Optimal Hedge Ratio Research Articles

COVID-19 pandemic and the crude oil market risk: hedging options with non-energy financial innovations

This study examines the hedging effectiveness of financial innovations against crude oil investment risks, both before and during the COVID-19 pandemic. We focus on the non-energy exchange traded funds (ETFs) as proxies for financial innovations given the potential positive correlation between energy variants and crude oil proxies. We employ a multivariate volatility modeling framework that accounts for important statistical features of the non-energy ETFs and oil price series in the computation of optimal weights and optimal hedging ratios. Results show evidence of hedging effectiveness for the financial innovations against oil market risks, with higher hedging performance observed during the pandemic. Overall, we show that sectoral financial innovations provide resilient investment options. Therefore, we propose that including the ETFs in an investment portfolio containing oil could improve risk-adjusted returns, especially in similar financial crisis as witnessed during the pandemic. In essence, our results are useful for investors in the global oil market seeking to maximize risk-adjusted returns when making investment decisions. Moreover, by exploring the role of structural breaks in the multivariate volatility framework, our attempts at establishing robustness for the results reveal that ignoring the same may lead to wrong conclusions about the hedging effectiveness.

Gold and US sectoral stocks during COVID-19 pandemic

In this study, we examine the hedging relationship between gold and US sectoral stocks during the COVID-19 pandemic. We employ a multivariate volatility framework, which accounts for salient features of the series in the computation of optimal weights and optimal hedging ratios. We find evidence of hedging effectiveness between gold and sectoral stocks, albeit with lower performance, during the pandemic. Overall, including gold in a stock portfolio could provide a valuable asset class that can improve the risk-adjusted performance of stocks during the COVID-19 pandemic. In addition, we find that the estimated portfolio weights and hedge ratios are sensitive to structural breaks, and ignoring the breaks can lead to overestimation of the hedging effectiveness of gold for US sectoral stocks. Since the analysis involves sectoral stock data, we believe that any investor in the US stock market that seeks to maximize risk-adjusted returns is likely to find the results useful when making investment decisions during the pandemic.

Hedging Dow Jones Islamic and conventional emerging market indices with CDS, oil, gold and the VSTOXX: A comparison between DCC, ADCC and GO-GARCH models

Our goal in this paper is to examine the time-varying optimal hedging ratios for the Dow Jones Islamic and conventional emerging stock market indices, hedged with oil, gold, and the VSTOXX as well as four emerging-country sectoral CDS indices (raw materials, industry, health care, and telecommunications). Using a rolling-window procedure with daily data, for the period from January 2000 to April 2019, along with, DCC, ADCC and GO-GARCH models as well as a hedging effectiveness criterion, we determine the best hedging instrument(s). Our findings prove that CDS indices are the best hedging instruments for both Islamic and conventional portfolios, as they have the highest hedging effectiveness. Our empirical results are robust to distribution assumptions and to the use of three MGARCH models in examining different refits (20, 40, and 60 days).

Hedging cryptos with Bitcoin futures

The introduction of derivatives on Bitcoin enables investors to hedge risk exposures in cryptocurrencies. Because of volatility swings and jumps in cryptocurrency prices, the traditional variance-based approach to obtain hedge ratios may not be suitable for hedgers. In this work, we consider two extensions of the traditional approach: first, different dependence structures are modelled by different copulae, such as the Gaussian, Student-t, Normal Inverse Gaussian and Archimedean copulae; second, different risk measures, such as value-at-risk, expected shortfall and spectral risk measures are employed to find the optimal hedge ratio. Extensive out-of-sample tests using the data from the time period December 2017 until May 2021 give insights in the practice of hedging various cryptos and crypto indices, including Bitcoin, Ethereum, Cardano, the CRIX index and a number of crypto-portfolios. Evidence shows that BTC futures can effectively hedge BTC and BTC-involved indices. This promising result is consistent across different risk measures and copulae except for the Frank copula. On the other hand, we observe complex and diverse dependence structures between non-BTC-related cryptocurrencies and the BTC futures. As a consequence, the hedge performance of non-BTC-related cryptocurrencies is mixed and even suitable for some assets.

Hedging Islamic and conventional stock markets with other financial assets: comparison between competing DCC models on hedging effectiveness

This study examines the hedging of Islamic and conventional stock markets risks using diverse financial assets (namely gold, crude oil, VISTOXX, VIX, CDSEU and DJCOM). We apply DCC, ADCC and FDCC models to account for heavy tails and asymmetric returns. We use rolling window analysis to construct out-of-sample one-step-ahead forecasts of dynamic conditional correlations and optimal hedge ratios. The findings indicate that the hedge ratios vary and depend upon the inclusion of hedging assets, portfolio composition and model used. The VISTOXX is the best asset to hedge Islamic and conventional stock portfolios. Moreover, the DCC model often leads to diversification benefits and hedging effectiveness better than the others models.

Optimal hedge ratios and hedging effectiveness: An analysis of the Turkish futures market

The main purpose of this comprehensive study is to determine the optimal hedge ratios and hedging effectiveness of different futures contracts traded on the Borsa Istanbul (BIST), namely the BIST 30 equity index, US dollar–Turkish lira currency futures (USD-TRY), euro–Turkish lira (EUR-TRY) currency futures, and gold futures. The efficiency of hedge ratios estimated through constant and time-varying econometric models, such as ordinary least squares (OLS) and diagonal VECH—a multivariate generalized autoregressive conditional heteroskedasticity (GARCH) model—are compared with a minimum variance hedge ratio framework. The periods before and after the merger of the Turkish Derivatives Exchange are analyzed with the models to capture changes in the hedging effectiveness of the contracts. We find that the diagonal VECH and constant models produce almost identical positive results for both periods, suggesting similar high hedging effectiveness for BIST 30 equity futures contracts. We conclude that BIST 30 equity futures contracts provide an efficient hedging mechanism for investors aiming to protect their spot equity portfolios. However, after Turkey's foreign exchange regulation amendment in 2017, the percentage of variance reduction improves greatly for the dynamic GARCH model, compared to the static OLS model, for USD-TRY and EUR-TRY futures contracts. Furthermore, the hedging effectiveness of currency futures contracts is negatively affected during the COVID-19 pandemic period beginning in 2020. Unlike other contracts, the hedging effectiveness of gold contracts is low in all periods.

Emerging market portfolios and Islamic financial markets: Diversification benefits and safe havens

We examine the relationship between Islamic and conventional stock market returns to see if Islamic financial markets provide portfolio diversification benefits and safe havens during turbulent times. Using daily data from January 1996 through September 2020 we consider conventional emerging stock market returns and some Islamic stock market returns and examine their interactions using causality-in-variance, dynamic conditional correlations, optimal hedge ratios, and causality-in-risk tests. Causality-in-variance test results show causality between Islamic stock returns and all emerging stock returns which indicates Islamic markets provide limited safe havens. Results from both time-varying conditional correlations and the hedge ratios show that there are positive and significant correlations between emerging stock markets and Dow Jones Islamic Market Index, which implies limited portfolio diversification benefits afforded by Islamic stock markets.

Linkages between gold and emerging Asian stock markets: New evidence from the Chinese stock market crash

This study examines the return and volatility transmission between gold and nine emerging Asian Stock Markets during the global financial crisis and the Chinese stock market crash. We use the VAR-AGARCH model to estimate return and volatility spillovers over the period from January 2000 through June 30, 2018. The results reveal the substantial return and volatility spillovers between the gold and emerging Asian stock markets during the global financial crisis and the Chinese stock market crash. However, these return and volatility transmissions vary across the pairs of stock markets and the financial crises. Besides, we analyze the optimal portfolios and hedge ratios between gold and emerging Asian stock markets during all sample periods. Our findings have important implications for effective hedging and diversification strategies, asset pricing and risk management.

VALUE-AT-RISK BASED APPROACH FOR CURRENCY HEDGING

Corporate FX risk management has gained complexity with an increased number of currencies involved and varying correlations among them. Existing literature has highlighted the need to account for cross-currency correlations when optimizing hedge ratios for portfolio management (Dowd, 1999). In this paper, we propose a Value-at-Risk (VaR) based model to estimate the optimal hedge ratio for a multi-national corporate that aims to minimize the cost of hedging at a given tolerance level of expected loss arising out of FX movement. The paper illustrates both parametric and historical methods of VaR estimation at a portfolio level as the first step in risk management. As a second step, an efficient-frontier is derived based on the expected VaR level at various hedge ratios and compared with associated hedge cost. The benefits of this approach include: identification of net exposures after correlations among currencies are accounted for in order to avoid duplication of hedges, and condensation of the parameters governing hedging decision into a single, intuitively-appealing number. The paper also highlights the need to frequently update the model’s assumptions as currency correlations and corporate exposures remain dynamic.
 
 JEL Classification Codes: C10, F31, G32, M20.

Volatility Spillovers and Correlations between Oil Prices and Stock Sectors in Turkey: Implications on Portfolio Hedging and Diversification Opportunities

This study investigates volatility spillover effects as well as hedging and diversification opportunities between sectoral stock returns and world crude oil prices in Turkey using the weekly closing prices of the BIST 100 and twenty-three sectoral stock indices for the period 2002-2018. DCC modelling is employed to investigate volatility spillovers between sectoral stock returns and oil prices. Findings reveal significant volatility spillovers from the oil market to the BIST 100 and twelve stock sectors. Furthermore, optimal hedge ratios, optimal portfolio weights, hedging effectiveness, diversification effectiveness and risk-adjusted returns of oil-stock portfolios are computed and compared. The results indicate that diversification is a more effective strategy than hedging in terms of risk (variance) reductions and risk-adjusted returns in the Turkish stock market.

Value-At-Risk Based Approach For Currency Hedging

Corporate FX risk management has gained complexity with increased number of currencies involved and varying correlations among them. Existing literature has highlighted the need to account for cross-currency correlations when optimizing hedge ratios for portfolio management (Dowd, 1999). In this paper, we propose a Value-at-Risk (VaR) based model to estimate the optimal hedge ratio for a multi-national corporate that aims to minimize the cost of hedging at a given tolerance level of expected loss arising out of FX movement. The paper illustrates both parametric and historical methods of VaR estimation at a portfolio level as the first step in risk management. As a second step, an efficient-frontier is derived based on the expected VaR level at various hedge ratios, and compared with associated hedge cost. The benefits of this approach include: identification of net exposures after correlations among currencies are accounted for in order to avoid duplication of hedges, and condensation of the parameters governing hedging decision into a single, intuitively-appealing number. The paper also highlights the need to frequently update the model’s assumptions as currency correlations and corporate exposures remain dynamic.

Can fiat currencies really hedge Bitcoin? Evidence from dynamic short-term perspective

Whereas much research has largely investigated the safe haven, diversifier and hedge proprieties of cryptocurrency, very few papers have analyzed the hedging issue of cryptocurrency with other assets. As such, this paper attempts to investigate the possibility if Bitcoin can be hedged by selected fiat currencies (EUR, JPY and GBP) as Bitcoin prices have experienced high and persistent volatility. To do so, we compute optimal hedge ratios between Bitcoin and fiat currencies over the period 02/02/2012–30/11/2017 based on the VAR-DCC-GARCH model, VAR-ADCC-GARCH model and VAR-component GARCH-DCC model. A rolling window analysis is employed to establish out-of-sample one-step-ahead forecasts of dynamic conditional correlations between different assets. This leads to establish time-varying hedge ratios and thus dynamic cross-hedging Bitcoin/fiat currency markets. The empirical results clearly show the time-varying correlations between Bitcoin and fiat currencies under different specifications, implying a dynamic behavior of the relationship between such assets. For all the proposed models, such dynamic correlations are rather characterized by trending downward over the period under study. The results also display time-varying hedge ratios which lead to an ongoing regular demand for rebalancing the hedged positions under different specifications. As a matter of fact, using various models which take into account different aspects of volatility and correlation structures allows to better implement dynamic hedging strategies.

Hedging with financial innovations in the Asia-Pacific markets during the COVID-19 pandemic: the role of precious metals

<abstract> In this study, we exploit the information contained in financial innovations in precious metals for hedging the risks associated with the Asia-Pacific equities during the current pandemic. We measure financial innovations as exchange traded funds (ETFs) for gold, silver, platinum and palladium which contrast with investment in the physical precious metals since the former tracks well the prices of the latter and as well provides cost-effective alternative to invest in the markets without storage costs. Based on the optimal portfolio weights and optimal hedge ratios, we find that gold offers the best hedge (followed by silver, platinum, and palladium) against the risk associated with the Asia-Pacific equities during the COVID-19 pandemic albeit with a lower hedging effectiveness during the pandemic. Overall, including gold ETFs in an Asia-Pacific equity portfolio would provide both a valuable portfolio combination that could improve the risk-adjusted performance of the market in addition to serving as an effective hedge for equity-related risks. </abstract>

THE ROLES OF ECONOMIC POLICY UNCERTAINTY AND THE COVID-19 PANDEMIC IN THE CORRELATION BETWEEN CRYPTOCURRENCY AND STOCK MARKETS

We are the first to explore the effect of economic policy uncertainty (EPU) and the COVID-19 pandemic on the correlation between the cryptocurrency index CRIX and the world stock market portfolio, as well as the hedging properties of CRIX. To this end, we mainly apply the dynamic conditional correlation model with mixed data sampling regressions, a threshold vector autoregressive model and the generalized impulse response function. We demonstrate that the correlation is influenced by the uncertainty stance of the economy and behaves differently in low-, medium- and high-uncertainty periods. Most of the abnormal market relations exist in high levels of EPU or during the COVID-19 period, and the impact of global EPU is greater than that of EPU originating in the United States, Europe, Russia and China. Moreover, the CRIX can serve as a hedge asset against the world stock market. The high (low) level of EPU has a significantly positive (negative) effect on the optimal hedge ratio of CRIX, which increases significantly during the COVID-19 period. Our findings have implications for risk management, portfolio allocations and hedging strategies.

SOME NOTES ABOUT THE MARTINGALE REPRESENTATION THEOREM AND THEIR APPLICATIONS

An important theorem in stochastic finance field is the martingale representation theorem. It is useful in the stage of making hedging strategies (such as cross hedging and replicating hedge) in the presence of different assets with different stochastic dynamics models. In the current paper, some new theoretical results about this theorem including derivation of serial correlation function of a martingale process and its conditional expectations approximation are proposed. Applications in optimal hedge ratio and financial derivative pricing are presented and sensitivity analyses are studied. Throughout theoretical results, simulation-based results are also proposed. Two real data sets are analyzed and concluding remarks are given. Finally, a conclusion section is given.

Dual and single hedging strategy: a novel comparison from the direct and cross hedging perspective

PurposeThe purpose of this paper is to deeply study and compare the dual and single hedging strategy, from the direct and cross hedging perspective.Design/methodology/approachThe authors not only first consider the dual hedge of integrated risks in this oil prices and foreign exchange rates setting but also make a novel comparison between the dual and single hedging strategy from a direct and cross hedging perspective. In total, six econometric models (to conduct one-step-ahead out-of-sample rolling estimation of the optimal hedge ratio) and two hedging performance criteria are employed in two different hedging backgrounds (direct and cross hedging).FindingsResults show that in the direct hedging background, a dual hedge cannot outperform the single hedge. But in the cross dual hedging setting, a dual hedge performs much better, possibly because the dual hedge brings different levels of advantages and disadvantages in the two different settings and the superiority of the dual hedge is more obvious in the cross dual hedging setting.Originality/valueThe existing literature that deals with oil prices and foreign exchange rates mostly concentrates on their relationship and comovements, while the dual hedge of integrated risks in this setting remains underresearched. Besides, the existing literature that deals with dual hedge gets its conclusions only based on a single specific background (direct or cross hedging) and lacks deeper investigation. In this paper, the authors expand the width and depth of the existing literature. Results and implications are revealing.

Volatility Connectedness between Clean Energy Firms and Crude Oil in the COVID-19 Era

The work investigates the volatility connectedness between oil price and clean energy firms over the period 2011–2020 (including the COVID-19 outbreak). Using the volatility spillover models, and dynamic conditional correlation, we are able to identify the volatility spillover effect between these financial markets and its implications for portfolio diversification. The results indicate a significant change in both static and dynamic volatility connectedness around the COVID-19 outbreak. For instance, total connectedness index changes from 21.36% (pre-COVID-19) to 61.23% (COVID-19). This finding shows the strong effect of the COVID-19 pandemic on these financial markets. Furthermore, we show how the WTI oil from the volatility transmitter (before the outbreak of the pandemic) becomes a risk receiver after the start of the global pandemic COVID-19. Our findings indicate that recent pandemic intensified volatility spillovers, supporting the financial contagion effects. Finally, we determine the optimal hedge ratios and portfolio weights. The estimates provided suggest the need for active portfolio management, taking into account the distinct characteristics of each sector and thus, the firm. For example, the optimal weight analysis shows how the clean sector has become important in optimal diversification strategies. Our results can be used for portfolio decisions and regulatory policymaking, particularly in the current context of high uncertainty.

Methanol futures hedging with skewed normal distribution by copula method

As an environmental protection fuel, methanol is widely used in national economy. The tremendous price fluctuation of methanol makes risk avoidance an important issue. However, traditional normal hypothesis in the existing literature underestimates the potential risk and leads to an inefficient hedging strategy, so we studied hedging strategy with methanol futures contracts based on the skewed normal hypothesis. Considering that copula methods allow us to construct a flexible multivariate distribution when solving the problem of asymmetry and nonlinearity, the dependence structure between spot and futures return is modelled through copula functions in this paper. Since likelihood equations do not have explicit solutions in the context of skewed normal, Genetic Algorithm is used to estimate the parameters of a skew normal distribution. To deal with the complexity of the proposed model, the artificial bee colony algorithm is adopted to search for the optimal solutions. Empirical results show that skewed normal distribution can represent the distribution characteristics of return better and improve the hedging effectiveness. Gaussian copula describes the dependence structure of spot and futures quite well. The algorithms designed to obtain the parameters in the marginal distributions and to find the optimal hedge ratio are effective and feasible.

Currency hedging for single-currency equity portfolios: Does cross-asset risk matter?

Foreign investors who are fully invested in a single-currency domestic equity portfolio are exposed to domestic equity risk, but also to currency risk. The standard approach to hedging the currency risk optimally is to estimate a single optimal hedge ratio, but this approach hedges only exchange rate risk, not cross-asset risk. We provide an alternative approach that estimates two optimal hedge ratios to adjust the currency exposures—one associated with the domestic currency and one associated with the foreign currency—and hedges both exchange rate risk and cross-asset risk. This alternative approach can significantly reduce risk.

Risk management and optimal capital structure under ambiguity

This study examines how managers’ perceived ambiguity influences risk management policies and capital structure decisions. After deriving the optimal hedge ratio and leverage ratio under ambiguity, we show the relationship between our results and recent studies. Our result supports the empirical evidence of a negative relationship between ambiguity and leverage ratio. We also find that the efficiency of hedging is an important factor when examining the value of hedging under ambiguity. The literature shows that the value of hedging increases with ambiguity; however, this result holds only when the efficiency of hedging is large, as in a full-hedge strategy.