Hedge Fund Strategies Research Articles

Geopolitical risk hedging or timing: Evidence from hedge fund strategies

An increasing number of investors are concerned about how they can diversify risks and profits amid surging geopolitical uncertainties. Using a geopolitical risk timing/hedging model, we investigate whether hedge fund managers can effectively hedge or time geopolitical risks by adopting different trading strategies. We find that excluding those in the global macro category, hedge funds with higher minimum investments and management fees exhibit greater success in hedging geopolitical risks. Meanwhile, global macro hedge funds, which have longer lockup periods, are more adept at timing geopolitical risks by increasing their market exposures. Furthermore, hedge funds which are the top geopolitical risk hedgers and timers demonstrate higher economic value than those in the bottom group over the subsequent one and three months. Our findings provide valuable insights into private investors’ selection of hedge funds during periods of heightened geopolitical risk.

Design of Single Valued Neutrosophic Hypersoft Set VIKOR Method for Hedge Fund Return Prediction

The theory of neutrosophic hypersoft set (NHSS) is an appropriate extension of the neutrosophic soft set to precisely measure the uncertainty, anxiety, and deficiencies in decision-making and is a parameterized family that handles sub-attributes of the parameters. In contrast to recent studies, NHSS could accommodate more uncertainty, which is the essential procedures to describe fuzzy data in the decision-making method. Hedge funds are financial funds, finance institutions that increase funds from stockholders and accomplish them. Usually, they try to make certain predictions and work with the time sequence dataset. A hedge fund is heterogeneous in its investment strategies and invests in a different resource class with various return features. Furthermore, hedge fund strategy is idiosyncratic and proprietary to the hedge fund manager, and the correct skills of fund managers are not visible to the stockholders. These reasons, united, make hedge fund selection a complex task for the stockholders. Different techniques have been analyzed to select the portfolio of hedge funds for investment. Machine-learning (ML) models employed used for performing individual hedge fund selection within hedge fund style classifications and forecasting hedge fund returns. Therefore, this study designs a new Single Valued Neutrosophic Hypersoft Set VIKOR Model for Hedge Fund Return Prediction (SVNHSS-HFRP) technique. The presented SVNHSS-HFRP technique aims to forecast the hedge fund returns proficiently. In the SVNHSS-HFRP technique, two stages of operations are involved. At the initial stage, the SVNHSS-HFRP technique, the SVNHSS is used for forecasting the hedge funds. Next, in the second stage, the moth flame optimization (MFO) system is applied to optimally choose the parameter values of the SVNHSS model. The performance validation of the SVNHSS-HFRP model is verified on a benchmark dataset. The experimental values highlighted that the SVNHSS-HFRP technique reaches better performance than existing techniques

Systematic ESG risk and hedge fund

<abstract> <p>We present a framework for linking hedge funds to environmental, social, and governance (ESG) investments based on systematic ESG risk. We proposed a double-factor model to explain the co-movement of asset returns due to two systematic risk factors: Adjusted market risk and systematic ESG risk. Complementing prior work that introduces ESG characteristic indicators as determinants of agents' utility functions, this framework leverages modern portfolio theory by establishing a channel through which systematic ESG shocks affect asset risk and, in turn, equilibrium expected returns. This approach enabled us to estimate empirical market prices for systematic ESG risk from real-world observations and derive the relationship between equilibrium expected returns and the loadings on systematic risk factors. Applying this framework to U.S. equity mutual funds, we found that the loadings of systematic ESG risk were significantly correlated with the expected return of the sorted portfolios. These results suggested that it is possible to design hedge fund strategies that capitalize on systematic ESG risk that varies over time.</p> </abstract>

Exploring Hedge Fund Strategies in Portfolio Management Using Financial Derivatives and Their Impact on Market Volatility

This paper aims to explore the strategies employed by hedge funds when using financial derivatives for portfolio management and their impact on market volatility. It begins with a discussion of the importance of hedge funds in the investment world, followed by an examination of the strategies they employ, including the use of financial derivatives such as futures, options and swaps. In addition, the influence of these strategies on market volatility is also analyzed. This study provides valuable insights on hedge fund investment strategies and their impact on the market and has important reference value for investors and hedge fund managers. Hedge fund has attracted more and more attention in the investment field. Its unique strategy and high return ability make it highly valued in the investment community. This article takes an in-depth look at the strategies employed by hedge funds when using financial derivatives for portfolio management and explores the impact of these strategies on market volatility.

Evolution and innovation of hedge fund strategies: A systematic Review of literature and framework for future research

Hedge funds are a dynamic and heterogeneous segment of the financial industry that employs various strategies to generate returns and manage risk. Despite their growing importance and impact on the global economy, hedge funds remain largely unregulated and opaque, posing challenges for researchers and regulators alike. This paper provides a systematic review of the academic literature on hedge fund strategies, covering their institutional, historical and performance characteristics; their purpose and effectiveness in achieving balanced portfolios; and the relationship of returns to manager skill, style, size and other factors. The paper also proposes a framework for future research on hedge fund strategies.

The Implementation and Refinement Hedge Fund Strategy in Chinese Commodity Market: MACD Trend Following

This work aims to explore the performance of the MACD Trend Following Strategy within the context of the Chinese market. This paper organizes a universe to study this strategy methodically and applies this traditional hedge fund strategy to the universe. This work gets a generally positive result by running a backtest using historical data. To solve some difficulties, the work includes double Confirmation of MACD and other technical indicators and adjusting the holding period. The strategy has been successful in Chinese futures trading. In addition, additional considerations for the strategy and trading recommendations are discussed. This work enhances the comprehension and application of the strategy.

Research on Different Hedge Fund Strategies

People are always pursuing the minimum risk while seeking for maximum profit when investing, so they often use a variety of different strategies or portfolios to reduce investment risk. Among these, hedge funds are the most common type of portfolio used by fund managers. By using different strategies to buy different stock portfolios, hedge funds can effectively hedge the risk of a single stock or fund, so as to minimize the risk. However, hedge funds contain many different strategies and not all the strategies can process effectively in the market. We must analyze the market and pick up the most suitable strategy. In this case, this article will discuss the effect of their actual operation in the market based on these strategies. The article will analyze five different hedge fund strategies, including three trades that are relatively successful and two trades which are relatively not so successful. Then the article will deeply analyze the reason why the strategy can fit the market or why did it fail the market. During the analysis, some strategies are suitable for the market while the other are not.

Challenging Hedge Funds by Mimicking Their Strategies

Since the launching of the first hedge fund, its ability to have a greater return with less volatility has attracted more and more people to get involved in this investment tool. Numbers of people either invest in hedge funds, or simply simulate the hedge fund strategy in order to obtain a higher return. This paper studies whether people can beat hedge funds by simply mimicking hedge funds strategies. The results are shown by comparing data from Goldman Sachs Hedge Industry VIP ETF, which stands for GVIP, and the long-short hedge fund index from November 2016 to July 2022. According to yahoo finance, GVIP seeks to invest 80% of its assets in its underlying index, depositary receipts representing securities included in its underlying index, and in underlying stocks in turns of depositary receipts included in its underlying index. First of all, the statistical return of GVIP and the long-short hedge fund index are analyzed in terms of their mean, standard deviation, and sharpe ratio. The number of months that GVIP outperforms hedge funds, and the maximum return gap are also concluded by using cross-sectional comparison. Secondly, some regressions are applied to obtain the preliminary conclusions of this paper. Thirdly, the FamaFrench five-factor model is applied to improve the accuracy of the model, so as to further analyze and verify the previous conclusions. Based on the statistical analysis, we can conclude that investors cannot beat hedge funds by mimicking their strategies.

Practical Applications of Hedge Fund Networks

In <b><i>Hedge Fund Networks</i></b>, from the Fall 2022 issue of <b><i>The Journal of Alternative Investments</i></b>, <b>Gueorgui Konstantinov</b> of <b>LBBW Asset and Wealth Management</b> explains the benefits of using network analysis to understand interactions among hedge funds, and particularly the transmission of risk. Networks based on graph theory can illustrate the interconnectedness of hedge fund strategies and visually display how risk can be concentrated and transmitted across funds. Some techniques include identifying cluster affiliations, computing centrality scores, graphing directed networks and correlation networks, distinguishing between hubs and authorities, and exploring alternative network models. Konstantinov shows how to develop a Hedge Fund Index of Centrality (HIC) and explores drivers of risk with factor analysis.

Hedge funds trading strategies and leverage

We introduce learning into the hedge fund managers’ risk choice problem with imperfect information. We find that with a constant but unobserved expected return on investment, learning induces managers to take more risks and increases manager compensation. When the return is stochastic, learning increases manager compensation and induces an aggressive leverage choice when funds perform poorly or managers’ belief about fund returns is low. When funds are close to the high-water mark or the return belief is high, the learning effect reverses. This situation generates a flatter leverage ratio, which helps explain the cross-sectional dispersion of hedge fund strategies’ market betas. Finally, comparative statistics for transition intensity show that procyclicality in the hedge fund industry declines.

Global Macro and Managed Futures Hedge Fund Strategies: Portfolio Differentiators?

Global Macro and Managed Futures Hedge Fund Strategies: Portfolio Differentiators?

Dissecting hedge funds' strategies

This paper dissects the dynamics of the hedge fund industry with four financial markets, including the equity market, commodities, currencies, and debt market by employing a large number of assets from these markets. We employ four main representative hedge fund strategy indices, and a cap-weighted global index to estimate an asymmetric dynamic conditional correlation (ADCC) GJR-GARCH model using daily data from April 2003 to May 2021. We break down the performance, riskiness, investing style, volatility, dynamic correlations, and shock transmissions of each hedge fund strategy thoroughly. Further, the impact of commodity futures basis on hedge funds' return is analyzed. Comparing the dynamic correlations during the 2008 global financial crisis (GFC) with COVID-19 pandemic reveals changing patterns in hedge funds' investing styles. There are strong and pervasive shock spillovers from hedge fund industry to other financial markets, especially to futures commodities. An increase in the futures basis of several commodities drives up hedge funds' performance. While hedge fund industry underperforms compared to equity market and commodities, the risk-reward measures show that hedge funds are superior to other markets, and safer than the bond market.

Practical Applications of Hedge Funds: Resolving Myths about ESG Integration

While environment, social, and governance (ESG) integration is widely accepted, hedge fund managers have integrated ESG factors into their investment process more slowly than other asset managers. Several myths and fallacies undermine hedge funds’ ESG conviction. In <b><i>Hedge Funds: Resolving Myths about ESG Integration</i></b>, from the Fall 2022 issue of <b><i>The Journal of Alternative Investments,</i> Dulari Pancholi</b> of <b>NEPC</b> discusses the myths and fallacies that undermine hedge funds’ ESG conviction and embraces a view of ESG investing that serves to debunk the myths. She seeks to encourage wider acceptance of ESG considerations in the process of managing hedge fund investments. She explains how including ESG factors in hedge fund strategies can positively impact the funds and their clients. A hedge fund manager may be able to increase the fund’s future risk-adjusted return, without necessarily giving the portfolio a social slant, by taking ESG factors into account early in the original underwriting process. Senior leadership must actively support firm-wide adoption while being strategic with the use of time and resources.

Hedge Fund Strategies Performance in Bad Market Condition Analysis

In this article, the performance of hedge fund strategies is measured and analyzed by the following aspects: potential risk of the strategies excepted return of selected hedge fund and the sample performance in pressured stock market conditions. The study will provide theoretical explanations of the efficacy of Merger Arbitrage, Mutual Fund strategies, and PE ratio-related hedge fund strategies and their profitability as well as risk tolerance. Throughout equity data collection, asset markets including the S&amp;P and NASDAQ have experienced downward pressure on systemic risk caused by inflation combined with quantitative tightening. These Macro factors have significantly contributed to the effectiveness of hedge portfolios; therefore, the article will focus on the performance of hedge fund strategies in the current market and analyze the efficiency of the strategies. According to the real-time hedge strategy trading data obtained from May/21st/2022 to July/01/2022, the Market Mutual strategy, as well as the Merger arbitrage, displayed the risk-averse characteristics of the hedging strategy during the underperforming period. On the other hand, P/E-based trades took on more systematic risk, which generated additional losses than expected.

Political risk, hedge fund strategies, and returns: Evidence from G7 countries

In this study, we examine the effects of political risk across a group of seven industrialised countries (G7) on hedge fund returns and further explore whether the effects of political risk on hedge fund returns vary according to hedge fund strategies employed by fund managers. Employing factor analysis to quantify political risk across the G7 countries, our results evince two interesting aspects. First, we find political risk to exert a negative and significant impact on hedge fund returns, suggesting that hedge fund performance tends to decrease as political risks across G7 nations increase. Second, the effects of political risk on hedge fund returns appear to vary with different hedge fund strategies employed by fund managers. Our results appear robust after employing three different analytical approaches and controlling a set of factors previously identified to affect hedge fund returns.

Hedge Funds: Resolving Myths about ESG Integration

Despite the widespread acceptance of the ESG concept, its adoption by the hedge fund industry has been relatively slower than in other asset classes. A series of misconceptions and myths seems to hinder the conviction level in the hedge fund universe. This article examines the top misconceptions about ESG integration and hopefully clears a path for increased adoption in the hedge fund investment management process. It argues that ESG integration can be adopted in all hedge fund strategies and provides meaningful benefits to both hedge funds and their clients. By incorporating ESG considerations early in the initial underwriting process, a hedge fund manager can potentially improve the future risk-adjusted return for the fund without necessarily creating a social tilt in the portfolio. Importantly, senior leadership should champion its firm-wide adoption by being intentionally strategic about the time commitment and resource allocation.

Corporate control and shareholder activism in Germany: An empirical analysis of hedge fund strategies

Government-initiated reforms of the German financial system two decades ago shifted corporate control activities from universal banks to capital markets. Hedge funds took advantage of these changes by acquiring stakes in weakly governed firms. For 653 hedge fund interventions between 2000 and 2020, this study analyzes the changes in financial and operating performance and firm characteristics before and after the event. We also assess the probabilities that a firm becomes a target and that an attack creates shareholders value. On average, hedge funds increased returns, with the magnitude depending on the period, level of aggressiveness, institutional ownership, and industry. Crisis and non-crisis results differ, as hedge funds strategies are mostly successful in a rising stock market environment. Typically, hedge funds targeted smaller and more visible firms with higher sales growth, lower leverage, and higher institutional ownership. After the attack, firm profitability and cash holdings decreased, leverage increased, while investments in M&A and capex declined. This research offers new empirical evidence on the success of hedge fund strategies in Germany and on the performance of targeted firms.

Hedge Fund Networks

Network theory helps to resolve allocation problems and issues of systematic risk propagation in hedge fund networks because it allows for the hedge funds to be shown as interacting entities. Importance scores and cluster analysis support the understanding of risk propagation and causality, and capture the time-varying interconnectedness among hedge fund strategies. Furthermore, considering cluster affiliation, network metrics derived from importance scores help separate active management from active risk monitoring and build diversified portfolios. Hedge fund indexes with large centrality scores are less meaningful as risk indicators because the importance scores are time-varying. Hedge fund indexes with low centrality scores are weakly connected, but their diversification and return enhancement advantages are time-varying. Correlation networks use asset prices, are the most widely used graphs, and are easy to implement. However, the difference between directed and correlation networks is one of the most important factors because there is a direction in risk flow.

Can Investors Benefit from Hedge Fund Strategies? Utility-Based, Out-of-Sample Evidence

We report systematic, out-of-sample evidence on the benefits to an already well-diversified investor that may derive from further diversification into various hedge fund strategies. We investigate dynamic strategic asset allocation decisions that take into account investors’ preferences, realistic transaction costs, return predictability, and the parameter uncertainty that such predictability implies. Our results suggest that not all hedge fund strategies benefit a long-term investor who is already well-diversified across stocks, government and corporate bonds, and REITs. However, when parameter uncertainty is accounted for, the best performing models offer net positive economic gains to investors with low and moderate risk aversion. Most of the realized economic value fails to result from mean-variance-type enhancements in realized performance but comes instead from an improvement in realized higher-moment properties of optimal portfolios.

HEDGE FUND STRATEGIES: PERFORMANCE, RISK AND DIVERSIFICATION OPPORTUNITIES / Hedge Fon Stratejileri: Performans, Risk Ve Çeşitlendirme Fırsatları

This study aimed at comparing the performances of distinct hedge fund strategies and assessing the diversification opportunities using hedge funds. This paper analyses the overall performance of distinct hedge fund strategies (as indices) for the period of 2001-2020. Hedge fund performances are compared using alternative risk adjusted performance metrics; first, alpha based on four asset-pricing models (CAPM, Fama-French 3 factor, Carhart and Fama-French 5 factor models); then, the Sharpe ratio. The findings of the study revealed that almost all hedge fund strategies outperform the benchmark return (MSCI World Index) and are superior in terms of risk/return measures. The alternative risk metrics used in the calculation of risk-adjusted performances did not cause a dramatic change in the rank ordering of the hedge fund strategies.