Measuring systemic risk with regime switching in tails

This paper motivates the importance of modeling nonlinearities in measuring systemic risk. I capitalize this motivation by generalizing the CoVaR approach proposed by Adrian and Brunnermeier (2016) to allow it switching between a high and a normal risk regime filtered from data.. Considering the U.S. large bank holding companies (BHCs), this paper shows that modeling regime changes in tails is capable of capturing both amplification and mean-reversion effects of an adverse shock to a bank's balance sheet on the banking system. Using the Kolmogorov–Smirnov test statistics with and without bootstrapping, I perform the significance test to identify systemically important financial institutions (SIFIs), and the stochastic dominance test to rank the identified SIFIs. The stochastic dominance test raises the concern that the CoVaR measure underestimates systemic risk contributions for SIFIs but overestimates for non-SIFIs. Finally, applying the BHCs' characteristics and housing market price to forecast the regime-switching systemic risk out-of-sample, I obtain from 4- and 8-quarter-ahead horizons a desirable countercyclical, forward-looking measure of systemic risk.     

Asset allocation under stochastic interest rate with regime switching

We investigate an optimal asset allocation problem in a Markovian regime-switching financial market with stochastic interest rate. The market has three investment opportunities, namely, a bank account, a share and a zero-coupon bond, where stochastic movements of the short rate and the share price are governed by a Markovian regime-switching Vasicek model and a Markovian regime-switching Geometric Brownian motion, respectively. We discuss the optimal asset allocation problem using the dynamic programming approach for stochastic optimal control and derive a regime-switching Hamilton–Jacobi–Bellman (HJB) equation. Particular attention is paid to the exponential utility case. Numerical and sensitivity analysis are provided for this case. The numerical results reveal that regime-switches described by a two-state Markov chain have significant impacts on the optimal investment strategies in the share and the bond. Furthermore, the market prices of risk in both the bond and share markets are crucial factors in determining the optimal investment strategies.     

Modeling the European cycle with factor structure and regime switching

This paper compares the stylized facts of the European growth cycle stemming from the Gross Domestic Product (GDP) of the European Monetary Union with an unobserved common factor derived from a dynamic factor model with regime switching. The aim of this paper is to provide empirical evidence about the most adequate indicator for short-term monitoring of the cyclical state of the European economy. Previous versions of this article have been presented at the 55th International Atlantic Economic Conference (Vienna, Austria, March 12–16, 2003) and at the VI Encuentro de Economía Aplicada (Granada, Spain, June 5–7, 2003). The author would like to thank the conference participants and an anonymous referee for their comments and suggestions.     

Measuring business cycles: A temporal disaggregation model with regime switching

In this paper, we propose a temporal disaggregation model with regime switches to disaggregate U.S. quarterly GDP into monthly figures. Alternative to the existing literature, our model is able to capture the nonlinear behaviors of both aggregated and disaggregated output series as well as the asymmetric nature of business cycle phases. To demonstrate the applicability of the proposed model, we apply the model with a Markov trend component to U.S. quarterly real GDP. The results suggest that the combination of a temporal disaggregation model with Markov switches leads to a successful representation of the data relative to the existing literature. Also, the inferred probabilities of unobserved states are clearly in close agreement with the NBER reference cycle on a monthly basis, which highlights the importance of nonlinearities in business cycle.     

Idiosyncratic risk matters! A regime switching approach

The evidence on the inter-temporal relation between idiosyncratic risk and future stock returns is conflicting and confusing. We shed new light on the issue using a more flexible econometric approach based on [Hamilton, J.D. 1989. A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57, 357–384.] regime switching model that accommodates the parameter instability of the forecasting relation between returns and financial variables. We find strong evidence suggesting that idiosyncratic risk is related to future stock market returns only in the low variance regime.     

Value of tax benefits of a dynamic debt policy with regime switching

The article presents a method for valuation of stochastic future income with three barriers: a default barrier, a pre-default barrier and a refinancing barrier. Between the pre-default and default barriers, there is an ongoing cost of financial distress. In this framework, we derive state-dependent present value factors that can be applied to problems of valuation of firms, optimal financial structure and mitigation of agency conflicts between managers and investors. We illustrate our method with an analysis of the value of tax benefits of a dynamic debt policy.     

Conditional Markov regime switching model applied to economic modelling

In this paper we discuss the calibration issues of regime switching models built on mean-reverting and local volatility processes combined with two Markov regime switching processes. In fact, the volatility structure of these models depends on a first exogenous Markov chain whereas the drift structure depends on a conditional Markov chain with respect to the first one. The structure is also assumed to be Markovian and both structure and regime are unobserved. Regarding this construction, we extend the classical Expectation–Maximization (EM) algorithm to be applied to our regime switching model. We apply it to economic data (Euro/Dollar (USD) foreign exchange rate and Brent oil price) to show that such modelling clearly identifies both mean reverting and volatility regime switches. Moreover, it allows us to make economic interpretations of this regime classification as in some financial crises or some economic policies.     

Optimal policy rules and regime switching in disequilibrium models

This paper emphasizes the need to search for globally optimal policy levels (for public production, say) in fix-price disequilibrium analysis. Regime-specific rules are inadequate. They ignore the fact that moving a policy towards its optimal level may move the economy from its initial disequilibrium regime to a different regime where the rule no longer applies.     

Volatility forecasting: long memory,regime switching and heteroscedasticity

In this article, we account for the first time for long memory, regime switching and the conditional time-varying volatility of volatility (heteroscedasticity) to model and forecast market volatility using the heterogeneous autoregressive model of realized volatility (HAR-RV) and its extensions. We present several interesting and notable findings. First, existing models exhibit significant nonlinearity and clustering, which provide empirical evidence on the benefit of introducing regime switching and heteroscedasticity. Second, out-of-sample results indicate that combining regime switching and heteroscedasticity can substantially improve predictive power from a statistical viewpoint. More specifically, our proposed models generally exhibit higher forecasting accuracy. Third, these results are widely consistent across a variety of robustness tests such as different forecasting windows, forecasting models, realized measures, and stock markets. Consequently, this study sheds new light on forecasting future volatility.     

Testing the null hypothesis of no regime switching with an application to GDP growth rates

This paper presents tests for the null hypothesis of no regime switching in Hamilton’s (Econometrica 57:357–384, 1989) regime switching model. The test procedures exploit similarities between regime switching models, autoregressions with measurement errors, and finite mixture models. The proposed tests are computationally simple and, contrary to likelihood based tests, have a standard distribution under the null. When the methodology is applied to US GDP growth rates, no strong evidence of regime switching is found. I thank Don Andrews, Peter Phillips, Yuichi Kitamura, Anat Bracha, Patrik Guggenberger, Orit Whiteman and three anonymous referees for useful comments and suggestions.     

Further evidence on international Islamic and conventional portfolios diversification under regime switching

This article investigates the comparative performance of International Islamic and conventional portfolio diversification across different financial market regimes and provides an optimal choice from an American investor’s viewpoint during the period 2002–2014. Using a bootstrap-based stochastic dominance (SD) test and monthly MSCI prices of Islamic stock market indices and their conventional counterparts in 38 countries from North and Latin America, Europe and Asia-Pacific regions, we find that SD relationships between Islamic and conventional optimal-diversified portfolios change systematically according to investment region and market regime. Essentially, for all regimes, US investors are indifferent between Islamic diversification and its conventional counterpart, which implies that arbitrage diversification opportunities are rare and short lived in all regions. However, across all regions, especially in a crisis regime, Islamic portfolio diversification can be a good substitute for conventional diversification. Islamic portfolio diversification in North and Latin America, Europe and Global regions is an optimal choice for the risk-averse American investors. Finally, results imply that portfolio diversification among Islamic market indices can be a good hedge, offering investors superior investment alternatives during any financial meltdown or economic slowdown due to the conservative nature of Sharia-compliant investments.     

Examining the stochastic behavior of REIT returns: Evidence from the regime switching approach

In this paper the stochastic behavior of the returns on real estate investment trusts (REITs) is examined by using the unobserved component Markov switching (UC-MS) model. This approach endogenously permits the volatility to switch as the date and regime change and allows us to decompose the permanent and transitory components in REIT returns at monthly frequencies. The empirical evidence clearly shows that, for all of the REIT returns, the overall variance of the transitory component is significantly smaller than the corresponding variance for the permanent component. The durations of the high-variance regimes for both the fundamental and transitory components are short-lived and revert to normal levels quickly.     

Irreversible investment with regime shifts

Under the real options approach to investment under uncertainty, agents formulate optimal policies under the assumption that firms’ growth prospects do not vary over time. This paper proposes and solves a model of investment decisions in which the growth rate and volatility of the decision variable shift between different states at random times. A value-maximizing investment policy is derived such that in each regime the firm's investment policy is optimal and recognizes the possibility of a regime shift. Under this policy, investment is intermittent and increases with marginal q. Moreover, investment typically is very small but, in some states, the capital stock jumps. Implications for marginal q and the user cost of capital are also examined.     

Impact of macroeconomic factors and country risk ratings on GCC stock markets: evidence from a dynamic panel threshold model with regime switching

This study examines the non-linear relationship between stock markets in GCC countries and their country risk ratings as well as with major macroeconomic factors. Based on a dynamic panel threshold model with two and four regimes, the results provide evidence of short-term asymmetry between first-lagged GCC stock returns and the performance of GCC stock markets. In addition, only the financial risk (FR) rating has a significant positive effect on the performance of GCC stock markets according to the prevailing regimes for the GCC lagged returns and the Brent oil market. Among the macroeconomic factors, improvements in the global stock markets, the MSCI Global Islamic Index, and the oil price increased the performance of GCC stock markets, whereas increases in the gold price, the 3-month U.S. Treasury bill rate, and the U.S. Treasury bond rate reduced the performance of the GCC stock markets. These results have important implications for investors, policymakers, and portfolio managers.     

Detecting hot and cold cycles using a Markov regime switching model—Evidence from the Chinese A-share IPO market

This paper focuses on detecting hot and cold IPO cycles in the Chinese A-share market using a Markov regime switching model. We introduce a set of observations to measure IPO activities, which include numbers of IPOs issued, levels of underpricing, market conditions and duration time from prospectus and listing, and thus establish a model to estimate these activities' average performance in hot and cold periods respectively. It is found that a hot period is related with an abundant supply of IPOs, high levels of underpricing, positive market conditions and short waiting time to listing after prospectus issue. Further, this paper depicts the turning points of hot and cold periods across the period from 1994 to 2005 for each observation. The cycles detected by the number of IPOs per month are the benchmark and then these cycles' robustness is tested by the other observations.     

A gradual switching regression model with autocorrelated errors

In this note, we set up the gradual switching regression model with autocorrelated errors and show the maximum likelihood estimation procedure. As an empirical example, we examine structural change in the energy demand in Japan at the first oil crisis.     

A dynamic Nelson-Siegel yield curve model with Markov switching

This paper proposes a model to better capture persistent regime changes in the interest rates of the US term structure. While the previous literature on this matter proposes that regime changes in the term structure are due to persistent changes in the conditional mean and volatility of interest rates we find that changes in a single parameter that determines the factor loadings of the model better captures regime changes. We show that this model gives superior in-sample forecasting performance as compared to a baseline model and a volatility-switching model. In general, we find compelling evidence that the extracted factors from our term structure models are closely related with various economic variables. Furthermore, we investigate and find evidence that the effects of macroeconomic phenomena such as monetary policy, inflation expectations, and real economic activity differ according to the particular regime realized for the term structure. In particular, we identify the periods where monetary policy appears to have a greater effect on the yield curve, and the periods where inflation expectations seem to have a greater effect in yield determination. We also find convincing evidence of a relationship between the regimes estimated by the various switching models with economic activity and monetary policy.     

Exchange rate regime verification: An alternative method of testing for regime changes

This work proposes a change in persistence test for identifying de facto exchange rate regime changes. The results from 25 African countries show that this approach is able to identify some regime changes not captured by existing methods.     

Endogenous timing in the switching of technology with Marshallian externalities

We analyze endogenous timing in the switching of technology. Each user chooses when to purchase a new product which embodies new technologies characterized by Marshallian externalities. The technological switch occurs when a large number of users purchase new products. Under complete information, multiple market equilibria exist, and one of the equilibria in which technological switching occurs is efficient. However, if we introduce even a small amount of uncertainty, the switch is delayed in the unique equilibrium under perfect competition, resulting in a loss of social welfare. The market power of a monopolistic supplier of new products alleviates this inefficiency.     

Global Stability with Spillovers*

This paper investigates the stability of a small, highly stylized economy, which has imperfectly informed traders visiting markets sequentially. Trading out of equilibrium is allowed. Roughly speaking, this system is found to be stable, even though spillovers are present, as long as the direct effects of price changes dominate the spillovers.