High Volatility Regime Research Articles

Global Currency Misalignments, Crash Sensitivity, and Downside Insurance Costs

We show that the profitability of currency carry trades can be understood as the compensation for exchange rate misalignment risk based on the rare disastrous model of exchange rates (Farhi and Gabaix, 2008). It explains over 97% of the cross-sectional excess returns and dominates other candidate factors, including volatility and liquidity risk. Both currency carry and misalignment portfolios trade on the position-likelihood indicator (Huang and MacDonald, 2013) that explores the probability of the Uncovered Interest Rate Parity (UIP) to hold in the option pricing model. To examine the crash story of currency risk premia, we employ copula method to capture the tail sensitivity (CS) of currencies to the global market, and compute the moment risk premia by model-free approach using volatility risk premia as the proxy for downside insurance costs (DI). We find: (i) notable time-varying currency risk premia in pre-crisis and post-crisis periods with respect to both CS and DI; and (ii) the pay-off components of the strategy trading on skew risk premia mimic the behavior of currency carry trades. We further reveal and rationalize the differences in the performances of currency portfolios doubly sorted by CS and DI. We propose a novel trading strategy that makes a trade-off of the time-variation in risk premia between low and high volatility regimes and is thereby almost immunized from risk reversals. It generates a sizable average excess return (6.69% per annum, the highest among several studied currency trading strategies over the sample period) and its alpha that cannot be explained by canonical risk factors, including hedge fund (Fung and Hsieh, 2001) and betting-against-beta (Frazzini and Pedersen, 2014) risk factors, and government policy uncertainty meausres (Baker, Bloom, and Davis, 2012). Unlike other currency trading strategies, its cumulative wealth is driven by both exchange rate and yield components. We also investigate the behavior of currency momentum that is shown subject to credit risk, similarly to its stock market version (Avramov, Chordia, Jostova, and Philipov, 2007): Winner currencies performance well when sovereign default probability is low and loser currencies provide the hedge against this type of risk when sovereign default probability hikes up. The changes in global sovereign CDS spreads contribute 59% of the variation to the factor that captures the common dynamics of the currency trading strategies. From asset allocation perspective, a crash-averse investor is better off by allocating about 40% of the wealth to currency-misalignment portfolio and about 35% to crash-sensitive portfolio in tranquil period while reallocating about 85% of portfolio holdings to downside-insurance-cost strategy during the financial turmoil.

Measuring level of risk exposure in tanker shipping freight markets

This is an attempt to study the volatility structure of the tanker freight market and its exposure to market shocks. Therefore, we introduce a two state regime to investigate the possibility of two different volatility structures in shipping tanker freight markets. Empirical evidence is found that in general terms, shipping tanker freight returns, shift between two regimes, a high volatility regime and a low volatility regime and that market shocks in general increase the volatility of freight returns and has a lasting effect. In regards to measuring freight risk, it seams that semi-parametric approaches are appropriate methods for measuring level of risk exposure for shipping freight markets.

Switching volatility and cross-market linkages in public property markets

The primary contribution of this study is to examine the changes in cross-market relationship in international public property markets from a volatility regime switching perspective from January 1990 to January 2012. We find that global developed public property markets can be adequately characterised by a SWARCH model. In particular, most of the persistence in real estate stock price volatility can be attributed to the persistence of low-, medium- and high-volatility regimes in international developed public property markets. Moreover, there is a significant volatility increase during the crises periods for all markets examined. However, the identified high-volatility regime appears short-lived. Based on the SWARCH results, we find that the dynamic linkages among the markets are positively dependent on volatility regime. Specifically, the market correlations, foreign market influence, aggregate variance spillover index and variance–covariance matrix have intensified as market volatility increases during this period. Moreover, the evolution of the cross-market linkages among the sample public property markets is influenced significantly by both a time trend and a volatility regime factor that are independent of the influences of the global stock market and national stock markets. Our results imply that risk-reduction via international diversification in public property markets may only hold true in low-volatility periods. Consequently, portfolio managers need to understand and implement volatility state-dependent optimal asset allocation in order to better advise their clients.

Regime Switching Model of US Crude Oil and Stock Market Prices: 1859 to 2013

This paper examines the relationship between US crude oil and stock market prices, using a Markov-Switching vector error-correction model and a monthly data set from 1859 to 2013. The sample covers the entire modern era of the petroleum industry, which typically begins with the first drilled oil well in Titusville, Pennsylvania in 1858. We estimate a two regime model that divides the sample into high- and low-volatility regimes based on the variance-covariance matrix of the oil and stock prices. We find that the high-volatility regime more frequently exists prior to the Great Depression and after the 1973 oil price shock caused by the Organization of Petroleum Exporting Countries. The low-volatility regime occurs more frequently when the oil markets fell largely under the control of the major international oil companies from the end of the Great Depression to the first oil price shock in 1973. Using the National Bureau of Economic research business cycle dates, we also find that the high-volatility regime more likely occurs when the economy experiences a recession.

Exchange rate movements and stock market returns in a regime-switching environment: Evidence for BRICS countries

We use a regime-switching model approach to investigate the dynamic linkages between the exchange rates and stock market returns for the BRICS countries (Brazil, Russia, India, China and South Africa). The univariate analysis indicates that stock returns of the BRICS countries evolve according to two different regimes: a low volatility regime and a high volatility regime. On the other hand, our evidence from Markov switching VAR models suggests that stock markets have more influence on exchange rates during both calm and turbulent periods. These empirical insights have important implications for portfolio investments and currency risk hedging.

Identifying and forecasting house prices: a macroeconomic perspective

This paper studies the forecasting performance of macroeconomic variables on housing returns and on the possible shifts of regimes in house price cycles. We motivate our empirical analysis based on a general equilibrium model, and use a Markov switching model to identify two regimes of housing returns: the high volatility (‘boom-bust’) regime and the low volatility (‘tranquil’) regime. Given US data –, we find that with a single-regime model inflation rate and federal funds rate perform better than other economic aggregates in predicting housing returns. Using the Markov switching model, inflation rate and the federal funds rate are the most consistent predictor for in-sample and out-of-sample forecast of the probability of the ‘boom-bust’ regime. The results imply that motives for inflation hedging and changes in monetary policy matter for the movements of future housing returns and the possible shifts of regimes in house price cycles.

The conditional performance of US mutual funds over different market regimes: do different types of ethical screens matter?

We investigate the performance of US mutual funds that employ different ethical criteria: religious, socially responsible, and irresponsible. Performance is evaluated over different market regimes using a Markov-switching conditional CAPM approach that endogenously defines different states of the market. This model is also extended to a multifactor context. The results show that estimates of performance vary across different market regimes. The Vice Fund, which invests in unethical firms, outperforms in low-volatility regimes, but underperforms in high-volatility regimes. These results contradict the Vice Fund’s claim that it constitutes a “solid investment during recessionary periods”. Our results show that socially responsible and morally responsible funds exhibit different performance across different market conditions, thereby supporting the use of performance evaluation models that take into account different market regimes. Overall, different types of ethical screens seem to lead to different performance patterns across different market regimes.

Volatility and welfare

This paper explores the relationship between volatility and welfare. Even though households prefer smooth streams of consumption and leisure, welfare can be increasing in the volatility of an exogenous driving force if factor supply is sufficiently elastic. We provide some analytical results for a model without capital, and do some quantitative exercises in a model with capital and a variety of shocks. Welfare is greater in high shock volatility regimes under plausible parameter values. Augmenting the model with features that increase the elasticity of factor supply extends the range of parameters over which higher volatility results in greater welfare.

Patterns of volatility transmissions within regime switching across GCC and global markets

Unlike previous studies, this paper examines volatility transmission patterns for pairs of six stock markets of countries of the Gulf Cooperation Council (GCC) and pairs of these markets with the three global markets (S&P 500 index, Oil-WTI prices and MSCI-world), using the Multi-Chain Markov Switching (MCMS) model. This approach allows for a distinction between well diverse transmission patterns including volatility spillover, interdependence, independence and co-movements, given changes from high to low volatility regimes and vice versa. The results find evidence of different transmission patterns between the GCC and the global markets, with stronger connections with the global equity than with the oil markets. These patterns are also highly sensitive to the regimes of the selected markets which are characterized by turbulence or tranquility. For the first global market (Oil-WTI), the results show evidence of strong interdependence between Oil and each of the Kuwait and Abu Dhabi markets. Additionally, there is spillover from Oil-WTI to Dubai whose economy depends on oil, real estate and tourism. Surprisingly, we find evidence of independence between Oil and each of the Saudi Arabia, Qatar and Oman markets. For the second global market (the U.S. S&P 500 index), the results support strong interdependence with Saudi Arabia, Dubai and Abu Dhabi. There is also spillover from the S&P 500 index to Kuwait and Oman. More interestingly, we find spillover from Qatar to the S&P 500 index. For the third global market (MSCI-World), there is interdependence between MSCI and Dubai. We also find evidence of spillover from the MSCI-world to Kuwait and Saudi Arabia. Finally, we provide results in terms of inference on the regimes of high and low volatility, allowing for the interpretation of the financial shocks and the dates in which they are transmitted from one market to another. Policy implications are also provided.

Nonlinearity in cap-and-trade systems: The EUA price and its fundamentals

In this paper we examine the nonlinear relation between the EUA price and its fundamentals, such as energy prices, macroeconomic risk factors and weather conditions. By estimating a Markov regime-switching model, we find that the relation between the EUA price and its fundamentals varies over time. In particular, we are able to identify a low and a high volatility regime, both showing a strong impact of the fundamentals on the EUA price. The most important EUA price drivers are changes on the stock market and energy prices. The gas price and a broad European equity index affect the EUA price positively in both regimes, while the coal price and the oil price have a significant, but also positive impact only during the high and the low volatility regime, respectively. The high volatility regime is predominant in phases when economic activities are on a decrease or when institutional changes harm the confidence in the stringency of the EU ETS. This holds during the recession of 2008 and 2009, as well as during 2011 and 2012 when the debt crisis impaired the European economic outlook.

Nonlinearity in Cap-and-Trade Systems: The EUA Price and its Fundamentals

In this paper we examine the nonlinear relation between the EUA price and its fundamentals, such as energy prices, macroeconomic risk factors and weather conditions. By estimating a Markov regime-switching model, we find that the relation between the EUA price and its fundamentals varies over time. In particular, we are able to identify a low and a high volatility regime, both showing a strong impact of the fundamentals on the EUA price. The high volatility regime is predominant during the recession of 2008 and 2009 - a time period in which the actual emissions sharply decreased due to the economic crisis.

The restoration of the gold standard after the US Civil War: A volatility analysis

This paper presents a new view on the gold price of greenbacks during and after the American Civil War by analyzing exchange-rate volatility rather than exchange-rate levels. Our empirical investigation detects regimes of high and low volatility alternating in a way that is consistent with a theoretical exchange-rate model in which the rate is primarily driven by investors’ expectations and not by fundamentals. We interpret these findings as evidence that monetary policy makers were surprisingly able to credibly announce the resumption to gold half a year before it actually took place on January 1, 1879. Given the intense political debate about the appropriate design of the United States’ financial system, this is a remarkable result. It indicates that the policy makers’ ability to anchor investors’ expectations is relevant to achieving asset-price stability as well as effectiveness of financial market regulation. The insights from this historical episode should therefore be of interest to policy makers and regulators combating financial crises like the ongoing current debt crises worldwide.

European ‘Fear’ Indices – Evidence before and during the Financial Crisis

We document a negative and asymmetric contemporaneous relation of European stock and implied volatility returns. The negative relation is significantly more pronounced at the highest quantile of the stock market return distribution (i.e. largest price decrease). The relation between stock returns and implied volatility exhibits differences consistent with European institutional and cultural clusters. For example, German stock market tends to be more responsive to changes in implied volatility compared to UK stock market. In addition, the volatility spread for these two markets persist for a longer period compared to other European volatility spreads. The degree of integration between the leading European (UK, Germany and France) volatility markets, however, is very high and shocks on the implied volatility spread die out within a few days. Our Markov switching model distinguishes three volatility regimes. Large changes in both, implied volatility and stock returns increase the probability that volatility enters a higher (from low to middle and from middle to high) volatility regime. Factor loadings obtained by principal component analysis (PCA) of volatility returns are also regime dependent. Compared to US, the changes in European implied volatility tend to be more driven by tilts and non-linear movements of the volatility term structure. Our findings lend support to the behavioral explanation of the stock return-implied volatility relation and have implications for risk management.

How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches

This paper examines the dynamic relationship between firm-level return volatility and public news sentiment. By using the new RavenPack News Analytics ⿿ Dow Jones Edition database that captures over 1200 types of firm-specific and macroeconomic news releases and their sentiment scores at high frequencies, we investigate the circumstances in which public news sentiment is related to the intraday volatility of the constituent stocks in the Dow Jones Composite Average (DJN 65). Two different conditionally heteroskedastic models are employed: the Fractionally Integrated Generalized Autoregressive Conditionally Heteroskedastic (FIGARCH) and the two-state Markov Regime-Switching GARCH (RS-GARCH) models. For most of the DJN 65 stocks, our results confirm the significant impact of firm-specific news sentiment on intraday volatility persistence, even after controlling for the potential effects of macroeconomic news. Compared with macroeconomic news sentiment, firm-specific news sentiment apparently accounts for a greater proportion of overall volatility persistence. Moreover, negative news has a greater impact on volatility than positive news. Furthermore, the results from the RS-GARCH model indicate that news sentiment accounts for a greater proportion of volatility persistence in the high-volatility regime (turbulent state) than in the low-volatility regime (calm state). In-sample forecasting performance and residual diagnostic tests suggest that FIGARCH generally outperforms RS-GARCH.

Investor herds and regime-switching: Evidence from Gulf Arab stock markets

This paper proposes a dynamic herding approach which takes into account herding under different market regimes, with concentration on the Gulf Arab stock markets – Abu Dhabi, Dubai, Kuwait, Qatar and Saudi Arabia. Our results support the presence of three market regimes (low, high and extreme or crash volatility) in those markets with the transition order ‘low, crash and high volatility’, suggesting that these frontier markets have a different structure than developed markets. The results also yield evidence of herding behavior under the crash regime for all of the markets except Qatar which herds under the high volatility regime. The findings of the cross-GCC herding model also demonstrate herding comovements and not spillovers and are also robust to the cross-GCC volatility shocks. The tests that underline the cross-volatility shocks suggest that the crash regime is a true regime and not a statistical artifact. Policy and portfolio diversification implications are discussed.

Market Regimes and Herding Behavior in Chinese A and B Shares

This paper proposes a Markov-Switching (MS) test of herding behavior in China’s segmented stock markets under a regime-changing environment. Using firm-level data on the A-shares (denominated in Chinese Renminbi) and B-shares (denominated in U.S. and Hong Kong dollars), we estimate an MS model of stock return dispersions to discern whether herding behavior exists under different market regimes. The findings suggest the presence of three market regimes (low, high and extreme or crash volatility) in all Chinese market segments with the common volatility transmission order of Low, High and Crash regimes, and that herding behavior is asymmetric, observed during the high and crash volatility periods only. We also find significant cross market herding effects from the A- to the B-share markets, suggesting that foreign institutional investors in the B-share markets pair with domestic investors during periods of market stress. Finally, we find that the A-share markets in China herd around the Hong Kong market during the high and crash volatility regimes, whereas no significant U.S. market effect is observed.

Consistent Pricing of Options on Leveraged ETFs

We consider the problem of pricing options on a leveraged ETF (LETF) and the underlying ETF in a model-consistent manner. We show that if the underlying ETF has Heston dynamics, then the LETF also has Heston dynamics so that options on both the ETF and the LETF can be priced analytically using standard transform methods. If the underlying ETF has tractable jump-diffusion dynamics, then the dynamics of the corresponding LETF are generally intractable in that we cannot compute a closed-form expression for the characteristic function of the $\log$-LETF price. In that event we either (i) evaluate the appropriate transform numerically or (ii) propose tractable approximations based on either moment-matching techniques or saddlepoint approximations to the LETF price dynamics under which the transform can be found in closed form. In a series of numerical experiments including both low- and high-volatility regimes, we show that the resulting LETF option price approximations are very close to the true prices which we calculate via Monte Carlo. Because approximate LETF option prices can be computed very quickly, our methodology should be useful in practice for pricing and risk-managing portfolios that contain options on both ETFs and related LETFs. Our numerical results also demonstrate the model dependency of LETF option prices, and this is particularly noticeable in high-volatility environments.

Investor Herds and Regime-Switching: Evidence from Gulf Arab Stock Markets

This paper proposes a dynamic herding approach which takes into account herding under different market regimes, with concentration on the Gulf Arab stock markets – Abu Dhabi, Dubai, Kuwait, Qatar and Saudi Arabia. Our results support the presence of three market regimes (low, high and extreme or crash volatility) in those markets with the transition order ‘low, crash and high volatility’, suggesting that these frontier markets have a different structure than developed markets. The results also yield evidence of herding behavior under the crash regime for all of the markets except Qatar which herds under the low and high volatility regimes. The findings of the cross-GCC herding model also demonstrate herding comovements and not spillovers and are also robust to the cross-GCC volatility shocks. The tests that underline the cross volatility shocks generally suggest that the crash regime is a true regime and not a statistical artifact. Policy and portfolio diversification implications are discussed.

Efficient and accurate log-Lévy approximations of Lévy-driven LIBOR models

The LIBOR market model is very popular for pricing inter- est rate derivatives, but is known to have several pitfalls. In addition, if the model is driven by a jump process, then the complexity of the drift term is growing exponentially fast (as a function of the tenor length). In this work, we consider a Levy-driven LIBOR model and aim at developing accurate and efficient log-Levy approximations for the dynamics of the rates. The approximations are based on truncation of the drift term and Picard approximation of suitable processes. Numerical experiments for FRAs, caps and swaptions show that the approximations perform very well. In addition, we also consider the log-Levy approximation of annuities, which offers good approximations for high volatility regimes.

Monetary policy implications of housing shift-contagion across regional markets

This paper extends the shift-contagion concept to housing price returns in order to examine co-movements between pairs of regional housing markets in the US. It associates nonlinearities of housing prices with the monetary policy criteria at disaggregate levels. The framework with Markov-switching volatility in Gravelle et al. (Journal of International Economics 68:409–423, 2006) is utilized to investigate housing contagion phenomena which are defined as the switches in the structural transmission of common shocks across regional housing markets. The empirical results suggest that interactions between regional and nationwide housing markets switch across low-volatility and high-volatility regimes of common shocks for the Northeast and the West whose housing price returns are nonlinear. In addition, there is the significantly time-varying interdependence between the West and each of the other three regional housing markets. The estimated indicator of the monetary policy effectiveness implies that monetary policies can be effective in the Northeast and the West because they are more closely linked with other regional housing markets in volatile phases which are subject to housing crises. Noticeably, the broken interrelationships between regional housing markets and real economies in the 2001 recession imply high vulnerability to housing bubbles for regional markets, while short-term monetary policies can be effective in stabilizing the housing market turmoil around 2007.