Testing stock market linkages for Poland and Hungary: A multivariate GARCH approach

This paper examines the linkages between the emerging stock markets in Warsaw and Budapest and the established markets in Frankfurt and the U.S. By using a four-variable asymmetric GARCH-BEKK model, we find evidence of returns and volatility spillovers from the developed to the emerging markets. However, as the estimated time-varying conditional covariances and the variance decompositions indicate limited interactions among the markets, the emerging markets are weakly linked to the developed markets. The implication is that foreign investors may benefit from the reduction of risk by adding the stocks in the emerging markets to their investment portfolio.     

Portfolio optimization in the presence of dependent financial returns with long memory: A copula based approach

In this paper, we seek to examine the effect of the presence of long memory on the dependence structure between financial returns and on portfolio optimization. First, we focus on the dependence structure using copulas. To select the best copula, in addition to the goodness of fit tests, we employ a graphical method based on visual comparison of the fitted copula density and the smoothed copula density estimated by wavelets. Moreover, we check the stability of the copula parameter. The empirical results show that the long memory affects the dependence structure. Second, we analyze the impact of this dependence structure on the optimal portfolio. We propose a new approach based on minimizing the Conditional Value at Risk and assuming that the dependence structure is modeled by the copula parameter. The empirical results show that our approach outperforms the traditional minimizing variance approach, where the dependence structure is represented by the linear correlation coefficient.     

Equity market integration in emerging Balkan markets

This paper examines long-run relationships among five Balkan emerging stock markets (Turkey, Romania, Bulgaria, Croatia, Serbia), the United States and three developed European markets (UK, Germany, Greece), during the period 2000-2009. Conventional, regime-switching cointegration tests and Monte Carlo simulation provide evidence in favour of a long-run cointegrating relationship between the Balkan emerging markets within the region and globally. Moreover, we apply the Asymmetric Generalized Dynamic Conditional Correlation (AG-DCC) multivariate GARCH model of Cappiello et al. (2006), in order to capture the impact of the 2007-2009 financial crisis on the time-varying correlation dynamics among the developed and the Balkan stock markets. Results show that stock market dependence is heightened, supporting the herding behaviour during the 2008 stock market crash period. Our findings have important implications for international portfolio diversification and the effectiveness of domestic policies, as these emerging markets are exposed to external shocks.     

Global market integration: An alternative measure and its application

Global markets seem to be increasingly integrated but there is no well-accepted measure of integration. We show that the correlation across markets is a poor measure; perfectly integrated markets can exhibit weak correlation. We derive a new integration measure based on the explanatory power of a multi-factor model and use it empirically to investigate recent trends in global integration. For most countries, there has been a marked increase in measured integration over the past three decades, but this is not indicated by correlations among country indexes.     

Asset market linkages: Evidence from financial, commodity and real estate assets

We use a general Markov switching model to examine the relationships between returns over three different asset classes: financial assets (US stocks and Treasury bonds), commodities (oil and gold) and real estate assets (US Case-Shiller index). We confirm the existence of two distinct regimes: a “tranquil” regime with periods of economic expansion and a “crisis” regime with periods of economic decline. The tranquil regime is characterized by lower volatility and significantly positive stock returns. During these periods, there is also evidence of a flight from quality - from gold to stocks. By contrast, the crisis regime is characterized by higher volatility and sharply negative stock returns, along with evidence of contagion between stocks, oil and real estate. Furthermore, during these periods, there is strong evidence of a flight to quality - from stocks to Treasury bonds.     

A stochastic frontier approach to modelling financial constraints in firms: An application to India

We propose the use of stochastic frontier approach to modelling financial constraints of firms. The main advantage of the stochastic frontier approach over the stylised approaches that use pooled OLS or fixed effects panel regression models is that we can not only decide whether or not the average firm is financially constrained, but also estimate a measure of the degree of the constraint for each firm and for each time period, and also the marginal impact of firm characteristics on this measure. We then apply the stochastic frontier approach to a panel of Indian manufacturing firms, for the 1997–2006 period. In our application, we highlight and discuss the aforementioned advantages, while also demonstrating that the stochastic frontier approach generates regression estimates that are consistent with the stylised intuition found in the literature on financial constraint and the wider literature on the Indian credit/capital market.     

Time series analysis for financial market meltdowns

There appears to be a consensus that the recent instability in global financial markets may be attributable in part to the failure of financial modeling. More specifically, it is alleged that current risk models have failed to properly assess the risks associated with large adverse stock price behavior. In this paper, we first discuss the limitations of classical time series models for forecasting financial market meltdowns. Then we set forth a framework capable of forecasting both extreme events and highly volatile markets. Based on the empirical evidence presented in this paper, our framework offers an improvement over prevailing models for evaluating stock market risk exposure during distressed market periods.     

Dynamics of international integration of government securities’ markets

This paper investigates the dynamics of international government bond market integration in six of the G7 economies over two decades leading up to the global crisis. It examines whether such integration had been significant; the extent to which integration at the short and long end of the yield curve differed; the nature of such integration; and the extent of the decoupling of the long rates from short rates. These issues are investigated using the rigorous smooth-transition copula-GARCH model framework. The results show that integration at the long end of the yield curve had been increasing, had become pronounced, and was significantly greater than at the short end. Decoupling between the short and long end of the yield curve was notable, with important implications for the efficacy of monetary policy in the period before the crisis.     

Financial market development and the importance of internal cash: Evidence from international data

We examine the impact of financial market development on the extent to which firms have to rely on internal capital for making investments. Using international data from 31 countries for the 1987–1997 period, we find evidence of a negative relationship between financial market development and the importance of internal capital. The evidence is consistent across different estimation procedures, alternative measures of financial constraints and cash flow, and the use of bootstrapped standard errors. Finally, we find that the distortionary effect of negative cash flow observations reported earlier for US data extends to international data as well.     

Explaining international stock correlations with CPI fluctuations and market volatility

This paper investigates the dynamic correlations among six international stock market indices and their relationship to inflation fluctuation and market volatility. The current research uses a newly developed time series model, the Double Smooth Transition Conditional Correlation with Conditional Auto Regressive Range (DSTCC-CARR) model. Findings reveal that international stock correlations are significantly time-varying and the evolution among them is related to cyclical fluctuations of inflation rates and stock volatility. The higher/lower correlations emerge between countries when both countries experience a contractionary/expansionary phase or higher/lower volatilities.     

Identifying the interaction between stock market returns and trading flows of investor types: Looking into the day using daily data

This paper introduces a new method for identifying the simultaneity between returns and trading flows. The proposed method enables us to identify the intraday interaction using daily data, and provides measures of the information content of trading flows, and their instantaneous response to public information and information revealed by market prices. Applying this method to daily data on investor types from the Korea Stock Exchange, we find significant intraday bi-directional interaction between flows and returns and their latent common drivers, altering some of the results of the previous literature based on Cholesky assumptions. Thus, we obtain a number of new insights concerning the behavior of investor types.     

Uninsurable risk and financial market puzzles

We compare the empirical performances of three risk-sharing arrangements involving idiosyncratic skill shocks: (a) where individuals are unable to directly insure their consumption against individual-specific shocks, (b) where agents strike long-term insurance contract with financial intermediaries involving a truth revelation constraint as in Kocherlakota and Pistaferri (2009), (c) full risk sharing. Based on the widely accepted assumption of cross-sectional log-normality of individual consumption levels, we work out closed form expressions of the pricing kernels for (a) and (b). We put these three models to test four financial market anomalies, namely the equity premium, currency premium, risk-free rate, and consumption-real exchange rate puzzles simultaneously in an integrated framework. We find that the pricing kernel associated with (a) outperforms the other two models in terms of the produced estimates of the agent’s preference parameters and the model ability to predict the equity and currency premia, the risk-free rate, and the log growth in the exchange rate. However, the predictive ability is still far from satisfactory for all three models under scrutiny.     

Contagion in financial markets after September 11: myth or reality?

Major global events can lead to a change in the cross‐country correlation of assets. Using stock prices from 25 economies, we test whether the terrorist attack in the United States on September 11, 2001, resulted in a contagion—an increase in correlation across global financial markets. Unlike prior works on contagion, we model the intrinsic heteroskedasticity. Our results indicate that international stock markets, particularly in Europe, responded more closely to U.S. stock market shocks in the three to six months after the crisis than before. Our evidence suggests that the benefits of international diversification in times of crisis are substantially diminished.     

Stock market reaction to fed funds rate surprises: State dependence and the financial crisis

This paper examines the response of US stock returns to Federal Funds rate (FFR) surprises between 1989 and 2012, focusing on the impact of the recent financial crisis. We find that outside the crisis period, stock prices increased as a response to unexpected FFR cuts. State dependence is identified with stocks exhibiting larger increases when interest rate easing coincided with recessions, bear markets, and tightening credit conditions. However, an important structural shift occurred during the crisis, changing the stocks’ response to FFR shocks and the nature of state dependence. Throughout the crisis period, stocks did not react positively to unexpected FFR cuts, which were interpreted as signals of worsening future economic conditions. This triggered a rebalancing of investment portfolios away from falling equities and towards safe-haven assets. Our results highlight the severity of the crisis and the ineffectiveness of conventional monetary policy close to the zero lower bound.     

A factor analysis approach to measuring European loan and bond market integration

By using an existing and a new convergence measure, this paper assesses whether bank loan and bond interest rates are converging for the non-financial corporate sector across the euro area. Whilst we find evidence for complete bond market integration, the market for bank loans remains segmented, albeit to various degrees depending on the type and size of the loan. Factor analysis reveals that rates on large loans and small loans with long rate fixation periods have weakly converged in the sense that, up to a fixed effect, their evolution is driven by common factors only. In contrast, the price evolution of small loans with short rate fixation periods is still affected by country-specific dynamic factors. There are few signs that bank loan rates are becoming more uniform with time.     

Information transmission in informationally linked markets: Evidence from US and Chinese commodity futures markets

This paper investigates information transmission and price discovery in informationally linked markets within the multivariate generalized autoregressive conditional heteroskedasticity and information share frameworks. Based on both synchronous and non-synchronous trading information from Chinese futures/spot markets, the New York Mercantile Exchange (NYMEX), Chicago Board of Trade (CBOT), and CME Globex futures markets for copper and soybeans, we show that there is a bidirectional relationship in terms of price and volatility spillovers between US and Chinese markets, with a stronger effect from US to Chinese markets than the other way around. Additionally, the NYMEX and CBOT play a more important role than the CME Globex in the flow of information from US to Chinese markets. Moreover, we find that Chinese copper market adjusts more quickly than the NYMEX copper market to correct the disparity between both markets. However, the converse is true in the case of soybeans. Finally, our results highlight the remarkable role of Chinese futures markets in the price formation process, though NYMEX and CBOT futures markets are the main driving force in price discovery.     

The dynamics of price discovery for cross-listed shares: Evidence from Australia and New Zealand

This paper studies the dynamics of price discovery for markets with bilateral cross-listings. Using a sample of four Australian stocks cross-listed in New Zealand and five New Zealand stocks cross-listed in Australia for the period January 2002 to December 2007, we assess Hasbrouck (1995) information shares and Grammig et al. (2005) conditional information shares over time. We observe that in both cases the home market is dominant in terms of price discovery. However, when studying price discovery over time, we find that the importance of the Australian market (the larger of the two markets) is increasing for both Australian and New Zealand domiciled firms. Finally, using panel regression analysis, we find that the growth in the importance of the Australian market is positively related to the growth in the size of the firm and negatively related to the size of the percentage spread in the Australian market, implying that as firms grow larger and their cost of trading in Australia declines, the Australian market becomes more informative.     

International diversification: An extreme value approach

International diversification has costs and benefits, depending on the degree of asset dependence. We study international diversification with two dependence measures: correlations and extreme dependence. We discover that dependence has typically increased over time, and document mixed evidence on heavy tails in individual countries. Moreover, we uncover three additional findings related to dependence. First, the timing of downside risk differs depending on the region. Surprisingly, recent Latin American returns exhibit little downside risk. Second, Latin America exhibits a great deal of correlation complexity. Third, according to the empirical results, correlation does not vary with returns, but extreme dependence does vary monotonically with regional returns. Our results are consistent with a tradeoff between international diversification and systemic risk. They also suggest international limits to diversification, and that international investors demand some compensation for joint downside risk during extreme events.     

A revisit to the dependence structure between the stock and foreign exchange markets: A dependence-switching copula approach

This paper develops a dependence-switching copula model to examine dependence and tail dependence for four different market statuses, namely, rising-stocks/appreciating-currency, falling-stocks/depreciating-currency, rising-stocks/depreciating-currency, and falling-stocks/appreciating-currency. The model is then applied to daily stock returns and exchange rate changes for six major industrial countries over the 1990–2010 period. The dependence and tail dependence among the above four market statuses are asymmetric for most countries in the negative correlation regime, but symmetric in the positive correlation regime. These results enrich the findings in the existing literature and suggest that analyzing cross-market linkages within a time-invariant copula framework may not be appropriate.     

Correlation dynamics in equity markets: evidence from India

This study is aimed at understanding the correlation dynamics of the equity markets from a developing country perspective using daily data from July 1997 to August 2006. A simple unconditional correlation estimate and dynamic time varying correlation estimate from a DCC-MVGARCH of Engle and Sheppard (2001) are derived for S&P CNX Nifty and other 10 world indices that includes four developed and six Asian country indices. The results show low correlation across S&P CNX Nifty with both Asian and developed nations. In addition a Logistic Smooth Transition Regression (LSTR) model is implemented and finds that the S&P CNX Nifty index is moving towards a better integration with other world markets but not at a very noteworthy phase. The low correlation provides space for the global funds to diversify risk in Indian markets.