Switching Vector Error Correction Model Research Articles

Listed Real Estate as an Inflation Hedge Across Regimes

AbstractThis paper examines the inflation-hedging capability of listed real estate (LRE) companies in the US from 1975 to 2023, and in three other economies—the UK, Japan, and Australia—from 1990 to 2023. By using a Markov switching vector error correction model (MS-VECM), we identify that the short-term hedging ability moves towards being negative or zero during turbulent periods. In stable periods, LRE provides good protection against inflation. In the long term, LRE offers a good hedge against expected inflation and shows a superior inflation hedging ability than stocks. Additionally, we identify inflation-hedging portfolios by minimizing the expected shortfall. This inflation-hedging portfolio allocation methodology suggests that listed real estate stocks should play a significant role in investor portfolios.

Regime dependent dynamics of parallel and official exchange markets in China: evidence from cryptocurrency

ABSTRACT This paper studies the dynamic relationship between the parallel and official exchange rates of Chinese Yuan (CNY) to U.S. Dollar (USD). Motivated by recent evidence about Bitcoin as a major channel for capital flight from China, we construct a parallel exchange rate implied by Bitcoin prices in the Chinese and U.S. crypto exchanges. While the dual exchange rates are cointegrated, adjustment to long-run equilibrium is non-linear and depends on policy changes and state of the markets. Results from our Markov Switching Vector Error Correction model suggest the parallel exchange rate responds one-to-one in the long-run with respect to an official exchange rate innovation. However, an unexpected change in the parallel rate is countered by an opposite and state-dependent response in the official exchange rate, suggesting active exchange policy interventions by the Chinese monetary authority.

A MARKOV SWITCHING VECM MODEL FOR RUSSIAN REAL GDP, REAL EXCHANGE RATE AND OIL PRICES

This paper considers an application of the Markov switching vector error correction model to the analysis of the long-run and the short-run dependence of Russian real GDP and real exchange on oil prices. An algorithm for estimation of the model with a priori information on a state of hidden Markov chain in some periods of time is provided. It is shown that for the period of 1999–2018 two different regimes are well defined: with a slow adjustment of real exchange rate and a sharp reaction of GDP in response to oil price shock and with a fast adjustment of real exchange rate and a slow adjustment of GDP in response to shock. We have concluded that floating ruble exchange rate is a natural stabilizer of the Russian economic activity.Keywords: Russian economy, GDP, real exchange rate, oil prices, error correction model, Markov switching model.JEL Classifications: С22, C51, E52, F31, F41DOI: https://doi.org/10.32479/ijeep.10667

A Markov Switching Cointegration Analysis of the CDS‐Bond Basis Puzzle

We investigate the long-run equilibrium relationship between credit default swap (CDS) premia and bond spreads for 65 U.S. corporate entities and 6 major banks over the period April 2011 – February 2018. Standard regression methods reveal that in 40 out of 71 entities, the two series fail to be cointegrated, which is puzzling because it represents a violation of the efficient market hypothesis. Differently from the previous literature, we estimate a Markov switching vector error correction model to capture the fact that regimes may be characterize the adjustment mechanism and the short-term dynamics between the spread series. We use this framework to investigate how the two markets contribute to the price discovery of credit risk. We find that there are many entities that switch between a regime where the adjustment to the long-run cointegrating relationship does not take place and a regime where one between the CDS or the bond markets leads the price discovery. Finally, we investigate whether the industry or other firm characteristics, such as the rating, the leverage, and the capital structure, may be relevant to determine which of the two markets is leads in the price discovery process.

A Markov-Switching Model for Indian Stock Price and Volume

Using weekly data from the Indian stock market, we examine the relationship between stock price and trading volume. Our framework is Markov Switching-Vector Error Correction Model (MS-VECM). We justify the use of nonlinear model using the Brock, Dechert and Scheinkman (BDS) test and the information criteria. The long-run dynamics are characterised by one cointegrating vector relating the price to trading volume. We find that stock price is weakly exogenous only in the high volatility regime. The MS-VECM with two regimes provides a good characterisation of the Indian stock market and performs well relative to the other linear and nonlinear models. JEL Classification: C32, G12, E32

Investigating the Price Transmission Mechanisms of Greek Fresh Potatoes, Tomatoes and Cucumbers Markets

Abstract This study investigates the price transmission mechanisms between the producer and the consumer for three major Greek agricultural products: fresh potatoes, tomatoes and cucumbers. The empirical analysis uses a Markov Switching Vector Error Correction model which accounts for asymmetric responses of the producer and the consumer to price increases and decreases. The asymmetric effects are tested with in-sample as well as out-of-sample measures for each state. The response of the producer and the consumer to long-run deviations from the equilibrium and to lagged price changes is investigated along with the nature of the price shocks for each state. The empirical results show that potatoes and cucumbers give rise to similar price mechanisms even though the underlying characteristics of these two markets are different. Moreover, the empirical analysis shows that tomatoes and cucumbers result in different price relationships between the producer and the consumer despite the similar market characteristics.

A Markov Switching Vector Error Correction Model on Oil Price and Gold Price Effect on Stock Market Returns

Stock market index represent a country growth and always as an interest for economist and statisticians. In this paper, the effect of oil price and gold price on stock market index on Malaysia, Singapore, Thailand and Indonesia are investigated and a two-regime Markov Switching Vector Error Correction model is used to examine the nonlinear properties model. Moreover, a two regime mean adjusted Markov Switching Vector Error Correction model is used in the study to capture the filtered and smoothed probabilities of the time series sequence in the economic model. Results found that the oil price and gold price affect the movement of the Malaysia, Singapore, Thailand and Indonesia stock market index and there is an asymmetric cycle since 97% of the total sample size is recorded in the growth state.

Modeling the Natural Gas Spot-futures Markets as a Regime Switching Vector Error Correction Model

While using the jump diffusion system controlled by the Markov-switching technique, this study designs a generalized dynamic conditional correlation (GDCC) time-varying transition probabilities (TVTP) Markov-switching vector error correction model (MRS-VECM) in which the parameters of the error correction term and the spot-futures correlations switches according the phase of volatility regime to reexamine the dynamics of the relationship between the natural gas spot and futures prices. The data used in this study is unleaded gasoline traded on the New York Mercantile Exchange, covering the period November 2, 1994 to June 2, 2009, resulting in 3,642 daily observations. Our empirical results are consistent with the following notions. First, the gasoline market reacts more quickly to the spot-futures price discrepancy when a high variance regime is encountered. Second, the spot-futures correlations vary considerably across various variance states, and the correlation for the high variance state is significantly lower than that of the low variance state. Third, the state-varying hedge ratios by our GDCC-TVTP-MRS-VECM could provide a more efficient futures hedging strategy when compared to conventional hedging models, such as the naïve, VECM, constant conditional correlation multivariate generalized ARCH (CCC-MVGARCH) and dynamic conditional correlation multivariate generalized ARCH (DCC-MVGARCH) models. Finally, the lagged spot-futures price deviation functions as an indicator for the variance-turning process.

A Markov regime switching approach for hedging energy commodities

This paper estimates constant and dynamic hedge ratios in the New York Mercantile Exchange oil futures markets and examines their hedging performance. We also introduce a Markov regime switching vector error correction model with GARCH error structure. This specification links the concept of disequilibrium with that of uncertainty (as measured by the conditional second moments) across high and low volatility regimes. Overall, in and out-of-sample tests indicate that state dependent hedge ratios are able to provide significant reduction in portfolio risk.

Regime dependence between the official and parallel foreign currency markets for US dollars in Greece

This paper models the short-run as well as the long-run relationship between the parallel and official markets for US dollars in Greece in a bivariate Markov Switching Vector Error Correction Model (MS-VECM) framework. Modelling exchange rates within this context can be motivated by the fact that the change in regime should be considered as a random event and not predictable. The results show that linearity is rejected in favour of a MS-VECM specification, which forms statistically an adequate representation of the data. Two regimes are implied by the model; the high volatility regime and the low volatility one and they provide quite accurately the state of volatility associated with economic and political events that took place in Greece during the 1970s and 1980s. Another implication is that there is evidence of regime clustering. Finally, Granger causality seems to be regime independent when we consider the hypothesis that official rate causes the parallel rate but it is regime dependent when we consider the opposite direction.

Real interest rates linkages between the USA and the UK in the postwar period

This paper addresses the issue of real interest rate linkages between the UK and the USA during the postwar period. We use a bivariate Markov switching vector error correction model, which accounts for both the regime switches in the real interest rates and their long-run cointegration properties over that period. We find strong evidence of two volatility regimes, namely a high-volatility and a low-volatility regime, jointly characterizing the US and the UK real interest rates. Evidence is found of high-volatility regime dependence between the two real interest rates. In addition, there is evidence of regime-dependent Granger causality: the US real interest rate Granger causes the UK only in the regime of high volatility. Copyright © 2005 John Wiley & Sons, Ltd.

Real Interest Rates Linkages Between the US and UK in the Postwar Period

This paper addresses the issue of real interest rate linkages between the UK and the US during the postwar period. We use a bivariate Markov switching vector error correction model, which accounts for both the regime switches in the real interest rates and their long-run cointegration properties over that period. We find strong evidence of two volatility regimes, namely a high volatility and a low volatility regime, jointly characterising the US and the UK real interest rates. Evidence is found of high volatility regime dependence between the two real interest rates. In addition, there is evidence of regime-dependent Granger causality: the US real interest rate Granger causes the UK only in the regime of high volatility. Regime-dependent impulse response analysis reveals that during the high volatility regime, the responses of each real interest rate to an exogenous shock to the other are more persistent than in the low volatility regime.