The relationship between two assets can be examined using various techniques such as correlation, lagged correlation, cointegration etc. Reference presented a new method called Quantile-on-Quantile Spillover Analysis to examine the relationship between two assets. This approach involves estimating Quantile Vector Autoregression (QVAR) models across different quantiles and then calculating …

A common belief in strategy design is that ‘more data is better.’ But is this always true? Reference examined the impact of the quantity of data in predicting realized volatility. Specifically, it focused on the accuracy of volatility forecasts as a function of data sampling frequency. The study was …

Time series momentum is a trading strategy that involves buying assets that have exhibited upward price trends and selling those that have shown downward trends over a specific time period. The premise is that assets with positive momentum will continue to perform well in the short term, while those with …

Pairs trading is a market-neutral strategy that involves simultaneously buying and selling two correlated assets to exploit their price discrepancies. The strategy aims to profit from the relative movements between the two assets, regardless of the overall market direction. Pairs trading requires careful selection of pairs and constant monitoring to …

Hedging is a risk management strategy used to offset potential losses in one investment by taking an opposing position in a related asset. By using financial instruments such as options, futures, or other derivatives, investors can protect their portfolios from adverse price movements. The primary goal of hedging is not …

Airbag options are a new structured product that has gained popularity among investors in the over-the-counter derivatives market. They offer protection against downside losses, similar to how an airbag protects in a car crash. Airbag options provide investors with downside risk protection in the event of a market “collision.” However, …

Machine learning is a subset of artificial intelligence that involves training algorithms to learn patterns from data and make predictions or decisions without being explicitly programmed. It encompasses a range of techniques, from simple linear regression to complex neural networks, and is used in various applications such as image and …

A Credit Default Swap (CDS) is a financial derivative that allows investors to hedge or speculate on the credit risk of a borrower, such as a corporation or government. In a CDS contract, the buyer of the swap makes periodic payments to the seller in exchange for protection against the …

The volatility risk premium (VRP) is the compensation investors receive for bearing the risk associated with fluctuations in market volatility, typically measured as the difference between implied and realized volatility. The VRP in equities has been studied extensively. However, relatively little attention has been paid to the VRP in other …

We have discussed at length the implied volatility and its relationships with realized volatility, volatility skew, dividend yield, and correlations. Moreover, it is interesting to examine implied volatility from a behavioural finance perspective. Reference studied the relationship between various countries’ implied volatilities and their cultural characteristics. Specifically, it utilized …