New Economics Papers
on Financial Markets
Issue of 2013‒09‒26
seven papers chosen by

  1. Statistical inference of co-movements of stocks during a financial crisis By Takero Ibuki; Shunsuke Higano; Sei Suzuki; Jun-ichi Inoue; Anirban Chakraborti
  2. Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500 By Peter C.B. Phillips; Shu-Ping Shi; Jun Yu
  3. On the fortunes of stock exchanges and their reversals: evidence from foreign listings By Fernandes, Nuno; Giannetti, Mariassunta
  4. Conditional Risk Premia in Currency Markets and Other Asset Classes By Lettau, Martin; Maggiori, Matteo; Weber, Michael
  5. The Peer Performance of Hedge Funds By David Ardia; Kris Boudt
  6. Volatility and dynamic conditional correlations of European emerging stock markets By Baumohl, Eduard; Lyocsa, Stefan
  7. Modeling the Volatility of the Dow Jones Islamic Market World Index Using a Fractionally Integrated Time Varying GARCH (FITVGARCH) Model By Adnen Ben Nasr; Ahdi N. Ajmi; Rangan Gupta

  1. By: Takero Ibuki; Shunsuke Higano; Sei Suzuki; Jun-ichi Inoue; Anirban Chakraborti
    Abstract: In order to figure out and to forecast the emergence phenomena of social systems, we propose several probabilistic models for the analysis of financial markets, especially around a crisis. We first attempt to visualize the collective behaviour of markets during a financial crisis through cross-correlations between typical Japanese daily stocks by making use of multi- dimensional scaling. We find that all the two-dimensional points (stocks) shrink into a single small region when a economic crisis takes place. By using the properties of cross-correlations in financial markets especially during a crisis, we next propose a theoretical framework to predict several time-series simultaneously. Our model system is basically described by a variant of the multi-layered Ising model with random fields as non-stationary time series. Hyper-parameters appearing in the probabilistic model are estimated by means of minimizing the 'cumulative error' in the past market history. The justification and validity of our approaches are numerically examined for several empirical data sets.
    Date: 2013–09
  2. By: Peter C.B. Phillips (Cowles Foundation, Yale University); Shu-Ping Shi (Australian National University); Jun Yu (Singapore Management University)
    Abstract: Recent work on econometric detection mechanisms has shown the effectiveness of recursive procedures in identifying and dating financial bubbles. These procedures are useful as warning alerts in surveillance strategies conducted by central banks and fiscal regulators with real time data. Use of these methods over long historical periods presents a more serious econometric challenge due to the complexity of the nonlinear structure and break mechanisms that are inherent in multiple bubble phenomena within the same sample period. To meet this challenge the present paper develops a new recursive flexible window method that is better suited for practical implementation with long historical time series. The method is a generalized version of the sup ADF test of Phillips, Wu and Yu (2011, PWY) and delivers a consistent date-stamping strategy for the origination and termination of multiple bubbles. Simulations show that the test significantly improves discriminatory power and leads to distinct power gains when multiple bubbles occur. An empirical application of the methodology is conducted on S&P 500 stock market data over a long historical period from January 1871 to December 2010. The new approach successfully identifies the well-known historical episodes of exuberance and collapse over this period, whereas the strategy of PWY and a related CUSUM dating procedure locate far fewer episodes in the same sample range.
    Keywords: Date-stamping strategy, Flexible window, Generalized sup ADF test, Multiple bubbles, Rational bubble, Periodically collapsing bubbles, Sup ADF test
    JEL: C15 C22
    Date: 2013–09
  3. By: Fernandes, Nuno; Giannetti, Mariassunta
    Abstract: Using a sample that provides unprecedented detail on foreign listings, new listings, and delistings for 29 exchanges in 24 countries starting from the early 1980s, we document a growing tendency of listings to concentrate in the U.S. and the U.K., and large changes in all exchanges’ ability to attract foreign companies. We highlight the following determinants of these patterns. First, during the sample period, investor protection improved in many countries. As investor protection improves in the country of origin, firms become less likely to list in countries with weak investor protection, but more likely to list in countries with strong investor protection, especially in the U.K. and the U.S. Second, we show that foreign listings are related to the exchange’s market valuation in the same way that domestic equity issues are and that firms that are more difficult to evaluate are more inclined to list in foreign exchanges with high valuations. JEL Classification: G15, G38, M41, M45, F40
    Keywords: Cross-listings, investor protection, market timing, SOX
    Date: 2013–09
  4. By: Lettau, Martin; Maggiori, Matteo; Weber, Michael
    Abstract: The downside risk CAPM (DR-CAPM) can price the cross section of currency returns. The market-beta differential between high and low interest rate currencies is higher conditional on bad market returns, when the market price of risk is also high, than it is conditional on good market returns. Correctly accounting for this variation is crucial for the empirical performance of the model. The DR-CAPM can jointly explain the cross section of equity, commodity, sovereign bond and currency returns, thus offering a unified risk view of these asset classes. In contrast, popular models that have been developed for a specific asset class fail to jointly price other asset classes.
    Keywords: Carry Trade; Conditional risk premia; Cross Section of Equities and Commodities; Currency Returns; Downside Risk; Exchange Rates; UIP
    JEL: F31 F34 G11 G15
    Date: 2013–05
  5. By: David Ardia; Kris Boudt
    Abstract: An essential component in the analysis of (hedge) fund returns is to measure its performance with respect to the group of peer funds. Through the analysis of risk-adjusted return percentiles an answer is given to the question how many funds are out-performed by the focal fund. In case all funds perform equally well, this approach will lead a random number between zero and one, depending on how lucky the fund is. We use the false discovery rate approach to construct relative performance ratios that account for the uncertainty in estimating the performance differential of two funds. Our application is on hedge funds, which leads us to develop a test for equality of the modified Sharpe ratio of two funds. The effectiveness of the method is illustrated with a Monte Carlo study and an empirical study is performed on the Hedge Fund Research database.
    Keywords: equal-performance ratio, false discovery rate, hedge fund, modified Sharpe ratio, out-performance ratio, peer group, performance measurement
    JEL: C12 C21 C22
    Date: 2013
  6. By: Baumohl, Eduard; Lyocsa, Stefan
    Abstract: This study examines the relationship between time-varying correlations and conditional volatility among eight European emerging stock markets and the MSCI World stock market index from January 2000 to December 2012. Correlations are estimated in the standard and asymmetric dynamic conditional correlation (DCC) model frameworks. The results can be summarized by three main findings: (1) asymmetry in volatility is not a common phenomenon in emerging markets; (2) asymmetry in correlations is found only with respect to the Hungarian stock market; and (3) the relationship between volatility and correlations is positive and significant in all countries included in the study. Thus, diversification benefits decrease during periods of higher volatility.
    Keywords: conditional volatility, time-varying correlations, emerging markets
    JEL: C32 G01 G15
    Date: 2013–09–18
  7. By: Adnen Ben Nasr (Laboratoire BESTMOD, ISG de Tunis, Universite de Tunis, Tunisia.); Ahdi N. Ajmi (College of Science and Humanities in Slayel, Salman bin Abdulaziz University, Kingdom of Saudi Arabia); Rangan Gupta (Department of Economics, University of Pretoria)
    Abstract: Appropriate modeling of the process of volatility has implications for portfolio selection, the pricing of derivative securities and risk management. Further, a large body of research has suggested that both long memory and structural changes simultaneously characterize the structure of financial returns volatility. Given this, in this paper, we aim to model conditional volatility of the returns of the Dow Jones Islamic Market World Index (DJIM), interest on which has come to the fore following the need for renovation of the conventional financial system, in the wake of the recent global financial crisis. To model the conditional volatility of the DJIM returns, accounting for both long memory and structural changes, we allow the parameters in the conditional variance equation of the Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity (FIGARCH) model to be time dependent, such that the parameters evolve smoothly over time based on a logistic smooth transition function, yielding a Fractionally Integrated Time Varying Generalized Autoregressive Conditional Heteroskedasticity (FITVGARCH) model. Our results show that, in terms of model diagnostics and information criteria, the FITVGARCH model performs better than the FIGARCH model in explaining conditional volatility of the DJIM returns, thus, highlighting the need to model simultaneously long-memory and structural changes in the volatility process of asset returns.
    Keywords: Volatility modeling, Long memory, Structural changes, Model specification
    Date: 2013–09

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