Aditya Vyas

Wallets Backend Lead at Stellar Development Foundation

[Aditya Vyas @adityavyas1702]

@USAndIndia What about an already scheduled visa appointment? Can we convert that in-person appointment into an interview-waiver appointment?

[Quantocracy @Quantocracy]

Machine Learning for Trading Pairs Selection [@Hudson_Thames] https://t.co/sk4fQLgyDZ

[Aditya Vyas @adityavyas1702]

@Quantocracy @hudson_thames Thanks Mike. Appreciate the kind words and glad to know the community finds our articles helpful :)

[Hudson & Thames @hudson_thames]

PortfolioLab 0.1.0 has been released!

Simply: pip install portfoliolab

Documentation: https://t.co/PenIGFzU2g

As we move more and more towards enterprise, we are formalizing our libraries.

We will be deprecating the MlFinLab port opt code 1 Feb, important to make the switch!

[Aditya Vyas @adityavyas1702]

@GYXdeals Wow this is something. What do you mean by the Ps5 banner?

[Aditya Vyas @adityavyas1702]

@kushan2020 Wow this is great! Did you try any other games?

[Hudson & Thames @hudson_thames]

MlFinLab 0.14 has been released!

+ Synthetic Data Generation
+ Networks
+ Optimal Mean Reversion
+ 6 New Notebooks

Click here to read more: https://t.co/hOCKN484lW

#MachineLearning #Research #Trading #Investing

[Valeriia Pervushyna @VPervushyna]

It is a great honor to be supported by such a renowned professor! Can't wait to implement more of his work!

A Python Package for Optimal Mean Reversion Trading by Tim Leung, Ph.D. https://t.co/kltq46gvY1

#quant #MachineLearning #research #StatArb

[Aditya Vyas @adityavyas1702]

@lopezdeprado Congratulations!

[Aditya Vyas @adityavyas1702]

@CapitalParadox @Quantocracy @ArturSepp @hudson_thames @CapitalParadox Yep, totally agree with you. Just that we wanted to cover all topics in our blog series ranging from some complex ones like Hierarchical Risk Parity to traditional Mean-Variance Optimisation.

More complex Bayesian techniques coming soon 😉

[Aditya Vyas @adityavyas1702]

Part-4 of "Portfolio Optimisation with MlFinLab" series goes through some commonly used methods of calculating the covariance matrices starting from simple methods like Maximum Likelihood, Minimum Covariance Determinant to more advanced ones like Shrinkage, Denoising and Detoning

[Aditya Vyas @adityavyas1702]

Risk has always played a very large role in the world of finance with the performance of a large number of investment and trading strategies being dependent on the efficient estimation of underlying market risk.

@hudson_thames #quantfinance

https://t.co/s4B33B5iAW

[Quantocracy @Quantocracy]

Portfolio Optimisation with MlFinLab: Theory-Implied Correlation Matrix [@Hudson_Thames] https://t.co/nWhYhlF3QH

[Aditya Vyas @adityavyas1702]

The TIC algorithm is now available as a Python implementation in MlFinLab and can be used in your research. Check out it's documentation here -

https://t.co/clQW259IQS

@hudson_thames #machinelearning #financialmachinelearning #portfolio_optimisation

[Aditya Vyas @adityavyas1702]

By combining external market views with empirical observations, @lopezdeprado 's TIC algorithm removes underlying noise from traditional correlation measurements and generates better estimates of the portfolio correlations in sync with economic theory.

https://t.co/8UUMLqPI5r

[Aditya Vyas @adityavyas1702]

New blog post on Hierarchical Equal Risk Contribution (HERC) - https://t.co/179wZ6SbCx

Using machine learning and multiple risk measures like CVaR and CDaR, HERC generates robust risk-adjusted portfolios with good out-of-sample performance.

#MachineLearning #quantfinance

[Aditya Vyas @adityavyas1702]

@Lowkey08811805 @lopezdeprado @hudson_thames @JacquesQuant Yes, technically we can use any other way of representing risk/correlation between assets. The methodology stays the same but the underlying representations of correlations of asset returns can change.

[Aditya Vyas @adityavyas1702]

Starting today, @hudson_thames is launching a blog post series titled “Portfolio Optimisation with MlFinLab”. The first post on hierarchical risk parity has been published:

https://t.co/V685kr2974

@lopezdeprado @JacquesQuant #quantfinance #machinelearning

[Aditya Vyas @adityavyas1702]

@MikeyDoh89 @hudson_thames @lopezdeprado @JacquesQuant @MikeyDoh89 Good question. I have not found any paper or discussion relating to placing volatility targets (for HRP). However, I did read a paper on placing constraints on the assets in HRP. Here is the link - https://t.co/3XeKDqPuFA

Maybe @lopezdeprado might have an idea 🙂

[Aditya Vyas @adityavyas1702]

All each article in this series is supplemented by an in-depth research notebook found in our research repository - https://t.co/IsGth4GRnI.

[Aditya Vyas @adityavyas1702]

These will be code-tutorial style blog posts aimed at guiding the user through the different sub-modules and algorithms in our portfolio optimisation module. Each post will cover a specific implementation and we will go through the different functionalities of using MlFinLab API.