Quantocracy’s Daily Wrap for 07/27/2020

I have used machine learning in trading strategies over the past 10 years. However my use of ML has often played a relatively small role in the overall design and success of the strategies. I use ML in specific signals or strategy sub-problems where the data / problem setup tends to have a robust statistical solution. This is as opposed to the Nirvana scenario where fundamental features and

Our first look at calendar influences was in analyzing the best time during the month to execute dual momentum trades. Studies here, here, and here show that stocks perform best early in the month. This is when institutional investors make changes to their portfolios. Prices then are most representative of their true value. Here are the Sharpe and Sortino ratios for our Global Equities Momentum

In the search for more and better factors, this article examines the cross-sectional relationship between historical skewness (see Jacks post here) and the returns on a robust set of assets and documents the premium for taking on skewness risk. The authors construct long/short portfolios across four global asset classes including equity indices, government bonds, commodities, and currencies

The alpha of global macro funds has been shrinking consistently over time However, correlations to equities & bonds were low on average, offering diversification benefits Capital allocators have been cautious on the strategy in recent years INTRODUCTION He-Man and the Masters of the Universe was a popular TV cartoon show in the 1980s, where a handsome Prince Adam was battling the evil Skeletor

Nowcasting is a modern approach to monitoring economic conditions in real-time. It makes financial market trading more efficient because economic dynamics drive corporate profits, financial flows and policy decisions, and account for a large part of asset price fluctuations. The main technology behind nowcasting is the dynamic factor model, which condenses the information of numerous correlated