Markets are typically volatile, and price movements accelerate during macroeconomic announcements. We have discussed the macroeconomic announcement premium and the related beta arbitrage strategy. Along this line of research, Reference examined the returns of delta-neutral straddles around macroeconomic announcements. By analyzing these returns, one can draw conclusions about the …

Identifying market regimes is important for understanding shifts in risk, return, and volatility across financial assets. With the advancement of machine learning, many regime-switching and machine learning methods have been proposed. However, these methods, while promising, often face challenges of interpretability, overfitting, and a lack of robustness in real-world deployment. …

Gold is an important asset class, serving as both a store of value and a hedge against inflation and market uncertainty. Therefore, performing predictive analysis of gold prices is essential. Reference evaluated several predictive methods for gold prices. It examined not only classical, statistical approaches but also newer machine …

Analyzing volatilities, correlations, and lead–lag relationships across financial assets is important for portfolio and risk management. As cryptocurrencies gain traction, research in this area is growing. Reference studies the causal relationships, volatility, and correlations among major cryptocurrencies and the Crypto Volatility Index (CVI). A distinctive aspect of this work …

Concentration risk arises when too much exposure is tied to a single firm, sector, or asset. If one company, or a handful of large players, becomes too big in a portfolio or market, their failure can drive outsized losses. In essence, concentration risk is the danger of being undiversified: the …

As cryptocurrencies become mainstream, liquidity in crypto derivatives such as perpetual futures and options is improving. They also attract more attention from researchers. Reference contributes to the growing literature on crypto derivatives by studying Bitcoin options volatility. Specifically, it shows that BTC options share both the “usual” and “unusual” …

Traditional quantitative methods often rely on structured data, such as time series. With the emergence of Large Language Models (LLMs), it is now possible to process unstructured data. A new line of research focuses on integrating unstructured data analysis into traditional frameworks. Along this line, Reference proposed the use …

A volatility index is a measure of expected future volatility derived from market data. For example, the VIX reflects expected volatility in the S&P 500 based on option prices. Reference constructed a novel volatility index, called the Speculative Volatility Index (SVI). It was motivated by the idea that the …

Momentum and mean-reverting approaches are two primary methods for trading linear (delta-one) assets. Their effectiveness depends on several factors, such as time horizon, investor behavior, liquidity, etc. Reference conducted a comprehensive literature review of momentum and mean-reverting approaches. It aims to answer two questions: How have momentum and contrarian …

Delta hedging is a technique used to reduce the directional risk of an options position. Most research in this area focuses on hedging with Black-Scholes-Merton (BSM) implied volatility or those derived from advanced volatility models. Reference compares the performance of delta hedging using implied volatility (IV) versus historical volatility …