Jim Simons Trading Secrets 1.2 SIMULATED Data Generation

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 million data points starting from just 750 data points during the Global financial crisis years of 2008-2011. Limited amount of data is one of the biggest drawbacks in quantitative trading.These data simulations can help us backtest even more and make sure our strategy works in all these simulations and thus giving us more confidence in deployment of strategy.
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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.

[@haedarajmi7083]

Thank you very much for this effort

[@LogicRat609]

woah this is amazing !!!

[@nussbaumerloris]

Great Video, thanks alot!

[@quantprogram]

Thanks for watching mate

[@gavinhill3164]

I think what your doing is really interesting, thanks

[@quantprogram]

Thanks much mate

[@sorte18]

It would be great if you could re-visit this, and create OHLC data in one of the models (say MC, for example).

[@kevinli522]

Thank you for your incredible videos. Could you pleas let me know how I can possibly leverage this Synthetic data generation to apply to a panel dataset? Thanks!

[@pedrofeliciano2150]

great video. congrats. I just found it strange that the geometric brownian motion with a positive drift is not positively biased.

[@proprietarycurez8463]

Do you even trade?

[@aaronmugume293]

Ive loved the video ❤

[@quantprogram]

Thanks mate

[@muhireinnocent2371]

Great content , thanks .Can i apply the same concept to forex trading and when it comes to training lets say a machine learning model how can i combine the simulated data with the real data and the fact that financial market data is a time series data like how would make sure that combine the datasets don't affect my datetime order. Thank you

[@osazemeusen1091]

Impressive lecture, thanks for sharing

[@quantprogram]

Glad you liked it!

[@sakshamsingh1415]

Really good video

[@quantprogram]

Thanks mate

[@efrainromero3959]

It's incredible this videos doesn't have hundreds of likes. This is real Smart Money trading strategies!. Then what the traders are learning?

[@quantprogram]

Thanks for watching mate. Happy you liked it

[@haedarajmi7083]

Most people are afraid to take risks because they do not trust their minds🥰

[@MySockKeepMyToesWarm]

I found this amusing on multiple channels I’ve come across. Majority of stuff that actually give great knowledge to the internet have very few views. It’s amazing but just shows you the perception of trading is so diluted with lies to the retail traders they don’t know truth when they see it! I’m generalizing and assuming but it is fascinating. Grateful to God for the wisdom to discern!

[@teeleo1363]

@@MySockKeepMyToesWarmabsolutely correct.. the few who like these videos are those 1% who grow their account..😂

[@BullBearInsights126]

does this strategy work u=in indian market

[@jordiplotnikovpous4844]

why do you take the logarithm of 1+percentage_increase, and not just 1+percentage_increase?

[@quantprogram]

Its important in financial analysis to use log returns. Difficult to explain in 1 comment but its advantage is huge when it comes to normalization of returns and also handling negative values along with analyzing statistical properties. There are lots of info available online including in youtube on the importance of using log returns

[@lteodorescu]

so what's the actual strategy mate ?

[@quantprogram]

The video is about data generation so we can efficiently test strategies

[@icyboy771z]

Even if the actual strategy is given to you the normal ppl like us won't be able to implement it because he has a team of specialized workers and huge database of data.