nep-fmk New Economics Papers
on Financial Markets
Issue of 2011‒11‒28
seven papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Do Hedge Funds Manipulate Stock Prices? By Ben-David, Itzhak; Franzoni, Francesco; Landier, Augustin; Moussawi, Rabih
  2. Are Stock and Housing Returns Complements or Substitutes? Evidence from OECD Countries By Guglielmo Maria Caporale; Ricardo M. Sousa
  3. Conditional Correlations and Volatility Spillovers Between Crude Oil and Stock Index Returns By Chia-Lin Chang; Michael McAleer; Roengchai Tansuchat
  4. The Rise and Fall of S&P500 Variance Futures By Chia-Lin Chang; Juan-Angel Jimenez-Martin; Michael McAleer; Teodosio Pérez-Amaral
  5. Riding the Yield Curve: A Spanning Analysis By Galvani, Valentina; Landon, Stuart
  6. A Cost-Benefit Analysis of Basel III: Some Evidence from the UK By Meilin Yan; Maximilian J. B. Hall; Paul Turner
  7. Natural Barrier to Entry in the Credit Rating Industry By Jeon, Doh-Shin; Lovo, Stefano

  1. By: Ben-David, Itzhak; Franzoni, Francesco; Landier, Augustin; Moussawi, Rabih
    Abstract: We find evidence of significant price manipulation at the stock level by hedge funds on critical reporting dates. Stocks in the top quartile by hedge fund holdings exhibit abnormal returns of 30 basis points in the last day of the month and a reversal of 25 basis points in the following day. Using intraday data, we show that a significant part of the return is earned during the last minutes of the last day of the month, at an increasing rate towards the closing bell. This evidence is consistent with hedge funds’ incentive to inflate their monthly performance by buying stocks that they hold in their portfolios. Higher manipulations occur with funds that have higher incentives to improve their ranking relative to their peers and a lower cost of doing so.
    Date: 2011–02
  2. By: Guglielmo Maria Caporale (Centre for Empirical Finance); Ricardo M. Sousa (Universidade do Minho - NIPE)
    Abstract: In this paper we use a representative consumer model to analyse the equilibrium relation between the transitory deviations from the common trend among consumption, aggregate wealth, and labour income, cay, and focus on the implications for both stock returns and housing returns. The evidence based on data for 15 OECD countries shows that when agents expect future stock returns to be higher, they will temporarily allow consumption to rise. Regarding housing returns, if housing assets are seen as complements to stocks, then investors react in the same way, but if they are instead treated as substitutes consumption will be temporarily reduced.
    Keywords: consumption, wealth, stock returns, housing returns, OECD countries
    JEL: E21 E44 D12
    Date: 2011
  3. By: Chia-Lin Chang (Department of Applied Economics, Department of Finance, National Chung Hsing University Taichung, Taiwan); Michael McAleer (Econometrisch Instituut (Econometric Institute), Faculteit der Economische Wetenschappen (Erasmus School of Economics), Erasmus Universiteit, Tinbergen Instituut (Tinbergen Institute).; Division of Marketing and International Business, Nanyang Technological University, Singapore.); Roengchai Tansuchat (Faculty of Economics Maejo University Chiang Mai, Thailand)
    Abstract: This paper investigates the conditional correlations and volatility spillovers between the crude oil and financial markets, based on crude oil returns and stock index returns. Daily returns from 2 January 1998 to 4 November 2009 of the crude oil spot, forward and futures prices from the WTI and Brent markets, and the FTSE100, NYSE, Dow Jones and S&P500 stock index returns, are analysed using the CCC model of Bollerslev (1990), VARMA-GARCH model of Ling and McAleer (2003), VARMA-AGARCH model of McAleer, Hoti and Chan (2008), and DCC model of Engle (2002). Based on the CCC model, the estimates of conditional correlations for returns across markets are very low, and some are not statistically significant, which means the conditional shocks are correlated only in the same market and not across markets. However, the DCC estimates of the conditional correlations are always significant. This result makes it clear that the assumption of constant conditional correlations is not supported empirically. Surprisingly, the empirical results from the VARMA-GARCH and VARMA-AGARCH models provide little evidence of volatility spillovers between the crude oil and financial markets. The evidence of asymmetric effects of negative and positive shocks of equal magnitude on the conditional variances suggests that VARMA-AGARCH is superior to VARMA-GARCH and CCC. The estimation and analysis of the volatility and conditional correlations between crude oil returns and stock index returns can provide useful information for investors, oil traders and government agencies that are concerned with the crude oil and stock markets, especially regarding optimal hedging across the two markets.
    Keywords: Multivariate GARCH, volatility spillovers, conditional correlations, crude oil prices, spot, forward and futures prices, stock indexes.
    JEL: C22 C32 G32
    Date: 2011
  4. By: Chia-Lin Chang (Department of Applied Economics, Department of Finance, National Chung Hsing University Taichung, Taiwan); Juan-Angel Jimenez-Martin (Departamento de Economía Cuantitativa (Department of Quantitative Economics), Facultad de Ciencias Económicas y Empresariales (Faculty of Economics and Business), Universidad Complutense de Madrid); Michael McAleer (Econometrisch Instituut (Econometric Institute), Faculteit der Economische Wetenschappen (Erasmus School of Economics), Erasmus Universiteit, Tinbergen Instituut (Tinbergen Institute).; Division of Marketing and International Business, Nanyang Technological University, Singapore.); Teodosio Pérez-Amaral (Departamento de Economía Cuantitativa (Department of Quantitative Economics), Facultad de Ciencias Económicas y Empresariales (Faculty of Economics and Business), Universidad Complutense de Madrid)
    Abstract: Volatility is an indispensible component of sensible portfolio risk management. The volatility of an asset of composite index can be traded by using volatility derivatives, such as volatility and variance swaps, options and futures. The most popular volatility index is VIX, which is a key measure of market expectations of volatility, and hence is a key barometer of investor sentiment and market volatility. Investors interpret the VIX cash index as a “fear” index, and of VIX options and VIX futures as derivatives of the “fear” index. VIX is based on S&P500 call and put options over a wide range of strike prices, and hence is not model based. Speculators can trade on volatility risk with VIX derivatives, with views on whether volatility will increase or decrease in the future, while hedgers can use volatility derivatives to avoid exposure to volatility risk. VIX and its options and futures derivatives has been widely analysed in recent years. An alternative volatility derivative to VIX is the S&P500 variance futures, which is an expectation of the variance of the S&P500 cash index. Variance futures are futures contracts written on realized variance, or standardized variance swaps. The S&P500 variance futures are not model based, so the assumptions underlying the index do not seem to have been clearly understood. As these two variance futures are thinly traded, their returns are not easy to model accurately using a variety of risk models. This paper analyses the S&P500 3-month variance futures before, during and after the GFC, as well as for the full data period, for each of three alternative conditional volatility models and three densities, in order to determine whether exposure to risk can be incorporated into a financial portfolio without taking positions on the S&P500 index itself.
    Keywords: Risk management, financial derivatives, futures, options, swaps, 3-month variance futures, 12-month variance futures, risk exposure, volatility.
    JEL: C22 G32
    Date: 2011
  5. By: Galvani, Valentina (University of Alberta, Department of Economics); Landon, Stuart (University of Alberta, Department of Economics)
    Abstract: The average return on long-term bonds exceeds the return on short-term bills by a large amount over short investment horizons. A riding-the-yield-curve investment strategy takes advantage of the higher returns on longer term bonds. This strategy involves the purchase of bonds with maturities longer than the investment horizon and the sale of these bonds, before they mature, at the end of the investment horizon. Most of the literature that evaluates this strategy compares only ex post average returns or Sharpe ratios. In this paper, we use spanning tests to provide formal statistical evidence on the benefits of investing in long bonds when the investment horizon is short. The results for both the US and Canada indicate that an investor with a short horizon is better off investing in short-term debt instruments than long-term bonds.
    Keywords: North American bond market; portfolio diversification; mean-variance spanning; yield curve
    JEL: G11 G12 G15
    Date: 2011–11–01
  6. By: Meilin Yan (School of Business and Economics, Loughborough University, UK); Maximilian J. B. Hall (School of Business and Economics, Loughborough University, UK); Paul Turner (School of Business and Economics, Loughborough University, UK)
    Abstract: This paper provides a long-term cost-benefit analysis for the United Kingdom of the Basel III capital and liquidity requirements proposed by the Basel Committee on Banking Supervision (BCBS, 2010a). We provide evidence that the Basel III reforms will have a significant net positive long-term effect on the United Kingdom economy. The estimated optimal tangible common equity capital ratio is 10% of risk-weighted assets, which is larger than the Basel III target of 7%. We also estimate the maximum net benefit when banks meet the Basel III longterm liquidity requirements. Our estimated permanent net benefit is larger than the average estimates of the BCBS. This significant marginal benenfit suggests that UK banks need to increase their reliance on common equity in their capital base beyond the level required by Basel III as well as boosting customer deposits as a funding source.
    Keywords: Basel III, Cost-Benefit analysis, Tangible Common Equity Capital, Liquidity
    JEL: C32 C53 G21 G28
    Date: 2011–11
  7. By: Jeon, Doh-Shin; Lovo, Stefano
    Abstract: We present an infinite horizon model that studies the competition between a relatively ineffective incumbent Credit Rating Agency (CRA) and a sequence of entrant CRAs that are potentially more e¤ective but whose ability in appraising default risk is unproven at the time they enter the market. We show that free entry competition in the credit rating business fails in selecting the most competent CRA as long as two conditions are met. First, investors and issuers trust the incumbent CRA to provide a sincere, although imperfect, assessment of issuers’ default risk. Second, CRAs cannot charge higher fees for low rating than for high rating. Under these conditions a rather incompetent CRA can dominate the market without being worried about potentially more competent entrants. We derive policy implications.
    JEL: D82 G29 L11 L13 L15
    Date: 2011–05–10

This nep-fmk issue is ©2011 by Kwang Soo Cheong. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.