Multivariate GARCH hedge ratios and hedging effectiveness in Australian futures markets

We use the All Ordinaries Index and the corresponding Share Price Index futures contract written against the All Ordinaries Index to estimate optimal hedge ratios, adopting several specifications: an ordinary least squares‐based model, a vector autoregression, a vector error‐correction model and a diagonal‐vec multivariate generalized autoregressive conditional heteroscedasticity model. Hedging effectiveness is measured using a risk‐return comparison and a utility maximization method. We find that time‐varying generalized autoregressive conditional heteroscedasticity hedge ratios perform better than constant hedge ratios in terms of minimizing risks, but when return effects are also considered, the utility‐based measure prefers the ordinary least squares method in the in‐sample hedge, whilst both approaches favour the conditional time‐varying multivariate generalized autoregressive conditional heteroscedasticity hedge ratio estimates in out‐of‐sample analyses.     

Dynamic conditional copula correlation and optimal hedge ratios with currency futures

This study investigates efficiency of the futures hedge implemented through the currency markets. The copula DCC-EGARCH model is estimated with the bivariate error correction term to minimize variance of the currency portfolios. The estimation results for the currencies of the Australian dollar, Canadian dollar, euro, British pound and Japanese yen show that the inclusion of the external realized variance estimators into the variance equation of the estimated model improves the model's ability to account for the clustered data variance. In hedging portfolios, the information content of the realized variance estimator effectively reduces the variance of the portfolios.     

Short-run deviations and time-varying hedge ratios: Evidence from agricultural futures markets

This paper investigates the hedging effectiveness of time-varying hedge ratios in the agricultural commodities futures markets using four different versions of the GARCH models. The GARCH models applied are the standard bivariate GARCH, the bivariate BEKK GARCH, the bivariate GARCH-X and the bivariate BEKK GARCH-X. Futures data for corn, coffee, wheat, sugar, soybeans, live cattle and hogs are applied. Comparison of the hedging effectiveness is done for the within sample period (1980–2004), and two out-of-sample periods (2002–2004 and 2003–2004). Results indicate superior performance of the portfolios based on the GARCH-X model estimated hedge ratio during all periods.     

Trend-following hedge funds and multi-period asset allocation

Abstract

Selected hedge funds employ trend-following strategies in an attempt to achieve superior risk-adjusted returns. We employ a lookback straddle approach for evaluating the return characteristics of a trend-following strategy. The strategies can improve investor performance in the context of a multi-period dynamic portfolio model. The gains are achieved by taking advantage of the funds' high level of volatility. A set of empirical results confirms the advantages of the lookback straddle for investors at the top end of the multi-period efficient frontier.     

Model-free hedge ratios and scale-invariant models

A price process is scale-invariant if and only if the returns distribution is independent of the price measurement scale. We show that most stochastic processes used for pricing options on financial assets have this property and that many models not previously recognised as scale-invariant are indeed so. We also prove that price hedge ratios for a wide class of contingent claims under a wide class of pricing models are model-free. In particular, previous results on model-free price hedge ratios of vanilla options based on scale-invariant models are extended to any contingent claim with homogeneous pay-off, including complex, path-dependent options. However, model-free hedge ratios only have the minimum variance property in scale-invariant stochastic volatility models when price–volatility correlation is zero. In other stochastic volatility models and in scale-invariant local volatility models, model-free hedge ratios are not minimum variance ratios and our empirical results demonstrate that they are less efficient than minimum variance hedge ratios.     

Diversification benefits of NFTs for conventional asset investors: Evidence from CoVaR with higher moments and optimal hedge ratios

This study investigates the risk and returns on one of the newest digital asset classes instruments, non-fungible tokens (NFTs), by accounting for tail dependence of higher-order moments and portfolio characteristics. We used a wide range of asset classes, encompassing equites, fixed income securities, and commodities, and document the desirable hedging and portfolio attributes of NFTs by employing Conditional Value-at-Risk (CoVaR) and ∆CoVaRs with various copula functions. We found that NFTs exhibit beneficial investment and hedging attributes under all market conditions, including the Covid-19 pandemic. Our findings have important implications for investors, risk managers, and regulators.     

Predictability of currency carry trades and asset pricing implications

This paper studies the time series predictability of currency carry trades, constructed by selecting currencies to be bought or sold against the US dollar, based on forward discounts. Changes in a commodity index, currency volatility and, to a lesser extent, a measure of liquidity predict in-sample the payoffs of dynamically re-balanced carry trades, as evidenced by individual and joint p-values in monthly predictive regressions at horizons up to six months. Predictability is further supported through out-of-sample metrics, and a predictability-based decision rule produces sizable improvements in the Sharpe ratios and skewness profile of carry trade payoffs. Our evidence also indicates that predictability can be traced to the long legs of the carry trades and their currency components. We test the theoretical restrictions that an asset pricing model, with average currency returns and the mimicking portfolio for the innovations in currency volatility as risk factors, imposes on the coefficients in predictive regressions.     

Including commodity futures in asset allocation in China

In this paper, we investigate the role of eight commodity futures in asset allocation in China during the period January 2004–December 2015. The Chinese commodities and stocks are moderately correlated. We use quantile regressions based on a value-at-risk model to examine the relation between these two markets. We find no risk spillovers between the markets, suggesting that stocks and commodities in China are exposed to different risks. Using different asset allocation strategies, we show that including soymeal and soybeans in the Chinese stock index can offer some diversification gains. However, other Chinese commodities may not be useful for portfolio diversification.     

Share restrictions and asset pricing: Evidence from the hedge fund industry

This paper presents evidence on the relation between hedge fund returns and restrictions imposed by funds that limit the liquidity of fund investors. The excess returns of funds with lockup restrictions are approximately 4–7% per year higher than those of nonlockup funds. The average alpha of all funds is negative or insignificant after controlling for lockups and other share restrictions. Also, a negative relation is found between share restrictions and the liquidity of the fund's portfolio. This suggests that share restrictions allow funds to efficiently manage illiquid assets, and these benefits are captured by investors as a share illiquidity premium.     

International asset returns and exchange rates

We present a consumption-based international asset-pricing model to study global equity premiums, the US riskfree rate and the cross section of international asset returns. The model entails idiosyncratic, country-specific consumption risk, which helps explain the magnitude of global equity premiums. It also features country-specific habit formation, which helps explain the level of the interest rate on the US short-term Treasury bills traded by domestic and international investors. We find that the model explains approximately 40–50% of the cross section of currency and equity premiums as well as expected returns from value and growth portfolios of at least a dozen countries. Changes in real exchange rates are responsible for explaining approximately half of the cross section of international asset returns.     

Common asset pricing factors in volatilities and returns in futures markets

Factor-based asset pricing models have been used to explain the common predictable variation in excess asset returns. This paper combines means with volatilities of returns in several futures markets to explain their common predictable variation. Using a latent variables methodology, tests do not reject a single factor model with a common time-varying factor loading. The single common factor accounts for up to 53% of the predictable variation in the volatilities and up to 14% of the predictable variation in the means. S&P500 futures volatility predicted by the factor model is highly correlated with volatility implied in S&P500 futures options. But both the factor and implied volatilities are significant in predicting future volatility. In derivatives pricing, both implied volatility from options and factors extracted from asset pricing models should be employed.     

Spot rates,forward rates and exchange market efficiency

This paper examines the relationship between forward exchange rates and subsequently observed spot rates. No evidence is found for a liquidity premium on forward exchange, indicating that the forward rate can be used as a proxy of the market's expectations and that open exchange positions involve little systematic risk. It is also shown that forward exhange is priced as if the exchange rate could be characterized by a diffusion process with a trend, although there is some evidence such a process does not adequately characterize the exchange rate in all cases.     

Optimal hedge ratio and hedging effectiveness of stock index futures: evidence from India

In a free capital mobile world with increased volatility, the need for an optimal hedge ratio and its effectiveness is warranted to design a better hedging strategy with future contracts. This study analyses four competing time series econometric models with daily data on NSE Stock Index Futures and S&P CNX Nifty Index. The effectiveness of the optimal hedge ratios is examined through the mean returns and the average variance reduction between the hedged and the unhedged positions for 1-, 5-, 10- and 20-day horizons. The results clearly show that the time-varying hedge ratio derived from the multivariate GARCH model has higher mean return and higher average variance reduction across hedged and unhedged positions. Even though not outperforming the GARCH model, the simple OLS-based strategy performs well at shorter time horizons. The potential use of this multivariate GARCH model cannot be sublined because of its estimation complexities. However, from a cost of computation point of view, one can equally consider the simple OLS strategy that performs well at the shorter time horizons.     

Risk appetite,carry trade and exchange rates

Using exchange rate data from four different countries (time zones), we examine the relationship between the Yen exchange rate against major currencies (i.e. USD/JPY, EUR/JPY, GBP/JPY, AUD/JPY and NZD/JPY) and measures of risk appetite (i.e. the S&P500 index, Dow Jones Industrial Average index and the VIX index). Our results show that the equity indexes, especially the Dow Jones Industrial Average, play a more important role in the determination of the Yen cross rates than VIX. The popular carry-trade currencies, i.e. NZD/JPY, AUD/JPY and GBP/JPY, are more affected by the US equity market than USD/JPY and EUR/JPY. While the long-term relationships are consistent across the four different time zones, the short-term dynamics are different. We find that the response of NZD/JPY, AUD/JPY and GBP/JPY to changes in the US stock market is much greater in the New Zealand and Australian zones than in the UK or US. Although the short-term relationship between exchange rates and the equity index is quite strong, the error correction speed is very sluggish. We also find evidence of asymmetric adjustment in the response of exchange rates to changes in global risk aversion. Carry trade currencies tend to appreciate gradually when conditions are favorable but fall sharply when market risk increases.     

Multiscale hedge ratio between the Australian stock and futures markets: Evidence from wavelet analysis

This paper examines the relationship between the Australian stock and futures markets over various time horizons. In contrast to methods employed in previous studies, wavelet analysis allows us to decompose data into various time scales. Using this technique and the Hurst exponent, we find that the Australian stock and futures markets are antipersistent. The wavelet correlation between the two markets varies over investment horizons, but remains very high. Furthermore, the magnitude of the correlation increases as the time scale increases, indicating that the stock market and the futures market of the All Ordinaries Index are found to be not fundamentally different. The hedge ratio increases as the wavelet time scale increases. In addition, the effectiveness of hedging strategies initially increases with the hedging horizon.     

Dynamic asset allocation with stochastic income and interest rates

We solve for optimal portfolios when interest rates and labor income are stochastic with the expected income growth being affine in the short-term interest rate in order to encompass business cycle variations in wages. Our calibration based on the Panel Study of Income Dynamics (PSID) data supports this relation with substantial variation across individuals in the slope of this affine function. The slope is crucial for the valuation and riskiness of human capital and for the optimal stock/bond/cash allocation both in an unconstrained complete market and in an incomplete market with liquidity and short-sales constraints.     

Optimal hedge ratios and alternative hedging strategies in the presence of cointegrated time-varying risks

This paper utilizes the inter-temporal relationship between the FTSE-100 stock index and its futures price level between 1992 and 1999 to examine the characteristics of several minimum variance hedge ratios and the performances of several alternative hedging strategies for dynamic portfolio management in the presence of cointegrated time-varying risks. Earlier studies neglected the importance of cointegration between the two variables which resulted in biased estimates. These studies, in general, also assume that the hedging period is the same as the estimation time interval. This paper also looks at several key issues when the holding period is longer than the estimation period, such as the construction of optimal minimum variance hedge ratios, and the trade-off between transaction costs and risk reduction.     

Testing for constant hedge ratios in commodity markets: a multivariate GARCH approach

We develop a new multivariate generalized ARCH (GARCH) parameterization suitable for testing the hypothesis that the optimal futures hedge ratio is constant over time, given that the joint distribution of cash and futures prices is characterized by autoregressive conditional heteroskedasticity (ARCH). The advantage of the new parameterization is that it allows for a flexible form of time-varying volatility, even under the null of a constant hedge ratio. The model is estimated using weekly corn prices. Statistical tests reject the null hypothesis of a constant hedge ratio and also reject the null that time variation in optimal hedge ratios can be explained solely by deterministic seasonality and time to maturity effects.