The hedging effectiveness of constant and time-varying hedge ratios using three Pacific Basin stock futures

This paper investigates the hedging effectiveness of Australian, Hong Kong, and Japanese stock futures markets. The traditional hedge and the minimum variance hedge ratios are all constant whereas the bivariate GARCH hedge ratio is time varying. The effectiveness of the hedge ratio is compared by investigating the out-of-sample performance of the three ratios. The whole sample consists of weekly returns from January 1990 to December 2000. Two 1-year, out-of-sample periods are used: January 1999 to December 1999 and January 2000 to December 2000. Results show that the time-varying GARCH hedge ratio outperforms the constant ratios in most of the cases. This is true using both out-of-sample periods.     

VaR模型在套期保值比率计算中的实证分析

提出了考虑套期保值期内不同期限价格风险的最小平均VaR套期保值比率计算模型。基于我国外汇市场及股票市场数据,用最小平均VaR套期保值模型进行了实证分析,并同常用的最小方差及最小VaR套期保值模型进行了对比,得出了最小平均VaR模型在套期保值过程中的效果要优于其他两种模型,并能更有效地降低投资者提前终止套期保值可能面临额外风险的结论。     

Simultaneously determined,time-varying hedge ratios in the soybean complex

Time-varying hedge ratios are derived which account for the dynamic characteristics of prices in the soybean complex. A multivariate generalized autogressive heteroskedastic (MGARCH) model, along with other conditional models, is used to specify the relevant covariance matrix. While the time-varying representations of the variance matrix are statistically appropriateex anteand ex posthedging effectiveness indicate that they provide minimal gain to hedging in terms of mean return and reduction in variance over a constant conditional procedure. Whether similar findings arise from other applications of GARCH models to optimal hedging is a question for further research.     

Estimating the optimal hedge ratio in the presence of potential unknown structural breaks

We propose a new approach in the estimation of the optimal hedge ratio that allows the hedge ratio to vary over time but without the necessity of frequently rebalancing the portfolio. We apply this in the context of the US and UK equity markets using weekly spot share prices and future share prices during the period 5 January 1999 to 29 September 2009. Our method is to test for cointegration in the presence of two potentially unknown structural breaks by determining the timing of each via the underlying data. The empirical findings reveal that the spot and future prices are strongly cointegrated in each market. The estimated parameters disclose that the optimal hedge ratio is not constant in case of the US and the UK. We find one negative and one positive shift in the optimal hedge ratio in the US. However, we find only one significant and positive shift in the optimal hedge ratio in the UK. The implication of these findings from the perspective of both investors as well as policy-makers is elaborated on in the main text.     

Optimal hedge ratio under a subjective re-weighting of the original measure

In this article we study a risk-minimizing hedge ratio with futures contracts, where the risk of the hedged portfolio is measured through a spectral risk measure (SRM), thus incorporating the degree of agent’s risk aversion. We empirically estimate the optimal hedge ratio (OHR) using a long time series of UK and US equity indices, the EURUSD and EURGBP exchange rates and four liquid commodities (Brent crude oil, corn, gold and copper), to represent different asset classes. Comparing the results with common OHRs (such as the minimum variance and the minimum expected shortfall), we find that the agent’s risk aversion has a material impact, and should not be ignored in risk management.     

Pension funds' allocations to hedge funds: an empirical analysis of US and Canadian defined benefit plans

This article investigates the characteristics of US and Canadian pension funds that allocate assets to hedge funds. The typical pension fund that invests in hedge funds is a large sophisticated pension fund that diversifies its portfolio across numerous classes of investments, private equity in particular, uses a core-satellite organization and has access to low delegation costs for alternative assets. Moreover, we find that pension funds investing in hedge funds significantly obtained higher global returns.     

股指期货在风险管理中的应用

股指期货属于金融期货的一种,是以股票市场的股票价格指数为标的物的期货合约.在很多发达的股票市场乃至资本市场中,股指期货扮演着规避风险、套期保值的重要角色.在利用股指期货对股票组合进行套期保值时,可能面临各种风险,其中,基差风险是套期保值者面临的最主要风险.利用向量误差修正模型可以估计最小风险套期保值比,为投资者综合选择风险最小的套期保值策略提供了现实的、可操作的定量分析工具.     

Hedging effectiveness comparisons: A note

This note examines the hedging effectiveness of three hedge strategies on twenty-four commodity and financial markets. Lien (Lien, D., 2005a, The use and abuse of the hedging effectiveness measure, International Review of Financial Analysis 14, 277–282, Lien, D., 2005b, A note on the superiority of the OLS hedge ratio, Journal of Futures Markets 25, 1121–1126.) suggest that, absent from estimation errors, the minimum variance (MV) hedge ratio attains the maximum post-sample hedging effectiveness when there is no structural change across estimation and comparison samples. When comparing the MV strategy with the naïve hedge ratio, we find sufficiently strong support for the conclusion. On the other hand, driven by estimation errors, weaker support is produced when comparing MV and error correction (EC) hedge strategy.     

最小平均VaR套期保值比率计算模型及实证研究

针对传统的套期保值模型只考虑最小化套期保值组合在到期日的价格风险,而且没有充分利用资产历史价格样本数据所提供的收益率信息的特点,本文提出了考虑套期保值期内不同期限价格风险的最小平均VaR套期保值比率计算模型。基于我国外汇市场及股票市场数据,本文对最小平均VaR套期保值模型进行了实证分析,并与常用的最小方差及最小VaR套期保值模型进行了对比,得出了最小平均VaR模型在套期保值过程中的效果要优于其他两种模型,能更有效地降低投资者提前终止套期保值可能面临额外风险的结论。     

Value of hedge and expected returns

We demonstrate how it is possible to generate value for an investor with a hedge attached to the buy-and-hold strategy of an S&P 500 index fund. We study the S&P 500 index portfolio (not including dividends) and the value-weighted S&P 500 index portfolio (including dividends) of the Center for Research in Securities Prices for 1967:01–2011:12, using the capacity utilization and the unemployment rates in real time to determine if a hedge position should be initiated or closed. A hedge is initiated if the capacity utilization, the unemployment rate or a combination of the two signals a contraction in the real economy. The hedge position is closed if it signals otherwise an expansion. We use utility gains (Campbell and Thompson 2008), the manipulation-proof performance measure (MPPM) statistics (Ingersoll et al. 2007) and the P-Sharpe ratio (Bailey and López de Prado 2012) to evaluate the performance of a particular hedge strategy. The empirical results show that there are infinitely many hedges that can generate positive utility gains, higher MPPM statistics and higher P-Sharpe ratios.     

The effectiveness of index futures hedging in emerging markets during the crisis period of 2008-2010: Evidence from South Africa

This article provides an assessment of the comparative effectiveness of four econometric methods in estimating the optimal hedge ratio in an emerging equity market, particularly the South African equity and futures markets. The article bases the effectiveness of hedging on volatility reduction and minimization of the coefficient of variation of hedged returns as well as risk-aversion-based utility maximization. The empirical analysis shows that the vector error-correction method and multivariate generalized autoregressive conditional heteroscedasticity methods are most effective over relatively long horizon, weekly and monthly hedging periods.     

A note on the hedging effectiveness of GARCH models

This note compares the hedging effectiveness of the conventional hedge ratio and time-varying conditional hedge ratios (of which GARCH ratio is a special case). It is shown that, in large sample cases, the conventional hedge ratio provides the best performance. For small sample cases, a sufficiently large variation in the conditional variance of the futures return is required to produce the opposite result. The result is due to the fact that the hedging effectiveness measure is based upon the unconditional variance; meanwhile, the conventional hedge ratio minimizes the unconditional variance and the conditional hedge ratio aims at minimizing the conditional variance.     

Is gold a hedge and safe haven for stock market?

The paper aims to examine the hedge and safe haven properties of gold relative to Dow Jones stock industry indices using quantile-GARCH approach. Splitting the sample period into two sub-periods, our results show that the hedge and safe haven properties of gold have a changing nature. In a whole period (1980–2017), gold is not a hedge for Oil&Gas, Basic materials and Utilities; gold is a safe haven for almost all sectors except Technology. While in sub-period I (1980–1995) gold is not a hedge for Oil&Gas but a strong safe haven for all sectors. In sub-period II (1996–2017) gold is not a hedge for Oil&Gas, Basic materials and Utilities, also not a safe haven for Oil&Gas, Basic materials, Utilities, Telecom and Technology.     

Cumulant instrument estimators for hedge fund return models with errors in variables

We revisit the factors incorporated in asset pricing models following the recent developments in financial markets – i.e., the rise of shadow banking and the change in the transmission channel of monetary policy. We propose two versions of the Fung and Hsieh (2004) hedge fund return model, especially an augmented market model which accounts for the new dynamics of financial markets and the procyclicality of hedge fund returns. We run these models with an innovative Hausman procedure, tackling the measurement errors embedded in the models factor loadings. Our empirical method also allows for confronting the drawbacks of the instruments used to estimate hedge fund asset pricing models.     

Modeling hedge fund exposure to risk factors

This paper examines the adjustment dynamics of hedge fund returns and studies their exposure to risk factors in a nonlinear framework for several types of strategies over the last two decades. Nonlinearity is justified by distortions due to the use of short selling, leverage, derivatives and illiquid assets for hedge fund strategies. Among nonlinear models, switching regime (STR) models are applied to reproduce the dynamics of hedge fund returns. This nonlinear multivariate modeling has the advantage of capturing the time-varying exposure of hedge fund strategies to risk factors, and of specifying the asymmetric relationship between hedge fund returns and risk. The findings are interesting and provide several contributions to the hedge fund literature. First, we show that the dynamics of hedge fund returns exhibit significant asymmetry and nonlinearity, indicating that they evolve and vary asymmetrically in accordance with stages in financial cycles. Second, hedge fund exposure to risk factors also varies over time, depending on the strategy and the regime. Finally, our modeling captures the most important changes in hedge fund exposure to risk factors induced by the recent global financial crisis (2008–2009).     

Equity market neutral hedge funds and the stock market: an application of score-driven copula models

In this article, we study the time-varying market neutrality of equity market neutral hedge funds. We use data from the Hedge Fund Research? Equity Market Neutral Index (HFRX EH), which represents the performance of a portfolio of individual equity market neutral hedge funds. For each day, we measure different levels of association of the Standard and Poor’s 500 (S&;P 500) index and the HFRX EH. We use non-linear dynamic conditional score models of location, scale and copula that, to the best of our knowledge, have not yet been applied in the body of literature on hedge funds. We study whether the neutrality of the HFRX EH that is evidenced in the body of literature for the period of April 1993–April 2003 also holds for the following decade, for the period of May 2003–December 2016. We estimate different average levels of association for the pre-, during- and post-periods of the US financial crisis of 2008. We find that the association of the S&;P 500 and the HFRX EH, on average, is significantly positive for the pre- and post-periods of the financial crisis, and it is significantly negative for the period during the financial crisis.     

Market volatility and the dynamic hedging of multi-commodity price risk

Commodity cash and futures prices experienced a severe boom-and-bust cycle between 2006 and 2009. Increases in commodity price volatility have raised concerns about the usefulness of commodity futures and options as risk management tools. Dynamic hedging strategies have the potential to improve risk management when conditional (co)variances depart significantly from their unconditional, long-run counterparts and may be useful to decision-makers despite their greater complexity and higher transaction costs. We propose a Nonparametric Copula-based Generalized Autoregressive Conditional Heteroscedastic (NPC-GARCH) approach to estimate time-varying hedge ratios, and evaluate the benefits of dynamic hedging during four sub-periods between 2000 and 2011 using a stylized Texas cattle feedlot management problem. The NPC-GARCH approach allows for a flexible, nonlinear and asymmetric dependence structure between cash and futures prices for different commodities. We find that NPC-GARCH dynamic hedging performs better than either static, GARCH-Dynamic Conditional Correlation (DCC) or GARCH-Baba, Engle, Kraft and Kroner (BEKK) hedging in terms of lower tail risk (expected shortfall), but that there is no significant difference between hedging approaches in terms of portfolio variance reduction.     

Is the cryptocurrency market a hedge against stock market risk? A Wavelet and GARCH approach

This study analyses six major cryptocurrencies and four global stock markets to explore the role of cryptocurrencies as a hedge, safe haven, and diversifier in stock markets. The study employs ADCC-GARCH and Wavelet Coherence Technique, using daily data from 4 January 2017 to 28 February 2023. The study has found that stock returns and unstable cryptocurrency returns have high volatility persistence in the long run. Besides, while unstable digital currencies (Bitcoin, Ethereum, Binance Coin, and Dogecoin) serve as a hedge during stable economic periods, they have not been a hedge during economic turmoil in the stock markets. Conversely, stablecoins (Tether and USD Coin) have been shown to have acted as a hedge during normal economic times and have offered a safe haven during economic downturns. Except for Tether, all cryptocurrencies' diversification capacity is time-varying. In stable economic conditions, they serve as diversifiers, but during turmoil, they do not. However, Tether serves as a diversifier regardless of the financial situation. Finally, the present investigation is expected to offer crucial information on hedge, safe haven and diversification for quasi-investors.     

Managing price risks using and local polynomial kernel forecasts

This study contributes to understanding price risk management through hedging strategies in a forecasting context. A relatively new forecasting method, nonparametric local polynomial kernel (LPK), is used to forecast prices and to generate ex ante hedge ratios. The selective multiproduct hedge based on the LPK price and hedge ratio forecasts is in general found to be better than continuous hedging, no hedging and alternative forecasting procedures. Selective multivariate hedging using the LPK is found to improve hog producer's expected returns. The findings indicate that combining hedging with forecasts, especially when using the LPK procedure, can improve price risk management.     

Dynamic hedge ratio for stock index futures: application of threshold VECM

This study represents one of the first papers in stock-index-futures arbitrage literature to investigate the effects of arbitrage threshold on stock index futures hedging effectiveness by using threshold vector error correction model (hereafter threshold VECM). Moreover, in contrast to prior studies focusing on examining case studies involving mature stock markets, this study not only adopts US S&P 500 stock market as the sample but also adds an analysis of one emerging stock market, Hungarian BSI and examines the differences between them. Finally, this investigation employs a rolling estimation process to examine the impact of arbitrage threshold behaviours on the setting of futures hedging ratio. The empirical findings of this study are consistent with the following notions. First, arbitrage behaviour reduces co-movement between futures and spot markets and increases the volatility of both futures and spot markets. Second, this article denotes the outer regime of futures-spot market for the case of Hungarian BSI (US S&P 500) as a crisis (an unusual) condition. Moreover, arbitrage threshold behaviours make remarkable (unremarkable) shift on optimal hedge ratio between two different market regimes for the case of Hungarian BSI (US S&P 500). Finally, the framework involving regime-varying hedge ratio designed in this study provides a more efficient futures hedge ratio design for Hungarian BSI stock market, but not for US S&P 500 stock market.