On real interest rate dynamics and regime switching

We find evidence of regime switching dynamics in the USA and the UK real interest rates over the period 1881–2003. For the UK, there is a regime in which the real interest rate displays a relatively stronger mean-reversion and a regime in which it displays a relatively weaker mean-reversion. The former regime is characterized by a relatively larger error in the estimation of the reversion parameter, and higher volatility. For the USA, the two regimes differ in volatility. The probability of transition from one regime to another is found to be significantly related to the inflation rate regime, and to the political regime. The results highlight the importance of regime switching in the dynamics of the real interest rate, as well as the role of inflation and political regimes in explaining this switching.     

Evidence of an asymmetry in the relationship between volatility and autocorrelation

This paper focuses on the general determinants of autocorrelation and the relationship between autocorrelation and volatility in particular. Using UK stock market index and individual stock price data, a multivariate generalized autoregressive conditional heteroskedasticity (M-GARCH) model is used to generate estimates of conditional autocorrelation. The covariance equation of this model is modified to include the potential determinants of autocorrelation including volatility, which is proxied using the time series of filtered probabilities of a Markov regime switching model. Consistent with the previous literature, this paper documents a negative relationship between volatility and autocorrelation. The results suggest that an asymmetry exists in this relationship which is attributed to the constraints placed on short selling.     

Volatility in stock returns for new EU member states: Markov regime switching model

In this paper, we investigate the volatility in stock markets for the new European Union (EU) member states of the Czech Republic, Hungary, Poland, Slovenia and Slovakia by utilising the Markov regime switching model. The model detects that there are two or three volatility states for the emerging stock markets. The result reveals that there is a tendency that the emerging stock markets move from the high volatility regime in the earlier period of transition into the low volatility regime as they move into the EU. Entry to the EU appears to be associated with a reduction of volatility in unstable emerging markets.     

Regime switching in the relationship between equity returns and short-term interest rates in the UK

This paper examines the relationship between UK equity returns and short-term interest rates using a two regime Markov-Switching EGARCH model. The results suggest one high-return, low variance regime within which the conditional variance of equity returns responds persistently but symmetrically to equity return innovations. In the other, low-mean, high variance, regime equity volatility responds asymmetrically and without persistence to shocks to equity returns. There is evidence of a regime dependent relationship between shorter maturity interest rate differentials and equity return volatility. Furthermore, there is evidence that events in the money markets influence the probability of transition across regimes.     

Regime Change and the Role of International Markets on the Stock Returns of Small Open Economies

We examine the influence of US, UK and German macroeconomic and financial variables on the stock returns of two relatively small, open European economies, Ireland and Denmark. Within a nonlinear framework, we allow for time variation via regime switching using a smooth transition regression (STR) model. We find that US (global) and UK and German (regional) stock returns are significant determinants of returns in both markets. Further, global information represented by oil and US asset price movements drive changes between states in each market. Significantly, the role of country‐specific domestic variables is typically confined to a single state while global and regional variables pervade all states.     

Worldwide reach of short selling regulations

We characterize legality and incidence of short selling in a worldwide, multimarket framework. Home country short selling restrictions curtail home market stock borrowing by 45% and reduce short selling of the country's American Depository Receipts (ADRs) by 68% due to regulatory reach. Also, the 2008 US ban on short selling of financial firms reduced borrowing in foreign locations. These findings are robust to controls for option availability, enforcement, returns, firm size, trading volume, dividends, ADR level, volatility, days-to-cover, and industry sector. Further, we show that investor conduct resulting from adherence to professional standards is a more powerful mechanism of regulatory reach than intergovernment cooperation.     

The world price of jump and volatility risk

We study international integration of markets for jump and volatility risk, using index option data for the main global markets. To explain the cross-section of expected option returns we focus on return-based multi-factor models. For each market separately, we provide evidence that volatility and jump risk are priced risk factors. There is little evidence, however, of global unconditional pricing of these risks. We show that UK and US option markets have become increasingly interrelated, and using conditional pricing models generates some evidence of international pricing. Finally, the benefits of diversifying jump and volatility risk internationally are substantial, but declining.     

Option pricing under regime switching

Abstract

This paper develops a family of option pricing models when the underlying stock price dynamic is modelled by a regime switching process in which prices remain in one volatility regime for a random amount of time before switching over into a new regime. Our family includes the regime switching models of Hamilton (Hamilton J 1989 Econometrica 57 357–84), in which volatility influences returns. In addition, our models allow for feedback effects from returns to volatilities. Our family also includes GARCH option models as a special limiting case. Our models are more general than GARCH models in that our variance updating schemes do not only depend on levels of volatility and asset innovations, but also allow for a second factor that is orthogonal to asset innovations. The underlying processes in our family capture the asymmetric response of volatility to good and bad news and thus permit negative (or positive) correlation between returns and volatility. We provide the theory for pricing options under such processes, present an analytical solution for the special case where returns provide no feedback to volatility levels, and develop an efficient algorithm for the computation of American option prices for the general case.     

Asset market linkages: Evidence from financial, commodity and real estate assets

We use a general Markov switching model to examine the relationships between returns over three different asset classes: financial assets (US stocks and Treasury bonds), commodities (oil and gold) and real estate assets (US Case-Shiller index). We confirm the existence of two distinct regimes: a “tranquil” regime with periods of economic expansion and a “crisis” regime with periods of economic decline. The tranquil regime is characterized by lower volatility and significantly positive stock returns. During these periods, there is also evidence of a flight from quality - from gold to stocks. By contrast, the crisis regime is characterized by higher volatility and sharply negative stock returns, along with evidence of contagion between stocks, oil and real estate. Furthermore, during these periods, there is strong evidence of a flight to quality - from stocks to Treasury bonds.     

Intraday periodicity, calendar and announcement effects in Euro exchange rate volatility

This paper provides an analysis of intraday volatility using 5-min returns for Euro-Dollar, Euro-Sterling and Euro-Yen exchange rates, and therefore a new market setting. This includes a comparison of the performance of the Fourier flexible form (FFF) intraday volatility filter with an alternative cubic spline approach in the modelling of high frequency exchange rate volatility. Analysis of various potential calendar effects and seasonal chronological changes reveals that although such effects cause deviations from the average intraday volatility pattern, these intraday timing effects are in many cases only marginally statistically significant and are insignificant in economic terms. Results for the cubic spline approach imply that significant macroeconomic announcement effects are larger and far more quickly absorbed into exchange rates than is suggested by the FFF model, and underscores the advantage of the cubic spline in permitting the periodicity in intraday volatility to be more closely identified. Further analysis of macroeconomic announcement effects on volatility by country of origin (including the US, Eurozone, UK, Germany, France and Japan) reveals that the predominant reactions occur in response to US macroeconomic news, but that Eurozone, German and UK announcements also cause significant volatility reactions. Furthermore, Eurozone announcements are found to impact significantly upon volatility in the pre-announcement period.     

Noise-trading, costly arbitrage, and asset prices: Evidence from US closed-end funds

The behavior of US closed-end funds is very different from that of UK funds. There is no evidence that the US funds' discounts are constrained by arbitrage barriers, no evidence that higher expenses increase discounts and no evidence that replication risk increases discounts but strong evidence that noise-trader risk is priced. The differences between US and UK funds may be due to the fact that small investors dominate US funds while institutional investors dominate UK funds, or because the sample selection method for the UK funds chooses only funds that are relatively easy to arbitrage.     

International portfolio flows and exchange rate volatility in emerging Asian markets

This paper investigates the effects of equity and bond portfolio inflows on exchange rate volatility using monthly bilateral data for the US vis-a-vis seven Asian developing and emerging countries (India, Indonesia, Pakistan, the Philippines, South Korea, Taiwan and Thailand) over the period 1993:01–2015:11. GARCH models and Markov switching specifications with time-varying transition probabilities are estimated in addition to a benchmark linear model. The evidence suggests that high (low) exchange rate volatility is associated with equity (bond) inflows from the Asian countries toward the US in all cases, with the exception of the Philippines. Therefore, capital controls could be an effective tool to stabilise the foreign exchange market in countries where flows affect exchange rate volatility.     

US exports and time-varying volatility of real exchange rate

The effect of exchange rate volatility on trade is a controversial issue in international economics. Despite a widespread view that an increase in exchange rates volatility reduces trade, there is no real consensus on the direction or the size of the exchange rate volatility–trade level linkages. This paper investigates the relationship between US trade volume and exchange rate volatility using cointegration and error-correction models. We use conditional variances of the real effective exchange rate (REER) series modeled as a generalized autoregressive conditional heteroskedastic (GARCH) process to measure the exchange rate volatility. The cointegration results indicate a significant negative relationship between US export volume and exchange rate volatility. The short-run dynamics of the relationship, however, show that the effects of both real exchange rates and exchange rate volatility are insignificant.     

Regime dependent determinants of credit default swap spreads

Credit default swap (CDS) spreads display pronounced regime specific behaviour. A Markov switching model of the determinants of changes in the iTraxx Europe indices demonstrates that they are extremely sensitive to stock volatility during periods of CDS market turbulence. But in ordinary market circumstances CDS spreads are more sensitive to stock returns than they are to stock volatility. Equity hedge ratios are three or four times larger during the turbulent period, which explains why previous research on single-regime models finds stock positions to be ineffective hedges for default swaps. Interest rate movements do not affect the financial sector iTraxx indices and they only have a significant effect on the other indices when the spreads are not excessively volatile. Raising interest rates may decrease the probability of credit spreads entering a volatile period.     

Modeling structural changes in the volatility process

GARCH-type models have been very successful in describing the volatility dynamics of financial return series for short periods of time. However, the time-varying behavior of investors, for example, may cause the structure of volatility to change and the assumption of stationarity is no longer plausible. To deal with this issue, the current paper proposes a conditional volatility model with time-varying coefficients based on a multinomial switching mechanism. By giving more weight to either the persistence or shock term in a GARCH model, conditional on their relative ability to forecast a benchmark volatility measure, the switching reinforces the persistent nature of the GARCH model. The estimation of this benchmark volatility targeting or BVT-GARCH model for Dow 30 stocks indicates that the switching model is able to outperform a number of relevant GARCH setups, both in- and out-of-sample, also without any informational advantages.     

Yield-factor volatility models

The term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the shape of the yield curve. In this paper, we develop a comprehensive model for volatility dynamics in the level, slope, and curvature of the yield curve that simultaneously includes level and GARCH effects along with regime shifts. We show that the level of the short rate is useful in modeling the volatility of the three yield factors and that there are significant GARCH effects present even after including a level effect. Further, we find that allowing for regime shifts in the factor volatilities dramatically improves the model’s fit and strengthens the level effect. We also show that a regime-switching model with level and GARCH effects provides the best out-of-sample forecasting performance of yield volatility. We argue that the auxiliary models often used to estimate term structure models with simulation-based estimation techniques should be consistent with the main features of the yield curve that are identified by our model.     

Can interest rate volatility be extracted from the cross section of bond yields?

Most affine models of the term structure with stochastic volatility predict that the variance of the short rate should play a ‘dual role’ in that it should also equal a linear combination of yields. However, we find that estimation of a standard affine three-factor model results in a variance state variable that, while instrumental in explaining the shape of the yield curve, is essentially unrelated to GARCH estimates of the quadratic variation of the spot rate process or to implied variances from options. We then investigate four-factor affine models. Of the models tested, only the model that exhibits ‘unspanned stochastic volatility’ (USV) generates both realistic short rate volatility estimates and a good cross-sectional fit. Our findings suggest that short rate volatility cannot be extracted from the cross-section of bond prices. In particular, short rate volatility and convexity are only weakly correlated.     

Dynamic optimal capital structure with regime switching

We investigate the optimal capital structure of a corporate when the dynamics of the assets (both growth rate and volatility) change following different states of the economy. Two structural models are examined in the paper. The first considers the case when the firm is not facing tax benefit and bankruptcy costs with a regime switching dynamics. This model extends the Black and Cox (J Financ 31:351–367, 1976) model to allow for regime switching risk. The second model incorporates both tax benefit and bankruptcy costs with a regime switching dynamics. This is is more realistic, and is an extension of the Leland (J Financ 49(4):1213–1252, 1994) model with regime switching risk. We obtain closed-form analytic solutions for the optimal capital structure and default barrier for both models.     

The frequency of regime switching in financial market volatility

The mechanism of risk responses to market shocks is considered as stagnant in recent financial literature, whether during normal or stress periods. Since the returns are heteroskedastic, a little consideration was given to volatility structural breaks and diverse states. In this study, we conduct extensive simulations to prove that the switching regime GARCH model, under the highly flexible skewed generalized t (SGT) distribution, is remarkably efficient in detecting different volatility states. Next, we examine the switching regime in the S&P 500 volatility for weekly, daily, 10-minute and 1-minute returns. Results show that the volatility switches regimes frequently, and differences between the distributions of the high and low volatility states become more accentuated as the frequency increases. Moreover, the SGT is highly preferable to the usually employed skewed t distribution.     

Forecasting crude oil volatility with geopolitical risk: Do time-varying switching probabilities play a role?

This study examines whether geopolitical risk (GPR) exhibits an ability to forecast crude oil volatility from a time-varying transitional dynamics perspective. Unlike previous studies that assume an oversimplification of the fixed transition probabilities for crude oil volatility, we develop an asymmetric time-varying transition probability Markov regime switching (AS-TVTP-MS) GARCH model. In-sample estimated results show that GPR yields strong evidence of regime switching behavior on crude oil volatility and that the negative shocks of GPR result in greater effects on switching probabilities than positive shocks. Out-of-sample results indicate that the AS-TVTP-MS GARCH model containing the GPR index outperforms other models, suggesting that the consideration of GPR information and time-varying regime switching together results in superior predictive performance. Moreover, the predictability of oil volatility is further verified to be economically significant in the framework of portfolio allocation. In addition, our results are robust to various settings.