Man versus machine: on artificial intelligence and hedge funds performance

Grobys, Klaus; Kolari, James W.; Niang, Joachim

doi:10.1080/00036846.2022.2032585

Cited by 8 publications

(1 citation statement)

References 37 publications

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“…A remarkable illustration of this is the paper "Man versus machine: on artificial intelligence and hedge funds performance", 2022, by Grobys et al [21], where the authors compare hedge funds' returns based on the level of automation and technology use and conclude that there is a strong correlation between lower levels of human involvement and higher returns.…”

Section: Discussionmentioning

confidence: 99%

Hedge performance of different asset classes in varying economic conditions

Mats

2024

reks

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In the realm of long-term investment, strategic portfolio allocation is an essential tool, especially in relation to risk management and return optimisation. There are many ways to pursue optimal portfolio composition, and their effectiveness depends on many factors, including the investor’s goals, risk appetite, and investment horizon. One of the primary means of portfolio optimisation is diversification. The core idea of diversification is to maintain a diverse portfolio with weakly correlated assets that can vastly reduce portfolio exposure to different market stress factors. Diversification is a fundamental strategy in investment and portfolio management that is essential for mitigating risk and enhancing potential returns over the long term. By spreading investments across various asset classes, sectors, geographies, and investment styles, diversification helps reduce the volatility of the overall portfolio. The main subject of this study is the theoretical basis of portfolio diversification and the analysis of historical data to derive optimal strategies for using uncorrelated assets to improve portfolio performance. This paper examines the correlation dynamics between different asset classes, such as stocks, bonds, and alternative investments, and their response to changes in inflation, interest rates, and market volatility, and tests it with historical data to deduce the optimal strategies for using uncorrelated assets to improve portfolio performance. The findings of this study prove the variable relationship between asset classes under specific economic conditions. This study uses historical data to show how different asset classes can be optimally leveraged or adjusted to mitigate risks and capitalise on opportunities presented by shifting economic indicators. This reveals that the hedging benefits of equities, bonds, and gold depend greatly on interest rates, market volatility, and inflation. It also provides guidelines for investors on optimal portfolio allocation and risk management. In conclusion, dynamic portfolio management is an essential tool for reducing the portfolio’s overall volatility while maximising returns. The diversification performance of different financial asset classes depends on major economic indicators such as inflation, interest rates, and market volatility. Investors seeking to optimise their portfolios in anticipation of or in response to economic changes, aiming to maximise returns while controlling for risk, can leverage these results.

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Section: Discussionmentioning

confidence: 99%