European equity market integration and joint relationship of conditional volatility and correlations

We analyse the integration patterns of seven leading European stock markets from 1990 to 2013 using daily data and mismatched monthly macroeconomic data. To study the mismatch of data frequencies we use the DCC-MIDAS (Dynamic Conditional Correlation – Mixed Data Sampling) technique developed by Colacito, Engle and Ghysels (Journal of Econometrics, 2011). We benchmark European integration patterns against the German stock market. The reported integration patterns show a clear divide between large and (relatively) small equity markets' short run and long run return correlations: the small markets display higher short run European convergences than the large markets and vice versa. The across-the-board divergence from Greek risk, during the crisis period, is the most unambiguous conclusion of our study. During this period, cross-country joint relationships of conditional variances and return correlations – a ‘convergence of risks’ resulting in global/regional contagious spillovers – are typically positive. Only exceptions are the German stock market's joint relationships.     

Emerging Stock Markets and International Asset Pricing

This article investigates whether emerging stock markets arenow part of the global financial market and characterizes returnbehavior in these markets. Tests of the conditional InternationalCapital Asset Pricing Model (ICAPM) reveal that eighteen ofthe twenty largest emerging markets were integrated with theworld market between December 1984 and December 1991, but thatmany of the same markets reject the model when data for 1977–84are used. These results suggest that large capital inflows fromindustrial economies, beginning in the late 1980s, caused pricesin emerging markets to reflect covariance risk with the worldportfolio, thus inducing their consistency with the ICAPM.     

Looking for risk premium and contagion in Asia-Pacific foreign exchange markets

This article tests pure contagion effects among four Asian foreign exchange markets, namely, Japan, Hong Kong, Singapore, and Taiwan during the 1997 Asian crisis. A conditional version of international capital asset pricing model (ICAPM) in the absence of purchasing power parity (PPP) is used to control for economic fundamentals or systematic risks. The empirical results show strong contagion effects in both conditional means and volatilities of those markets after systematic risks have been accounted for. Specifically, the contagion-in-mean effects are mainly driven by the past return shocks in Hong Kong, Singapore, and Taiwan. As for contagion in volatility, the lead/lag relationships appear to be multidirectional among Japan, Singapore, and Taiwan, but between Hong Kong and Singapore, and between Hong Kong and Taiwan, they are unidirectional, with Hong Kong playing the dominant role in generating negative volatility shocks. In addition, the conditional ICAPM with asymmetric multivariate general autoregressive conditional heteroscedastic in mean (MGARCH(1,1)-M) structure is able to explain/predict on average 17.28% of the return variations in those markets. Therefore, this study provide a further evidence that the time-varying risk premium is a very strong candidate in explaining the predictable excess return puzzle [Lewis, K. K. (1994). Puzzles in international financial markets. NBER Working Paper No. 4951] since the risk premia founded in this article are not only statistically significant but also economically significant.     

Market integration and currency risk in Asian emerging markets

Most of the Asian emerging stock markets started to liberalize their markets in 1990s. In this paper, I examine whether those markets have become integrated with world stock market since the 1990s by estimating and testing a dynamic version of international CAPM (ICAPM) in the absence of purchasing power parity (PPP) using a parsimonious multivariate GARCH-in-Mean (MGARCH-M) approach. I also investigate to what extent the liberalization process has affected the cost of capital and price volatility for each market. The empirical results show that Philippines was segmented from the world stock market before its liberalization date, but no evidence of market segmentation is found for the other five markets (India, Korea, Malaysia, Taiwan, and Thailand) before their liberalization dates. However, all six markets have become integrated after opening up their markets to foreign investors. In addition, the estimated risk premia are lower after the liberalization, indicating that the liberalization process has reduced the cost of capital for their domestic firms. Moreover, there is no evidence of extra market volatility introduced by capital market liberalization, and on the contrary, the markets have become more stabilized through the liberalization process.     

Measures of equity home bias puzzle

The paper develops measures of home bias for 42 countries over the period 2001 to 2011 by employing various models: international capital asset pricing model (ICAPM), classical mean-variance, minimum-variance, Bayes–Stein, Bayesian, and multi-prior correction to Bayesian. ICAPM country portfolio weights are computed relative to world market capitalization. Bayesian model allows for various degrees of mis-trust in the ICAPM and multi-prior model's investors' ambiguity aversion. Mean-variance computes optimal weights by sample estimates of mean and covariance matrix of sample return and Bayes–Stein improves precision associated with estimating the expected return of each asset. The paper finds that, for few countries, there is not much change in home bias measures using various models. Foreign listing, idiosyncratic risk, beta, natural resources rents, size, global financial crisis and institutional quality have significant impact on home bias. There are policy implications associated with home bias.     

Unbiased estimation of expected return using CAPM

Estimation of expected return is required for many financial decisions. For example, an estimate for cost of capital is required for capital budgeting and cost of equity estimates are needed for performance evaluation based on measures such as EVA. Estimates for expected return are often based on the Capital Asset Pricing Model (CAPM), which states that expected excess return (expected return minus the risk-free rate) is equal to the asset's sensitivity to the world market portfolio (β) times the risk premium on the “world market portfolio” (the market risk premium). Since the world market portfolio, by definition, contains all assets in the world, it is not observable. As a result, an estimate for expected return is commonly obtained by taking an estimate for β based on some index (as a proxy for the world market portfolio) and an estimate for the market risk premium based on a potentially different index and multiplying them together. In this paper, it is shown that this results in a biased estimate for expected return. This is undesirable since biased estimates lead to misallocation of funds and biased performance measures. It is also shown in this paper that the straightforward procedure suggested by Fama and MacBeth [J. Financ. Econ. 1 (1974) 43] results in an unbiased estimate for expected return. Further from the analysis done, it follows that, for an unbiased estimate, it does not matter what proxy is used, as long as it is used correctly an unbiased estimate for expected return results.     

Time-varying risk premia and the cross section of stock returns

This paper develops and estimates a heteroskedastic variant of Campbell’s [Campbell, J., 1993. Intertemporal asset pricing without consumption data. American Economic Review 83, 487–512] ICAPM, in which risk factors include a stock market return and variables forecasting stock market returns or variance. Our main innovation is the use of a new set of predictive variables, which not only have superior forecasting abilities for stock returns and variance, but also are theoretically motivated. In contrast with the early authors, we find that Campbell’s ICAPM performs significantly better than the CAPM. That is, the additional factors account for a substantial portion of the two CAPM-related anomalies, namely, the value premium and the momentum profit.     

Exposure to the world and trading-bloc risks: A multivariate capital asset pricing model

This paper employs a capital asset pricing model that incorporates both world and trading-bloc factors to show that the recent trend of trade regionalism has led to segmentation of world stock markets. The model is developed within a multivariate GARCH framework. The conditional time-varying betas are derived to examine the dynamics of risk exposures to the world and trading-bloc factors. The results show risk exposure behaviour that is not revealed using static risk estimates.     

Regional integration of the East Asian stock markets: An empirical assessment

The aim of this paper is to study the dynamics of regional financial integration in East Asia over the 1990:01–2012:08 period. To this end, we use the international capital asset pricing model (ICAPM) to assess the evolution of financial market integration through time and evaluate their risk premia. We also construct an Asian currency basket in order to obtain a reference currency in this area. Our empirical analysis is based on the multivariate GARCH-DCC approach with time-varying correlations. Our results show that the East Asian stock markets were partially segmented (except for Japan) within their region until approximately 2008. However, the last years are characterized by an upward trend in the regional integration of stock markets. Our findings also show that the risk premium related to regional stock markets is significant for all countries.     

Time-Varying Expected Returns in International Bond Markets

This article examines the predictable variation in long-maturity government bond returns in six countries. A small set of global instruments can forecast 4 to 12 percent of monthly variation in excess bond returns. The predictable variation is statistically and economically significant. Moreover, expected excess bond returns are highly correlated across countries. A model with one global risk factor and constant conditional betas can explain international bond return predictability if the risk factor is proxied by the world excess bond return, but not if it is proxied by the world excess stock return.     

Estimating the Intertemporal Risk–Return Tradeoff Using the Implied Cost of Capital

We argue that the implied cost of capital (ICC), computed using earnings forecasts, is useful in capturing time variation in expected stock returns. First, we show theoretically that ICC is perfectly correlated with the conditional expected stock return under plausible conditions. Second, our simulations show that ICC is helpful in detecting an intertemporal risk–return relation, even when earnings forecasts are poor. Finally, in empirical analysis, we construct the time series of ICC for the G–7 countries. We find a positive relation between the conditional mean and variance of stock returns, at both the country level and the world market level.     

Time-varying risk premia in foreign exchange and equity markets: evidence from Asia–Pacific countries

This paper examines the validity of the risk premia hypothesis in explaining deviations from Uncovered Interest Parity (UIP) and the role of deviations from Purchasing Power Parity (PPP) in the pricing of foreign exchange rates and equity securities in five Asia–Pacific countries and the US. Using weekly data from 1 January, 1988 to 27 February, 1998, I find that conditional variances are not related to the deviations from UIP in any statistical sense based on an univariate GARCH(1,1)-M model. As I consider both foreign exchange and equity markets together and test a conditional international CAPM (ICAPM) in the absence of PPP, I cannot reject the model based on the J-test by Hansen (Econometrica 50 (1982), 1029–1054) and find significant time-varying foreign exchange risk premia present in the data. This empirical evidence supports the notion of time-varying risk premia in explaining the deviations from UIP. It also supports the idea that the foreign exchange risk is not diversifiable and hence should be priced in both markets.     

The relationship between risk and expected return in Europe

We employ MIDAS (mixed data sampling) to study the risk–expected return trade-off in several European stock indices. Using MIDAS, we report that in most indices there is a significant positive relationship between risk and expected return. This strongly contrasts with the result we obtain when we employ both symmetric and asymmetric GARCH models for conditional variance. We also find that asymmetric specifications of the variance process within the MIDAS framework improve the relationship between risk and expected return. As an additional application, we analyze the extent to which European stock markets are integrated, which is a particularly relevant issue, especially following the launch of the Euro in January 1999. Finally, we propose a bivariate MIDAS specification to test the pricing significance of the hedging component within an intertemporal risk–return trade-off with multiple European market indices.     

Uncovering the Risk–Return Relation in the Stock Market

There is ongoing debate about the apparent weak or negative relation between risk (conditional variance) and expected returns in the aggregate stock market. We develop and estimate an empirical model based on the intertemporal capital asset pricing model (ICAPM) that separately identifies the two components of expected returns, namely, the risk component and the component due to the desire to hedge changes in investment opportunities. The estimated coefficient of relative risk aversion is positive, statistically significant, and reasonable in magnitude. However, expected returns are driven primarily by the hedge component. The omission of this component is partly responsible for the existing contradictory results.     

The risk–return relations in the Singapore stock market

This paper examines the risk–return relations in the Singapore stock market for the period April 1986 to December 1998. Though beta is significantly related to realized returns, the explanatory power is low. Adding other stock characteristics such as skewness and kurtosis provides limited incremental benefits. However, when a conditional framework based on up and down markets is introduced, the explanatory power increases more than 100 times and there is a significant positive (negative) relation between beta and returns when the market excess returns are positive (negative). The same relation applies when unsystematic risk, total risk and kurtosis are added separately to the beta–return relation during up and down markets with increased explanatory power. Our results indicate that other stock characteristics in addition to beta are also important in pricing risky assets and investors do not hold diversified portfolios. Our results are also checked and compared with another conditional model with time-varying betas conditional on a set of economic variables.     

The relationship between stock returns and volatility in international stock markets

This study examines the relationship between expected stock returns and volatility in the 12 largest international stock markets during January 1980 to December 2001. Consistent with most previous studies, we find a positive but insignificant relationship during the sample period for the majority of the markets based on parametric EGARCH-M models. However, using a flexible semiparametric specification of conditional variance, we find evidence of a significant negative relationship between expected returns and volatility in 6 out of the 12 markets. The results lend some support to the recent claim [Bekaert, G., Wu, G., 2000. Asymmetric volatility and risk in equity markets. Review of Financial Studies 13, 1–42; Whitelaw, R., 2000. Stock market risk and return: an empirical equilibrium approach. Review of Financial Studies 13, 521–547] that stock market returns are negatively correlated with stock market volatility.     

The empirical relationship between risk and return: evidence from the UK stock market

Previous studies reach no consensus on the relationship between risk and return using data from one market. We argue that the world market factor should not be ignored in assessing the risk-return relationship in a partially integrated market. Applying a bivariate generalized autoregressive conditional heteroscedasticity in mean (GARCH-M) model to the weekly stock index returns from the UK and the world market, we document a significant positive relationship between stock returns and the variance of returns in the UK stock market after controlling for the covariance of the UK and the world market return. In contrast, conventional univariate GARCH-M models typically fail to detect this relationship. Nonnested hypothesis tests supplemented with other commonly used model selection criteria unambiguously demonstrate that our bivariate GARCH-M model is more likely to be the true model for UK stock market returns than univariate GARCH-M models. Our results have implications for empirical assessments of the risk-return relationship, expected return estimation, and international diversification.     

MEAN AND VOLATILITY SPILLOVERS ACROSS MAJOR NATIONAL STOCK MARKETS: FURTHER EMPIRICAL EVIDENCE

This paper provides additional insight into the nature and degree of interdependence of stock markets of the United States, Japan, the United Kingdom, Canada, and Germany, and it reports the extent to which volatility in these markets influences expected returns. The analysis uses the multivariate GARCH-M model. Although they are considered weak, statistically significant mean spillovers radiate from stock markets of the U.S. to the U.K., Canada, and Germany, and then from the stock markets of Japan to Germany. No relation is found between conditional market volatility and expected returns. Strong time-varying conditional volatility exists in the return series of all markets. The own-volatility spillovers in the U.K. and Canadian markets are insignificant, supporting the view that conditional volatility of returns in these markets is “imported” from abroad, specifically from the U.S. Significant volatility spillovers radiate from the U.S. stock market to all four stock markets, from the U.K. stock market to the Canadian stock market, and from the German stock market to the Japanese stock market. The results are robust and no changes occur in the correlation structure of returns over time.     

The impact of monetary policy surprises on asset return volatility: the case of Germany

This paper investigates the impact of monetary policy surprises by the FED or Bundesbank/ECB on the return volatility of German stocks and bonds using a GARCH-M model. We show that stock return volatility is susceptible to monetary policy surprises in the United States, whereas monetary policy surprises in the Euro zone matter for bond return volatility. These findings are robust for other Euro zone stock markets, but not significant for other Euro zone bond markets. The empirical evidence also suggests that monetary policy surprises have larger effects on German stock return volatility in bear markets than in bull phases. Moreover, our results support the claim that stock return volatility can be negatively correlated with stock returns, contradicting predictions made by many asset pricing models (e.g., CAPM or ICAPM) and the empirical finding of an insignificant relationship often reported in the literature.

Time-varying risk The case of the American computer industry

A bivariate GARCH-in-mean model for individual stock returns and the market portfolio is designed to model volatility and to test the conditional Capital Asset Pricing Model versus the conditional Residual Risk Model. We find that a univariate model of volatility for individual stock returns is misspecified. A joint modelling of the market return and the individual stock return shows that a major force driving the conditional variances of individual stocks is the history contained in the market return variance. We find that a conditional residual risk model, where the variance of the individual stock return is used to explain expected returns, is preferred to a conditional CAPM. We propose a partial ordering of securities according to their market risk using first and second order dominance criteria.