Return and Volatility Spillovers and Cojump Behavior Between the U.S. and Korean Stock Markets

ABSTRACT

In this study, we examine return spillover, volatility transmission, and cojump behavior between the U.S. and Korean stock markets. In particular, we focus on cojump behavior between the two markets in order to explain the transmission of unexpected shocks. We find that the U.S. stock market causes return spillover effects in the Korean stock market, and there is significant volatility transmission between the two markets. Importantly, we find a stronger association in size, as compared with intensity, of cojumps between the U.S. and Korean stock markets, particularly during the recent financial crisis.     

The Halloween Effect and Japanese Equity Prices: Myth or Exploitable Anomaly

Bouman and Jacobsen (American Economic Review 92(5), 1618–1635, 2002) examine monthly stock returns for major world stock markets and conclude that returns are significantly lower during the May–October periods versus the November–April periods in 36 of 37 markets examined. They argue that, in general, the Halloween strategy outperforms the buy and hold strategy thereby casting doubt on the validity of the efficient market paradigm. More recently, Maberly and Pierce (Econ Journal Watch 1(1), 29–46, 2004) re-examine the evidence for U.S. equity prices and conclude that Bouman and Jacobsen’s results are not robust to alternative model specifications. Extending prior research, this paper examines the robustness of the Halloween strategy to alternative model specifications for Japanese equity prices. The Halloween effect is concentrated in the period prior to the introduction of Nikkei 225 index futures in September 1986. After the internationalization of Japanese financial markets in the mid-1980s, the Halloween effect disappears.JEL classification: G14, G15     

Momentum and Foreign Investors: Evidence from the Korean Stock Market

Abstract:

We examine whether the price impact of foreign investors on the Korean stock market from December 2000 to February 2007 generated a momentum phenomenon. In our empirical results, foreigners seem to have exerted a significantly positive impact on prices in “up” markets (periods of positive stock returns), but have had little impact on prices in “down” markets (periods of negative returns). We document that the impact of foreigners’ trades is concentrated in large companies. Most importantly, when the market is in the up state, the returns of stocks of large companies that were positively affected by foreign investors in the previous six-month period continue to increase in the subsequent six-month period. As a result, the subsequent six-month return on a past “winner” stock portfolio is significantly higher than that on a past “loser” stock portfolio. This brings to mind a momentum phenomenon that has been reported not to exist in the Korean stock market.     

Firm characteristics,alternative factors,and asset-pricing anomalies: evidence from Japan

Based on the errors-in-variables-free approach proposed by Brennan et al. [J. Financial Econ., 1998, 49, 345–373], we investigate the competing explanatory capabilities of alternative multi-factor models when examining various asset-pricing anomalies using Japanese data for the period 1978–2006. We find that turnover and book-to-market (BM) ratio are the two major characteristics that significantly explain the average stock returns. A further sub-period analysis reveals that the turnover effect is significant only before 1990, but cannot be explained by any multifactor models. In contrast, the BM premium is significant only after 1990, and can be explained by the Fama–French three-factor model. Thus, the results suggest that asset-pricing anomalies documented in the literature are not universal, and may be different across different markets.     

Modifying a simple agent-based model to disentangle the microstructure of Chinese and US stock markets

We modify a simple agent-based model (ABM) proposed by Franke and Westerhoff [J. Econ. Dyn. Control, 2012, 36(8), 1193–1211] through considering the price limits and the motion of the fundamental value. The method of simulated moments is applied to calibrate both initial and modified ABMs with CSI 300 and S&P 500 respectively, and the goodness-of-fit of each ABMs is tested. The calibration results indicate that the modified model performs better than initial one. Then, we utilize the GSL-div, proposed by Lamperti [Econometrics Stat, 2018, 5, 83–106.], to verify the explanatory power of ABMs. In this procedure, 13 ARCH family models are introduced as benchmarks. The result shows that the explanatory power of modified ABM exceeds ARCH models in both markets, while initial ABM may be defeated by some of the ARCH family models in explaining the microstructure of CSI 300. Finally, a heuristic algorithm is designed to disentangle the insights of Chinese and US stock markets to the observed time horizon through calibrating the initial fundamental value, and Kupiec test is used to check the robustness of the calibration. The result indicates that the explanation of modified model is robust in both markets, while initial model lost its robustness when explaining S&P 500.     

Covariance and correlation stationarity: Experiences from seven Asian emerging markets

Because of the rising interest and the growing importance of the Asian emerging markets in international diversification, this paper examines the covariance and correlation stationarity in stock return relationships among seven Asian emerging markets. This paper also covers the issue of seasonality in stock return co-movements. Empirical results show that because the correlations among them and those with other developed markets are very small, huge gains from diversifying into the seven Asian emerging markets are possible. Results on stationarity indicate that correlation matrices of stock returns are much more stable then the corresponding variance-covariance matrices and that the length of the estimation period seems to have no impact on the stationarity of the correlation matrix. We also found that virtually no seasonality in the correlations exists among the seven Asian emerging markets. However, we did find that during our sample period covariance among stock returns is nonstationary in January. The author thanks an anonymous referee ofFinancial Engineering and the Japanese Markets for the valuable comments on the earlier version of this article.     

Idiosyncratic volatility and cross‐sectional stock returns in Southeast Asian stock markets

We examine the role of idiosyncratic risk in five ASEAN markets of Malaysia, Singapore, Thailand, Indonesia, and the Philippines. Our research was motivated by the findings of Ang et al. (2006, 2009) of a ‘puzzling’ negative relation between idiosyncratic volatility and 1‐month ahead stock returns in developed markets and the suggestion of the ubiquity of these results in other markets. In contrast, we find no evidence of an idiosyncratic volatility puzzle in these Asian stock markets; instead, we document a positive relationship between idiosyncratic volatility and returns in Malaysia, Singapore, Thailand, and Indonesia and no relationship in the Philippines. The idiosyncratic volatility trading strategy could result in significant trading profits in Malaysia, Singapore, Thailand, and to some extent in Indonesia. Our study underscores the fact that generalizing empirical results obtained in developed stock markets to new and emerging markets could potentially be misleading.     

Statistical analysis of financial time series under the assumption of local stationarity

The aim of this paper is to apply a nonparametric methodology developed by Donoho et al(2003 IEEE Trans. Signal Processing 53614–27) for estimating an autocovariance sequence to the statistical analysis of the return of securities and discuss the advantages offered by this approach over other existing methods such as fixed-window-length segmentation procedures. Theoretical properties of adaptivity of this estimation method have been proved for a specific class of time series, namely the class of locally stationary processes, with an autocovariance structure which varies slowly over time in most cases but might exhibit abrupt changes of regime. This method is based on an algorithm that selects empirically from the data the tiling of the time–frequency plane which exposes best in the least-squares sense the underlying second-order time-varying structure of the time series, and so may properly describe the time-inhomogeneous variations of speculative prices. The applications we consider here mainly concern the analysis of structural changes occurring in stock market returns, VaR estimation and the comparison between the variation structure of stock index returns in developed markets and in developing markets.     

Asia-Pacific Stock Market Integration: New Evidence by Incorporating Regime Changes

ABSTRACT

This work provides new evidence of Asia-Pacific stock market integration by incorporating the regime changes of each stock market through the smooth transition autoregressive (STAR) model. According to empirical results, most Asia-Pacific stock market returns follow STAR dynamics to a significant degree with more rapid and frequent regime changes of a shorter nature compared with G7 markets. A series of STAR-based Granger causality tests reveal evidence of stronger equity market integration compared with linear Granger causality tests. We also find that Asia-Pacific stock markets are integrated in different levels. Finally, we provide evidence that in the early twenty-first century the influence of China and the United States on Asia-Pacific stock markets has been maintained while that of Japan has been weakened.     

Short-horizon contrarian and momentum strategies in Asian markets: An integrated analysis

In this paper, we test the profitability of short-term contrarian and momentum strategies, which take into account the effects of trading activity, size/value characteristics, and asymmetric investor responses to news regarding stock markets in Japan, Taiwan, Korea, Hong Kong, Malaysia, Thailand, and Singapore during 1990-2000. Except for the Taiwanese and Korean markets, “winner” (“loser”) portfolios experience subsequent reversal (momentum) of stock prices. Among actively traded stocks, significant contrarian profits can be obtained from only “winner” portfolios in Japan, while sizeable momentum profits from “loser portfolios” in both Japan and Hong Kong.     

Does the stock market predict real activity? Time series evidence from the G-7 countries

This paper extends one aspect of the US stock market study of Fama (1990) and Schwert (1990). We examine the relationship between industrial production (IP) growth rates and lagged real stock returns for the G-7 countries using both in-sample cointegration and error-correction models and the out-of-sample forecast-evaluation procedure of Ashley et al. (1980). The cointegration tests show a long-run equilibrium relationship between the log levels of IP and real stock prices, while the error-correction models indicate a correlation between IP growth and lagged real stock returns for all countries except Italy. The out-of-sample tests show that in several sub-periods the US, UK, Japanese, and Canadian stock markets enhance predictions of future IP.     

Growing pains: The evolution of new stock index futures in emerging markets

Analyzing the first seven years of trading in Turkish stock index futures (BIST 30) and contrasting that to the progress of Korean (KOSPI 200) and Taiwanese (TAIEX) markets, we find that BIST 30 initially experiences a persistent mispricing and speculative trading similar to KOSPI 200 but it also experiences the largest increase in hedge effectiveness, becoming hedger-dominated similar to TAIEX. Most significantly, we demonstrate that spot market short-sell quote volume is a good measure of short-sale constraints and a significant determinant of mispricing in BIST 30. A methodological contribution of this paper is a four-equation multivariate VAR framework to analyze the volatility impact of futures.     

An index of market shocks based on multiscale analysis*

Abstract

Financial markets are places of sudden and violent price movements. Nevertheless, financial crises lack a universally recognized way of assessing their gravity. This has motivated the measure recently proposed and applied to the exchange rates market by Zumbach et al (2000a Int. J. Theor. Appl. Finance 3 347–55). This measure relies on an analogy with geophysics: the scale of market shocks (SMS) is equivalent to the Richter scale used for earthquakes. More precisely, as a market is the place where economic agents—with different investment horizons—interact, the SMS definition is a weighted aggregation of volatility measures corresponding to these different horizons. In this paper, we implement and apply a similar measure to stock markets, and adapt it to take into account some extra features of these markets.

The volatilities are first described, and then used to assess the market instability perceived by a market participant. The evolution of our index of market shocks (IMS)—after rescaling for easy interpretation—is presented using different computational methods.

The IMS is then compared with another multiscale measure, the multifractal spectrum width, and we also investigate the links between the IMS and the daily close-to-close returns and volatility. Finally, we describe the recent turbulence on the French market using the IMS as an exploratory tool, concluding that the events of September 2001 proved to be a major shock compared to the Russian and Asian crises.     

Why Do Price Limits Exist in Stock Markets? A Manipulation‐Based Explanation

Numerous stock market regulators around the world impose daily price limits on individual stock price movements. We derive a simple model that shows that price limits may deter stock market manipulators. Based on our model's implications, we predict that regulators impose price limit rules for markets where the likelihood of manipulation is high. We present empirical evidence consistent with this hypothesis. Our study is the first to formally propose a manipulation‐based rationale for the existence of price limits in stock markets.     

An extensive analysis on the Japanese markets via S. Taylor's model

Applying S. Taylor's approach (1986), we make an extensive analysis on the Japanese stock market, foreign exchange market and the Japanese Government Bond Futures market. The purpose of this paper is to empirically reveal the structure of the Japanese markets via Taylor's model rather than to propose a new model. For this reason, we include a variety of analyzed data particularly for the Japanese stock market and the foreign exchange market because the results can be used in a different manner. The paper consists of three parts. But each part can be read separately. Part 1: Overshooting hypothesis for Japanese stock prices Part 2: A trend movement in daily/weekly Yen-Dollar exchange rates Part 3: Price variations of Japanese Government Futures. In the first part, the stock prices are shown to over-respond to new information, which is different from the behaviors of stock prices in other markets. In Part 2, a trend movement is revealed in Yen-Dollar exchange rates. In Part 3, a strategy in the Japanese Government Bond futures markets is shown to perform better than a buy and hold strategy.     

ESTIMATING THE DEPENDENCE STRUCTURE OF SHARE PRICES: A COMPARATIVE STUDY OF THE UNITED STATES AND JAPAN

In this paper, we show that estimating the correlation structure of domestic share prices via the Overall Mean method cannot be considered universally superior to estimation at the Full Historical level for all countries. Specifically, the Japanese data show that the Full Historical Model outperforms the Overall Mean Model in forecasting accuracy, while the opposite is true with the U.S. data. We derive a Composite Model that analytically explains this contrasting result. The Industry Mean Model, which allows for efficient ex ante portfolio selection via a simple algorithm, is likely to be the best forecasting model applicable to both the U.S. and Japanese stock markets.     

An analysis of trading strategies in eleven European stock markets

Abstract

In recent years, the validity of the weak form efficient market hypothesis (EMH) has been called into question as several studies have uncovered evidence that technical trading rules have predictive ability with respect to both developed and emerging stock market indices. This study analyses the forecasting power of 2 of the most popular trading rules using index data for a selection of 11 European stock markets over the January 1991 to December 2000 period. The findings indicate that the emerging markets included in this paper are informationally inefficient; these markets displayed some degree of predictability in their share returns, although the developed markets did not. Furthermore, the results point to large differences in the performance of the rules examined; while small size filters consistently outperformed the buy-and-hold strategy in the emerging markets examined even after the consideration of transaction costs, the performance of the moving average rules was erratic and varied dramatically from market to market.     

Time-consistent reinsurance and investment strategies for an AAI under smooth ambiguity utility

This paper investigates time-consistent reinsurance(excess-of-loss, proportional) and investment strategies for an ambiguity averse insurer(abbr. AAI). The AAI is ambiguous towards the insurance and financial markets. In the AAI's attitude, the intensity of the insurance claims' number and the market price of risk of a stock can not be estimated accurately. This formulation of ambiguity is similar to the uncertainty of different equivalent probability measures. The AAI can purchase excess-of-loss or proportional reinsurance to hedge the insurance risk and invest in a financial market with cash and an ambiguous stock. We investigate the optimization goal under smooth ambiguity given in Klibanoff, P., Marinacci, M., & Mukerji, S. [(2005). A smooth model of decision making under ambiguity. Econometrica 73, 1849–1892], which aims to search the optimal strategies under average case. The utility function does not satisfy the Bellman's principle and we employ the extended HJB equation proposed in Björk, T. & Murgoci, A. [(2014). A theory of Markovian time-inconsistent stochastic control in discrete time. Finance and Stochastics 18(3), 545–592] to solve this problem. In the end of this paper, we derive the equilibrium reinsurance and investment strategies under smooth ambiguity and present the sensitivity analysis to show the AAI's economic behaviors.     

The Dynamic Extreme Co-Movement between Chinese Stock Market and Global Stock Markets

ABSTRACT

We use time-varying Symmetrized Joe-Clayton Copula model to study the extreme co-movement (boom or crash together) between the Chinese stock market and major stock markets in the world from 2007 to 2017, including developed markets and stock markets on “Belt and Road Initiative” (hereafter B.R.I.). We find that the extreme co-movement probability between Chinese market and “Belt and Road Initiative” markets is higher than developed markets at both tails. Then we study important “real” and “non-fundamental” factors affecting the excess co-movement probability, including bilateral trade openness, financial integration, and economic policy uncertainty. The results of panel regression analysis show that: the bilateral financial integration has significant effects over the lower tail dependence between Chinese and developed markets, but does not affect the extreme co-movement between Chinese and B.R.I. markets. And the bilateral trade openness is an important factor for the extreme co-movement at both tail between Chinese and global markets. The economic policy uncertainty index, especially China’s economic policy uncertainty, plays a key role in the extreme co-movement between Chinese and developed markets at both tails. However, it has sizable effects only at the upper tail co-movement between Chinese and B.R.I. markets.     

24-Hour realized volatilities and transatlantic volatility interdependence

This paper proposes an innovative econometric approach for the computation of 24-h realized volatilities across stock markets in Europe and the US. In particular, we deal with the problem of non-synchronous trading hours and intermittent high-frequency data during overnight non-trading periods. Using high-frequency data for the Euro Stoxx 50 and the S&P 500 Index between 2003 and 2011, we combine squared overnight returns and realized daytime variances to obtain synchronous 24-h realized volatilities for both markets. Specifically, we use a piece-wise weighting procedure for daytime and overnight information to take into account structural breaks in the relation between the two. To demonstrate the new possibilities that our approach opens up, we use the new 24-h volatilities to estimate a bivariate extension of Corsi et al.’s [Econom. Rev., 2008, 27(1–3), 46–78] HAR-GARCH model. The results suggest that the contemporaneous transatlantic volatility interdependence is remarkably stable over the sample period.