nep-fmk New Economics Papers
on Financial Markets
Issue of 2016‒04‒04
eight papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Stock Return Predictability: Evaluation based on Prediction Intervals By Charles, Amelie; Darne, Olivier; Kim, Jae
  2. Amount of news before stock market fluctuations By Tahira, Yoshifumi; Mizuno, Takayuki
  3. Time-varying Volatility and the Power Law Distribution of Stock Returns By Warusawitharana, Missaka
  4. Trust and stock market correlation: a cross-country analysis By Liu, Yuna
  5. Dynamic Connectedness of Asian Equity Markets By Roberto Guimarães-Filho; Gee Hee Hong
  6. Stock exchange integration and price jump risks - The case of the OMX Nordic exchange mergers By Liu, Yuna
  7. Financial integration and Japanese stock market By Guesmi, Khaled; Kablan, Sandrine
  8. Time Varying Volatility Modeling of Pakistani and leading foreign stock markets By Ghouse, Ghulam; Khan, Saud Ahmed; Arshad, Muhammad

  1. By: Charles, Amelie; Darne, Olivier; Kim, Jae
    Abstract: This paper evaluates the predictability of monthly stock return using out-of-sample (multi-step ahead and dynamic) prediction intervals. Past studies have exclusively used point forecasts, which are of limited value since they carry no information about the intrinsic predictive uncertainty associated. We compare empirical performances of alternative prediction intervals for stock return generated from a naive model, univariate autoregressive model, and multivariate model (predictive regression and VAR), using the U.S. data from 1926. For evaluation free from data snooping bias, we adopt moving sub-sample windows of different lengths. It is found that the naive model often provides the most informative prediction intervals, outperforming those generated from the univariate model and multivariate models incorporating a range of economic and financial predictors. This strongly suggests that the U.S. stock market has been informationally efficient in the weak-form as well as in the semi-strong form, subject to the information set considered in this study
    Keywords: Autoregressive Model, Bootstrapping, Financial Ratios, Forecasting, Interval Score, Market Efficiency
    JEL: G12 G14
    Date: 2016–03–18
  2. By: Tahira, Yoshifumi; Mizuno, Takayuki
    Abstract: The views of the Wikipedia pages of companies listed in the Dow Jones Industrial Average (DJIA) were correlated with the future DJIA changes. Such an increase in views suggest that new information is circulating about these companies. We elucidate that such fluctuations in the number of news articles about a stock market are correlated with the future changes of its index by investigating 9,150,000 news articles distributed by Thomson Reuters and the stock market indexes between December 2007 and April 2012. When the number of news articles about companies listed in NYSE and NASDAQ increase/decrease in one week, the Standard & Poor's 500 index (S&P500 index) tends to fall/rise in the next week. On the other hand, the fluctuation in other stock market indexes, which are rarely correlated with NYSE and NASDAQ, are basically random. Markets notably react to the fluctuation in the number of business sector news articles. These characteristics are observed every year.
    Keywords: Econophysics, Stock market, Business news, Exogenous shock
    Date: 2016–03
  3. By: Warusawitharana, Missaka
    Abstract: While many studies find that the tail distribution of high frequency stock returns follow a power law, there are only a few explanations for this finding. This study presents evidence that time-varying volatility can account for the power law property of high frequency stock returns. The power law coefficients obtained by estimating a conditional normal model with nonparametric volatility show a striking correspondence to the power law coefficients estimated from returns data for stocks in the Dow Jones index. A cross-sectional regression of the data coefficients on the model-implied coefficients yields a slope close to one, supportive of the hypothesis that the two sets of power law coefficients are identical. Further, for most of the stocks in the sample taken individually, the model-implied coefficient falls within the 95 percent confidence interval for the coefficient estimated from returns data.
    Keywords: Tail distributions ; high frequency returns ; power laws ; time-varying volatility
    JEL: C58 D30 G12
    Date: 2016–03–18
  4. By: Liu, Yuna (Department of Economics, Umeå University)
    Abstract: Several studies have shown that the level of trust between agents is an important determinant of financial decisions. This paper studies this issue further by analyzing whether the measured level of trust in different countries can explain bilateral stock market correlations. Using a panel of 62 countries and 1891 country-pairs over a period of ten years, the effect of generalized trust on stock market correlations is analyzed. One finding is that generalized trust among nations is a robust predictor for stock market correlation. Another is that the trust effect is larger for countries which are close to each other which indicates that distance mitigates the trust effect. Finally, we confirm the effect of trust upon stock market correlations, by using particular trust data (bilateral trust between country A and country B) as an alternative measurement of trust.
    Keywords: International Financial Markets; Stock Market Correlation; Trust; Volatility; Portfolio Diversification; Stock Market Participation
    JEL: D31 F15 G11 G15
    Date: 2016–03–16
  5. By: Roberto Guimarães-Filho; Gee Hee Hong
    Abstract: Understanding how markets are connected and shocks are transmitted is an important issue for policymakers and market participants. In this paper, we examine the connectedness of Asian equity markets within the region and vis-Ã -vis other major global markets. Using time-varying connectedness measures, we address the following questions: (1) How has connectedness in asset returns and volatilities changed over time? Do markets become more connected during crises periods? (2) Which markets are major sources and major recipients of shocks? Has there been a shift in terms of the net shock givers and shock receivers (directional connectedness over time)? Finally, we investigate the connectedness between China’s equity markets and other countries’ equity markets since August 2015 to highlight the growing importance of emerging market economies, particularly China, as sources of shocks.
    Date: 2016–03–09
  6. By: Liu, Yuna (Department of Economics, Umeå University)
    Abstract: The impact of the stock market mergers that took place in the Nordic countries during 2000 – 2007 on the probabilities for stock price jumps, i.e. for relatively extreme price movements, are studied. The main finding is that stock market mergers, on average, reduce the likelihood of observing stock price jumps. The effects are asymmetric in the sense that the probability of sudden price jumps is reduced for large and medium size firms whereas the effect is ambiguous for small size firms. The results also indicate that the market risk has been reduced after the stock market consolidations took place.
    Keywords: Tests for jumps; International financial markets; Market structure; Integration; Common trading platform; Mergers; Acquisitions
    JEL: C22 C51 C58 G15 G34 L10
    Date: 2016–03–16
  7. By: Guesmi, Khaled; Kablan, Sandrine
    Abstract: Our paper tests the conditional version of the International Capital Asset Pricing Model (ICAPM) applying a parsimonious multivariate DCC - GARCH process. By permitting the prices of risk and the level of market integration to vary through time, our results show that Japan experienced increases in the degree of regional integration in last years. The increasing integration into regional financial markets alone is unlikely to provide a sound ground for a currency union in ASEAN+5 at this stage, but improvement in welfare gains in the ASEAN+5 economies by means of further risk sharing is possible.
    Keywords: Financial integration, ICAPM, ASEAN, DCC-GARCH
    JEL: C32 F31 F36 G12
    Date: 2015
  8. By: Ghouse, Ghulam; Khan, Saud Ahmed; Arshad, Muhammad
    Abstract: This study estimates the volatility of Pakistani and leading foreign stock markets. Daily data are used from nine international equity markets (KSE 100, NIKKEI 225, HIS, S&P 500, NASDAQ 100, DOW JONES, GADXI, FTSE 350 and DFMGI) for the period of Jan, 2005 to Nov, 2014. The whole data set is used for modeling of time varying volatility of stock markets. Univariate GARCH type models i.e. GARCH and GJR are employed for volatility modeling of Pakistani and leading foreign stock markets. The residual analysis also employed to check the validity of models. Our study brings important conclusions for financial institutions, portfolio managers, market players and academician to diagnose the nature and level of linkages between the financial markets.
    Keywords: Volatility, Equity Market, GARCH and GJR
    JEL: G1 G15
    Date: 2015–12–30

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