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QuantProgram
Великобритания
Добавлен 19 авг 2020
Educational channel focusing on quantitative finance and investment concepts using math and coding with the application to finance. We are not trading/day trading gurus, our goal is purely to upload content that helps viewers learn enough coding and math skills to be a fully fledged quantitative trader. Subscribers can improve their knowledge and awareness about new developments in quant finance, the risk associated with it along with the opportunity it provides
Disclaimer: The contents provided in the channel are purely educational. We do not provide any financial or investment advice. There is a very high degree of risk involved in trading. Past results are not indicative of future returns. quantprogram.com and all individuals affiliated with this site assume no responsibilities for your trading and investment results. The contents, videos, columns, articles and all other features are for educational purposes only and should not be construed as investment advice.
Disclaimer: The contents provided in the channel are purely educational. We do not provide any financial or investment advice. There is a very high degree of risk involved in trading. Past results are not indicative of future returns. quantprogram.com and all individuals affiliated with this site assume no responsibilities for your trading and investment results. The contents, videos, columns, articles and all other features are for educational purposes only and should not be construed as investment advice.
How Machine Learning/AI Traders Beats Retail Traders with Example Strategy for Beginners
In this video we will discuss how traders who use machine learning strategies will outperform the retail traders in future. We will also explain how to create a machine e learning strategy right from scratch.
The entire code is only available for our Prometheus students and can be found in the Strategies and Code section
www.quantprogram.com/store
We are thinking of creating a course purely focussing on Machine Learning and AI based trading strategies. We will only launch it if there is substantial interest as it takes lot of work to create one. Let us know if you are interested through the link below
www.quantprogram.com/MLCourseRegister
Our Course's
www.quantprogram.com/store
Full Beginner Tu...
The entire code is only available for our Prometheus students and can be found in the Strategies and Code section
www.quantprogram.com/store
We are thinking of creating a course purely focussing on Machine Learning and AI based trading strategies. We will only launch it if there is substantial interest as it takes lot of work to create one. Let us know if you are interested through the link below
www.quantprogram.com/MLCourseRegister
Our Course's
www.quantprogram.com/store
Full Beginner Tu...
Просмотров: 31 505
Видео
Portfolio Backtest of Stan Weinstein's Trading Strategy
Просмотров 3,1 тыс.4 месяца назад
We do a portfolio level backtest of Stan Weinstein Trading strategy in Quantconnect along with discussion of S&P500 CAGR to Drawdown ratio. We also discuss personal portfolio performance from last year and current year. Pinescript Code for Stan Weinstein Trading Strategy: www.quantprogram.com/StanWeinsteinOptin Quantconnect code is only available for Prometheus Customers If you want to know det...
The Hidden Edge: Trading using Linear Regression
Просмотров 15 тыс.7 месяцев назад
Today we will discuss how we can use the linear regression indicator to create a mean reverting strategy that has beaten the SPY buy and hold. You can download the pinescript code for the strategy below. www.quantprogram.com/LRegression_Optin The high performance edition is only for students and can be found in the "Codes" section in the QuantProgram Prometheus Course Our Course's www.quantprog...
QuantConnect Full Tutorial 2023 - Worlds Best AlgoTrading Engine
Просмотров 38 тыс.10 месяцев назад
One of the biggest challenges retail quant traders face is in the automation/execution. Its easy to perform backtest and other quantitative analysis and there are many softwares that allow this. Quantconnect solves this problem easily. With many famous brokers integrated to Quantconnect, going live is so easy with just a few clicks. Quantconnect is used by many systematic hedge funds as it serv...
Jim Simons Trading Secrets 1.2 SIMULATED Data Generation
Просмотров 64 тыс.Год назад
Inspired form the book about Jim Simons “The man who solved the market” and how they simulated or created data to perform quantitative analysis we discuss in this video how to create millions of data points for research. This data ranges from Heston model, to Geometric Brownian motion and Monte Carlo models. By doing 1000 simulations on each of these models , we were able create more than 2 mil...
How our 9 Algo Strategies Predicted NVIDIA's Big Move: Cracking the Code
Просмотров 5 тыс.Год назад
Nvidia had one of the biggest overnight moves that has shocked the financial markets and traders from around the world. Many of our algorithmic trading strategies where long on Nvidia prior to this which gave gave both our subscribers and our students early entry to this stock and participate in this move. In this video we dissect how an anomaly of confluence was created wherein practically mos...
Jim Simons Trading Secrets 1.1 MARKOV Process
Просмотров 390 тыс.Год назад
Jim Simons is considered to be one of the best traders of all time he has even beaten the like of Warren Buffet, Peter Lynch, Steve Cohen and Ray Dalio. Jim's Renaissance Technologies and Medallion Fund are purely quantitative trading funds. The methodology he and his team uses are highly secretive but there are lots of hidden clues and approaches that could be found in the book The Man Who Sol...
Blueprint ChatGPT Prompts for Trading Strategy
Просмотров 12 тыс.Год назад
This is a momentum trading strategy created on Tradingview Pinescript using Chagpt4 prompts. GPT4 is the latest update to GPT3. its got some great returns across stocks. But has got a weakness which is found in all momentum and trend following strategies and that is the drawdown. We discuss on how to reduce drawdowns by position sizing and portfolio backtesting. We also give examples of that al...
Coding HIGH WIN RATE RSI Divergence Indicator in Pinescript
Просмотров 12 тыс.Год назад
We will discuss how to code a RSI divergence Indicator signal in tradingview pine script version 5. Make sure you don't use it for super shorter time frames. The shorter you go more the signal but less the accuracy. This indicator can spot so good reversal points if used wisely. The code can be downloaded below. Let us know if you have any questions. HAPPY TO HELP Click on the link below if you...
Michael Burry Invests $30 Million in 7 Stocks
Просмотров 2,2 тыс.Год назад
Michael Burry has invested in 7 new stocks at a total value of approximately $30million. In this video we shall discuss the theory on why he has invested in the stock and the opportunities we have as investors in these stock. Make sure to do due diligence before investing in any of these stocks. If you wish to calculate the fair value or intrinsic value of a stock watch our video below. Chapter...
Top 5 AI Stocks to Invest in 2023
Просмотров 3,3 тыс.Год назад
The AI revolution is here and there are many stocks that are up for grabs. This could be the greatest opportunity to invest in these stocks and some of them are in the early adoption stages. Many companies will be or have already hired these companies and there are great potential for investing in these stocks to get great returns. Make sure to do due diligence before investing in any of these ...
Calculate Intrinsic Value of a Stock like Warren Buffet - Example 2023
Просмотров 2,9 тыс.Год назад
Due to the current market recessionary scenario, there are lots of good stocks trading at extremely cheap prices. In this video we explain how Warren Buffet calculates the intrinsic value of a stock by using the Discounted Cash flow model. We have explained in detail how to value a company by taking the example in AAPL stock. If you have any doubts in the calculation feel free to download the t...
Retail Traders Algo made $900,000 in 1 day
Просмотров 8 тыс.Год назад
Navinder Singh Sarao was a retail trader in London who according to CFTC was one of the reasons of the Flash Crash that took place in May 6 2010. He went on to make $900,000 that specific day and overall went on to make $42 million dollars. Some of the strategies he used include spoofing. In this video we explain how the event of flash crash took place and how Navinder went on to perform his sp...
ChatGPT Trading strategy 20097% returns?
Просмотров 1,3 млнГод назад
Creating a trading strategy with chatgpt seems interesting and thats what we will do in this video. We will discuss the benefits and the learning advantages in the algo trading and quant trading industry by using ChatGPT with many examples in Python and Pinescript codes. Our Course's www.quantprogram.com/store Algorithmic Trading Python FULL TUTORIAL ruclips.net/video/GDMkkmkJigw/видео.html Ful...
On Balance Volume Indicator Hedge Fund Entry Signals
Просмотров 6 тыс.Год назад
Unlike other indicators OBV is a leading indicator as it takes volume into account unlike price. By using the OBV Divergence you can really know whether the big players like institutional funds are accumulating or distributing shares and thus pick reversal points. The code can be downloaded below. Let us know if you have nay questions. HAPPY TO HELP Click on the link below if you want to downlo...
MFI Money Flow Index Strategy Backtested Tradingview Pine Script
Просмотров 13 тыс.Год назад
MFI Money Flow Index Strategy Backtested Tradingview Pine Script
Turtle Trading Strategy Backtested Tradingview Pinescript
Просмотров 34 тыс.Год назад
Turtle Trading Strategy Backtested Tradingview Pinescript
Larry Williams Strategy Backtested Tradingview Pinescript
Просмотров 24 тыс.Год назад
Larry Williams Strategy Backtested Tradingview Pinescript
Bollinger Band Trading Strategy Backtested in Tradingview Pinescript
Просмотров 8 тыс.Год назад
Bollinger Band Trading Strategy Backtested in Tradingview Pinescript
Breakout Strategy Backtested Pinescript Tradingview
Просмотров 6 тыс.Год назад
Breakout Strategy Backtested Pinescript Tradingview
RSI Strategy Backtested In Pinescript Tradingview
Просмотров 29 тыс.2 года назад
RSI Strategy Backtested In Pinescript Tradingview
ADX Strategy Backtested in Tradingview Pinescript
Просмотров 7 тыс.2 года назад
ADX Strategy Backtested in Tradingview Pinescript
Backtesting Donchian Breakout Strategy In Python
Просмотров 6 тыс.2 года назад
Backtesting Donchian Breakout Strategy In Python
Best MACD Strategy on Pinescript Tradingview for Stocks
Просмотров 5 тыс.2 года назад
Best MACD Strategy on Pinescript Tradingview for Stocks
Pullback Strategy Backtested in Tradingview
Просмотров 7 тыс.2 года назад
Pullback Strategy Backtested in Tradingview
Algorithmic Trading Python for Beginners - FULL TUTORIAL
Просмотров 451 тыс.2 года назад
Algorithmic Trading Python for Beginners - FULL TUTORIAL
Tradingview Pinescript Version 5 FULL TUTORIAL 2023
Просмотров 71 тыс.2 года назад
Tradingview Pinescript Version 5 FULL TUTORIAL 2023
Trailing Stop Loss Code for your Backtest in Tradingview Pinescript
Просмотров 26 тыс.2 года назад
Trailing Stop Loss Code for your Backtest in Tradingview Pinescript
superv
Great stuff but in all your videos you need to check the 'buy and hold equity' checkbox in the TV strategy tester when showing these stats on the videos, lots of times 13000% return looks great in theory except that buy and hold in same period on that stock would've yielded an even higher return, rendering the activetrading strategy useless. Please be transparent with the relative stats
Useless you are a math PhD and work with other PhDs, quant is bullshit. Citadel and 2 Sigma are using quant and both have crap returns compare to the market.
Not true. 2023: Citadel 15% vs SPX 24% 2022: Citadel 38% vs SPX -19% 2021: Citadel 26% vs SPX 26% 2020: Citadel 24% vs SPX 16% Average CAGR of past 4 years Citadel 25% vs SPX 10%. Just because citadel got beaten last year doesn't mean it was beaten every year or on average. Definitely not "bul****" result aye! 2 sigma has multiple quant funds. Some did well some didnt. Not to mention fights from co-owners. Cant find their proper past 4 to 5 year performance
@@quantprogram source?
@@quantprogram My point was more about the fact that a massive fund like Citadel is having a hard time producing +20% YoY returns. And also, you cant take raw performance as a benchmark.What was Citadel net-after-fees?
Source: You can search it online. All hedge funds need to file or submit filings and returns whether it’s citadel or Berkshire to submit taxes and for client information. It’s public information. You could have checked the sources before your comment as well and you would have not made that wrong comment.
No. You literally said in quotes "citadel and 2 sigma are using quant and both have crap returns to market". Which is not true. You never said 20+. You never said after fees either. We can't guess what your point is. But from your initial comment "crap returns to market"is wrong. Even then lets take net fees into account. Assuming citadel operates 2 -20 fee structure. It could be much lower these days due to competition but lets take the higher end so we know the worst case fees. 2% operational fee 20% performance fee. Citadel performance year by year post net fees. 2023: Citadel 15% After fees 10.4% 2022: Citadel 38% After fees 28.8% 2021: Citadel 26% After fees 19.2% 2020: Citadel 24% After fees 17.6% Average CAGR of citadel after fees 18.82% vs SPX 10% There is a reason why big investors invest in these funds even with knowing the fees and thats purely because of their outperformance to that of the market, contrary to your comment that they "have crap returns compare the market." The video is purely about creating quant trading strategies. We didn't ask you to invest in any quant fund nor advice you to. This comment is purely in response of your initial comment "quant is bu****" and "crap returns compare to the market" which are both wrong.
Hmm doesn't have high alpha
How do we trade with 90 companies in our portfolio? Won't only some of the companies have the trade signals at any given point? Do you just trade on the 5 that have the signal that day and the other 85 just sit there dormant? Curious if you could explain the logistics of having a large portfolio looks, in this context, thanks
Yes you are correct. Lets say there are only 5 trade signals today. Then only 5 positions will be entered at 1% equity allocated to each position. so total 5% equity will be allocated. There wont be any more positions. Now if tomorrow there is another 10 new signals. Then another 10 will be added. Now the total equity allocated will be 15%. The rule is that maximum there will only be 90 position allocated. This is the whole advantage of algo/quant trading. You can do many positions thus achieving diversification which in turn reduces drawdowns which in turn increases cagr to drawdown ratio. This cant be done manually as it will be too much work. It can but not consistently everyday. The code does this all for you. So you can have multiple strategies which trades thousands of stocks simultaneously. This is how quant traders get a massive advantage from retail manual traders.
i still got confused about those punctuation, , ; make me so dizzy. Do u have any tips for pure beginner :(
Unfortunately no mate. You have to go through these. No way around it. Coding is a bit annoying that way. After a awhile you'll get used to it
The chart is at 5 minutes, but he's saying 200 DAYS moving average.. Am I missing something?
Hey guys, just saw 4ra’s new promo video, and it’s amazing! feeling so much more confident betting there now! ✨ the way they are promoting makes it feel super reliable.
The chances of winning on 4RBT are unmatched, now it's time for the World Cup T20 🏅🔥
Watched the last matches and bet on 4RA, it was so much fun, now I'm excited for the World Cup T20 😁🎊
Seeing a legend like Finch backing 4ra makes me trust their bets and games even more, man. Solid choice! 👌💸
Finch's presence in 4ra ads is huge, bro. It shows they care about quality and sports expertise. 🌟
Who caught Finch's last promo on 4ra, man? Made betting on cricket matches more exhilarating than ever! 🎥🎰
Since Finch joined 4RBT, I've noticed more of my cricket buddies here, man. He's definitely bringing in the crowd! 🏏👫
Finch's tips on 4ra's platform are gold, bro. Betting feels like you're actually part of the game! 📊
Did you guys see Finch promoting 4RA, man? Gave me the confidence to place my first bet today! 🚀👍
Totally agree, man. It's awesome that 4ra brings in real cricket stars like Finch. Makes it so much more relatable, bro. Cricket and 4ra just got even better with Finch onboard, man. Can't wait for the next IPL bets. 🎉🏆
Finch as ambassador means 4RBT is serious about their cricket bets, man, right? 🤔💯
Just saw Finch is now 4ra's face, bro! Feeling more confident betting there now! ✨
🎉 It's more fun competing and sharing the platform with people you know, right? What’s the best part of 4RABET for you
📈 Sharing strategies with friends has really ramped up my betting game. Got any tactics you swear by
🤑 Following some tips from my brother turned into a decent win last month. Ever had a win that felt extra sweet because it came from a tip
🃏 Was introduced to the poker tables by a friend who’s pretty good at it. Have you dabbled in any card games on 4RABET
🎱 I stick to slots for the most part; it's easy and I don't have to think too hard. What's your go-to for a relaxed gaming session
🚀 My friend suggested trying the crash games for a quick thrill, and wow, were they right! Have you taken a shot at those yet
🎡 I'm mostly into roulette; the vibe feels just like a real casino. Got any favorites when it comes to table games
🏏 I got into cricket betting because my colleague made it sound so exciting. Have you picked up any new interests from friends on there
🎲 A buddy of mine was all about their live casino games. He finally convinced me to try. You ever get pulled into a game from a friend's recommendation
when the method is known by the market. the efficiency will go down. trader need to find another method that in private use.
Well, I guess, this is one of those "advisers" from a broker company, who want to make you trade all the time without any good reason. One thing I can tell you for sure. May be, something like that worked 50 years ago. But if Medallion would base their trading on such 5Ups nonsense strategies during the last 20 years, they would went belly up long time ago.
Their win rate is less than 51%. 50.x %
I will look at the Quant basic coarse thanks for the heads up!🙏
Nice just getting into Trading vue ~ONI
I doubt Markov processes can be used for trading by themselves, especially if they are based on historic data, anything that uses historic data will not work. But they might be used in conjunction with something else. That's why these trading models are a secret.
Thanks for watching and for the comment. We have to use historic data. There is no other option, we dont have future data as we dont know the future. The other option is to use simulated data. But even for simulated data we need historic data, ie a base to find out this simulated data. For example if i want to simulate the weather data of london, i need the historic data of london and simulate it from there. I cant get historic data of dubai or talke the average weather of planet earth and simulate it for london. We talked about creating simulated data in our other youtube video. We used methods like monte carlo. Regardless we cant ignore historic data as there is no other option. it has to be involved some way or the other.
4:37 to 5:06 "A Markov process is basically a random sequence of events where the probabilities of the future is based on the current state. It's not based on the past. Tomorrow's probabilities depends upon today. It's not dependent upon yesterday." 12:27 However here later in the video, with your transition matrix and up_counts, down_counts, up_to_up, etc. You are using historical data to estimate these probabilities. 15:23 And here the condition uses 5-6 days. So what was actually meant here...? Did you mean that the future state is based on the present state, but the probabilities of the movement are estimated from past data?
Thanks for watching and commenting. You're first statement is correct. Just as described in the video. For the 2nd statement. While the markov property dictates that future states depend only on the present state, we still need to determine the transition probabilities. These probabilities describe how likely it is to move from one state to another. To calculate the probabilities, historical data is used. This involves looking at past sequences of events to calculate the frequency of transitions from one state to another. 3rd statement. You can use whatever days as long as thats the perspective state. Then it follows Markov property/framework .So 5 days back is first state and yesterday the 2nd state. The use of historical data to estimate probabilities does not contradict the Markov property but rather supports it by providing the necessary statistical basis for making state transitions.
THE WHOLE TIMELINE : 00:06 Algorithmic trading 06:21 Libraries like imagine, yfinance, pandas, numpy, and matplotlib can be imported and used to perform various functions. 19:02 Learned how to download, manipulate, and analyze data 24:46 The graph shows the performance of Apple, Coca-Cola, and SBY stocks normalized to 100. 36:18 The code demonstrates the use of divide, subtract, and shift functions on a data frame. 42:03 The main point is about handling and manipulating data in Python. 53:43 Calculate the mean and standard deviation of multiple stocks. 1:00:35 Comparing risk and reward of different stocks 1:12:08 Download 20 random stocks, calculate risk and reward, compare covariance and correlation, and find the best five to invest in based on assessment. 1:17:25 Log return is a more accurate measure of returns compared to simple returns 1:29:08 Calculate and plot the 50-day and 200-day moving averages and the exponential moving average (EMA) for a given stock. 1:34:44 Re-indexing data in pandas to include missing days and manage missing values 1:45:58 The annual average return for Apple stock is 17.5% with a standard deviation of 45% 1:51:31 Apple stock experienced a significant drawdown of 82% on December 23, 1997. 2:02:53 The strategy involves going long or short based on the SMA values 2:08:42 The buy and hold strategy had higher returns compared to the 50-100 day moving average strategy, but it's not necessarily the ideal strategy. 2:20:25 The function allows testing of trading strategies based on moving averages 2:26:12 Multiple strategies for multiple strokes 2:37:54 The strategy of using SMA 50 and SMA 100 seems to work well in the SPY stock. 2:44:00 Create a Python file for backtesting strategies 2:55:23 The text discusses downloading and working with data using APIs. 3:00:49 Focus on achieving a fast increase from 10842.72 to 10849.08
This is the first 3 hour course video I could finish! Very engaging and fun.. Learnt soo much about python and how to exercise and test strategies.. Loved every bit of it! Can you make any video on how to integrate Neural networks and AI to generate automated strategies.. Atleast how to go about the process would be of great help!
I was thinking the same of creating a neural networks video. Hopefully should be done in the next couple of weeks. Thanks for watching and also the nice comment. Appreciate it mate.
Is it posible to do an AI for SMC strategies. SMC involves experience and discretion so I dont know of it is possible
Very inspiring video! Though I suspect that stellar results on the test set mostly come from the fact that you are exploiting the data leak. quantiles that you use to open positions are calculated using the future data (of the entire test set). In real trading, you don't know upfront what will the quantiles of the future predictions spanning years ahead be. Also, it's a good practice to turn any duplicated code into a procedure to reduce possible copy-paste errors and easу maintainability. Good candidate for that here is the featurization code. Also, best practice for combining preprocessing with models is to use pipelines. Plus, PCA needs prior data normalization, therefore, optimal way would be make_pipeline(StandardScaler(),PCA(),your_model). Another necessary step is comparing your model with a dummy model (DummyRegressor in this case) and checking whether your model is having a real gain over random guessing.
Thanks for watching. The testing data and training data are completely separate. Quantile calculations are also separate. I can confirm that there has been no data leaks. You can go through the code and run it yourself to confirm the same.
I wish people would understand that market secrets are not allowed to go on the net....dark net maybe, certainly not on youtube.,,,The people that own the markets own youtube too....Anything on youtube or the net regarding the market is most likely going to be an unintentional or intentional throw off
Well most people dont even have the money to start trading nor would they even know where to start so I dont think they care
Compounded his swing trades for rapid growth, Warren buffet does it the slow buy and hold way
Is there a discount code I can use when buying the course
I suspected Jim Simons also does correlation trading based on what mathematicians call 'action limits' within 'activity networks'. When two financial instruments or asset classes deviate from known means and standard deviations over time, an 'action limit' can be set in the algorithm, for example: changes in the price of a 10 year T-note has shown a strong correlation to the price of copper divided by the price of gold. If a rare event occurs beyond three standard deviations say, calculated by a computer program, then it is highly probable the price of copper will fall and the price of gold will rise so the correlation with the price the T-note regresses toward the mean more. The 'action limit' looks like mu = +/- 2.5 STD/square root of N, where N is the number of values in the sample of copper/gold ratios, say. So the computer will automatically short coper and buy gold at certain times until the action limit is no longer triggered. It has to do with 'critical path analysis' where vertices in the path represent different activities to be performed, as in the computer generating orders to buy, sell, short, etc.
You are amazing sir. Do you come from inside the industry?
@@Serenelove520 Thanks. Yes, I manage a charitable endowment.
@@StephenDoty84 Hey, I'm currently a college student studying computer science looking to get into quantitative finance. I'd love to talk to you about the work you do; do you have any email/social where I could message you?
One day someone will be able to do this with NVIDIA.
At 1:46, what are the values on the Y-axis and what are the units? What is the Y-axis telling you?
Can you use QuantConnect to connect to Interactive Brokers to trade options on stocks?
What do you think about using renko chart instead of japanese candles?
Not ideal to use Renko. it takes away the time element and also keeping a constant brick size or what brock size to use can create issues. Honestly for me renko only looks good in chart, there is reallly limited practical use for renko
which course are you referring to for the strategy you talked about at 17:30?
Apologies for the delayed response. Its the Prometheus course
If you think you are going to do this in just over 3 hours by following along that is not going to happen. Plan for 3 days. Just a great video. So much information. Thank you.
Took me exactly 4 days!
Well explained video