Machine learning (ML) is increasingly prominent in modern finance and is being adopted across a wide range of applications. However, using ML to extract alpha remains nontrivial. Reference proposes a novel approach to improving the risk-adjusted returns of momentum strategies using machine learning. It employs three ML methods—linear regression, …

The volatility risk premium (VRP) refers to the systematic difference between implied volatility and subsequent realized volatility. Much of the academic literature focuses on developing strategies to harvest the VRP directly. However, Reference departs from this conventional approach by proposing the use of the VRP as a market-timing mechanism. …

Delta hedging is a critical component of option portfolio management. In the research literature, most studies assume strict delta hedging, where portfolio delta is maintained at zero. Reference relaxes this restriction by introducing a partial delta hedging technique that conditions the hedge ratio on the confidence of the underlying’s …

Modeling and forecasting volatility is critically important for portfolio construction and risk management. Numerous volatility models exist, and one established line of research incorporates trading volume, motivated by the idea that volume reflects the rate of information flow into prices and is therefore positively related to volatility. Reference extends …

The Black–Scholes–Merton (BSM) model is the most frequently used option pricing framework in finance. However, it relies on simplifying assumptions, some of which are not realistic. Ongoing efforts aim to extend and generalize the BSM model, and Reference represents a recent contribution in this direction. The paper proposes an …

In today’s digital era, social media is ubiquitous, and market participants are exposed to an unprecedented volume of financial information. While investors are arguably more informed, it remains an open question whether this translates into better and more disciplined decision-making. A recent incident illustrates this concern: a group of online …

The Fractal Market Hypothesis (FMH) is increasingly studied and applied by both finance academics and practitioners. We previously discussed the use of Detrended Fluctuation Analysis to estimate the Hurst exponent for major cryptocurrencies. Continuing this line of research, Reference applies Multifractal Detrended Fluctuation Analysis (MFDFA) to examine cryptocurrency, commodity, …

The Black–Scholes–Merton (BSM) model is a cornerstone of derivative pricing; however, it is not without limitations, and researchers continue to extend it. Reference proposes an extension by incorporating intraday momentum into the BSM framework. This is achieved by introducing a drift term that represents intraday momentum, measured using a …

Investors and traders often suffer from behavioral biases, which is where behavioral finance originates. Among these biases, recency bias is probably the most detrimental, yet it has infrequently been studied in a comprehensive, quantitative manner. Reference addresses this gap by investigating recency bias in stocks with high idiosyncratic volatility …

Predicting market direction is challenging, and forecasting market crashes is even more difficult, yet this remains a growing area of research. We previously discussed market correction prediction, and Reference continues this line of inquiry by examining how machine learning can be used to predict market crashes within the Adaptive …