Our Investment Philosophy

Introduction:

Stock market performances have higher returns compared to free risk investments in long term prospective. Essentially, the risk adjusted returns are still higher within stock markets compared to other types of investments.

THE EQUITY PREMIUM PUZZLE:

There is an important puzzle in economical literature called “The Equity Premium Puzzle”.

The Equity Premium Puzzle raises the questions of “why is the risk adjusted return within the stock market much higher than the risk free return?” and “why are people still preferring to put their money in risk free assets?”

An answer to this puzzle was found by the famous Nobel Prize winning “Prospect Theory”.

Prospect Theory argues that people are not only risk averse but also rather they are loss averse. So, they would be much more sensitive to their losses compared to their wins.

Our Quantitative investment strategies:

Our current model is achieved through eight years of research and development. We have tested many different strategies. The experience which we got from these years of R&D projects, gave us a vision to combine different methods for our final investment plan. A short brief of all the tested strategies is:

Pair trading and statistical arbitrage between equities

Deep learning and other unsupervised learning methods

Real time fundamental analysis
Event studies

Natural language processing (NLP) for financial news

Macroeconomics regime switching models

Our final model is mixed approach from results we got from all of the mentioned projects.

Our back testing approach:

One of the most important aspects of evaluating a quantitative investment strategy is how the strategy had performed in previous periods.

Out of sample predictions:

To avoid over fitting for back testing, we used out of sample predictions only. Meaning that for any prediction that is presented in this document only historical prices prior to the point of prediction have been used.

Robustness of prediction:

To make sure that our results are robust, we have generated an artificial prices using Monte carlo simulation with properties similar the original asset prices. Results of each trading strategies are reported for simulated prices as well.

Global Assets Diversification:

We aim to benefit from diversification in three ways:

Risk reduction

More return opportunities

Cross country diversification

we have adopted an algorithm for investment in indices of main international markets, such as:

Stock Markets:

S&P500
NASDAQ
US single stock
US OPTION MARKET
DAX
Shanghai
UAE
Saudi Arabia

Commodities markets:

Oil
Gold

Cryptocurrency

Bitcoin