Can We Use Active Share Measure as a Predictor?

Active Share is a popular metric used to gauge how actively managed a portfolio is compared to its benchmark, but its predictive power for fund performance is questionable. Our research suggests that high Active Share often reflects exposure to systematic equity factors rather than genuine stock-picking skill. Additionally, inaccuracies in benchmark selection can distort the metric’s insights, making it unreliable as a standalone measure. A more effective approach is to conduct a factor analysis of alpha to better understand a manager’s performance and true sources of over/underperformance.

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How To Profitably Trade Bitcoin’s Overnight Sessions?

As interest in cryptocurrencies continues to surge, driven by each new price rally, crypto assets have solidified their position as one of the main asset classes in global markets. Unlike traditional assets, which primarily trade during standard working hours, cryptocurrencies trade 24/7, presenting a unique landscape of liquidity and volatility. This continuous trading environment has prompted us to investigate how Bitcoin, the flagship cryptocurrency, behaves across intraday and overnight periods. With Bitcoin’s growing availability to both retail and institutional investors through ETFs and other investment vehicles, we hypothesized that trading activity in these distinct timeframes could reveal patterns similar to those seen in traditional markets, where returns are often impacted by liquidity shifts during off-peak hours.

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How to Improve ETF Sector Momentum

In this article, we explore the historical performance of sector momentum strategies and examine how their alpha has diminished over time. By analyzing the underlying causes behind this decline, we identify key factors contributing to the underperformance. Most importantly, we introduce an enhanced approach to sector momentum, demonstrating how this solution significantly improves the performance of an ETF sector momentum strategy, making it once again an effective tool for systematic investors.

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How to Improve Commodity Momentum Using Intra-Market Correlation

Momentum is one of the most researched market anomalies, well-known and widely accepted in both public and academic sectors. Its concept is straightforward: buy an asset when its price rises and sell it when it falls. The goal is to take advantage of these trends to achieve better returns than a simple buy-and-hold strategy. Unfortunately, over the last decades, we have been observers of the diminishing returns of the momentum strategies in all asset classes. In this article, we will present an intra-market correlation filter that can help significantly improve commodity momentum performance and return this strategy once again into the spotlight.

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Revisiting Trend-following and Mean-reversion Strategies in Bitcoin

Over the past few years, significant shifts in the financial landscape have reshaped the dynamics of global markets, including the cryptocurrency sector. Events such as the ongoing war in Ukraine, rising inflation rates, the soft landing scenario in the US economy, and the recent Bitcoin halving have all profoundly impacted market sentiment and price movements. Given these developments, we decided to revisit and reassess trading strategies, specifically Trend-following and Mean-reversion in Bitcoin published in 2022, which utilized data from November 2015 to February 2022. This new study explores how these strategies would have performed from November 2015 to August 2024, taking recent changes into account. The study also examines market changes between February 2022 and August 2024, highlighting developments since previous research. Additionally, it evaluates the influence of seasonality on Bitcoin’s price action, similar to our previous article – The Seasonality of Bitcoin. By analyzing these factors, we aim to provide deeper insights into the evolving behavior of the world’s leading cryptocurrency and guide investors through the complexities of today’s market environment.

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