VaR Estimation: Variance-Covariance and Historical Simulation Methods

June 7, 2022
Sergey Okun This article was written by Sergey Okun – Senior Financial Analyst, I Know First, Ph.D. in Economics.

Summary:

  • VaR allows us to estimate possible financial losses in different scenarios.
  • Historical Simulation VaR provides us with a significantly different result from the respective Variance-Covariance VaR for very high confidence intervals which depends on the normality assumption.
  • The I Know First AI algorithm provides us with the tool to select the most promising stocks.

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Machine Learning Trading, Stock Market, and Chaos

September 1, 2021

taliTali Soroker is a Financial Analyst at I Know First.

Summary

  • There is a notable difference between chaos and randomness making chaotic systems predictable, while random ones are not
  • Modeling chaotic processes are possible using statistics, but it is extremely difficult
  • Machine learning can be used to model chaotic processes more effectively
  • I Know First has employed artificial intelligence and machine learning in order to make predictions in the stock market
  • Definitions for underlined words can be found in the Glossary at the end of the article


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Algorithmic Trading Strategies For European Stocks: Returns Up to 193%

November 5, 2017

In the following article we analyze a series of trading strategies directly adoptable by I Know First clients and which have generated returns up to 193% over the period going from August 2015 to April 2017.

The strategies follow the algorithm’s signals and invest daily in the strongest ones from the package “European Stocks” hence resulting in a portfolio continuously in line with the program’s recommendations and with the evolving market.

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Algorithmic trading strategies

Algorithmic Performance