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Multi-Asset Seasonality and Trend-Following Strategies

Last Updated on 10 February, 2024 by Rejaul Karim

Abstract Of Paper

The paper “Multi-Asset Seasonality and Trend-Following Strategies” delves into a comprehensive exploration of seasonality patterns across diverse asset classes, offering valuable insights into their implications for investment strategies. Nick Baltas investigates a strategy that leverages same-calendar-month past average returns within commodity and equity index universes, unveiling statistically and economically significant premia.

However, recognizing the practical complexities associated with the direct capitalization of these premia, the study proposes an innovative approach of actively integrating seasonality signals into a trend-following strategy by adjusting long and short positions accordingly.

The seasonality-adjusted trend-following strategy emerges as a substantial enhancement to the raw strategy, affording significant improvements across both commodities and equity indices.

While acknowledging the potential impact of increased turnover on performance, the study highlights the potential for genuine improvements with judicious methodological amendments and consideration of trading costs.

Here you can download the PDF and original paper of Multi-Asset Seasonality and Trend-Following Strategies.

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Author

Nick Baltas
Imperial College Business School; Goldman Sachs International

Conclusion

In conclusion, “Multi-Asset Seasonality and Trend-Following Strategies” presents compelling insights into the integration of seasonality patterns within investment strategies across various asset classes.

Nick Baltas’ exploration unveils a strategy that harnesses same-calendar-month past average returns, yielding statistically and economically significant premia within commodity and equity index universes.

Recognizing the practical challenges associated with direct capitalization of these premia due to high turnover and associated costs, the study proposes an innovative approach of actively incorporating seasonality signals into a trend-following strategy.

The resulting seasonality-adjusted trend-following strategy emerges as a substantial enhancement, offering superior performance across both commodities and equity indices. While acknowledging the potential impact of increased turnover on performance, the study underscores the potential for genuine improvement, facilitated by judicious methodological amendments and consideration of trading costs.

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FAQ

Q1: What is the main focus of the research paper “Determinants of Trader Profits in Futures Markets” by Michaël Dewally, Louis H. Ederington, and Chitru S. Fernando?

A1: The research paper focuses on exploring the intricate dynamics of trader profits in crude oil, gasoline, and heating oil futures markets. It uses a unique proprietary dataset to empirically test predictions of commodity futures pricing models and provides substantial insights into the determinants of trader profits.

Q2: What are the key findings regarding the polarity of profits between hedgers and speculators, and the influence of hedging pressure on trader profits?

A2: The study reveals statistically and economically significant evidence indicating the polarity of profits between hedgers and speculators. Hedgers tend to have negative profits, while speculators exhibit positive profits, aligning with the risk premium hypothesis. Additionally, the research highlights the impactful influence of hedging pressure on trader profits, indicating that traders who hold positions opposite to likely hedgers in aggregate tend to have higher profits.

Q3: How does the research contribute to understanding the variations in trader profits related to inventories and price volatility in commodity futures markets?

A3: The analysis uncovers variations in trader profits linked to inventories and price volatility, supporting the modern theory of storage. The findings indicate that profits on long positions vary inversely with inventories and directly with price volatility. Importantly, these associations are established while considering macroeconomic risk factors and trader characteristics, providing nuanced insights into the factors influencing trader profitability in commodity futures markets.

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