation of it. Am I right? is there another version of it?
The developer is not super active to be sure. You can try looking on the github to see if anyone has the same problems as you. Probably have to downgrade some packages
One more question.. I am backtesting intraday strategy on 5 mins data and i want to limit the number of trades to say 1 or 2 .. Is there any in built function to achieve the limit on number of trades per day? FYI.. I am getting data from excel file.
@@ChadThackray Thanks for the answer.. But somehow m not able to fix this .. I saw ur video for how to use constraints. But particularly for limiting number of trades per day how to make it work.. that i am unable to do yet.
it seems like there's not much attention given to effectively utilizing multiple ticker symbols' data... is that because backtesting.py isn't well suited for this kind of use-case? seems like it's well thought out and everything, but does it shine in backtesting over any possible SET of ticker symbols? Could you maybe do something quick on this?
i see... do people really only run strategies on a single ticker symbol? seems so odd.. you think there would be some awareness of algorithms considering "universes" of stocks that have been filtered down based on criteria, and then traded...@@ChadThackray
Thanks for the video, awesome explanations! New subscription ;) I'm left thinking if it's possible to use some of the functions of the library in a different code which is mean to do trades and not only backtesting? Specifically, the bars since function. I ask because as I understand it as of now (after watching the video), you only seem to be able to use it inside a class which is extending the Strategy class imported also from this specific library, your RsiOscillator in this case.
nice video, i just have a question. im looking into de the documentation how i can set the data to the strategy instead of using GOOG or EURUSD. Buy i still not able to find it. Do you know how to feed the data to the strategy from a csv file?
i'm just guessing, but i dont know if i just need to set self.data = my_data, where my_data is a pd.DataFrame with my data. but i'm looking if its correct and the structure fo the datafram because what i read in the doc seems to be de open_time as index. am i correct?
@@ChadThackray thanks a lot. Im creating an indicator, the SSL because i didnt found it in talib library to test it. But i still have the problem with my dta. With GOOG its not issue but with my data it is. It has the Open High Low Close columns but im using 5m timeframe and my open_time colmn i setted as the index. is that correct? the Documentation doesnt says much about the topic
hey, nice intro. Waht about position sizing with futures or CFDs ? With margins, over night margins, what about slippage, broker costs as well as spreads?
Great content, thanks for your work! I am struggling with the size of the position for the backtesting. I am trying to risk 1% of the available cash per position so I enter the sl and size = 0.01. However, the risk is completely off and it only risk 0.014% I am also confused because in the video you just enter size without stop loss, but risk is normally calculated in function of the sl Would you maybe have a solution please? Thanks for your help!
You multi-timeline test code is somehow broken. Not sure how or how to fix. It has something to do with this line: self.daily_rsi = self.I(ta.rsiI, pd.Series(self.data.Close), self.rsi_window). It doesn't think that ta.rsil is a thing
Hi Chad, thanks for your video, it's helping me very much. Here I have a question when following your video finish the first step(backtesting sell when rsi>70 and buy at rsi < 30) pf.stats show Duration is 3116 days, but raw data GOOG only has 2148 rows. Is it right?
Hello!! Excellent video. I am exactly the code shown in the video, however I get the following error: "TypeError: Can't instantiate abstract class GoldenCross with abstract method init". What can it be, the version of python (I use 3.8.0)?
hi, let's say i have computed my own signals before i want to run the backtest, they are not derived from tecnical analysis, how can i backtest the strategy given from entering a position upon the signal is in and exiting when the signal is out (not shorting just exiting)? i only find videos on tecnical analysis i dont understand how to backtest a personal strategy not tecnical
@@ChadThackray sorry im newbie i dont get it :( let's say i have the OHLC of the sock and i have a column in a different dataset with only 0 if signal is to stay out and 1 if signal is to stay in, how can i backtest it with this library? is it possible?
@@w-asabi2784 Yeah lots of people are asking about this. Difficult to explain in youtube comments. I'll make a video on it in the next couple weeks going into more detail on custom indicators
@@ChadThackray thanks! I was thinking in deploying it with mljar-Mercury. By the way, would you recieve my personal resume please? I'm looking for job :)
Hi there. When I try to do a backtest on bitcoin with 10,000 equity it shows the order size as 1 even though it should be less than 1. Is this possible?
One last question. Is is there anyway the Return % output can be the total amount of each ReturnPct? At the moment the Return% is the total PnL divided by the initial capital.
![BLACK BAG - Official Trailer [HD] - Only in Theaters March 14](http://i.ytimg.com/vi/Du0Xp8WX_7I/mqdefault.jpg)
This is an amazingly good tutorial and you, Chad, are an amazingly good teacher/guide. You don't make things more complicated than they are. You stay on track.
Best tutorial of backtesting.py on youtube !, thanks
Holy ...!! I've been waiting for a course for this library, thanks!!
Perfect course! The best out there by far.
What I still don't get is how to replace a sl or tp if a certain event happens.
For example I would like to move my stop loss up if a take profit of another order was hit.
You can access the trades with self.trades and you can adjust the stop loss and take profit by doing for example for trade in self.trades: trade.sl=NEW_VALUE
This is a fantastic tutorial, errors and all. You're a hero!!
Great video Chad. I really appreciate you taking the time. I'm three months into learning Python and stock investing and I was able to follow along this entire video.
Good luck Darrell!
I was looking for this type of tutorial you are the man❤❤
I am watching your tutorial over the others because your using VIM as your editor :)
This shows the commitment of a person to learn beyond what is required
Awesome work and thank you for the wonderful tutorial !
This is the best tutorial on backtesting iN RUclips.. a quick question. How do I for loop through different strategy classes for running tests in backtesting.py
Thank you for another Great video. I really do Love your video and channel, so much information on topics where there is hardly any information elsewhere ✌️. BTW, could you post in the description a pros and cons table comparing VectorBT vs. Backtesting.py or perhaps you can make a short 5 min video comparing the differences and highlighting the use cases.
great work, this is excellent. I also appreciate the northern accent. It's been a while since I've heard a proper one.
Hi Chad, Thank you for the good video. If I had known this video first, I could have saved a lot of time. But I was able to get a lot of ideas from watching this video. Thanks once again.
Absoultely love the content, thanks for your hard work and grit.
Thanks a lot for this! Found exactly what I was looking for to run optimization.
Very interresting and clever explanation about backtesting. I'm looking since a few months for readable and understandable content about backtesting, and .. I just found it now :) Thanks for that.
I'm more "crypto market" oriented, and more scalping strategy interrested (I don't have so much time to trade :'( )
Thanks for this video, and waiting for the next ones.
PS : I modified this message and deleted my "request" about developping a BOT, it is in your blog ;)
Chad, I really appreciate your content, very well explained, you are an excellent teacher and your content is incredible! thanks again! I will study all the content on your channel!
Thank u… By the way, I like your contents a lot because of your exclusive content, as well as your deep and soothing voice,
With that British accent :)
so because of that, I can normally watch an hour-long video with no boring
Thank you for sharing this. I learn a lot from you ! much respect !
How to set the transaction time? For example, trading is only done between 8-12 New York time.
Another great Backtesting video Chad
Very Informative, helpful and Educational video! Thx for the tutorial man!
Hello, by default is doing size of units, how will be possible to make sizes with decimals, for example always enter with 0.95 of equity in ethereum, should be units with decimals
Very good tutorial. I have some problems to install TA-LIB on my Win11 computer, because of the Python version that I have (3.11). I solved this by creating an environment with Python 3.10.
Thank you for taking the time to do this... Very helpfull to me.
Awesome tutorial! Learnt a lot! Thanks a lot.
Thanks for sharing your wealth of knowledge in this excellent series Chad. I love your name by the way.
this was wonderful, thank you very much
Good tutorial and introduction of this backtest library! Thanks. One last question: Would you bet your real money on strategies that you have tested with this library?
dude you're the fucking best please post more about algotrading thanks
Brilliant. Very high quality work ❤
That was an awesome tutorial, thanks a lot!
22:00 when we did optimization over a much larger set of configs, we maximized the return and the sharp ratio improved as well. Why is it a bad thing. Please explain =) THanks
that was an excellent tutorial, thanks for sharing, liked and subbed.
You are just amazing !! thankyou so much for sharing your knowledge
Excellent tutorial. I like the simplicity of this library. It's too bad it can't test and aggregate results for multiple tickers.
There is a way to do it. By using for loop, where you will be able to test multiple tickers and even multiple timeframe. (if this is what you mean, it's easy to do it especially with this library, compare to freqTrade)
@@damienong1462 No, that's not what I meant. Looping just runs a sequential series of separate tests. What I'm talking about involves trading multiple instruments as a single strategy.
Maybe cover trailing stop in a future video? Or can you replace an open order to sell with a new order that you want instead? For example a trailing stop % from the average price, not the close?
Hi Chad, this is a wonderful tutorial. Very well explained with the right context.I need help with the date column from a CSV file. python is not reading it as DateTime format but instead, it is reading it as an object. Not able to solve it, and because which not getting Sharpe and other ratios.
I would look into the pd.to_datetime function from pandas, that will help you convert the date column from a string into datetime format
@@ChadThackray Thanks a lot. It worked. not the ratios are being calculated.😊👍
Hi @@ChadThackray, I am observing that my entries and exits are delayed by two candles not sure why it is happening. Send you an email with the python code and data file. Thanks
Chad, another really good training tutorial . Are you able to share the python code with each of your tutorialss pls?
so seems backtesting.py can't trade with fractional sizes (fractional ethereum for example 0.99 have to be 1 or 2 ethereum)
dude this was fantastic... helped a ton..thx...
thank you very much. this is very gorgeous video !!!! . It is very helpful.
EDIT SOLVED: Downgrading bokeh to 2.4.3 solved the plotting issue
I am unable to see the plotting using Jupyter notebooks. I've looked through the issue tracker and the fixes didn't work(or I couldn't figure out how to downgrade Python to 3.7).
Any ideas?
Is there any particular reason you need jupyter? If not you can just run it as a regular .py
@@ChadThackray Thank you for answering! I just like Jupyter, but I had the same problem with VSCode as well
@@BOSprodz I had the same problem in both places to.
Thank´s for your Idea. I used pip install bokeh==2.4.3 in MacOS for degreed bokeh from 3.0.3 to 2.4.3 and then the HTML in safari browser was ok.
Hi Chad, thanks for the detailed tutorial! Is it possible to backtest mulit-asset strategies using this API i.e. say option straddle strategy, or say buying a stock and shorting an index at the same time if a signal is generated? Otherwise this would be really limited long/short strategies only and not dollar/delta neutral strategies.
noob question here, what is that screen at 5:10 when you type "from backtesting import Backtest, Strategy" ? i successfully downloaded python, and my 'pip install backtest' in the CMD window worked, but where do i go to get what you have at 5:10? what screen is that? thx!
I'm using vim here as my text editor on the command line. You might want to use something like visual studio code or pycharm or similar program, which will do the same thing
Hi Chad! I hope you are doing really well. Thanks for this amazing tutorial! Do you know if it's possible to do live trading with a strategy developed using this library?
Chad's course is amazing. Sorry if not the place to answer, but I happen to be working on a video to try to easily convert to Interactive Brokers live trading so eventually check out my video in maybe a week or so lol.
Great video sir. Quick question. Delving deeper into algorithmic trading, I’ve found that mere backtesting isn’t sufficient and processes like out-of-sample backtesting, Sample parameter optimization, walk-forward optimization and Monte Carlo Simulation are viltal to creating a solid system. Question is: how do you conduct these tests with Python?
You are correct. There are many videos here on youtube that will teach you how to do these other tests. Some of those topics I've covered myself on this channel
@@ChadThackray cool. I’ll check them out. Thank you
How to write a strategy in backteting like : input data to backtest is one-minute chart, logic : get High and Low of 2 PM (5 minute candle), and then if current close > high buy order with target 20points , if current close < low sell with tartget of 20 points.
Thanks
Hey Chad great work, i have a question. If i have a dictionary of dataframes for 50 stocks. All of the dataframes have the same start and end date. So how can i run a backtest over all of them instead of running the backtest only one a single dataframe?
Great video, very informative.
I am just having one problem while applying the multitimeframe strategy. If resample_apply is done on an indicator which takes more than one inputs, it is giving all sorts of errors.
self.tf2MDI = resample_apply(
'3T',ta.MINUS_DI(high,low,price,self.n) As an example is not working
There is df.droplevel(axis=0, level=2) to drop "rsi_window" index level. That would be more reasonable to use instead of grouping and using meaningless .mean method.
i needed this today. chad sent
In the tutorial, there is example to resample from daily to weekly data such as:
self.weekly_rsi = resample_apply("W-FRI", talib.RSI, self.data.Close, self.rsi_window).
However for future contract such as MNQ, its session opening time is not exactly in the same day (using Eastern Time as base). For example MNQ's monday session starts trading from Sunday 6PM ET until Monday 5PM ET.
Than for the above case, how do you define "session", "daily" and "weekly" resample?
Thank you so much!
hi i have a huge problem, if i fix the quantity 1 i don’t work the code regarding the peack and the final how can i fix it?
thx for the very detailed tutorial! appreciate it!
hi there. I would like use Bollinger Bands and consider "lenght" and "stdev" as variables to be used within the optimization function. have you got some solving answer?!??!?! pllsssssss
Hi Chad, how confident are you to deploy a strategy after backtesting it? As in is there a strategy that is as profitable as/reflects the backtest without too many discrepancies? If not till what extent can we trust the backtest stats?
Depends on your setup but generally a backtest alone is not enough. Paper trade it before deploying actual cash
Thank you for the detailed explanation.
I have a question, what's the difference between
'''
crossover(self.daily_rsi, self.upper_bound)
'''
and
'''
self.daily_rsi [-1] > self.upper_bound
'''
It would be helpful for the explanation :)
Thanks first!
btw,
I want to ask:
'''
self.buy(sl = 0.95 * price)
'''
Does that mean if the order is less than 95% of the price, the order will be sold?
Or if the order is bought when the price is 95% of the current price?
I am new to python and was just curious what you're using to write your code in? I couldn't make it out when you said it in the beginning but would like to use the same platform
I'm using Vim, a command line based text editor
@@ChadThackray Thank you!
Can we put constraints on more than 1 parameter, and maximize/minimize several (more than 1) parameters?
Thank you! Nice video! Is there any way to save the equity line data, so that you can, for example, draw it with matplotlib?
Yep! You can get it from the stats. So you have something like:
output = bt.run()
curve = output._equity_curve
If you look it's just under all the other stats like sharpe, etc. You get a nice pandas df you can plot to your heart's content
If I run a backtest using moving averages with n periods, the dataframe will contain Nan values for the first n1 periods. So the strategy will actually not be backtested at the start date I initially set up. But it will compare with a buy and hold return strategy using the correct dataframe. So the comparison is actually not correct. What would be the fix?
def next():
if len(self.data) < n:
return
….continue with your code….
@@sChaikovsky Here is my code:
class SMAcross(Strategy):
n1 = 20
n2 = 50
def init(self):
self.sma1 = self.I(SMA, self.data.Close,self.n1)
self.sma2 = self.I(SMA, self.data.Close,self.n2)
def next(self):
if crossover(self.sma1,self.sma2):
self.buy()
elif crossover(self.sma2,self.sma1):
self.sell()
Can you help me please
@@borism4849 Just insert this under def next(self):
if len(self.data) < self.n2:
return
if crossover…
self.buy()
elif crossover,,,,
self.sell()
@@sChaikovsky This will not solve the issue. Let's say my dataframe starts on January 1, 2015. Whether I add "if len(self.data) < self.n2" or not, the SMA cross strategy will start in n2 periods after January 1, 2015. But when I run output, the start period of the buy and hold strategy will still be January 1, 2015. So the periods for both strategies will not be the same.
@@borism4849 then you need to create backtesting library by yourself. Their backtesting library will start from the first date on your input data frame.
I think instead of caring so much about NA values, you should focus on finding the best strategy with optimized parameters.
NA values period is where no tradings took place, so your money still be the same.
If you care so much about NA values, why don’t you prepare everything (e.g. 2 sma values into your data frame) first. Then in init() function you don’t need to perform anything, just type only “pass”.
But by doing this, you will not be able to use their optimize function anymore I think.
Nothing in this world cannot answer for all of what you need, you need to create it by yourself. I create everything by myself too. I just use everything on the internet as the guideline.
Hey, great content! I'm wondering how your init function is working properly without a double underscore..isn't init usually a dunder method?
Thanks.
It's not a real __init__ function. We're just overriding a function from the parent class
nice video, what about extending the Stats with CAGR/MaxDD?
Great tutorial!
I have a question. Why is my stats not calculating any of the Ratios or Volatility, there is multiple trades and everything else is displayed. Ratios and Volatility are NaN values.
Found the answer, you should change the data frame like this with pandas:
spx500.set_index('Date', inplace=True)
Awesome Tutorial, Thanks a lot.
Hi Chad, is there any possibility to extend the _trades dataframe with for example the stop loss and take profit? Or any other trade attribute like a specific trade enty criteria? This would be very helpful to analyse which trades working and which are not working.
It's open source so anything is possible. I would just build my own logger though in the main logic and use that to analyse
could you make more in depth explanations for each action you can make with this library?
Hi Chad @ 1:15 you said it doesn’t try to integrate with a broker does that mean i can only backtest and optimise i cant trade with it via api or whatever. I’m a python beginner
Yes, there are no live trading functionalities. You could probably modify it to do that if you wanted, but it wouldn't be too easy
is there any other forex backtesting library, because I am having an issue regarding order size, leverage, lot size which are bit different than stock or crypto market...It would be very helpful. Thank you
Awesome video. I dont know how you got the plot going so well. For me its just a white screen. All the stats show in python just no plot
Glad you liked it! On the github issues for the library it says to install bokeh==2.4.3 to fix the problem.
@@ChadThackray Wow. Thank you. Its working now
I found It @Chaf Thackray . As soon i GET hom i'll try
I justo hace a question
When i'm un the next method
To use the actual data and the before injusto need yo use (for ex) self.rsi[-1] and [-2].?
Amazing video!
@chad...how can it be run to test bracket orders
Can you use a ML algorithm as part of your strategy? (ML algorithm will be trained on data to say buy, sell, or hold?) Thanks for the video! You're awesome
Great Video! Can you simultaneously do a backtesting on all 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
😀
Thanks for the video. Many questions and queries come to me.
How to code a stop loss and take profit as a percentage of the purchasing power?
Is there bibliography of online courses regarding this backtesting library?
It's a relatively niche library so there's not much content out there. Hence this video
It's a relatively niche library so there's not much content out there. Hence this video
Enjoyable and informative video.
how do you use a backtesting strategy to do live trading? is there an easy way to re-use this code and instead of do backtesting do live trading?
An easy way is to use a framework that does both. Backtesting.py only does backtesting.
@@ChadThackray thanks for the reply, so I think I should use backtrader then. Any recommendation if I'm looking to trade forex?
I was thinking in collecting the last n candles live with the broker api and run the backtesting strategy, every time that a new candle is added, the backstesting strategy is run again and place an order (or close one) according to the last row of generated dataframe. Ugly? yes, not the best performance? yes. But since I will be using 1 minutes candles, it doesn't have to be fast. @@ChadThackray
good tutorial, one question about soft recording. How do you do it? lol
Hi Chad, I am interested in running the backtesting with multiple threads in gpu-process. Could you please help to talk more about how to run it with GPU?
You can use CUDA
Have you succeeded in that?
You really are a Chad. Fr
great video however I have a complex indicator which I am struggling to backtest. Do you have any strategies that you have built which are complex for example VIX/VVIX correlation?
how is gone since then?
Excellent video
Hi Chad, thank you for this video. I think that backtesting.py is not supported anymore because there are allot of errors when trying to run even a basic installation of it. Am I right? is there another version of it?
The developer is not super active to be sure. You can try looking on the github to see if anyone has the same problems as you. Probably have to downgrade some packages
One more question.. I am backtesting intraday strategy on 5 mins data and i want to limit the number of trades to say 1 or 2 .. Is there any in built function to achieve the limit on number of trades per day? FYI.. I am getting data from excel file.
You can add a custom constraint function on the optimizer. I've done this in one of my backtesting.py videos but from memory I can't recall which
@@ChadThackray Thanks for the answer.. But somehow m not able to fix this .. I saw ur video for how to use constraints. But particularly for limiting number of trades per day how to make it work.. that i am unable to do yet.
it seems like there's not much attention given to effectively utilizing multiple ticker symbols' data... is that because backtesting.py isn't well suited for this kind of use-case? seems like it's well thought out and everything, but does it shine in backtesting over any possible SET of ticker symbols? Could you maybe do something quick on this?
You can just for loop over different symbols. Backtesting portfolios of different assets really isn't very good in backtesting.py though
yea i mean if you're wanting to define a universe of stocks.. is that not really a thing backtesting.py can accommodate@@ChadThackray
i see... do people really only run strategies on a single ticker symbol? seems so odd.. you think there would be some awareness of algorithms considering "universes" of stocks that have been filtered down based on criteria, and then traded...@@ChadThackray
Thanks for the video, awesome explanations! New subscription ;)
I'm left thinking if it's possible to use some of the functions of the library in a different code which is mean to do trades and not only backtesting? Specifically, the bars since function.
I ask because as I understand it as of now (after watching the video), you only seem to be able to use it inside a class which is extending the Strategy class imported also from this specific library, your RsiOscillator in this case.
nice video, i just have a question. im looking into de the documentation how i can set the data to the strategy instead of using GOOG or EURUSD. Buy i still not able to find it. Do you know how to feed the data to the strategy from a csv file?
i'm just guessing, but i dont know if i just need to set self.data = my_data, where my_data is a pd.DataFrame with my data. but i'm looking if its correct and the structure fo the datafram because what i read in the doc seems to be de open_time as index. am i correct?
@@cosmicblack Just load in the CSV as a pandas dataframe. Then feed it in the same as we do for GOOG
@@ChadThackray thanks a lot. Im creating an indicator, the SSL because i didnt found it in talib library to test it. But i still have the problem with my dta. With GOOG its not issue but with my data it is. It has the Open High Low Close columns but im using 5m timeframe and my open_time colmn i setted as the index. is that correct? the Documentation doesnt says much about the topic
hey, nice intro. Waht about position sizing with futures or CFDs ? With margins, over night margins, what about slippage, broker costs as well as spreads?
Great content, thanks for your work!
I am struggling with the size of the position for the backtesting. I am trying to risk 1% of the available cash per position so I enter the sl and size = 0.01. However, the risk is completely off and it only risk 0.014%
I am also confused because in the video you just enter size without stop loss, but risk is normally calculated in function of the sl
Would you maybe have a solution please?
Thanks for your help!
Brilliant video
Hey what do you think of quant connect?
You multi-timeline test code is somehow broken. Not sure how or how to fix.
It has something to do with this line: self.daily_rsi = self.I(ta.rsiI, pd.Series(self.data.Close), self.rsi_window). It doesn't think that ta.rsil is a thing
Hi Chad, thanks for your video, it's helping me very much.
Here I have a question when following your video finish the first step(backtesting sell when rsi>70 and buy at rsi < 30)
pf.stats show Duration is 3116 days, but raw data GOOG only has 2148 rows.
Is it right?
Hello. the source code is like that trades_df['Duration'] = trades_df['ExitTime'] - trades_df['EntryTime']
just between entry time and exit time
@@jungkyunyang5184 Thanks😀
Thank you for the vid! Did you leave the TA-lib installation link anywhere? I'm not seeing it
Just updated the description
@@ChadThackray Cool, thank you! Great video, by the way.. it got me up and running!
Hello!! Excellent video. I am exactly the code shown in the video, however I get the following error: "TypeError: Can't instantiate abstract class GoldenCross with abstract method init". What can it be, the version of python (I use 3.8.0)?
Type def init(self) instead of def __init__(self) . It was my mistake too
hi, let's say i have computed my own signals before i want to run the backtest, they are not derived from tecnical analysis, how can i backtest the strategy given from entering a position upon the signal is in and exiting when the signal is out (not shorting just exiting)? i only find videos on tecnical analysis i dont understand how to backtest a personal strategy not tecnical
Just make your own function, then make it into an indicator, then use that to run your trading logic
@@ChadThackray sorry im newbie i dont get it :( let's say i have the OHLC of the sock and i have a column in a different dataset with only 0 if signal is to stay out and 1 if signal is to stay in, how can i backtest it with this library? is it possible?
@@w-asabi2784 Yeah lots of people are asking about this. Difficult to explain in youtube comments. I'll make a video on it in the next couple weeks going into more detail on custom indicators
@@ChadThackray thank you so much :) ill activate the bell then
It's amazing the plot function, there is a way to export it?
The plot is saved as a html file in the folder you run the script from, so you can re-use that.
Alternatively you can just screenshot it
@@ChadThackray thanks! I was thinking in deploying it with mljar-Mercury. By the way, would you recieve my personal resume please? I'm looking for job :)
Hi there. When I try to do a backtest on bitcoin with 10,000 equity it shows the order size as 1 even though it should be less than 1. Is this possible?
Backtesting.py doesn't deal in fractions of an asset by default. I have another video on how to deal with this situation
@@ChadThackray Thankyou for your reply. Are you able to point me to the right video? Thanks
@@ChadThackray Found it ruclips.net/video/3yu4FWmTNh0/видео.html
One last question. Is is there anyway the Return % output can be the total amount of each ReturnPct? At the moment the Return% is the total PnL divided by the initial capital.
Great channel - I wonder if you have come across Empyrial portfolio analysis
And if so what do you think of it