Switching asymmetric GARCH and options on a volatility index

Few proposed types of derivative securities have attracted as much attention and interest as option contracts on volatility. Grunbichler and Longstaff (1996) is the only study that proposes a model to value options written on a volatility index. Their model, which is based on modeling volatility as a GARCH process, does not take into account the switching regime and asymmetry properties of volatility. We show that the Grunbichler and Longstaff (1996) model underprices a three‐month option by about 10%. A Switching Regime Asymmetric GARCH is used to model the generating process of security returns. The comparison between the switching regime model and the traditional uni‐regime model among GARCH, EGARCH, and GJR‐GARCH demonstrates that a switching regime EGARCH model fits the data best. Next, the values of European call options written on a volatility index are computed using Monte Carlo integration. When comparing the values of the option based on the Switching Regime Asymmetric GARCH model and the traditional GARCH specification, it is found that the option values obtained from the different processes are very different. This clearly shows that the Grunbichler‐Longstaff model is too stylized to be used in pricing derivatives on a volatility index. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:251–282, 2004     

Regime switching in the yield curve

The article investigates the effect of interest‐rate variance on the shape of the yield curve with the use of a bivariate two‐state Markov switching model for the short‐rate changes and the yield curve slope. The two states are characterized by the variance of the short‐rate changes: low and high variance. In the high‐variance regime the yield curve becomes steeper with the interest‐rate variance; in the low‐variance regime the slope is independent hereof. A nonswitching specification amounts to averaging across the two states. The economy is in the high‐variance state during unusual economic periods. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:315–336, 2004     

Regime switching models for the Mexican peso

The Mexican peso has shown long periods of tranquility that suddenly give rise to short volatile periods. We characterize this exchange rate process by estimating a series of regime switching regressions and comparing the different specifications as pioneered by Meese and Rogoff [J. Int. Econ. 14 (1983) 3]. We find evidence for two clearly identified regimes: one with an appreciating trend and low volatility, and another with large depreciations and high volatility. We use the estimated model to explain the bias implied in the peso forward market. Finally, we show that duration dependence or fundamentally driven transition probabilities do not improve the model's forecasting power.     

The Volatility Behavior and Dependence Structure of Commodity Futures and Stocks

This study finds substantial risk diversification potential between certain commodity groups and stocks by exploring the dependence between their patterns of regime switching. None of the commodity groups share a common volatility regime with stocks, nor are the regime‐switching patterns of grains, industrials, metals, or softs, dependent on that of stocks. Simultaneous volatile regimes of commodity futures and stocks tend to be infrequent and short‐lived. In addition, in spite of financial contagion, animal products, grains, and softs typically demonstrate very low correlations with stocks even in simultaneous volatile regimes. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 34:93–101, 2014     

Regime-switching and interest rates in the European monetary system

This paper examines the impact that a currency target zone has on short-term interest rates. For a number of countries in the European Monetary System, we characterize the short rate using a regime-switching model that allows for a differently parameterized mean-reverting square-root process in each regime. We find that the volatility, the level, and the speed-of-adjustment are all higher in the regime that is operative during speculative attacks and currency crises. Moreover, we allow the conditional probability of being in each regime to be state-dependent so the model can be used to examine questions relating to the likelihood of realignments and the stability of the target zone system.     

Modeling the conditional mean and variance of the short rate using diffusion,GARCH, and moving average models

This article introduces a two‐factor‐discrete‐time‐stochastic‐volatility model that allows for departures from linearity in the conditional mean and incorporates serially correlated unexpected news, asymmetry, and level effects into the definition of conditional volatility of the short rate. The new class of econometric specifications nests many popular existing symmetric and asymmetric GARCH as well as diffusion models of the short‐term interest rate. This study attempts to determine the correct specification of conditional mean and variance of the short rate by developing a more general econometric framework that allows for nonlinear effects in the drift of the short rate, and that defines the conditional volatility as a nonlinear function of unexpected information shocks and interest rate levels. The existing and alternative models are compared in terms of their ability to capture the stochastic behavior of the short‐term riskless rate. The empirical results indicate that the relative performance of the two‐factor models in predicting the future level and variance of interest‐rate changes is superior to the nested models. © 2000 John Wiley & Sons, Inc. Jrl Fut Mark 20:717–751, 2000     

Regime‐switching in stock index and Treasury futures returns and measures of stock market stress

We investigate bivariate regime‐switching in daily futures‐contract returns for the US stock index and ten‐year Treasury notes over the crisis‐rich 1997–2005 period. We allow the return means, volatilities, and correlation to all vary across regimes. We document a striking contrast between regimes, with a high‐stress regime that exhibits a much higher stock volatility, a much lower stock–bond correlation, and a higher mean bond return. The high‐stress regime is associated with higher average values of stock‐implied volatility, stock illiquidity, and stock and bond futures trading volume. The lagged implied volatility from equity‐index options is useful in modeling the time‐varying transition probabilities of the regime‐switching process. Our findings support the notions that: (1) stock market stress can have a material influence on Treasury bond pricing, and (2) the diversification benefits of combined stock–bond holdings tend to be greater during times with relatively high stock market stress. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:753–779, 2010     

THE IMPORTANCE OF THE RETENTION RATIO IN A KALECKIAN MODEL WITH DEBT ACCUMULATION

By using a Kaleckian model with debt accumulation, Hein (2007; Metroeconomica, 56 (2), pp. 310–39) found that the long‐run equilibrium value of the debt–capital ratio is positive and stable only if interest rates are extremely high and if the short‐run equilibrium exhibits the ‘debt‐led’ growth regime. However, this conclusion crucially depends on the assumption that the retention ratio of firms is equal to unity. By relaxing this assumption, we show that there exists a positive and stable long‐run equilibrium even under the ‘debt‐burdened’ regime without any constraint on the nominal interest rate.     

Intraday Volatility in Interest‐Rate and Foreign‐Exchange Markets: ARCH,Announcement, and Seasonality Effects

We explore the determinants of intraday volatility in interest‐rate and foreign‐exchange markets, focusing on the importance and interaction of three types of information in predicting intraday volatility: (a) knowledge of recent past volatilities (i.e., ARCH or Autoregressive Conditional Heteroskedasticity effects); (b) prior knowledge of when major scheduled macroeconomic announcements, such as the employment report or Producer Price Index, will be released; and (c) knowledge of seasonality patterns. We find that all three information sets have significant incremental predictive power, but macroeconomic announcements are the most important determinants of periods of very high intraday volatility (particularly in the interest‐rate markets). We show that because the three information sets are not independent, it is necessary to simultaneously consider all three to accurately measure intraday volatility patterns. For instance, we find that most of the previously documented time‐of‐day and day‐of‐the‐week volatility patterns in these markets are due to the tendency for macroeconomic announcements to occur on particular days and at particular times. Indeed, the familiar U‐shape completely disappears in the foreign‐exchange market. We also find that estimates of ARCH effects are considerably altered when we account for announcement effects and return periodicity; specifically, estimates of volatility persistence are sharply reduced. Separately, our results show that high volatility persists longer after shocks due to unscheduled announcements than after equivalent shocks due to scheduled announcements, indicating that market participants digest information much more quickly if they are prepared to receive it. However, contrary to results from equity markets, we find no evidence of a meaningful difference in volatility persistence after positive or negative price shocks. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21: 517–552, 2001     

Markov switching GARCH models of currency turmoil in Southeast Asia

This paper analyzes exchange rate turmoil with a Markov switching GARCH model. We distinguish between two different regimes in both the conditional mean and the conditional variance: “ordinary” regime, characterized by low exchange rate changes and low volatility, and “turbulent” regime, characterized by high exchange rate devaluation and high volatility. We also allow the transition probabilities to vary over time as functions of economic and financial indicators. We find that real effective exchange rates, money supply relative to reserves, stock index returns, and bank stock index returns and volatility contain valuable information for identifying turbulent and ordinary periods.     

A UNIFIED FRAMEWORK FOR PRICING CREDIT AND EQUITY DERIVATIVES

We propose a model which can be jointly calibrated to the corporate bond term structure and equity option volatility surface of the same company. Our purpose is to obtain explicit bond and equity option pricing formulas that can be calibrated to find a risk neutral model that matches a set of observed market prices. This risk neutral model can then be used to price more exotic, illiquid, or over‐the‐counter derivatives. We observe that our model matches the equity option implied volatility surface well since we properly account for the default risk in the implied volatility surface. We demonstrate the importance of accounting for the default risk and stochastic interest rate in equity option pricing by comparing our results to Fouque et al., which only accounts for stochastic volatility.     

An empirical comparison of continuous time models of the short term interest rate

This article tests the performance of a wide variety of well-known continuous time models—with particular emphasis on the Black, Derman, and Toy (1990; henceforth BDT) term structure model—in capturing the stochastic behavior of the short term interest rate volatility. Many popular interest rate models are nested within a more flexible time-varying BDT framework that allows us to compare the models and find the proper specification of the dynamics of short rates. The empirical results indicate that the equilibrium models that do not allow the drift and diffusion parameters to vary over time and parameterize the volatility only as a function of interest rate levels overemphasize the sensitivity of volatility to the level of interest rate and fail to model adequately the serial correlation in conditional variances. On the other hand, the GARCH-based arbitrage-free models with time-dependent parameters in the drift and diffusion functions define the volatility only as a function of unexpected information shocks and fail to capture adequately the relationship between interest rate levels and volatility. This study shows that the most successful models in capturing the dynamics of short term interest rates are those that introduce time-dependent parameters to the short rate process and define the conditional volatility as a function of both the interest rate levels and the last period's unexpected news. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 777–797, 1999     

A two‐mean reverting‐factor model of the term structure of interest rates

This article presents a two‐factor model of the term structure of interest rates. It is assumed that default‐free discount bond prices are determined by the time to maturity and two factors, the long‐term interest rate, and the spread (i.e., the difference) between the short‐term (instantaneous) risk‐free rate of interest and the long‐term rate. Assuming that both factors follow a joint Ornstein‐Uhlenbeck process, a general bond pricing equation is derived. Closed‐form expressions for prices of bonds and interest rate derivatives are obtained. The analytical formula for derivatives is applied to price European options on discount bonds and more complex types of options. Finally, empirical evidence of the model's performance in comparison with an alternative two‐factor (Vasicek‐CIR) model is presented. The findings show that both models exhibit a similar behavior for the shortest maturities. However, importantly, the results demonstrate that modeling the volatility in the long‐term rate process can help to fit the observed data, and can improve the prediction of the future movements in medium‐ and long‐term interest rates. So it is not so clear which is the best model to be used. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23: 1075–1105, 2003     

Determinants of Japanese Yen interest rate swap spreads: Evidence from a smooth transition vector autoregressive model

This study investigates the determinants of variations in the yield spreads between Japanese yen interest rate swaps and Japan government bonds for a period from 1997 to 2005. A smooth transition vector autoregressive (STVAR) model and generalized impulse response functions are used to analyze the impact of various economic shocks on swap spreads. The volatility based on a GARCH (generalized autoregressive conditional heteroskedasticity) model of the government bond rate is identified as the transition variable that controls the smooth transition from a high volatility regime to a low volatility regime. The break point of the regime shift occurs around the end of the Japanese banking crisis. The impact of economic shocks on swap spreads varies across the maturity of swap spreads as well as regimes. Overall, swap spreads are more responsive to the economic shocks in the high volatility regime. Moreover, a volatility shock has profound effects on shorter maturity spreads, whereas the term structure shock plays an important role in impacting longer maturity spreads. Results of this study also show noticeable differences between the nonlinear and linear impulse response functions. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:82–107, 2008     

A direct solution method for pricing options in regime‐switching models

Pricing financial or real options with arbitrary payoffs in regime‐switching models is an important problem in finance. Mathematically, it is to solve, under certain standard assumptions, a general form of optimal stopping problems in regime‐switching models. In this article, we reduce an optimal stopping problem with an arbitrary value function in a two‐regime environment to a pair of optimal stopping problems without regime switching. We then propose a method for finding optimal stopping rules using the techniques available for nonswitching problems. In contrast to other methods, our systematic solution procedure is more direct as we first obtain the explicit form of the value functions. In the end, we discuss an option pricing problem, which may not be dealt with by the conventional methods, demonstrating the simplicity of our approach.     

Credit cycle dependent spread determinants in emerging sovereign debt markets

We address credit cycle dependent sovereign credit risk determinants. In our model, the spread determinants' magnitude is conditional on an unobservable endogenous sovereign credit cycle as represented by the underlying state of a Markov regime switching process. Our explanatory variables are motivated in the tradition of structural credit risk models and include changes in asset prices, interest rates, implied market volatility, gold price changes and foreign exchange rates. We examine daily frequency variations of U.S. dollar denominated Eurobond credit spreads of four major Latin American sovereign bond issuers (Brazil, Colombia, Mexico and Venezuela) with liquid bond markets during March 2000 to June 2011. We find that spread determinants are statistically significant and consistent with theory, while their magnitude remarkably varies with the state of the credit cycle. Crisis states are characterized by high spread change uncertainty and high sensitivities with respect to the spread change determinants. We further document that not only changes of local currencies, but also changes of the Euro with respect to the U.S. dollar are significant spread drivers and argue that this is consistent with the sovereigns' ability to pay.     

On the Existence of Finite-Dimensional Realizations for Nonlinear Forward Rate Models

We consider interest rate models of the Heath–Jarrow–Morton type, where the forward rates are driven by a multidimensional Wiener process, and where the volatility is allowed to be an arbitrary smooth functional of the present forward rate curve. Using ideas from differential geometry as well as from systems and control theory, we investigate when the forward rate process can be realized by a finite-dimensional Markovian state space model, and we give general necessary and sufficient conditions, in terms of the volatility structure, for the existence of a finite-dimensional realization. A number of concrete applications are given, and all previously known realization results (as far as existence is concerned) for Wiener driven models are included and extended. As a special case we give a general and easily applicable necessary and sufficient condition for when the induced short rate is a Markov process. In particular we give a short proof of a result by Jeffrey showing that the only forward rate models with short rate dependent volatility structures which generically possess a short rate realization are the affine ones. These models are thus the only generic short rate models from a forward rate point of view.     

Predicting Stock Market Movements in the United States: The Role of Presidential Approval Ratings*

In this paper we analyze whether presidential approval ratings can predict the S&P 500 returns over the monthly period of July 1941 to April 2018, using a dynamic conditional correlation multivariate generalized autoregressive conditional heteroscedasticity (DCC‐MGARCH) model. Our results show that standard linear Granger causality test fail to detect any evidence of predictability. However, the linear model is found to be misspecified due to structural breaks and nonlinearity, and hence, the result of no causality from presidential approval ratings to stock returns cannot be considered reliable. When we use the DCC‐MGARCH model, which is robust to such misspecifications, in 69% of the sample period, approval ratings in fact do strongly predict the S&P 500 stock return. Moreover, using the DCC‐MGARCH model we find that presidential approval rating is also a strong predictor of the realized volatility of S&P 500. Overall, our results highlight that presidential approval ratings is helpful in predicting stock return and volatility, when one accounts for nonlinearity and regime changes through a robust time‐varying model.     

FIRE SALES FORENSICS: MEASURING ENDOGENOUS RISK

We propose a tractable framework for quantifying the impact of loss‐triggered fire sales on portfolio risk, in a multi‐asset setting. We derive analytical expressions for the impact of fire sales on the realized volatility and correlations of asset returns in a fire sales scenario and show that our results provide a quantitative explanation for the spikes in volatility and correlations observed during such deleveraging episodes. These results are then used to develop an econometric framework for the forensic analysis of fire sales episodes, using observations of market prices. We give conditions for the identifiability of model parameters from time series of asset prices, propose a statistical test for the presence of fire sales, and an estimator for the magnitude of fire sales in each asset class. Pathwise consistency and large sample properties of the estimator are studied in the high‐frequency asymptotic regime. We illustrate our methodology by applying it to the forensic analysis of two recent deleveraging episodes: the Quant Crash of August 2007 and the Great Deleveraging following the default of Lehman Brothers in Fall 2008.     

Optimal Futures Hedging Under Multichain Markov Regime Switching

Most of the existing Markov regime switching GARCH‐hedging models assume a common switching dynamic for spot and futures returns. In this study, we release this assumption and suggest a multichain Markov regime switching GARCH (MCSG) model for estimating state‐dependent time‐varying minimum variance hedge ratios. Empirical results from commodity futures hedging show that MCSG creates hedging gains, compared with single‐state‐variable regime‐switching GARCH models. Moreover, we find an average of 24% cross‐regime probability, indicating the importance of modeling cross‐regime dynamic in developing optimal futures hedging strategies. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 34:173–202, 2014