Risk contagion among international stock markets

We develop a stochastic volatility model with jumps in returns and volatility to analyze the risk spillover from the U.S. market and the regional market to a number of European countries’ equity markets. The key advantage of this approach compared to the earlier approaches is that it enables us to identify jumps and investigate spillover of extreme events across borders. We find that a large part of the jumps in the local markets are due to the U.S. market and the regional market. The U.S. contribution to the variances is in general below the contribution from the regional market. In general, we observe an increasing integration during the last two decades, which, to some extent, can be related to the advancement of the European Union. Furthermore, we show that the identification of the jumps can be used as a useful signal for portfolio reallocation.     

Financial globalization, financial crises and contagion

Two observations suggest that financial globalization played an important role in the recent financial crisis. First, more than half of the rise in net borrowing of the U.S. non-financial sectors since the mid-1980s has been financed by foreign lending. Second, the collapse of the U.S. housing and mortgage-backed-securities markets had worldwide effects on financial institutions and asset markets. Using an open-economy model where financial intermediaries play a central role, we show that financial integration leads to a sharp rise in net credit in the most financially developed country and to large asset price spillovers of country-specific shocks to bank capital. The impacts of these shocks on asset prices are amplified by bank capital requirements based on mark-to-market.     

Testing stock market contagion properties between large and small stock markets

Review of Quantitative Finance and Accounting - The heterogeneity of large and small stock market structures results in different degrees of cross-market contagion. The causality test reveals that...     

Return predictability in African stock markets

This paper models weekly index returns adjusted for thin trading as a nonlinear autoregressive process with conditional heteroscedasticity to investigate the weak-form pricing efficiency of 11 African stock markets. Specifically, the use of the EGARCH-M model allows us to capture how conditional volatility affects the pricing process without imposing undue restrictions on the parameters of the conditional variance equation. On the basis of such a robust model, we are able to reject the evidence in prior studies that the Nigerian stock market is weak-form efficient. On the other hand, we confirm extant results that the markets in Egypt, Kenya, and Zimbabwe are efficient while that of South Africa is not weak-form efficient. We also generate new results, which point to the efficiency of the stock markets in Mauritius and Morocco, while the markets in Botswana, Ghana, Ivory Coast, and Swaziland are not consistent with weak-form efficiency.     

Political crises and the stock market integration of emerging markets

This paper investigates the role of political crises in explaining the degree of stock market integration in emerging markets over the period 1991-2006. Using the International Crisis Behavior database, which contains detailed information on political crises around the world, and employing data on more than 15,500 firms, we assess whether political crises affect stock market integration in 19 emerging markets in South and East Asia, Latin America, and Central and Eastern Europe. We conclude that crises with certain characteristics generally reduce the level of stock market integration in these regions. In particular, the beginning of a political crisis, its severity, the involvement of the US in the conflict, and the number of parties involved in a crisis all have impacts on the level of stock market integration in these markets.     

Crude oil shocks and African stock markets

In this paper, we investigate the impact of crude oil shocks on selected African stock markets using a Structural Vector Autoregressive model and a two-state regime smooth transition regression framework on monthly data from January 2000 to July 2018. The study is timely given the fast-growing energy sector and stock markets in Africa as well as the place of Africa in international trade. Selected markets are classified into oil-exporting (Nigeria, Tunisia, and Egypt) and oil-importing (Botswana, South Africa, Kenya, and Mauritius). The key findings are as follows: global demand shock does not really matter in oil-importing countries; there is little evidence that oil supply shock affects the real stock return for oil-exporting and oil-importing countries; oil-specific shock is significant for most countries investigated; negative price shocks have more impact than positive price shocks. The findings from this study have important implications for investors whose portfolios may comprise of assets from African stock markets and crude oil. Given the importance of oil in the global market, one would typically avoid equities that suffer from its shock. This study provides the indicators to inform that decision.     

Financial crises and the dynamics of the spillovers between the U.S. and BRICS stock markets

We examine the spillover dynamics between the U.S. and BRICS stock markets using the multivariate DECO-GJR-GARCH model and spillover index method. We identify time variations in volatility equicorrelation and significant dynamic spillovers between these stock markets, as well as an increased impact of uncertainty on spillovers. Spillovers between markets intensify after the inception of the global financial crisis and subsequent European sovereign debt crisis. We also find, following the commencement of the crisis periods, that the U.S., Brazilian, and Chinese markets are net volatility transmitters, whereas the Russian, Indian, and South African markets are net recipients. These results shed new light on the information transmission channels between the U.S. and BRICS stock markets.     

The impact of the 2008 and 2010 financial crises on the Hurst exponents of international stock markets: Implications for efficiency and contagion

This study analyzes how the 2008 and 2010 financial crises, which began in the US and Greece respectively, affected the Hurst exponents of index returns of the stock markets of Belgium, France, Greece, Japan, the Netherlands, Portugal, the UK and US. We perform two innovative statistical tests for this purpose. The first assesses whether the returns exhibit a long memory in the pre-crisis and crisis periods and determines the extent to which the Hurst exponents, calculated with the multifractal detrended moving average technique (MFDMA), differ from the tranquil to the crisis periods. The second test uses copula models to assess whether the correlation between the local Hurst exponents of the markets where the crises originated and those of the other markets increased due to the crises. The results of the first test suggest that although most of the returns exhibit a long memory in the 2008 crisis period, this is not the case in either the pre-crisis or the 2010 crisis periods. These findings shed light on the dynamics of market efficiency. The results of the second test show a significant increase in correlation between the local Hurst exponents of several markets, suggesting the existence of financial contagion. We observed that the 2008 crisis had a greater impact on the memory properties of stock returns than the 2010 financial crisis.     

Financial crises in efficient markets: How fundamentalists fuel volatility

When a financial crisis breaks out, speculators typically get the blame whereas fundamentalists are presented as the safeguard against excessive volatility. This paper proposes an asset pricing model where two types of rational traders coexist: short-term speculators and long-term fundamentalists, both sharing the same information set. In this framework, excess volatility not only exists, but is actually fueled by fundamental trading. Consequently, efficient markets are more volatile with a few speculators than with many speculators. Regulators should therefore be aware that efforts to limit rational speculation might, surprisingly, end up increasing volatility.     

The wandering weekday effect in major stock markets

This paper reports a wandering weekday effect: the pattern of day seasonality in stock market returns is not fixed, as assumed in the Monday or weekend effects, but changes over time. Analysing daily closing prices in eleven major stock markets during 1993–2007, our results show that the wandering weekday is not conditional on average returns in the previous week (the “twist” in the Monday effect). Nor does it diminish through the period of analysis. The results have important implications for market efficiency, and help to reconcile mixed findings in previous studies, including the reported disappearance of the weekday effect in recent years.     

Deconstructing the Nasdaq bubble: A look at contagion across international stock markets

Share prices for the technology, media, and telecommunication (TMT) sector experienced phenomenal growth and decline at the turn of this century in the U.S. and many other OECD economies. We investigate whether contagion occurred from the U.S. to other international stock markets after the Nasdaq bubble collapsed. Results document a significant structural break in comovements between the international TMT sectors, and suggest that the collapse of the stock market in more than a dozen countries is tied to close sectoral links (particularly in TMT), and cannot be attributed to widespread contagion. We also show the importance of modeling the intrinsic heteroskedasticity in the data using a GARCH framework for inferences on contagion.     

Volatility and cross correlation across major stock markets

Several papers have documented the fact that correlations across major stock markets are higher when markets are more volatile—this is done by comparing unconditional correlations over sub-periods or by using conditional correlations that are time varying. In this paper we examine the relation between correlation and variance in a conditional time and state varying framework. We use a switching ARCH (SWARCH) technique that does two things. One, it enables us to model variance as state varying. Two, a bivariate SWARCH model allows us to go from conditional variance to state varying covariances and correlations and hence test for differences in correlations across variance regimes. We find that the correlations between the U.S. and other world markets are on average 2 to 3.5 times higher when the U.S. market is in a high variance state as compared to a low variance regime. We also find that, compared to a GARCH framework, the portfolio choices resulting from our SWARCH model lead to higher Sharpe ratios.     

Asymmetric semi-volatility spillover effects in EMU stock markets

The aim of this paper is to quantify the strength and the direction of semi-volatility spillovers between five EMU stock markets over the 2000–2016 period. We use upside and downside semi-volatilities as proxies for downside risk and upside opportunities. In this way, we aim to complement the literature, which has focused mainly on the contemporaneous correlation between positive and negative returns, with the evidence of asymmetry also in semi-volatility transmission. For this purpose, we apply the Diebold and Yilmaz (2012) methodology, based on a generalized forecast error variance decomposition, to downside and upside realized semi-volatility series. While the analysis of Diebold and Yilmaz (2012) is based on a stationary VAR, we take into account the long-memory behaviour of the series, by using the multivariate extension of the HAR model (named VHAR model). Moreover, we cast light on how the choice of the normalization scheme can bias the net-spillover computation in a full sample as well as in a rolling sample analysis.     

Integration of emerging stock markets with global stock markets

Financial integration for emerging economies should be seen as a long-term objective. In this paper, we examine stock market integration among five selected emerging stock markets (Brazil, China, Mexico, Russia and Turkey) and developed markets of the US, UK and Germany. The bounds testing approach to cointegration and error-correction modeling are used on monthly data from January 2001 to December 2014 to determine the short-run and long-run relationship between emerging stock market returns and the returns of the developed stock markets. The results show evidence of the existence of short-run integration among stock markets in emerging countries and the developed markets. However, the long-run coefficients for stock market returns in all emerging countries show a significant relationship only with Germany stock market return. The empirical findings in this study have important implications for academicians, international investors, and policymakers in emerging markets.     

Correlation in price changes and volatility of major Latin American stock markets

This paper seeks to investigate the short-run dynamics between five major Latin American stock markets (Argentina, Brazil, Chile, Colombia and Mexico). Unlike previous research on these markets, the joint distribution of stock returns is estimated as a vector autoregression (VAR) with innovations following an exponential GARCH process. Our study is carried out using closing stock market prices covering the period 25 May 1992 to 16 May 1997. The results revealed that these countries have significant first and second moment time dependencies. In general, the markets of these countries exhibit stronger volatility than mean spillovers. Further, our results indicate that these markets exhibit stronger volatility spillovers than other regions of the world. In view of these dependencies, the conditional correlations between these markets are different from their conventional simple counterparts. Since the correlation is the catalyst in portfolio diversification and an essential parameter in the calculation of the cost of capital, we anticipate that international investors and corporate managers will find our results very interesting.     

Co-movements of sector index returns in the world's major stock markets in bull and bear markets: Portfolio diversification implications

In this paper, principal components analysis and Granger causality tests are used to study the portfolio diversification implications of the co-movements of sector indexes in the US, UK, German, French, and Japanese stock markets in bull and bear markets. We find that, in a bull market, investors can obtain more benefit with global diversification than with domestic diversification even if they invest in the same sector in different countries as opposed to investing in different sectors within the same country. In a bear market, the sectors of different countries tend to be more closely correlated and country diversification opportunities are limited.     

Firm ratings, momentum strategies, and crises: evidence from the US and Taiwanese stock markets

This paper investigates whether there is a link between momentum profitability and firm ratings. We follow traditional and practical (non-) investment-grade classifications to divide into three rating groups, high, median, and non investment-grade group (HIG, MIG, and NIG) since firm ratings express risk in relative rank order to contain valuable information. This study considers the US and Taiwanese stock markets. We find that firm ratings momentum strategies can even earn positive profits, larger than na?ve momentum, supporting that firm ratings can be used to strengthen naive momentum effects. By comparisons, the US firm ratings momentum with NIG produces larger profits than HIG but opposite in direction and V-shaped pattern in Taiwan. With an examination of crises on firm ratings momentum, we find that firm ratings momentum indeed helps increase the payoff during (non-)crises although firm ratings momentum profits should be strong following non-crises states and weak following crises states. However, firm ratings momentum profits partially result from the predictability of business cycle, calendar months, and information asymmetries. Our results highlight the critical importance of using firm ratings screens in empirical momentum studies.     

Forecasting financial crises and contagion in Asia using dynamic factor analysis

In this paper we use principal components analysis to obtain vulnerability indicators able to predict financial turmoil. Probit modelling through principal components and also stochastic simulation of a Dynamic Factor model are used to produce the corresponding probability forecasts regarding the currency crisis events affecting a number of East Asian countries during the 1997–1998 period. The principal components model improves upon a number of competing models, in terms of out-of-sample forecasting performance.