New Economics Papers
on Financial Markets
Issue of 2009‒11‒21
seven papers chosen by

  1. Shareholder value creators in the Dow Jones: Year 2008 By Fernandez, Pablo; Bermejo, Vicente J.
  2. The riskiness of corporate bonds By Marco Taboga
  3. A Framework for CAPM with Heterogenous Beliefs By Carl Chiarella; Roberto Dieci; Xue-Zhong He
  4. The Economic Value of Volatility Timing in the Athens Stock Exchange By Dimitrios Vortelinos
  5. Realized Volatility and Jumps in the Athens Stock Exchange By Dimitrios Vortelinos; Dimitrios Thomakos
  6. Spillover effect: A study for major capital markets and Romania capital market By Cristina Belciuganu
  7. Asymmetric Conditional Volatility on the Romanian Stock Market By Florin Stanciu

  1. By: Fernandez, Pablo (IESE Business School); Bermejo, Vicente J. (IESE Business School)
    Abstract: During 2008, only 2 of the companies included in the Dow Jones (Wall Mart and McDonalds) created value, while in 2007 16 of these companies did it. The market value of the 300 companies was $2.9 trillion in 2008 and $4.4 trillion in 2007. The top shareholder value creators in 2004 were Exxon, General Electric, Ebay, Johnson & Johnson and Qualcomm. We define created shareholder value and provide the ranking of created shareholder value for the 500 companies. We also calculate the created shareholder value of the 500 companies during the twelve-year period 1993-2004. General Electric was the top shareholder value creator and AT&T was the top shareholder value destroyer during the twelve-year period. On average, the small market capitalization companies of the S&P were more profitable. The volatility of the S&P fell since 1998 to 2004, but the volatility of his components increased on average.
    Keywords: shareholder value creation; created shareholder value; shareholder value added; shareholder return:
    JEL: G12 G31 M21
    Date: 2009–09–03
  2. By: Marco Taboga (Bank of Italy)
    Abstract: When the riskiness of an asset increases, then, arguably, some risk-averse agents that were previously willing to hold on to the asset are no longer willing to do so. Aumann and Serrano (2008) have recently proposed an index of riskiness that helps to make this intuition rigorous. We use their index to analyze the riskiness of corporate bonds and how this can change over time and across rating classes and how it compares to the riskiness of other financial instruments. We find statistically significant evidence that a number of financial and macroeconomic variables can predict time-variation in the riskiness of corporate bonds, including in ways one might not expect. For example, a higher yield-to-maturity lowers riskiness by reducing the frequency and the magnitude of negative holding-period returns.
    Keywords: riskiness, corporate bonds, predictability
    JEL: G10 C46
    Date: 2009–10
  3. By: Carl Chiarella (School of Finance and Economics, University of Technology, Sydney); Roberto Dieci (Department of Mathematics for Economics and Social Sciences, University of Bologna); Xue-Zhong He (School of Finance and Economics, University of Technology, Sydney)
    Abstract: We introduce heterogeneous beliefs in to the mean-variance framework of the standard CAPM, in contrast to the standard approach which assumes homogeneous beliefs. By assuming that agents form optimal portfolios based upon their heterogeneous beliefs about conditional means and covariances of the risky asset returns, we set up a framework for the CAPM that incorporates the heterogeneous beliefs when the market is in equilibrium. In this framework we first construct a consensus belief (with respect to the means and covariances of the risky asset returns) to represent the aggregate market belief when the market is in equilibrium. We then extend the analysis to a repeated one-period set-up and establish a framework for a dynamic CAPM using a market fraction model in which agents are grouped according to their beliefs. The exact relation between heterogeneous beliefs, the market equilibrium returns and the ex-ante beta-coeffcients is obtained. CAPM and Heterogeneous beliefs.
    Date: 2009–08–01
  4. By: Dimitrios Vortelinos
    Abstract: This paper examines the economic value of various realized volatility and covariance estimators under the strategy of volatility timing. There are used three types of portfolios: Global Minimum Variance, Capital Market Line kai Capital Market Line with only positive weights. The state-of-the-art estimators of volatilities and covariances use 5-min high-frequency intraday data. The dataset concerns the FTSE-20, FTSE-40 and FTSE-80 indices of the Athens Stock Exchange (ASE). As far as I know, this is the rst work of its kind for the ASE equity market. Results concern not only the comparison of various estimators but also the comparison of different types of portfolios, in the strategy of volatility timing. The economic value of the contemporary non-parametric realized volatility estimators is more significant than the covariance of the daily squared returns. Moreover, the economic value of each estimator changes with the volatility timing.
    Keywords: portfolio analysis, intraday data, optimal sampling, microstructure, volatility forecasting, covariance, Athens Stock Exchange, volatility timing.
    Date: 2009
  5. By: Dimitrios Vortelinos; Dimitrios Thomakos
    Abstract: We test for and model volatility jumps for three major indices of the Athens Stock Exchange (ASE). Using intraday data we first construct several, state-of-the-art realized volatility estimators. We use these estimators to construct the jump components of volatility and perform various tests on their properties. Then we use the class of Heterogeneous Autoregressive (HAR) models for assessing the relevant effects of jumps on volatility. Our results expand and complement the previous literature on the ASE market and, in particular, this is the first time, to the best of our knowledge, that volatility jumps are examined and modeled for the Greek market, using a variety of realized volatility estimators.
    Keywords: Athens Stock Exchange , Bipower variation, Heterogeneous autoregressive models, Realized volatility, Volatility jumps.
    Date: 2009
  6. By: Cristina Belciuganu
    Abstract: In this paper we focus our attention on the tail risk and how different capital markets are influencing each other. Previous studies have detected return and volatility across countries during crises periods. Using the well-know Value at Risk (VaR) measure for heavy tailed financial returns, our objective is to detect if the information for a negative shock in a foreign market helps the forecast of the behavior of another market. We calculate 1 day, 95% and 99% Value at Risk for major US stock indices- S&P 500, NASDAQ 100, DJ INDUSTRIALS, major European stock indices – CAC 40, FTSE100, DAX30 and for Romanian stock index-BET. The VaR for each index is calculated the following techniques: Historical Simulation, Variance Approach and Extreme Value Theory. Spillover effects being the influence of one market on others, is examined using the Granger causality, for daily changes of the VAR series.
    Keywords: spillover effects, capital market
    Date: 2009–10
  7. By: Florin Stanciu
    Abstract: Recent studies show that a negative shock in stock prices will generate more volatility than a positive shock of similar magnitude. The aim of this paper is to test the hypothesis under which the the conditional variance of stock returns is an asymmetric function of past information. This paper investigates the volatility of the Romanian Stock Market using daily observations from BETC Index for the period from 1998 to 2008. The empirical analysis supports the hypothesis of asymmetric volatility; hence, good and bad news of the same magnitude have different impacts on the volatility level. In order to assess asymmetric volatility we use autoregressive conditional heteroskedasticity specifications known as TARCH and EGARCH. Our results show that the conditional variance is an asymmetric function of past innovations raising proportionately more during market declines, a phenomenon known as the leverage effect.
    Keywords: asymmetric conditional volatility, stock market
    Date: 2009–10

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