Global Hedging Research Articles

Deep hedging of long-term financial derivatives

This study presents a deep reinforcement learning approach for global hedging of long-term financial derivatives. A similar setup as in Coleman et al. (2007) is considered with the risk management of lookback options embedded in guarantees of variable annuities with ratchet features. The deep hedging algorithm of Buehler et al. (2019a) is applied to optimize neural networks representing global hedging policies with both quadratic and non-quadratic penalties. To the best of the author’s knowledge, this is the first paper that presents an extensive benchmarking of global policies for long-term contingent claims with the use of various hedging instruments (e.g. underlying and standard options) and with the presence of jump risk for equity. Monte Carlo experiments demonstrate the vast superiority of non-quadratic global hedging as it results simultaneously in downside risk metrics two to three times smaller than best benchmarks and in significant hedging gains. Analyses show that the neural networks are able to effectively adapt their hedging decisions to different penalties and stylized facts of risky asset dynamics only by experiencing simulations of the financial market exhibiting these features. Numerical results also indicate that non-quadratic global policies are significantly more geared towards being long equity risk which entails earning the equity risk premium.

Global Hedging through Post-Decision State Variables

Unlike delta-hedging or similar methods based on Greeks, global hedging is an approach that optimizes some terminal criterion that depends on the difference between the value of a derivative security and that of its hedging portfolio at maturity or exercise. Global hedging methods in discrete time can be implemented using dynamic programming. They provide optimal strategies at all rebalancing dates for all possible states of the world, and can easily accommodate transaction fees and other frictions. However, considering transaction fees in the dynamic programming model requires the inclusion of an additional state variable, which translates into a significant increase of the computational burden. In this short note, we show how a decomposition technique based on the concept of post-decision state variables can be used to reduce the complexity of the computations to the level of a problem without transaction fees. The latter complexity reduction allows for substantial gains in terms of computing time and should therefore contribute to increasing the applicability of global hedging schemes in practice where the timely execution of portfolio rebalancing trades is crucial.

Hedging efficiently under correlation

We show that when a derivative portfolio has different correlated underlyings, hedging using classical greeks (first-order derivatives) is not the best possible choice. We first show how to adjust greeks to take correlation into account and reduce P&L volatility. Then we embed correlation-adjusted greeks in a global hedging strategy that reduces cost of hedging without increasing P&L volatility, by optimization of hedge re-adjustments. The strategy is justified in terms of a balance between transaction costs and risk-aversion, but, unlike more complex proposals from previous literature, it is completely defined by observable parameters, geometrically intuitive, and easy to implement for an arbitrary number of risk factors. We test our findings on a CVA hedging example. We first consider daily re-hedging: in this test, correlation-adjusted greeks allow the reduction of P&L volatility by more than 30% compared to standard deltas. Then we apply our general strategy to a context where a CVA portfolio is exposed to both credit and interest rate risk. The strategy keeps P&L volatility in line with daily standard delta-hedging, but with massive cost-saving: only six rebalances of the illiquid credit hedge are performed, over a period of six months.

Short-term Hedging for an Electricity Retailer

A dynamic global hedging procedure making use of futures contracts is developed for a retailer of the electricity market facing price, load and basis risk. Statistical models reproducing stylized facts are developed for the electricity load, the day-ahead spot price and futures prices in the Nord Pool market. These models serve as input to the hedging algorithm, which also accounts for transaction fees. Backtests with market data from 2007 to 2012 show that the global hedging procedure provides considerable risk reduction when compared to hedging benchmarks found in the literature.

Minimizing CVaR in global dynamic hedging with transaction costs

This study develops a global derivatives hedging methodology which takes into account the presence of transaction costs. It extends the Hodges and Neuberger [Rev. Futures Markets, 1989, 8, 222–239] framework in two ways. First, to reduce the occurrence of extreme losses, the expected utility is replaced by the conditional Value-at-Risk (CVaR) coherent risk measure as the objective function. Second, the normality assumption for the underlying asset returns is relaxed: general distributions are considered to improve the realism of the model and to be consistent with fat tails observed empirically. Dynamic programming is used to solve the hedging problem. The CVaR minimization objective is shown to be part of a time-consistent framework. Simulations with parameters estimated from the S&P 500 financial time series show the superiority of the proposed hedging method over multiple benchmarks from the literature in terms of tail risk reduction.

Hedging Efficiently Under Correlation

We show that when a derivative portfolio has different correlated underlyings, hedging using classical greeks (first-order derivatives) is not the best possible choice. We first show how to adjust greeks to take correlation into account and reduce P&L volatility. Then we embed correlation-adjusted greeks in a global hedging strategy that reduces cost of hedging without increasing P&L volatility, by optimization of hedge re-adjustments. The strategy is justified in terms of a balance between transaction costs and risk aversion, but, unlike more complex proposals from previous literature, it is completely defined by observable parameters, geometrically intuitive, and easy to implement for an arbitrary number of risk factors. We test our findings on a CVA hedging example. We first consider daily re-hedging: in this test correlation-adjusted greeks allow to reduce P&L volatility by more than 30% compared to standard deltas. Then we apply our general strategy to a context where a CVA portfolio is exposed to both credit and interest rate risk. The strategy keeps P&L volatility in line with daily standard delta hedging, but with massive cost-saving: only six rebalances of the illiquid credit hedge are performed, over a period of six months.

Global Diversification and Hedging by High Technology Firms

This paper examines the operational hedging strategies of high technology firms and how they are related to financial hedging. We use a sample of 216 firms, consisting of 108 operationally-hedged high technology firms and a size and industry matched sample of 108 non-operationally-hedged firms. We find that derivatives users are larger and are more R&D intensive than non-derivative users. Our regression analysis results show that operational hedging and financial hedging are complementary. However, firms that use financial hedging are able to significantly lower their exchange rate exposure. Finally, our results show that financial hedging adds value for our sample of high technology firms, while operational hedging does not.

Global Currency Hedging: Evidence from Conditional Coskewness and Cokurtosis

Global Currency Hedging: Evidence from Conditional Coskewness and Cokurtosis

Global Currency Hedging: What Role Should Foreign Currency Play in a Diversified Investment Portfolio?

Currency hedging is an important tool in reducing portfolio volatility for globally diversified equity and bond investors. Equity investors whose base currency is a reserve currency should fully hedge or even overhedge. Bond investors, regardless of their base currency, should also fully hedge.

Volatility transmission: what do Asia‐Pacific markets expect?

PurposeThe purpose of this paper is to investigate the international information transmission of return and volatility spillovers from US and Japan markets to Asia‐Pacific markets using daily stock market return data covering the period (1991‐2004).Design/methodology/approachThis paper considers a volatility spillover model by applying a bivariate Baba, Engle, Kraft and Kroner‐Generalized Autoregressive Conditional Heteroskedastic model, for each of the Asia‐Pacific countries against the Japan and the USA using daily returns for the period (1991‐2004). Splitting the sample into two non‐overlapping sub‐samples, the paper investigates whether the efforts for more economic, monetary and financial integration have fundamentally altered the sources and intensity of volatility spillovers to the individual stock market.FindingsIn the majority of the markets under scrutiny, we provide evidence of direct volatility spillovers, running mainly from the Japanese and US markets and pointing to more rapid information transmission during the recent years. First, the volatility of the Asia‐Pacific markets is becoming influenced more by the US market for the recent years. Second, for international investors to get profits from the returns of Asia‐Pacific securities, it is necessary to pay attention to the US market directly. Third, Korea, Singapore and Hong Kong are among the most Asia‐Pacific markets vulnerable to shocks from US investors due to the large ratio of portfolio holding. However, implementing global hedging strategies on Asia‐Pacific markets requires the information concerning the Japanese volatility behaviour.Originality/valueThis paper should be of interest to a broad practitioners and academics including those interested in modelling volatility for financial market risk management.

Global Currency Hedging

Global Currency Hedging

Impact of capital control measures on the Malaysian stock market

PurposeThe purpose of this paper is to examine the extent to which the capital control measures implemented by the Malaysian central bank in late 1998 had an influence on segmenting the Malaysian equity market from other major equity markets.Design/methodology/approachThe S&P 500, the Nikkei 225 Index, the STI Index and the KLSE Composite Index are considered. The discrete wavelet transform technique – “Haar” is employed to decompose the series into various time scales during the pre‐ and post‐capital control periods in Malaysia. The decomposed series are then used to estimate the interdependence between KLSE Composite Index with the other three markets at various time scales.FindingsThe empirical findings support three conclusions. First, in the pre‐capital control period, Singapore is the most influential market followed by the US across all time scales in transmitting news into Malaysia. Second, after the imposition of capital controls, the spillover effects from Singapore to Malaysia have declined substantially, suggesting a reduced integration between these two markets. Finally, in the post‐capital control period, all three markets appear to be imparting a similar but moderate level of influence on the Malaysian market.Research limitations/implicationsTo explore the return and volatility spillovers, the use of return and volatility series at different time scales provided a greater level of insight into the dynamics than the standard approaches which employ only one series in the time domain.Originality/valueThe results from this paper will have potential implications for asset allocation, the pricing of domestic securities, the implementation of global hedging and trading strategies and the evaluation of regulatory proposals to restrict international capital flows.

Analyzing Callable and Convertible Bonds when the Modigliani-Miller Assumptions are Violated

We analyze callable, convertible, and callable-convertible bonds in a dynamic model with restructuring, taxation, and transaction/bankruptcy costs. In this setting, calling when conversion value equals call price is not generally optimal. Late (early) calls are optimal when the conversion ratio is high (low) and the debt coupon is low (high). If volatility is fixed, pure callable bonds with a substantial call premium maximize firm value, committing equity to second-best restructuring policies. Convertibles are dominated in this context, since the backdoor equity component of the bond is tax-inefficient. The model is extended to allow for instantaneous risk shifting. Call provisions shorten effective maturity, but are not sufficient to induce hedging. Convertible bonds induce hedging, and the optimal conversion ratio trades off incentive provision against tax costs. Convertibles dominate pure callable bonds only when costs of risk shifting are sufficiently high. Although they mitigate risk shifting incentives, no convertible bond can induce global hedging, since equity is infinitely risk loving near default. In addition, convertible bonds exacerbate underinvestment incentives, since conversion privileges reduce marginal q.