Backtesting py reddit It's relatively lightweight compared to other libraries like backtracker, and made to be extendable by the user. Strategy Which is the best and easy to use python library for beck testing trading strategies with custom indicators and multiple/mixed time frames? pybacktest – Vectorized backtesting framework in Python / pandas, designed to make your backtesting easier. py PyAlgotrade bt Feb 23, 2025 · Backtesting. If anyone has any recommendations of other frameworks or how to accomplish this, it would be greatly appreciated! for python and backtesting, use the yahoo finance API so you can retrieve data, import yfinance as yf, is the code and define the asset, timeframe, and all that and feed it into your model Backtesting in Python, recommendations please. py built it’s SMA indicator """ return pd. I built a back tester without significant library use (some pandas) in 150 lines as a class that can backtest any indicator that can return true false for any CSV data series at any interval. I have now built my own backtesting class that is a close 1:1 copy of my live trading class. I just went through this process with a client of mine who has excellent python skills from a non-trading domain and wanted to start auto-trading. I also want to be able to do automatic trading, but a good backtesting system is my main priority. py library. trade is a crypto framework that supports backtesting as well as live trading. This is pretty slow in my opinion. Past performance does not always guarantee future returns, but it's good practice to test your strategy (or trading algorithm) before you go ham. Serie A place for redditors to discuss quantitative trading, statistical methods, econometrics, programming, implementation, automated strategies, and bounce ideas off each other for constructive criticism. We would like to show you a description here but the site won’t allow us. Fast Python framework for backtesting trading and investment strategies on historical candlestick data. Many of major exchanges/brokers offer API. ), integrate those into the backtest, then iterate this process until your backtest matches your live trades as well as possible. py for strategy optimization in this tutorial: Easy Trading Strategy Optimization with backtesting. I would rather not code my own backtester if at all possible. But then you run it live and you find out your live trades don't match your backtest, so you see which trades you missed. EDIT: Is there an update on this? Still, backtesting has a tremendous value. 6+, Pandas, Tensorflow, etc. I am still a relatively new programmer (python and algoam working on a bot/algorithm that relies on two indicators from pandas. I've done pip3 install backtesting and it still isn't working. So the best I could do is to use python to facilitate the manual backtesting Download the data in the timeframe that I'm trading in e. py y vectorbt. Apparently it is not as extensive as backtrader or so, but I believe its the best starting point for me. PyAlgoTrade: This is another Python library focused on backtesting trading strategies. My main goal is to be able to design solid backtests where I can write custom indicators. py library pretty OK, but I am having trouble describing in code any strategy more complex than some MA-crossover variation. But then discovered that there are lots of such frameworks on python, so I got lost very fast what to use For example, this list contains too many of them. Tensorcharts, Quantower, etc. What I like about it is that the interface to build strategies is pretty simple/intuitive and the backtest accuracy is pretty good. py gets me further to achieving this take profit functionality than VectorBT does. Jun 10, 2023 · En artículos previos hemos usado la librería backtrader, pero existen también otras librerías de backtesting en Python bastante populares como Backtesting. We chose backtesting. They do nice charting for you, but their mechanisms to place and fill orders have a lot of bugs. I am in the process of putting together a strategy pipeline am now looking at the backtesting. I think I have found enough limitations/oddness in backtrader, so I'm playing with backtesting. py Module I'm trying to import the module "backtesting" and I keep getting "No module named backtesting". Day trader here, just started to backtest. py I am getting wildly different results with TV saying 31% profit long only and backtesting. Py offers similar functionality for free. It also supports Python, but just with its bundled library of functions. These are the libraries/platforms I've considered so far: QuantConnect Backtrader Backtesting. Instead, I would like to place an order based on a specific level, if an intra-bar event occurs. My data source is currently MetaTrader 5 (it has a ready to use libraries for Python) I was about to start building my own framework for backtesting and live trading etc. I believe inly the first video is really necessary, and explains everything you need in an hour. Backtesting is a way of feeding your current trading strategy to a script that applies it on historical data, in order to determine how successful it could be in the future. But to look at past data need to scroll and scroll. Now when you run that backtest, it looks really good. The nice thing is the backtest from the day, minute to the tick-level for accurate intra-day scalping strategies. Pass each bar to a Simple Moving Average that calculates the last value 4. (Manual - clicking range of dates on TradingView) QuantConnect has an online "IDE" that runs python, and you can think of their API / framework like a library. py (Python Tutorial). For US stock, there’s even better package. I was also wondering this. If Yahoo data is broken, try with other sources such Alpaca, Interactive Brokers and similar. py. Loop over the data 3. Every strategy will be different and the differences are nontrivial. Charting (wether real-time or only for the backtesting results) Collection of real-time data (although it's a lot better to rely on a reliable data source) Start slow by being able to backtest something: Read a csv file 2. I just retrieves data from closing on different timeframes and do not use real-time ticks yet. TA. 90% of the time any framework sold with prepackaged test cases perform poorly. Hi, Just a quick question, any one here using backtrader python library? It is supposed to be the best backtesting solution for python but it is really annoying! To speed up the development, I’m considering leveraging an existing backtesting library like backtrader. There is a reason cython is so popular. If you want to just check the candlebar in 1 minute timeframe, you can sign up for free with a gmail account. I would like to backtest this strategy in python. It is not possible to track the spread in past time series, you can roughly average it. py and so on. Oh, that stock dipped 10% below the open at 9:30:01 and you didn't have the open price fast enough to know that. You can learn more about using backtesting. For example, a professional tennis player pretending to be an amateur tennis player or a famous singer smurfing as an unknown singer. Plenty of tutorials, examples, and notebooks. Arcade Trader is the best for non-developers (Natural Language) and Javascript. Vector BT Pro is the absolute best backtesting library out there. Tradovate. py for a backtesting framework. py and was able to get a tested strategy to the point of generating a plotted chart of the results. I can backtest tens of millions of parameter combinations in couple hours, pull/store/resample data from many sources, and all sorts of other benefits. But depends on what you are doing. Python is also great but better to use Python with strategies that involve price levels or arbitrage etc. En el pasado tuvieron mucho auge zipline (la base de quantopian) y pyalgotrade, pero han quedado un poco más en el olvido. There is a GREAT youtube playlist explaining how to work with it. Absorbed a lot of Quantiopian users after the company closed, and has a pretty active community in general. py, it seems like the options are to place an order at the close of the current bar or open of the next bar. I'm already familiar with python, so I would prefer this to be a python library - but not a hard requirement. There’s an equivalent in python called backtest. You can use it to optimize what you want, such as “most profit” or “highest win rate”, etc. If you have something to teach others post here. But I'm an odd guy, so I tent to get overly annoyed when a framework shows me limitations. Hey guys, I'm learning algo-trading and I'm trying to select a good backtesting framework/library. 15 minutes to run my backtest for one symbol on 5 days worth of stock data. . Apr 6, 2022 · Can this library allowed me to buy on open and then sell on close? I tried the trade on close = true parameter, but that causes both buys/sells to happen on close, and if that is set to false, then buys/sells happen on open. Do any of the backtesting libraries handle these peculiarities well? That really depends in your requirements for the testing framework. Ideally I would like something that fits in with my stack, which is the usual suspects: Python 3. I am trying to use Backtester to see if the algorithm I wrote works over time. For crypto, there’s jesse, which I found is the best backtesting python package, unfortunately for now, it only covers crypto. That's exactly what I meant to say. There's peculiarities with futures given the variation in tick size and value. I didn't know Tradersync and it can be a very good alternative for the backtesting visual feedback. Python is fast to prototype but is a bear to get fast. The keys are: If the requested period is p, the actual final period is p + 1 before a meaningful value can be delivered. In my experience, the gold standard is to find a promising system with a backtest, forward test it, figure out the things that your backtest got wrong (fills, slippage, etc. There are several to choose from but that one seems like the most well-supported and actively worked on at the moment. I was using Python before and build my own backtesting system, but now I am learning MQL5 because I felt like a lot of stuff I would still need to build is already there. By using a vectorized approach to calculate backtesting results, it indeed makes the test lightning faster but with a trade-off of its accuracy, because it is subject to look-ahead bias (as you feed in all historical data into algorithms at one time) unlike event-driven backtesting tool which loop in the market data one by one and make the The official Python community for Reddit! Stay up to date with the latest news, packages, and meta information relating to the Python programming language. : These platforms provide advanced charting at a high cost, whereas Algo. I’m not 100% certain that I coded it correctly so I’m trying to examine the chart to make sure buys and sells are correct. Backtesting is a very nuanced subject and for this reason I recommend building your backtests from scratch. I’m looking for a breakdown that explains the parts of the chart it generates. To be specific, I can use the backtesting. They're seem to be a lot of different packages/frameworks for Backtesting strategy's out there for python, curious what people here tend to use? I know some people will recommend to build your own, but would prefer to use one (rather than reinvent the wheel) and extend on it if possible in particularly in the analysis afterward Backtesting is I've been learning python and am trying to do backtesting and created a pretty basic strategy to make it easy. I do know python, but still learning how to code my strategy out. Caso práctico Here's an image of my bot's 3 years backtest of BTCUSD trades. if a large number of trades are stopped by commissions or spreads it is probably because your trades are closed in a handful of candles, in a relatively low time frame (5 minutes or 1 minute). Can I ask, what are common pitfalls to watch out for when trading live, versus a backtest? How might trading live lose money despite a backtest winning big? Edit: fixed the image link, sorry Not only is this a library for backtesting and not a source for data, but this library is really crappy. For forex, I use python & backtesting (I found it similar but easier to learn that backtrader). The strategy is simple enough to code, but so far I haven't had success backtesting. The initial approach involves integrating pre-defined (hard coded) strategies and indicators, with parameters adjustable within the indicators themselves. What is the current state of play for backtesting in Python. The video has to be an activity that the person is known for. If what you are doing is super math heavy python is pretty good choice. PyAlgoTrade supports market, limit, stop, and stop-limit orders, and includes a variety of Backtesting. Series: """ Returns n-period rolling max of array arr. py: While useful for strategy backtesting, it lacks seamless deployment capabilities. Python is my main language mainly because of pytorch. We thank you! See alternatives. Feb 11, 2024 · Note: Understanding how backtesting works is quite beneficial for creating profitable strategies, but it is not required to re-invent the wheel when there’s no need; hence you can use a library I… It takes way too long to gather data for improvements having to wait all day for the results. Unfortunately they do not support Python based backtesting frameworks, but mainly brokers. A celebrity or professional pretending to be amateur usually under disguise. Steep learning curve and $25 per month, but well worth it. They have an optimize() function that looks for the best possible combination of values in a simple example strategy. Any particular resources or paths to go down to improve my ability to translate strategy ideas into code would be super helpful! Use Backtrader results as an input into your own system, the actual "core" of your strategy. About the backtesting period, I agree that the market regime has changed and backtesting for more than 730 days might not really give me good and useful results. Before reporting bugs or posting to the discussion board, please read contributing guidelines, particularly the section about crafting useful bug reports and ``` -fencing your code. I’m new to using Backtesting. I tend to use python to explore different ideas, but once an idea becomes something I want to backtest typically the math is pretty easy to translate to Go. If you have questions or are new to Python use r/learnpython We would like to show you a description here but the site won’t allow us. Series, n: int) -> pd. class TestClass(Strategy): n = 20 def RollingHigh(self,arr: pd. Posted by u/getrichinfo - 10 votes and 13 comments We would like to show you a description here but the site won’t allow us. py is more of a library that uses pandas dataframes. Then build your own Python backtesting tool if you don’t want to learn how to use ready backtesting modules like Backtrader, backtesting. With that said, it’s also the language I prefer algo trading in either way. Within backtesting. py saying -58% long only. g 3mins. I recently was working on something that essentially required backtesting a bunch of parameter sets for a specific metric written in python. If your system is just looking at excel sheets (yes, a bit contrived) just backtest with Backtrader and make a python adapter to transform the results into excel sheets. This is because the UpDay and DownDay concepts in the indicator need to look one position backwards, which means an initial wait period of 1 is needed. I wasn't able to fix them all, but I was able to debug to a certain point where I got some backtesting working. md for a list of alternative Python backtesting frameworks and related packages. If you expect "testing scenarios for specific type of trading strategies), you wont find anything like that. 🔎 📈 🐍 💰 Backtest trading strategies in Python. I am reading through the quickstart guide of backtesting. It allows users to specify trading strategies using full power of pandas, at the same time hiding all boring things like manually calculating trades, equity, performance statistics and creating visualizations. But people in this sub always suggest doing backtest for as far as you can, so I want more years of data for that. I am combining different indicators to find an entry point and an exit point. This is a custom indicator I made with pandas mirroring how backtesting. It's been around for about 2 years. py which does EXACTLY what you’re looking for. True. The author also has a backtesting library on GitHub called qstrader, which has the same sort of event driven architecture. Right now it takes about 1. Jesse. I have a strategy that I have implemented in TradingView and also in Python using Backtesting. From the research that I've done, it seems that some of the top libraries are zipline, backtrader and pyalgotrade. Regarding Ninjatrader, it's in C#, and most of the other frameworks are in python, so I discarded it mainly for a language reason. The backtest engine is open source but the live trading part has a one time fee. Currently developing a strategy in python (100%) using metatrader5 python package to connect to the mt5 terminal. How would you backtest this strategy: criterias: new day; if BTC drops x% below daily open; and then BTC rises y% above daily open; place limit buy at daily open and stop loss z% below daily open I'd say backtrader is more of a framework, and backtesting. But the only option is to convert your pinescript strategy/indicator to python and test it that way. I have found that backtesting . You’ll have access to tons of indicators and the ability to backtest your strategy across a bunch of assets. I'm not sure I understand your question, but play around with this code and then re read the docs. I asked myself the same question and landed on backtesting. Depend on which assets you trade. This seems like an ad, but I actually prefer coding in Python :P Right now I would still use Python for data analysis and ML models. Structuring the backtest to the strategy will help provide some assurance that performance can be appropriately evaluated with as little bias as possible. I’m a beginner coder but use both Python and Pinescript. Hopefully this gets you going. I'm getting great results, but this is my first rodeo. rrkkqewcnzzgmakayswbtcpjgkmfbtdfpgmlbrhcoourlbzchpdthshjqyancwjujrumqkoosqfviwjms
Backtesting py reddit It's relatively lightweight compared to other libraries like backtracker, and made to be extendable by the user. Strategy Which is the best and easy to use python library for beck testing trading strategies with custom indicators and multiple/mixed time frames? pybacktest – Vectorized backtesting framework in Python / pandas, designed to make your backtesting easier. py PyAlgotrade bt Feb 23, 2025 · Backtesting. If anyone has any recommendations of other frameworks or how to accomplish this, it would be greatly appreciated! for python and backtesting, use the yahoo finance API so you can retrieve data, import yfinance as yf, is the code and define the asset, timeframe, and all that and feed it into your model Backtesting in Python, recommendations please. py built it’s SMA indicator """ return pd. I built a back tester without significant library use (some pandas) in 150 lines as a class that can backtest any indicator that can return true false for any CSV data series at any interval. I have now built my own backtesting class that is a close 1:1 copy of my live trading class. I just went through this process with a client of mine who has excellent python skills from a non-trading domain and wanted to start auto-trading. I also want to be able to do automatic trading, but a good backtesting system is my main priority. py library. trade is a crypto framework that supports backtesting as well as live trading. This is pretty slow in my opinion. Past performance does not always guarantee future returns, but it's good practice to test your strategy (or trading algorithm) before you go ham. Serie A place for redditors to discuss quantitative trading, statistical methods, econometrics, programming, implementation, automated strategies, and bounce ideas off each other for constructive criticism. We would like to show you a description here but the site won’t allow us. Fast Python framework for backtesting trading and investment strategies on historical candlestick data. Many of major exchanges/brokers offer API. ), integrate those into the backtest, then iterate this process until your backtest matches your live trades as well as possible. py for strategy optimization in this tutorial: Easy Trading Strategy Optimization with backtesting. I would rather not code my own backtester if at all possible. But then you run it live and you find out your live trades don't match your backtest, so you see which trades you missed. EDIT: Is there an update on this? Still, backtesting has a tremendous value. 6+, Pandas, Tensorflow, etc. I am still a relatively new programmer (python and algoam working on a bot/algorithm that relies on two indicators from pandas. I've done pip3 install backtesting and it still isn't working. So the best I could do is to use python to facilitate the manual backtesting Download the data in the timeframe that I'm trading in e. py y vectorbt. Apparently it is not as extensive as backtrader or so, but I believe its the best starting point for me. PyAlgoTrade: This is another Python library focused on backtesting trading strategies. My main goal is to be able to design solid backtests where I can write custom indicators. py library pretty OK, but I am having trouble describing in code any strategy more complex than some MA-crossover variation. But then discovered that there are lots of such frameworks on python, so I got lost very fast what to use For example, this list contains too many of them. Tensorcharts, Quantower, etc. What I like about it is that the interface to build strategies is pretty simple/intuitive and the backtest accuracy is pretty good. py gets me further to achieving this take profit functionality than VectorBT does. Jun 10, 2023 · En artículos previos hemos usado la librería backtrader, pero existen también otras librerías de backtesting en Python bastante populares como Backtesting. We chose backtesting. They do nice charting for you, but their mechanisms to place and fill orders have a lot of bugs. I am in the process of putting together a strategy pipeline am now looking at the backtesting. I think I have found enough limitations/oddness in backtrader, so I'm playing with backtesting. py Module I'm trying to import the module "backtesting" and I keep getting "No module named backtesting". Day trader here, just started to backtest. py I am getting wildly different results with TV saying 31% profit long only and backtesting. Py offers similar functionality for free. It also supports Python, but just with its bundled library of functions. These are the libraries/platforms I've considered so far: QuantConnect Backtrader Backtesting. Instead, I would like to place an order based on a specific level, if an intra-bar event occurs. My data source is currently MetaTrader 5 (it has a ready to use libraries for Python) I was about to start building my own framework for backtesting and live trading etc. I believe inly the first video is really necessary, and explains everything you need in an hour. Backtesting is a way of feeding your current trading strategy to a script that applies it on historical data, in order to determine how successful it could be in the future. But to look at past data need to scroll and scroll. Now when you run that backtest, it looks really good. The nice thing is the backtest from the day, minute to the tick-level for accurate intra-day scalping strategies. Pass each bar to a Simple Moving Average that calculates the last value 4. (Manual - clicking range of dates on TradingView) QuantConnect has an online "IDE" that runs python, and you can think of their API / framework like a library. py (Python Tutorial). For US stock, there’s even better package. I was also wondering this. If Yahoo data is broken, try with other sources such Alpaca, Interactive Brokers and similar. py. Loop over the data 3. Every strategy will be different and the differences are nontrivial. Charting (wether real-time or only for the backtesting results) Collection of real-time data (although it's a lot better to rely on a reliable data source) Start slow by being able to backtest something: Read a csv file 2. I just retrieves data from closing on different timeframes and do not use real-time ticks yet. TA. 90% of the time any framework sold with prepackaged test cases perform poorly. Hi, Just a quick question, any one here using backtrader python library? It is supposed to be the best backtesting solution for python but it is really annoying! To speed up the development, I’m considering leveraging an existing backtesting library like backtrader. There is a reason cython is so popular. If you want to just check the candlebar in 1 minute timeframe, you can sign up for free with a gmail account. I would like to backtest this strategy in python. It is not possible to track the spread in past time series, you can roughly average it. py and so on. Oh, that stock dipped 10% below the open at 9:30:01 and you didn't have the open price fast enough to know that. You can learn more about using backtesting. For example, a professional tennis player pretending to be an amateur tennis player or a famous singer smurfing as an unknown singer. Plenty of tutorials, examples, and notebooks. Arcade Trader is the best for non-developers (Natural Language) and Javascript. Vector BT Pro is the absolute best backtesting library out there. Tradovate. py for a backtesting framework. py and was able to get a tested strategy to the point of generating a plotted chart of the results. I can backtest tens of millions of parameter combinations in couple hours, pull/store/resample data from many sources, and all sorts of other benefits. But depends on what you are doing. Python is also great but better to use Python with strategies that involve price levels or arbitrage etc. En el pasado tuvieron mucho auge zipline (la base de quantopian) y pyalgotrade, pero han quedado un poco más en el olvido. There is a GREAT youtube playlist explaining how to work with it. Absorbed a lot of Quantiopian users after the company closed, and has a pretty active community in general. py, it seems like the options are to place an order at the close of the current bar or open of the next bar. I'm already familiar with python, so I would prefer this to be a python library - but not a hard requirement. There’s an equivalent in python called backtest. You can use it to optimize what you want, such as “most profit” or “highest win rate”, etc. If you have something to teach others post here. But I'm an odd guy, so I tent to get overly annoyed when a framework shows me limitations. Hey guys, I'm learning algo-trading and I'm trying to select a good backtesting framework/library. 15 minutes to run my backtest for one symbol on 5 days worth of stock data. . Apr 6, 2022 · Can this library allowed me to buy on open and then sell on close? I tried the trade on close = true parameter, but that causes both buys/sells to happen on close, and if that is set to false, then buys/sells happen on open. Do any of the backtesting libraries handle these peculiarities well? That really depends in your requirements for the testing framework. Ideally I would like something that fits in with my stack, which is the usual suspects: Python 3. I am trying to use Backtester to see if the algorithm I wrote works over time. For crypto, there’s jesse, which I found is the best backtesting python package, unfortunately for now, it only covers crypto. That's exactly what I meant to say. There's peculiarities with futures given the variation in tick size and value. I didn't know Tradersync and it can be a very good alternative for the backtesting visual feedback. Python is fast to prototype but is a bear to get fast. The keys are: If the requested period is p, the actual final period is p + 1 before a meaningful value can be delivered. In my experience, the gold standard is to find a promising system with a backtest, forward test it, figure out the things that your backtest got wrong (fills, slippage, etc. There are several to choose from but that one seems like the most well-supported and actively worked on at the moment. I was using Python before and build my own backtesting system, but now I am learning MQL5 because I felt like a lot of stuff I would still need to build is already there. By using a vectorized approach to calculate backtesting results, it indeed makes the test lightning faster but with a trade-off of its accuracy, because it is subject to look-ahead bias (as you feed in all historical data into algorithms at one time) unlike event-driven backtesting tool which loop in the market data one by one and make the The official Python community for Reddit! Stay up to date with the latest news, packages, and meta information relating to the Python programming language. : These platforms provide advanced charting at a high cost, whereas Algo. I’m not 100% certain that I coded it correctly so I’m trying to examine the chart to make sure buys and sells are correct. Backtesting is a very nuanced subject and for this reason I recommend building your backtests from scratch. I’m looking for a breakdown that explains the parts of the chart it generates. To be specific, I can use the backtesting. They're seem to be a lot of different packages/frameworks for Backtesting strategy's out there for python, curious what people here tend to use? I know some people will recommend to build your own, but would prefer to use one (rather than reinvent the wheel) and extend on it if possible in particularly in the analysis afterward Backtesting is I've been learning python and am trying to do backtesting and created a pretty basic strategy to make it easy. I do know python, but still learning how to code my strategy out. Caso práctico Here's an image of my bot's 3 years backtest of BTCUSD trades. if a large number of trades are stopped by commissions or spreads it is probably because your trades are closed in a handful of candles, in a relatively low time frame (5 minutes or 1 minute). Can I ask, what are common pitfalls to watch out for when trading live, versus a backtest? How might trading live lose money despite a backtest winning big? Edit: fixed the image link, sorry Not only is this a library for backtesting and not a source for data, but this library is really crappy. For forex, I use python & backtesting (I found it similar but easier to learn that backtrader). The strategy is simple enough to code, but so far I haven't had success backtesting. The initial approach involves integrating pre-defined (hard coded) strategies and indicators, with parameters adjustable within the indicators themselves. What is the current state of play for backtesting in Python. The video has to be an activity that the person is known for. If what you are doing is super math heavy python is pretty good choice. PyAlgoTrade supports market, limit, stop, and stop-limit orders, and includes a variety of Backtesting. Series: """ Returns n-period rolling max of array arr. py: While useful for strategy backtesting, it lacks seamless deployment capabilities. Python is my main language mainly because of pytorch. We thank you! See alternatives. Feb 11, 2024 · Note: Understanding how backtesting works is quite beneficial for creating profitable strategies, but it is not required to re-invent the wheel when there’s no need; hence you can use a library I… It takes way too long to gather data for improvements having to wait all day for the results. Unfortunately they do not support Python based backtesting frameworks, but mainly brokers. A celebrity or professional pretending to be amateur usually under disguise. Steep learning curve and $25 per month, but well worth it. They have an optimize() function that looks for the best possible combination of values in a simple example strategy. Any particular resources or paths to go down to improve my ability to translate strategy ideas into code would be super helpful! Use Backtrader results as an input into your own system, the actual "core" of your strategy. About the backtesting period, I agree that the market regime has changed and backtesting for more than 730 days might not really give me good and useful results. Before reporting bugs or posting to the discussion board, please read contributing guidelines, particularly the section about crafting useful bug reports and ``` -fencing your code. I’m new to using Backtesting. I tend to use python to explore different ideas, but once an idea becomes something I want to backtest typically the math is pretty easy to translate to Go. If you have questions or are new to Python use r/learnpython We would like to show you a description here but the site won’t allow us. Series, n: int) -> pd. class TestClass(Strategy): n = 20 def RollingHigh(self,arr: pd. Posted by u/getrichinfo - 10 votes and 13 comments We would like to show you a description here but the site won’t allow us. py is more of a library that uses pandas dataframes. Then build your own Python backtesting tool if you don’t want to learn how to use ready backtesting modules like Backtrader, backtesting. With that said, it’s also the language I prefer algo trading in either way. Within backtesting. py saying -58% long only. g 3mins. I recently was working on something that essentially required backtesting a bunch of parameter sets for a specific metric written in python. If your system is just looking at excel sheets (yes, a bit contrived) just backtest with Backtrader and make a python adapter to transform the results into excel sheets. This is because the UpDay and DownDay concepts in the indicator need to look one position backwards, which means an initial wait period of 1 is needed. I wasn't able to fix them all, but I was able to debug to a certain point where I got some backtesting working. md for a list of alternative Python backtesting frameworks and related packages. If you expect "testing scenarios for specific type of trading strategies), you wont find anything like that. 🔎 📈 🐍 💰 Backtest trading strategies in Python. I am reading through the quickstart guide of backtesting. It allows users to specify trading strategies using full power of pandas, at the same time hiding all boring things like manually calculating trades, equity, performance statistics and creating visualizations. But people in this sub always suggest doing backtest for as far as you can, so I want more years of data for that. I am combining different indicators to find an entry point and an exit point. This is a custom indicator I made with pandas mirroring how backtesting. It's been around for about 2 years. py which does EXACTLY what you’re looking for. True. The author also has a backtesting library on GitHub called qstrader, which has the same sort of event driven architecture. Right now it takes about 1. Jesse. I have a strategy that I have implemented in TradingView and also in Python using Backtesting. From the research that I've done, it seems that some of the top libraries are zipline, backtrader and pyalgotrade. Regarding Ninjatrader, it's in C#, and most of the other frameworks are in python, so I discarded it mainly for a language reason. The backtest engine is open source but the live trading part has a one time fee. Currently developing a strategy in python (100%) using metatrader5 python package to connect to the mt5 terminal. How would you backtest this strategy: criterias: new day; if BTC drops x% below daily open; and then BTC rises y% above daily open; place limit buy at daily open and stop loss z% below daily open I'd say backtrader is more of a framework, and backtesting. But the only option is to convert your pinescript strategy/indicator to python and test it that way. I have found that backtesting . You’ll have access to tons of indicators and the ability to backtest your strategy across a bunch of assets. I'm not sure I understand your question, but play around with this code and then re read the docs. I asked myself the same question and landed on backtesting. Depend on which assets you trade. This seems like an ad, but I actually prefer coding in Python :P Right now I would still use Python for data analysis and ML models. Structuring the backtest to the strategy will help provide some assurance that performance can be appropriately evaluated with as little bias as possible. I’m a beginner coder but use both Python and Pinescript. Hopefully this gets you going. I'm getting great results, but this is my first rodeo. rrkkq ewc nzzgm akaysw btcpj gkmfbtd fpgmlb rhcoou rlbzch pdthshj qyancw juj rumqkoo sqfv iwjms