Tail risk hedging is a strategy designed to protect portfolios against extreme market moves that occur infrequently but have a significant impact when they do. These “tail events” lie at the far ends of a return distribution and often coincide with financial crises, sharp market crashes, or systemic shocks. A …

Thanks to the advancement in computing technologies, we’re seeing more widespread use of machine learning, especially deep learning, in the financial services sector. It’s no longer just a theoretical tool; it’s showing up in everything from credit risk models to algorithmic trading strategies. Reference provides a comprehensive review of …

Financial asset fragility refers to the vulnerability of an asset’s price to sudden and disproportionate changes in response to shocks, even if those shocks are relatively small. This fragility often stems from factors like excessive leverage, crowded positioning, liquidity mismatches, or overreliance on certain market assumptions. Reference utilized the …

Managing portfolios using volatility as a filter has proven effective. Reference builds on this research by proposing the use of volatility of volatility for portfolio management. The rationale behind using volatility of volatility is that it represents uncertainty. Unlike risk, which refers to situations where future returns are unknown …

Stress testing and scenario analysis are essential tools in portfolio management, helping portfolio and risk managers assess potential vulnerabilities under extreme market conditions. By simulating adverse scenarios such as financial crises, interest rate shocks, or geopolitical events, these techniques provide insights into how a portfolio might behave under stress and …

A Large Language Model (LLM) is an advanced AI system trained on vast amounts of text data to understand, generate, and analyze human language. In finance, LLMs are used for tasks like analyzing earnings reports, generating market sentiment analysis, automating financial research, and enhancing algorithmic trading strategies. They can process …

Earnings announcements impact a company’s stock volatility. Reference examined the earnings reports of Dow Jones Industrial Average components over 10 years to better understand the relationship between different volatility regimes and the time it takes for earnings information to be fully absorbed by the market. The study focuses on …

The Hurst exponent is a statistical measure used to assess the long-term memory and persistence of a time series. It quantifies the tendency of a system to revert to the mean, follow a random walk, or exhibit a trending behavior. A Hurst exponent (H) value between 0 and 0.5 indicates …

The volatility risk premium (VRP) is the difference between the implied volatility of options and the realized volatility of the underlying asset, representing the compensation investors earn for taking on volatility risk. Recent research suggests that the VRP is specifically a reward for bearing overnight risk. Reference goes further …

Sometimes, investors come across trading opportunities that offer outsized returns, but they may not fully understand the risks they are taking on. These risks can include operational risks, counterparty credit risks, or hidden optionality within a financial note. Reference examines the role of liquidity risks in the returns of …