Markov-Switching GARCH Modelling of Value-at-RisK

This paper proposes an asymmetric Markov regime-switching (MS) GARCH model to estimate value-at-risk (VaR) for both long and short positions. This model improves on existing VaR methods by taking into account both regime change and skewness or leverage effects. The performance of our MS model and single-regime models is compared through an innovative backtesting procedure using daily data for UK and US market stock indices. The findings from exceptions and regulatory-based tests indicate the MS-GARCH specifications clearly outperform other models in estimating the VaR for both long and short FTSE positions and also do quite well for S&P positions. We conclude that ignoring skewness and regime changes has the effect of imposing larger than necessary conservative capital requirements

Markov Switching Risk Premium and the term structure of interest rates. Empirical evidence from US post-war interest rates

This paper considers the basic present value model of interest rates under rational expectations with two additional features. First, following McCallum (1994), the model assumes a policy reaction function where changes in the short-term interest rate are determined by the long-short spread. Second, the short-term interest rate and the risk premium processes are characterized by a Markov regime-switching model. Using US post-war interest rate data, this paper finds evidence that a two-regime switching model fits the data better than the basic model. The estimation results also show the presence of two alternative states displaying quite different features.term-structure, risk premium, Markov regime-switching

Contagion between United States and european markets during the recent crises

The main objective of this paper is to detect the existence of financial contagion between the North American and European markets during the recent crises. To accomplish this, the relationships between the US and the Euro zone stock markets are considered, taking the daily equity prices of the Standard and Poor’s 500 as representative of the United States market and for the European market, the five most representative indexes. Time Series Factor Analysis (TSFA) procedure has allowed concentrating the information of the European indexes into a unique factor, which captures the underlying structure of the European return series. The relationship between the European factor and the US stock return series has been analyzed by means of the dynamic conditional correlation model (DCC). Once the DCC is estimated, the contagion between both markets is analyzed. Finally, in order to explain the sudden changes in dynamic US-EU correlation, a Markov switching model is fitted, using as input variables the macroeconomic ones associated with the monetary policies of the US as well as those related to uncertainty in the markets. The results show that there was contagion between the United States and European markets in the Subprime and Global Financial crises. The two-regime Markov switching model has helped to explain the variability of the pair-wise correlation. The first regime contains mostly the financially stable periods, and the dynamic correlations in this regime are explained by macroeconomic variables and other related with monetary policies in Europe and US. The second regime is explained mainly by the Federal Funds rate and the evolution of the Euro/US Exchange rate.Peer ReviewedPostprint (published version

Extending dynamic segmentation with lead generation: A latent class Markov analysis of financial product portfolios

A recent development in marketing research concerns the incorporation of dynamics in consumer segmentation.This paper extends the latent class Markov model, a suitable technique for conducting dynamic segmentation, in order to facilitate lead generation.We demonstrate the application of the latent Markov model for these purposes using a database containing information on the ownership of twelve financial products and demographics for explaining (changes in) consumer product portfolios.Data were collected in four bi-yearly measurement waves in which a total of 7676 households participated.The proposed latent class Markov model defines dynamic segments on the basis of consumer product portfolios and shows the relationship between the dynamic segments and demographics.The paper demonstrates that the dynamic segmentation resulting from the latent class Markov model is applicable for lead generation.market segmentation;Markov chains;marketing;demography;measurement

TESTING HABITS IN AN ASSET PRICING MODEL

We develop a model of asset pricing assuming that investor's behavior is habit forming. The model predicts that the effect of consumption growth shocks on the risk premium depends on the business cycle phase of the economy. This empirical implication is tested with a Markovswitching VAR model on the US postwar economy. The results show that the response of the risk premium to shocks to consumption is not significantly different over the business cycle phases of the economy. We interpret this as evidence against the habit formation hypothesis of the investor's behavior.Habit formation, Equity premium, Business cycle, Markovswitching VAR models

Risk assessment in a Markov switching framework.

Framework; Risk; Risk assessment;