In today’s age of AI and machine learning, developing trading strategies from historical data is becoming increasingly accessible. As a result, a growing portion of the research process is shifting from model development to model validation. However, unlike the sell-side, where model validation guidelines are well established, the buy-side literature …

The volatility risk premium (VRP) is the difference between implied volatility and subsequently realized volatility, reflecting the compensation investors pay for volatility insurance. It has long been held that the VRP is generally negative for option buyers and positive for option sellers. However, market dynamics and regimes evolve over time, …

Sentiment analysis has become an important tool in financial markets, helping researchers and practitioners extract information from news articles, social media, and other textual sources. Reference introduces a new concept called Narrative Risk Premia. Like sentiment analysis, it analyzes market discourse using news, analyst reports, and institutional communications, but …

Considerable research has been devoted to the study of the VIX futures term structure, showing that the shape of the curve contains valuable information about the future direction of volatility. Trading strategies have been developed based on the informational content of the VIX futures curve. However, much less attention has …

The volatility risk premium (VRP) is the difference between implied volatility and subsequently realized volatility, and is one of the most extensively studied phenomena in options markets. We previously discussed Reference , which decomposes the VRP into upside and downside components and studies their dynamics separately. Reference applies a …

Regime detection and classification are important in portfolio management and asset allocation. One of the key inputs into regime detection models is volatility. Reference examines which volatility measure is most effective for regime classification. The authors study three volatility measures, Implied volatility (VIX/VIXBR), GARCH conditional volatility, Historical volatility. They …

Social media sentiment has become increasingly important in modern portfolio and risk management. Most studies on social media rely on aggregate sentiment measures, such as average bullishness scores or overall positive-versus-negative comment ratios. Reference introduces an innovative approach to analyzing social media sentiment by investigating network effects, specifically how …

Prediction is central in finance. A growing line of research uses cross-asset signals to forecast market movements. A recent example showed that Bitcoin can serve as a strong leading indicator in a machine learning-based trading system. Along similar lines, Reference examines whether cryptocurrency overnight returns, defined as price changes …

Gold and silver have been strong recently, with upward trends and increased volatility. Reference studies the price dynamics of leading precious metals, gold, silver, platinum, and palladium, over the period from December 9, 2019, to March 1, 2026, dividing the sample into pre- and post-COVID subperiods. The study employs …

Regime classification is important in asset and risk management. Traditional approaches classify regimes based on direction, bullish or bearish, and volatility, high or low. Reference departs from this framework and instead classifies markets as mean-reverting or trending. Specifically, it uses return thresholds of 0.5%, 0.75%, and 1% to define …