Pairs trading is a market-neutral strategy that exploits temporary deviations in the price relationship between two historically correlated or cointegrated assets by going long the undervalued asset and short the overvalued asset, aiming to profit from spread mean reversion. There is an emerging study in the literature that highlights the …

Accurately forecasting volatility is essential in portfolio and risk management. Typically, volatility forecasting is performed using econometric models such as GARCH and ARIMA. These methods can also be applied to cryptocurrencies. However, a unique feature of cryptocurrencies is their higher susceptibility to market sentiment. We have discussed their sensitivity to …

Volatility targeting is a risk and portfolio management technique that adjusts exposure based on changes in asset volatility. We have discussed volatility targeting methods in previous posts, for example, Applying Volatility Management Across Industries. While effective, this technique requires frequent rebalancing. As with any approach involving high turnover, such as …

AI-assisted trading is a growing area in quantitative finance. However, concerns have emerged that it may destabilize markets. We recently discussed how trading strategies generated by large language models could introduce new systemic risks to financial markets. Continuing this line of research, Reference examines how AI trading affects market …

Sentiment analysis is a growing research area in quantitative finance, especially with the advancement of Large Language Models (LLMs) and Natural Language Processing (NLP). Sentiment-based trading plays an important role in traditional finance; however, it is even more relevant in DeFi and crypto markets, which are known for their volatility …

The variance risk premium (VRP) is a well-researched topic in quantitative finance. The VRP is the difference between the market-implied variance and the expected realized variance of an asset. Usually, the VRP is positive, reflecting the compensation investors demand for bearing volatility risks. Reference extends this analysis further and …

Large language models (LLMs) are advanced artificial intelligence systems trained on vast amounts of text data to understand and generate human-like language. LLMs can perform a wide range of language tasks, including translation, summarization, question answering, and code generation. Their versatility has made them valuable tools across industries, from finance …

Delta hedging is a method used to reduce or eliminate the directional risk of an options position. In most delta hedging schemes, delta is calculated using the Black-Scholes-Merton (BSM) model. However, the BSM delta is not always accurate due to the assumptions embedded in the model. For a more accurate …

Trend following is an investment strategy that seeks to capture gains by identifying and trading in the direction of established market trends. Trend followers aim to ride sustained movements, upward or downward, using rules-based systems often driven by price momentum, moving averages, or breakout signals. Trend following is a popular …

The profit and loss of an options trading strategy can be path-dependent, meaning that interim price movements, not just the final outcome, significantly influence profits and losses due to factors like dynamic hedging, early exercise risk, and volatility shifts. A well-known example is the PnL of a delta-hedged option position, …