Author: Harbourfront Technologies

Enhancing Trading Strategies Using Model Uncertainty

Most trading systems focus on algorithms for generating entry and exit signals. When the performance deteriorates, developers often try to introduce additional filters and/or modify system parameters. Reference applied a novel technique, called Dynamic Model Averaging (DMA), to improve model performance. Basically, DMA estimates model uncertainty, and a trade …

Volatility Risk Premium Seasonality Across Calendar Months

Seasonality in investing refers to the tendency of financial markets or specific assets to exhibit predictable patterns at certain times of the year. These patterns can arise due to recurring economic, behavioral, or institutional factors. Understanding and analyzing seasonal trends can help investors time their trades more effectively and enhance …

Time Series vs. Machine Learning: A Systematic Evaluation

Forecasting is important in finance, as it helps investors, analysts, and institutions make informed decisions under uncertainty. Up to now, most forecasting techniques have relied on traditional time series methods, such as ARIMA, GARCH, and exponential smoothing. However, with recent advancements in machine learning and artificial intelligence, these technologies have …

Tail Risk Hedging with Corporate Bond ETFs

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 …