Multifractality and Market Efficiency Across Asset Classes

Posted on January 10, 2026 By Harbourfront Technologies

The Fractal Market Hypothesis (FMH) is increasingly studied and applied by both finance academics and practitioners. We previously discussed the use of Detrended Fluctuation Analysis to estimate the Hurst exponent for major cryptocurrencies. Continuing this line of research, Reference applies Multifractal Detrended Fluctuation Analysis (MFDFA) to examine cryptocurrency, commodity, …

Incorporating Momentum into Option Pricing Models

Posted on January 6, 2026 By Harbourfront Technologies

The Black–Scholes–Merton (BSM) model is a cornerstone of derivative pricing; however, it is not without limitations, and researchers continue to extend it. Reference proposes an extension by incorporating intraday momentum into the BSM framework. This is achieved by introducing a drift term that represents intraday momentum, measured using a …

Quantifying Recency Bias in Investor Volatility Expectations

Posted on January 2, 2026 By Harbourfront Technologies

Investors and traders often suffer from behavioral biases, which is where behavioral finance originates. Among these biases, recency bias is probably the most detrimental, yet it has infrequently been studied in a comprehensive quantitative manner. Reference addresses this gap by investigating recency bias in stocks with high idiosyncratic volatility …

Forecasting Market Crashes with Machine Learning Techniques

Posted on December 29, 2025 By Harbourfront Technologies

Predicting market direction is challenging, and forecasting market crashes is even more difficult, yet this remains a growing area of research. We previously discussed market correction prediction, and Reference continues this line of inquiry by examining how machine learning can be used to predict market crashes within the Adaptive …

Delta Hedging with Implied vs. Historical Volatility, Part 2

Posted on December 25, 2025 By Harbourfront Technologies

Hedging is an important topic in portfolio and risk management; however, relatively little research has been conducted in this area. Many questions remain open, such as when to hedge, how frequently to hedge, and which volatility measure should be used in hedging decisions. We have previously discussed whether hedging should …

Toward Rigorous Validation of Data-Driven Trading Strategies

Posted on December 21, 2025 By Harbourfront Technologies

With the rapid advancement in computing power, quantitative researchers can now develop trading strategies quickly, employing multiple variables and methodologies. These approaches extend beyond traditional time-series and statistical models to include machine learning and AI-based techniques. However, such models often deliver impressive in-sample results but fail in live trading, largely …

Intraday Elasticity Between VIX Futures and Volatility ETPs

Posted on December 17, 2025 By Harbourfront Technologies

VIX futures and ETPs are widely used instruments for both volatility speculation and hedging, making a clear understanding of their behavior essential for these purposes. Several studies have examined the relationship between spot VIX, VIX futures, and volatility-linked ETNs. Reference contributes to this literature by analyzing the sensitivity of …

Short-Term Stock Price Forecasting Using Geometric Brownian Motion

Posted on December 13, 2025 By Harbourfront Technologies

In these days of big data, machine learning, and AI, many researchers are showing growing interest in sophisticated models for stock price prediction or to refine basic models of stock dynamics. Reference takes the opposite approach. It uses a classical model for stock price dynamics—the Geometric Brownian Motion (GBM)—and …

Option Pricing with Quantum Mechanical Methods

Posted on December 9, 2025 By Harbourfront Technologies

It is well known that put options are often overpriced, especially in equities. The literature is filled with papers explaining this phenomenon. However, most research still relies on the Black-Scholes-Merton framework, where the underlying asset follows a Geometric Brownian Motion (GBM). Reference also addresses this question, but it departs …

Enhancing the Wheel Strategy with Bayesian Networks

Posted on December 5, 2025 By Harbourfront Technologies

The option wheel strategy is a systematic approach that combines selling cash-secured puts and covered calls. The process begins by selling puts on a stock the investor is willing to own; if assigned, the investor acquires the shares and then sells covered calls against the position to collect additional premium. …