Trendfollowing

The primary motivation behind our study stems from an observation of the Global Tactical Asset Allocation (GTAA) strategies throughout the existing papers – the majority of them require relatively frequent rebalancing from the point of view of the ordinary investor. Portfolio rebalancing is usually done on a weekly or monthly basis, and while this period may seem overly boring and slow for the majority of traders (who like to trade on intraday or daily basis), fans of GTAA strategies are not traders; they are investors. Of course, some like to follow the ebbs and flows of the market. But a lot of investors just want to have a life. The financial market is not their hobby. However, on the other hand, they also do not want to hold just the passive buy & hold portfolio. Recognizing the demand for the semi-active strategy, we introduce our novel Pragmatic Asset Allocation.

In a game of poker, it is usually said that when you do not know who the patsy is, you’re the patsy. The world of finance is not different. It is good to know who your counterparties are and which investors/traders drive the return of anomalies you focus on. We discussed that a few months ago in a short blog article called “Which Investors Drive Factor Returns?“. Different sets of investors and their approaches drive different anomalies, and we have one more paper that helps uncover the motivation of investors and traders for trading and their impact on anomaly returns.

Seasonality effects, one of the most fascinating phenomena in the world of finance, have captured the attention of investors and researchers worldwide. Since these anomalies are often driven by factors other than general market trends, they usually don’t correlate strongly with market movements, which can help reduce the portfolio’s overall risk. Following the theme of our previous article Are There Seasonal Intraday or Overnight Anomalies in Bitcoin?, we decided to extend the data and conduct a more in-depth analysis of our earlier findings. This article explores potential seasonal patterns related to Bitcoin, focusing on whether these patterns are influenced by factors such as current market trends or the level of volatility in the market.

The commodity momentum strategy is a crucial driving force behind Commodity Trading Advisor (CTA) strategies, as it capitalizes on the persistence of price trends in various commodity markets. By identifying and exploiting these trends, CTAs can achieve robust returns and diversification benefits. In their new paper, John Hua FAN and Xiao QIAO (February 2023) present their perspective and understanding of cross-country and cross-sector influences on the behavior of commodity momentum beyond established commodity fundamentals focusing on U.S. and China markets.

It’s always fun to push the boundaries of technology and see what it can do. The AI chatbots are the hot topic of current discussion in the quant blogosphere. So we have decided to test OpenAI’s ChatGPT abilities. Will we persuade it to become a data analyst for us? While we may not be there yet, it’s clear that AI language models like ChatGPT can soon revolutionize how we approach to finance and data analysis.

In the last third installment, we will finish exploring the world of market timing strategies (see parts 1 & 2). We will focus on yield curve predictors and incorporate all three ideas (price-based, macro-economic, and yield curve predictors) into one final trading strategy that yields an annual return above that of the stock market while doubling its Sharpe ratio and reducing maximal drawdown by two thirds.