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CodeTrading
United Kingdom
Приєднався 18 лют 2021
Education channel providing simple and quick lessons on related topics: Python, Data Analysis, Machine Learning and data driven applications like stocks and currencies trading.
I hope these videos will be of help, Good luck to you in your coding journey !
🍓Discover how easy Python can be. Learning Courses Discounts (links below):
* Algorithmic Trading In Python
* Python basics,
* Object Oriented Programming In Python
* Data Analysis In Pandas And NumPy
* Machine Learning In Trading
Python is easy to learn and if I could do it then surely you can as well !
DISCLAIMER: The information contained in this channel is presented for educational purposes ONLY, I am NOT a financial expert nor a financial consultant, if you decide to use any of the content of this channel you may do so at your own responsibility. Although I do my best to provide reliable information I am NOT responsible for any losses incurred due to any trading systems presented on this channel.
I hope these videos will be of help, Good luck to you in your coding journey !
🍓Discover how easy Python can be. Learning Courses Discounts (links below):
* Algorithmic Trading In Python
* Python basics,
* Object Oriented Programming In Python
* Data Analysis In Pandas And NumPy
* Machine Learning In Trading
Python is easy to learn and if I could do it then surely you can as well !
DISCLAIMER: The information contained in this channel is presented for educational purposes ONLY, I am NOT a financial expert nor a financial consultant, if you decide to use any of the content of this channel you may do so at your own responsibility. Although I do my best to provide reliable information I am NOT responsible for any losses incurred due to any trading systems presented on this channel.
Profitable Strategy Using Bollinger Bands and RSI Automated in Python
In this video, we present a profitable trading strategy using Bollinger Bands and RSI indicators, automated in Python. The strategy combines Bollinger Bands, RSI, and specific candle patterns to detect reversal points and identify optimal entry positions. We backtest the strategy using Python, accounting for commissions and spread costs, and achieve positive returns. The video covers the strategy rules, demonstrates the Python code used for backtesting, and provides a downloadable link for the code. By integrating Bollinger Bands, RSI, and Python automation, this approach aims to enhance your trading performance. Join us to learn how to implement this effective strategy and test trading results with automated Python scripts.
]]] Drop a comment if you feel like sharing and supporting with some ideas!
Subscribe for more Python trading tutorials and backtesting strategies.
°°° Discount Vouchers for my Algorithmic Trading and Python courses:
💲 Algorithmic Trading: bit.ly/CouponAlgorithmicTrading
💲 Data Analysis with Numpy and Pandas: bit.ly/CouponDataAnalysis
💲 Machine Learning Methods In Algorithmic Trading: bit.ly/CouponMachineLearningTrading
Download the Python Code (notebook):
drive.google.com/file/d/1zG8sAum1_hQn9t-51yA4vgnz6D6dnwDB/view?usp=sharing
And the data file I used in the video:
drive.google.com/file/d/1k2kGyG2hfr3tvIAcCYUIXD8uj32TBO71/view?usp=sharing
#bollingerbands #tradingstrategy #technicalanalysis #stockmarket #finance #investing #automatedtrading #algorithmictrading
]]] Drop a comment if you feel like sharing and supporting with some ideas!
Subscribe for more Python trading tutorials and backtesting strategies.
°°° Discount Vouchers for my Algorithmic Trading and Python courses:
💲 Algorithmic Trading: bit.ly/CouponAlgorithmicTrading
💲 Data Analysis with Numpy and Pandas: bit.ly/CouponDataAnalysis
💲 Machine Learning Methods In Algorithmic Trading: bit.ly/CouponMachineLearningTrading
Download the Python Code (notebook):
drive.google.com/file/d/1zG8sAum1_hQn9t-51yA4vgnz6D6dnwDB/view?usp=sharing
And the data file I used in the video:
drive.google.com/file/d/1k2kGyG2hfr3tvIAcCYUIXD8uj32TBO71/view?usp=sharing
#bollingerbands #tradingstrategy #technicalanalysis #stockmarket #finance #investing #automatedtrading #algorithmictrading
Переглядів: 20 692
Відео
Surprising Differences in Bollinger Bands: Python Backtesting & Strategy Analysis
Переглядів 10 тис.21 день тому
Explore the intriguing variations in Bollinger Bands calculations in our latest video, "Surprising Differences in Bollinger Bands: Python Backtesting & Strategy Analysis." In this tutorial, we automate Rayner Teo's powerful Bollinger Bands strategy using Python and backtest it on historical data to analyze its performance. Bollinger Bands are a popular technical analysis tool, but surprisingly ...
Automate Trading Bot Parameter Optimization with Python: A Comprehensive Guide!
Переглядів 8 тис.Місяць тому
In this video, we show you how to automate the optimization of trading bot parameters using Python. Our simple trading strategy, which we previously backtested and deployed live, required weekly updates to the trading parameters to keep the bot optimized on the most recent data. To automate this process, we developed a Python code that includes the trading bot components and automates the optim...
How to Spot and Avoid Overfitting and Underfitting in Algorithmic Trading
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Welcome to our deep dive into the intricacies of algorithmic trading models and the often misunderstood concepts of overfitting and underfitting. In this video, we explore the truth about how trading strategies are actually developed and optimized, providing you with insights into why and how certain algorithmic trading models succeed. Algorithmic trading, like any advanced artificial intellige...
How Skipping Trading Fees Unlocks True Indicator Potential
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Discover the strategic advantage of testing trading indicators without the distortion of commissions. In this insightful video, we dive deep into why skipping trading fees during the initial phases of strategy testing isn't just an oversight-it's a crucial step to evaluate the raw performance of potential indicators. By isolating indicators from trading costs, we can accurately assess their eff...
Inside The Alligator Trading Strategies With Advanced Analysis In Python
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Explore the Alligator Indicator with our comprehensive Python backtesting tutorial. Delve into the world of financial trading algorithms as we dissect one of the most intriguing technical analysis tools, the Alligator Indicator, reputed for its unique approach to market trend analysis. This video tutorial offers an in-depth examination of a strategy purported to harness the Alligator Indicator'...
The Truth About MACD Trading | Algorithmic Strategy Backtest In Python
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Discover the Truth About MACD Trading as we dive deep into an Algorithmic Strategy Backtest in Python. Ever stumbled upon trading strategies promising high win rates? We put one of the most talked-about strategies, the MACD trading strategy, under the microscope to verify its claims of an 80% win rate. This video is your ultimate guide to understanding, applying, and backtesting the MACD tradin...
The Most Realistic Automated Trading Analysis Using Python
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How To Improve A Live Trading Bot For Forex Part 2 of 2 | The Python Code
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Trading with Python: Simple Scalping Strategy
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Boost Trading Returns by 30% with Python Automation of Price Channel Breakouts
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Maximizing Profits with Python Backtesting: Price Breakout Strategy & Dynamic Trade Management
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Automated Price Break Out Detection: Algorithmic Trading In Python
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Strong Support and Resistance Levels Detection With Python For FOREX And Stocks Trading Algorithms
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Algorithmic Trading Alerts In Python For Forex And Stock Markets
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Channel Break Out Indicator In Python
Thanks!
How are you able to connect your trading bot to the trading platform
Hi again. I'm struggling to understand what does the "size" variable means as a parameter to the buy( ) or sell ( ) methods. Does it mean a % of the equity, like the risk we take in that trade or does it mean the lot size, for instance, 0.04 would mean 4 mini lots ??? I've been digging in the backtesting.py file. In the Trade class, in the "pl", "pl_pct" and "value" getters, the "size" meaning a fraction of the equity doesn't make much sense to me, and therefore that's where I get confused.
Hello, how do you assign the data to the Strategy class? I mean, when you use, self.data, how do you connect that variable, with the dataframe you have been processing until now ?
Hi, self.data will bring in the dataframe that you provided when you call the backtest function afterwards, notice I am passing a df parameter somewhere to launch the backtest.
Thanks a lot. I have one more question. But I'll ask it in some other video comments section, because the doubt is related to some other matter not dealt with, in this video
Awesome job Francis thanks a lot! im here from udemy ;). Have u try this strategy with stochastic i/o rsi? and maybe adding a trailing stop...
Hi, thank you for sharing. I didn't spend all the time I wanted on this strategy yet, I think it is tunable still...
what is the backtesting result for this strategy ?
As is not well, but it has to be combined with other indicators (mainly trend indicators) to provide good potential.
😎📈
Thank you!
I think there is a small but important mistake with MACD here. ============= help(ta.macd) gives us this: Returns: pd.DataFrame: macd, histogram, signal columns. ============= but the way way you append the columns is MACD, SIGNAL, HISTOGRAM am I missing something here?
Now I am perplexed I will have to go back and verify the code! but thank you for pointing this out, I guess this can be easily verified also on the plot
@@CodeTradingCafe i think i know what is wrong, the code you use is based on talib's output. You thought that ta and talib are consistent in their output signature since so much of ta is based on talib. Unfortunately they are not :( just swap ta with talib and you are good. ========================= help(talib.MACD): Outputs: macd macdsignal macdhist =========================
Makes sense, thank you for getting back, so I assume talib is being called in the background I wasn't aware of the differences!
@@CodeTradingCafe glad to help you. Love your content.
Are you currently running any bot with real money? can you share the status of that bots like you previously did?
Hi, actually around +8% to +14% yearly return (so I can't buy an airplane yet). I run it on low risk setup but I can push it up to 20% yearly I just don't like risk. It runs on the daily and 4H timeframe so it's slow, around 2 signals per month.
@@CodeTradingCafe Thank you for replying
hello please help me in using this in trading view for INDIAN share market
Hi, unfortunately I don't trade specific markets but you can adapt any of my codes on this channel. Good luck!
This is a horrible strategy 😂
All scalping strategies are horrible except very few, it's hard to find something consistent on low timeframes.
Maybe use the ATR as a stop loss?
Yes I tried it in other videos, can't remember which ones, but in the recent videos I frequently include the ATR for SL and TP levels.
What do you think of adding bid-ask spread and slippage?
On lower timeframes that would cancel most of the returns, on 4H and daily it's good, actually the commission I added 0.002 is relatively large and covers for spread and slippage)
I am not sure if you are still active on this channel. If the HL has been broken during descending impulse, we can check the Fibonacci levels to see if it is the right entry or not. If the price broke below and already crossed 61.8% Fib level, it can be a wrong trade.
Hi, thank you for sharing, yes I am still following up a bit. Good point I actually have another vid on the Fibonacci entry levels we can combine both videos/codes I guess.
@@CodeTradingCafe Thank you for the reply. I sent you an email to you. Please check and let me know.
Any chance this can be coded in PINEScript to create a indicator in TV
Hi, it can be translated but I don't do pinescript myself (try with chat GPT it might help)
I don't know, dudes. I think crypto and all these ICOs are just a bubble. Well, crypto is good for transfers and so on, but I don't engage in trading. It's too risky. My friend recently lost $5000 there. I invest crypto in the Unimantic platform, their MEV bots do all the work for you. I've never had any problems with it, unlike platforms like Binance or others. I'm just speaking from personal experience that it's better not to engage in market manipulation and rely on proven things.
This video is a great help...thank you
Thank you for your support, good luck!
Dude it was the same problem that made mu furious 2years ago, and I couldn't understand it. THANKS YOU! This class was a blessing!
Glad it helped! thank you for your support!
60% return from 2011 to 2024?
Yes but these strategies can be deployed on multiple assets at the same time so you can trade for instance 30 assets in parallel.
This grid trading video was great. You're such a natural teacher. I know its a year since you did this video but maybe its a good candidate for an update? I had a few questions. 1. Its not clear in live conditions whether you would place pending orders? 2. Have you tested this live? 3. Ironically in the little I've looked at grids, when the market is really moving fast then slippage can grow a lot or the grid kinda collapses. You've got such clever ideas, i wonder if you have any ideas of how to protect or opt out of trades. In those situations. 4. Id be interested to see a video on a triangular arbitrage. Scalping forex trade, eg long eurjpy long usdjpy short eurusd. 5. Lastly, so many awesome ideas you've shared. What strategies do you actually trade yourself. Thanks for all the great learnings! R
Hi, thank you for your comment. To be honest I was always intrigued by different grid systems, and as I mentioned in the video I once did over 1000% returns in just 6 weeks (real money account, trading manually though), I got lucky the market was ranging with no trend during that time. I would very much consider revisiting these systems I will do a small bibliography around it. For slippage and fees I think the easiest and best solution is increase timeframe, higher timeframes include larger movements that can easily cover trading fees and slippage. My personal trading is very simple, price action patterns combined with candles patterns on the 4H and daily timeframes, slow but safe. Good luck!
@@CodeTradingCafe you got me thinking some more about this. I know you trade FX, like I've tended to, however... I've been concerned about the speed of moves and news at certain times. Perhaps trading a basket of stocks and/or hedging going into news might make this a safer trading strategy. Inversely correlated instruments might also help with drawdown.
I think hedging and triangulation is another world of trading it has a different set of rules on its own, I am not an expert on this but I will revisit few books see if I can dig anything interesting.
Hi this is wonderful high probability setups. Thanks for sharing. Whrere can I find the python code?
Hi, thank you, the code is in the link in the description
@@CodeTradingCafe Thanks for the reply. Tried the code shows error
sir pl. code for india stock market
Hi, really sorry I am not familiar with the indian market, but if you like a strategy here you can adapt easily to any asset you are trading.
sir pl. code for indian market
Hi, really sorry I am not familiar with the indian market, but if you like a strategy here you can adapt easily to any asset you are trading.
Your work and you both are great! I loved all your videos, it is amazing. I feel like I am Fan of you. Quite impressed (obviously the work) but looking at the replies more impressed. Hates off!!
Thank you so much 😀 your support is much appreciated! Good luck for your coding... and trading.
Only 18 trades and 66% return over such immense timeframe (13 years) is actually pretty bad. Notice that the dataframe has an open value of 59.2 in the first row and a close value of 101.386 in the last row. Buying the asset in the first day and selling in the last yields a return of 71.26% by doing absolutely nothing. The strategy is actually underperforming the simplest strategy, which is buying and holding.
Hi, thank you for sharing, I understand your point I do agree partially though. The buy and hold strategy works only on increasing assets, imagine I tried the same strategy on a different stock or a forex that went down so basically the buy and hold will be in the negative, I avoid taking it as a reference. I do agree though that the number of trades is low however I have read many professional traders books and they do have this kind of "selective" strategies too, the solution is to run the strategy on multiple assets at the same time.
I luv yr channel
and my channel loves you :) thank you for your support
which market can use for this strategy? Can it use for forex, please?
Any market might work and might not, we need to try it, but yes I think forex is a good start.
By the way, if you get bored, you could always try "VP's" No Nonsense FX algo !
I could code it, is it freely accessible somewhere?
Discarding short trades and you get 100% WR
Thank you for pointing this out. But I am afraid the total number of trades is low so this is not very accurate we would have to test it on different assets as well.
Nice video, helped me understand the question. My Solution in Swift: guard !A.isEmpty, A.count <= 100000, X >= 1 && X <= 100000 else { return -1 } var distance = Dictionary(uniqueKeysWithValues: (1...X).map { ($0, " ") }) for (i, item) in A.enumerated() { distance[item] = nil if distance.isEmpty { return i } } return -1
Thanks for sharing, not a swift expert but I guess the algorithm is the same. Good luck!
just plotting and looking they are close does not mean its accurate enough ....u need metrics ok, even if u do training and testimg..u need to assess ur accuracy
Hi yes I agree, there is another video showing more realistic analysis check it out ua-cam.com/video/lhrCz6t7rmQ/v-deo.html
Your videos inspired my to build my own trading bot. I created a oanda demo account and wrote some code and deployed it. The problem i currently have, is that i have to pay a lot of swap. (I did some research, as far as I understand its just overnight fees.) The swap is in my case really high, nearly 0.1% of my invested capital per day. When investing in stocks over a few months, the swap would eat all my profits. Especially on the daily timeframe. What can i do about that? (I am new to that subject, so it is possible that i missed something very obvious)
Hi, yes I suffered from swap at some point with Oanda, and sometimes swap can be positive meaning you earn on the opened trades! yes it's a small interest for some forex pairs and in one direction for example on USDCHF if you buy/long you get interest but if you short you pay interest... anyway to get rid of this check in your region if Oanda has other types of accounts that don't make you pay swap or overnight fees, if not check other brokers as well, my friend uses CFI in the MiddleEast region he can leave Forex trades opened for 3 month with no additional fees!
@@CodeTradingCafe Thank you for the explanation! It makes a lot of sense. I am currently working an a BTCUSD Trading Bot and it got great results in the backtests over the last 4 years. The strange thing is, that i have to pay swap for going long and short. I will probably have to switch the broker, but that should not be that big of a deal.
@CodeTradingCafe I have a strategy. Could you please check and let me know 1. RSI above RSI MA 2. close should be above 20 ema to take entry
Hi, this is not a strategy, it's 2 indicators combined, there is a lot to consider when you need to backtest including the trade management part. You need to provide more details like the length of the RSI, the length of the MA of the RSI, when RSI above MA are we talking exactly about when the RSI crosses above the MA?... If you decide to code strategies, the advantage you will gain is thinking in details :) I strongly encourage you to try, your whole trading experience will change. Edit: sorry I just noticed how long my message is.
@@CodeTradingCafe thanks for your reply. Yes, I am working on strategy based on these 2 indicators to take entry.
Hi, I've been trying to adapt your code for FX (EURUSD H1 in this case) In the Scatter chart part (e.g) the following line threw a type error line=dict(color='green', width=1), - which was corrected with line={'color': 'green', 'width': 1}, However, once I was in the backtest section, the following errors occurred ValueError: Long orders require: SL (1.080610316351981) < LIMIT (1.08264156) < TP (1.0825096836480192) ValueError: Short orders require: TP (1.1016589696057346) < LIMIT (1.10151738) < SL (1.1035810303942652) Any tips on how to debug this, please ?
Hi, yes the TP values are not aligned with the trades and the TP distances, recheck the conditions why and how are these values messed up, so it's basically the values of TP and sL you need to recheck the rules and make sure the values are computer correctly.
What about gbt algorithms like xgboost & catboost for price prediction?
Price prediction is a long shot, I did try xgboost for trend category prediction it's also complicated, simple methods work better!
❤
Thank you !
hi, i love your videos ! Do you have the script to implement this strategy in Tradingview ? Thanks
Thank you for your support, I am just on python no other coding languages for now :)
Just joined and the code link won’t load into Phythpn or Anaconda to test, any suggestion is appreciated
Open Jupyter notebook and try to load/open the file from there.
This works best in only sideways market
I agree it doesn't seem robust enough to me, can be revisited with mods later on maybe.
Oh, I love you guys, the best market analysis! Seriously, why not mention Unimantic?
Thank you for your support, we're not aware of UM
What's up with spammers trying to promote this unheard of unimantic? Leave us alone, no one wants to buy your crappy unimantic
Thank you for your amazing videos. They are always so clear and very helpful and I have learned a lot from them. I am having an issue with determining support and resistance as I get the following attribute error when trying to create my ss and rr lists: 'DataFrame' object has no attribute 'low'. The data from my broker exports the low values under the column '<LOW>', however I have defined my low as = list(df['<LOW>']). Am I doing something wrong? Your help would be greatly appreciated.
Glad you like them! Thank you for your support. Actually yes the error you are encountering is related to the names of the columns, for example if the title of the column is LOW you to change all the occurrences of low to LOW... just as you did, now since you are still getting the error it means that there is still an unchanged 'low' somewhere in your code. Check it out again and let me know if it works.
@@CodeTradingCafe Thank you for your response and help with this! I've looked through the code again and all instances seem to be correct, but I am still getting the error. I can email you a screenshot of the error message if you think that would help?
Send me a screenshot maybe I can figure it out
@@CodeTradingCafe Thank you very much Sir, I really appreciate it!
Amazing contribution. You made it easy to start for many people. Thanks for keep contributing!
My pleasure! Thank you for your constant support, you always bring something nice into the comments :) enjoy coding and Good luck.
Thanks! Great video with very interesting strategy! You gave me a number of ideas to try ;-)
Great to hear! Coding is always good bringing new ideas I find it stimulating.
In trading, possessing technical analysis skills is not sufficient on its own; discipline and emotional maturity play crucial roles in achieving success. Embracing the mindset of "time in the market vs. timing the market" proves valuable, especially during market fluctuations. I attribute my growing daily earnings to Flora Legziel's valuable insights and daily trade signals, coupled with my commitment to continuous learning. Kudos to the journey ahead!
I've just looked up her full name on my browser and found her webpage without sweat, very much appreciate this
It's unexpected to come across her name here. She understands every beginner’s intention and fix you to a trading course that matches your capacity, she knows her stuff! Her advice has been invaluable to my trading journey. Definitely worth giving a shot!
It is really refreshing to see a comment about Flora. I have worked with her also for months now, reached out after reading more about her on the internet. she simplifies matters, whether it's a market surge or drop; her approach consistently keeps you ahead of the trend, She's a guru i'll say
Investing has proven to be an incredibly beneficial decision. My cryptocurrency profits continue to play a substantial role in growing my overall wealth, reducing my reliance on my salary
Nice to see this here, Flora Legziel's understanding of market indicators is impressive. She knows exactly when to enter and exit trades for maximum profit. her siignals are top notch
I think the key is mostly the two conditions of price action... one candle closing outside of the BB and the other surpassing it in the other direction and to the other side of the BB. I bet it works on multiple timeframes but is best on the H1. Just a hunch.
Hi thank you, I was actually willing to try 1H I don't remember I have made any video here using 1H timeframe...
What would be helpful is a calculation of the buy and hold max drawdown so we can see how a strategy compares on a drawdown basis ie an 8% out performance vs B&H is great IF max drawdown is lower by 20%
Following code could be used: def calculate_max_drawdown(data): # Calculate daily returns data['Daily Return'] = data['Adj Close'].pct_change() # Calculate cumulative returns data['Cumulative Return'] = (1 + data['Daily Return']).cumprod() # Calculate the running maximum data['Running Max'] = data['Cumulative Return'].cummax() # Calculate drawdown data['Drawdown'] = data['Cumulative Return'] / data['Running Max'] - 1 # Calculate the maximum drawdown max_drawdown = data['Drawdown'].min() return round(max_drawdown * 100, 2)
That's a good point, sometimes B&H seems better in returns but might be risky in DD, we can easily run a backtest just buying at the beginning of the dataframe and holding till the end of the test. Thank you for the code as well!
Can we get a video on how to create a auto trader placer after having signals. Just to apply signals in that bot and it will auto place the trade with martingale included in quotex
Hi, I have few videos on this, live trading bot running from python, check this one for example: ua-cam.com/video/bZhtvvFm17A/v-deo.html
Hi. Nice effort. Had seen the guy that tried this on all russell index stocks. He uses it in 5m , 15m 30m and 1h timeframes.
Thank you! yes I am not a fan of minutes timeframes but I could test it on 30M or lower for example, if anything interesting I will get back with a video.
Bro I want to backtest it on Btc usdt 4HR time frame I will do backtest and put the result as comments here....
Good luck! and thank you for sharing!