Hedging Performance Research Articles

Futures hedging in crude oil markets: A comparison between minimum-variance and minimum-risk frameworks

Most of existing studies on crude oil futures hedging aim to minimizing the variance of hedged portfolio. In this paper, we evaluate the hedging performance in a different framework of minimum-risk and try to find the optimal hedge model. We employ a total of ten popular econometric specifications including three constant and seven dynamic hedge ratio models. Our results suggest that none of the models of interest can outperform all competitors in or out of sample for all futures contracts. The constant hedge ratio models perform better than the dynamic hedge ratio models under the min-V framework, but the situation overturns under the min-R framework with the DCC-GARCH performs best. More importantly, the equal-weighted combination of all constant and dynamic hedge ratios results in better out-of-sample performance than the combination of either type of hedge ratios only.

Crude oil price shocks and hedging performance: A comparison of volatility models

From a practical perspective, it is crucial to hedge the crude oil price risk in periods of dramatic price change. In this study, we directly investigate the performance of crude oil hedge portfolios in the five periods in which the largest oil price shocks in history occurred. We use stochastic volatility (SV), GARCH, and the diagonal BEKK model to estimate the minimum variance hedge ratio of hedge portfolios. Our empirical results provide evidence that hedging strategies based on the SV model are able to outperform the GARCH and BEKK models in terms of variance reduction. Our results are also consistently valid for various hedge horizons. Interestingly, although it is important to estimate variance and covariance accurately when constructing minimum variance portfolios, we find that reducing the mean squared and mean absolute errors does not guarantee superior hedge performance.

Carry Cost Rate Regimes and Futures Hedge Ratio Variation

This paper tests whether the traditional futures hedge ratio (hT) and the carry cost rate futures hedge ratio (hc) vary in accordance with the Sercu and Wu (2000) and Leistikow et al. (2019) “hc” theory. It does so, both within and across high and low spot asset carry cost rate (c) regimes. The high and low c regimes are specified by asset across time and across currency denominations. The findings are consistent with the theory. Within and across c regimes, hT is inefficient and hc is biased. Across c regimes, hc’s Bias Adjustment Multiplier (BAM) does not vary significantly. Even though hc’s bias-adjusted variant’s BAM is restricted to old data that is from a different c regime, the hedging performance of hc and its bias-adjusted variant (=hc × BAM), are superior to that for hT. Variation in c may account for the hT variation noted in the literature and variation in c should be incorporated into ex ante hedge ratios.

Optimal Hedge Ratio and Hedging Effectiveness in Stock Futures Market: Evidence from National Stock Exchange, India

The major objective of the study is to examine the performance of optimal hedge ratio and hedging effectiveness in stock futures market in National Stock Exchange, India by estimating the following econometric models like Ordinary Least Square (OLS), Vector Error Correction Model (VECM) and time varying Multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) model by evaluating in sample observation and out of sample observations for the period spanning from 1st January 2011 till 31st March 2018 by accommodating sixteen stock futures retrieved through www.nseindia.com by considering banking sector of Indian economy. The findings of the study indicate both the in sample and out of sample hedging performances suggest the various strategies obtained through the time varying optimal hedge ratio, which minimizes the conditional variance performs better than the employed alterative models for most of the underlying stock futures contracts in select banking sectors in India. Moreover, the study also envisage about the model selection criteria is most important for appropriate hedge ratio through risk averse investors. Finally, the research work is also in line with the previous attempts Myers (1991), Baillie and Myers (1991) and Park and Switzer (1995a, 1995b) made in the US markets

Asymptotic expansion method for pricing and hedging American options with two-factor stochastic volatilities and stochastic interest rate

ABSTRACTWe consider the pricing and hedging of American put options under the double Heston model with CIR stochastic interest rate. With an explicit exercise rule American option is approximated by barrier option for which the solution to the partial differential equation is derived by a short-maturity asymptotic expansion. Combining with control variate technique by Fourier-cosine expansion we analytically derive American puts prices and hedging parameters. We also construct a Delta-Vega-Rho hedging strategy of the proposed model for American puts and implement it by Monte Carlo simulation. Numerical results show that the presented pricing method is fast and accurate, the hedging performance of the proposed model is better than that of the BS, Heston and double Heston model.

3년 국채선물의 일중 시간별 헤지성과 및 가격발견 연구

3년 국채선물의 일중 시간별 헤지성과 및 가격발견 연구

PORTFOLIO SELECTION BETWEEN A MATURE MARKET AND SELECTED EMERGING MARKETS INDICES IN THE PRESENCE OF STRUCTURAL BREAKS

ABSTRACTThe paper examines the influence of the structural breaks on the optimal weights, hedge ratios and hedge effectiveness index (HEI) of risk‐minimizing portfolios composed of S&P500 and selected emerging markets’ indices from East Europe, Asia and South America. We employ a bivariate DCC‐EGARCH models without and with structural breaks and we find better estimation features when structural breaks are included in the model. However, we do not find evidence that insertion of structural breaks increases portfolio hedging performances. The differences that exist between optimal weights, hedge ratios and HEI values are so small that tangible economic benefit for international investors do not exist.

Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?

We assess whether the long-run volatilities of Bitcoin, global equities, commodities, and bonds are affected by global economic policy uncertainty. Empirical results provide evidence supporting this hypothesis, except in the case of bonds. For Bitcoin investors, the results imply the ability to use information about the state of global economic uncertainty to enhance the predictions of Bitcoin volatility. We further examine whether the correlation between Bitcoin and global equities, commodities, and bonds are affected by global economic policy uncertainty. Empirical results reveal that global economic policy uncertainty has a negative significant impact on the Bitcoin-bonds correlation and a positive impact on both Bitcoin-equities and Bitcoin-commodities correlations, suggesting the possibility of Bitcoin acting as a hedge under specific economic uncertainty conditions. Interestingly, the hedging effectiveness of Bitcoin for both global equities and global bonds enhances slightly after considering the level of global economic policy uncertainty. Such a weak effect of the state of global economic uncertainty on the hedging ability of Bitcoin implies that investors cannot substantially enhance the hedging performance of Bitcoin under different economic uncertainty conditions.

Minimum-Variance Hedging Oil Price Risk for US Energy ETF Investors: Out-of-Sample Investigation

Oil price experienced crashes during the period of the 2008 global financial crisis and the recent period of oil price crisis in 2014. Hedging oil price risk becomes more important for energy industry investors. In this paper, we investigate the out-of-sample dynamic hedging performance by using the oil futures based on 11 methods for estimating the minimum-variance optimal hedge ratio for 5 US energy ETFs. Except variance, we also study the difference in average returns and utilities between the unhedged strategy and the hedged strategy by employing statistical tests. Finally, we study explore the performance of the hedged strategy in terms of cumulative return and variance under different oil market regimes.

Nested Stochastic Valuation of Large Variable Annuity Portfolios: Monte Carlo Simulation and Synthetic Datasets

Dynamic hedging has been adopted by many insurance companies to mitigate the financial risks associated with variable annuity guarantees. To simulate the performance of dynamic hedging for variable annuity products, insurance companies rely on nested stochastic projections, which is highly computationally intensive and often prohibitive for large variable annuity portfolios. Metamodeling techniques have recently been proposed to address the computational issues. However, it is difficult for researchers to obtain real datasets from insurance companies to test metamodeling techniques and publish the results in academic journals. In this paper, we create synthetic datasets that can be used for the purpose of addressing the computational issues associated with the nested stochastic valuation of large variable annuity portfolios. The runtime used to create these synthetic datasets would be about three years if a single CPU were used. These datasets are readily available to researchers and practitioners so that they can focus on testing metamodeling techniques.

Dynamic hedging using the realized minimum-variance hedge ratio approach – Examination of the CSI 300 index futures

This paper investigates the dynamic hedging performance of the high frequency data based realized minimum-variance hedge ratio (RMVHR) approach. We comprehensively examine a number of popular time-series models to forecast the RMVHR for the CSI 300 index futures, and evaluate the out-of-sample dynamic hedging performance in comparison to the conventional hedging models using daily prices, as well as the vector heterogeneous autoregressive model using intraday prices. Our results show that the dynamic hedging performance of the RMVHR-based methods significantly dominates that of the conventional methods in terms of both hedging effectiveness and tracking error volatility in the out-of-sample forecast period. Furthermore, the superiority of the RMVHR-based methods is robust in different market structures and different volatility regimes, including China's abnormal market fluctuations in 2015 and the US financial crisis in 2008.

The Study on the Hedge Performance of VKOSPI Futures

The Study on the Hedge Performance of VKOSPI Futures

Risk-sharing finance governance: Islamic vs conventional indexes option pricing

PurposeRisk governance has an important influence on the hedging performances in option pricing and portfolio hedging in both discrete and dynamic case for both conventional and Islamic indexes. The paper aims to discuss these issues.Design/methodology/approachThis paper explores option pricing and portfolio hedging in a discrete and dynamic case with transaction costs. Monte Carlo simulations are applied to both conventional and Islamic indexes in US and UK markets. Simulations show that conventional and Islamic assets do not exhibit the same price and portfolio hedging strategy governance.FindingsThe authors conclude that Islamic assets show different option price and hedging strategy compared to their conventional counterpart.Originality/valueThe research question of this paper aims at filling the gap in the empirical literature by exploring option price and hedging structure for both conventional and Islamic indexes in US and UK stock markets.

SPATIAL DEPENDENCE AND AGGREGATION IN WEATHER RISK HEDGING: A LÉVY SUBORDINATED HIERARCHICAL ARCHIMEDEAN COPULAS (LSHAC) APPROACH

AbstractAdverse weather-related risk is a main source of crop production loss and a big concern for agricultural insurers and reinsurers. In response, weather risk hedging may be valuable, however, due to basis risk it has been largely unsuccessful to date. This research proposes the Lévy subordinated hierarchical Archimedean copula model in modelling the spatial dependence of weather risk to reduce basis risk. The analysis shows that the Lévy subordinated hierarchical Archimedean copula model can improve the hedging performance through more accurate modelling of the dependence structure of weather risks and is more efficient in hedging extreme downside weather risk, compared to the benchmark copula models. Further, the results reveal that more effective hedging may be achieved as the spatial aggregation level increases. This research demonstrates that hedging weather risk is an important risk management method, and the approach outlined in this paper may be useful to insurers and reinsurers in the case of agriculture, as well as for other related risks in the property and casualty sector.

Coherence, connectedness and dynamic hedging effectiveness between emerging markets equities and commodity index funds

In this paper, we examine the hedging performance of two emerging markets equities indices represented by Morgan Stanley Capital International (MSCI) - Emerging Market (EM) and MSCI-BRIC (Brazil, Russia, India, and China) with the two globally traded commodities indices viz. Standard & Poor's Goldman Sachs Commodity Index (S&P-GSCI, henceforth GSCI) and Bloomberg Commodity Index (BCOM) and two US-linked financial factors viz. the implied volatility index of S&P 500 index (VIX) and the US bond futures. The study uses the daily data for the period 04 January 2004 to 30 November 2017 and adopts three-step procedure. In the first step, we examine the wavelet coherence among these indices followed by connectedness analysis in the second step. In the third step, we estimate the dynamic conditional correlations models to calculate the time-varying hedge ratios and use the rolling-window approach to estimate one-step-ahead forecast of dynamic conditional volatility. The estimated results suggest the existence of a higher level of dynamic coherence and connectedness between equities and commodities benchmarks, implying that the investors do not care much about the composition of these indices. The extent of comovement is almost same in the case of EM and BRIC. However, both equities indices (EM & BRIC) exhibit a negative correlation with VIX and BOND. The results of connectedness and dynamic conditional correlations capture the major turning points. The optimal hedge ratios suggest that the VIX is the most desirable asset for hedging choices followed by BCOM and GSCI. Thus, it can be concluded that the emerging markets equities indices can be combined with commodities indices for hedging and risk diversification purpose.

Dynamic hedging performance and downside risk: Evidence from Nikkei index futures

This paper assesses the incremental value of dynamic futures hedging models in minimizing downside risks including value-at-risk, expected shortfall, exponential spectral risk measure and lower partial moment over unconditional hedging approaches. We estimate hedge ratios using dynamic conditional correlation models incorporating high-frequency measures of volatility and correlation under multivariate skewed t-distributions. In the out-of-sample analysis with daily rebalancing and a portfolio hedged with Nikkei 225 futures, the unconditional minimum downside risk approaches perform worse than the proposed conditional approaches. The use of high-frequency measures possibly improves performance of the conditional downside-risk hedging models.

Dynamic Hedging Performance of the CSI 300 Index Futures - The Realized Minimum-Variance Hedge Ratio Approach

This paper comprehensively investigates the dynamic hedging performance of China’s CSI 300 index futures by using the realized minimum-variance hedge ratio (RMVHR) as an efficient way to utilize the high-frequency intraday information. We thoroughly examine a number of RMVHR-based time-series models for CSI 300 index futures, and evaluate the out-of-sample dynamic hedging performance in comparison to the conventional hedging models using daily prices, as well as the vector heterogeneous autoregressive model using five-minute prices. Our results show that the dynamic hedging performance of the RMVHR-based methods robustly dominates that of the conventional methods in terms of major performance measures including the hedge ratio, the hedging effectiveness, the portfolio return and the Sharp ratio in the out-of-sample forecast period. Furthermore, the superiority of the RMVHR-based methods is consistent during different volatility regimes of China’s financial markets, including China’s abnormal market fluctuations in 2015.

Hedging salmon price risk

ABSTRACTSalmon price is highly volatile and hard to predict, which obscures planning decisions and raises financing costs for market participants. This study considers hedging the spot price uncertainty with salmon futures contracts. It uses a new framework of hedging under square loss, consisting of a new objective function, an optimal hedge ratio and a measure of hedging effectiveness. The new framework aims at minimizing the expected squared forecast error. It generalizes the classical minimum variance hedging as it relaxes the assumption of known expected prices. The salmon futures contracts deliver satisfactory hedging performance, albeit constrained by low liquidity. Therefore, I suggest holding the contract through maturity rather than closing the futures and the spot positions simultaneously. This strategy alleviates the liquidity issue and saves transaction costs. All things considered, hedging with salmon futures is a moderately effective way of handling the salmon price uncertainty.

What is a better cross-hedge for energy: Equities or other commodities?

Can energy futures returns be effectively hedged? If so, what is the best hedge instrument? We study the hedging performance of several cross-hedges including the equity market, oil and gas equities, precious metals, industrial metals, and agricultural commodities. Our main conclusion is that cross-hedging of fluctuations in the energy market is generally not very effective and that any reduction in overall risk is small unless the oil and gas equity index is used. While all cross-hedges have performed better since 2007, the oil and gas equity index is the most effective, reducing risk by up to 20%, but it is also the most expensive.

Do commodities effectively hedge real estate risk? A multi-scale asymmetric DCC approach

We examine the hedging performance of commodities futures for US real estate portfolios in a multi-scale setting. Dynamic asymmetric conditional correlations and thereafter optimal hedge ratios of real estate stock returns with commodities index, gold, oil and bond returns are estimated to examine hedge effectiveness under heterogeneous market expectations. Rolling window based out-of-sample one-step-ahead forecasts show that commodities index (gold) provide the best hedge to US real estate stocks for short-term (long-term) investments. The results are robust to the choice of model refits and rolling window sizes and provide useful implications for alternate markets’ investors.