http://repub.eur.nl/res/concept/jel-G/ Recent publications classified by JEL Code G en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/39847/ 2014-04-15T00:00:00Z Accurate prediction of risk measures such as Value at Risk (VaR) and Expected Shortfall (ES) requires precise estimation of the tail of the predictive distribution. Two novel concepts are introduced that offer a specific focus on this part of the predictive density: the censored posterior, a posterior in which the likelihood is replaced by the censored likelihood; and the censored predictive likelihood, which is used for Bayesian Model Averaging. We perform extensive experiments involving simulated and empirical data. Our results show the ability of these new approaches to outperform the standard posterior and traditional Bayesian Model Averaging techniques in applications of Value-at-Risk prediction in GARCH models. Gatarek, L.T. Hoogerheide, L.F. Honing, K. http://repub.eur.nl/res/pub/39433/ 2013-03-21T00:00:00Z The purpose of the paper is to discuss ten things potential users should know about the limits of the Dynamic Conditional Correlation (DCC) representation for estimating and forecasting time-varying conditional correlations. The reasons given for caution about the use of DCC include the following: DCC represents the dynamic conditional covariances of the standardized residuals, and hence does not yield dynamic conditional correlations; DCC is stated rather than derived; DCC has no moments; DCC does not have testable regularity conditions; DCC yields inconsistent two step estimators; DCC has no asymptotic properties; DCC is not a special case of GARCC, which has testable regularity conditions and standard asymptotic properties; DCC is not dynamic empirically as the effect of news is typically extremely small; DCC cannot be distinguished empirically from diagonal BEKK in small systems; and DCC may be a useful filter or a diagnostic check, but it is not a model. Caporin, M. McAleer, M.J. http://repub.eur.nl/res/pub/39191/ 2013-03-07T00:00:00Z Raviv, E. http://repub.eur.nl/res/pub/39186/ 2013-03-04T00:00:00Z In this paper, we develop a modified maximum likelihood (MML) estimator for the multiple linear regression model with underlying student t distribution. We obtain the closed form of the estimators, derive the asymptotic properties, and demonstrate that the MML estimator is more appropriate for estimating the parameters of the Capital Asset Pricing Model by comparing its performance with least squares estimators (LSE) on the monthly returns of US portfolios. The empirical results reveal that the MML estimators are more efficient than LSE in terms of the relative efficiency of one-step-ahead forecast mean square error in small samples. Bian, G. McAleer, M.J. Wong, W-K. http://repub.eur.nl/res/pub/38779/ 2013-01-31T00:00:00Z There has recently been growing interest in modeling and estimating alternative continuous time multivariate stochastic volatility models. We propose a continuous time fractionally integrated Wishart stochastic volatility (FIWSV) process. We derive the conditional Laplace transform of the FIWSV model in order to obtain a closed form expression of moments. We conduct a two-step procedure, namely estimating the parameter of fractional integration via log-periodgram regression in the first step, and estimating the remaining parameters via the generalized method of moments in the second step. Monte Carlo results for the procedure shows reasonable performances in finite samples. The empirical results for the bivariate data of the S&P 500 and FTSE 100 indexes show that the data favor the new FIWSV processes rather than one-factor and two-factor models of Wishart autoregressive processes for the covariance structure. Asai, M. McAleer, M.J. http://repub.eur.nl/res/pub/38776/ 2013-01-22T00:00:00Z Allen, D.E. Anwar, A.M. McAleer, M.J. Powell, R.J. Singh, A.K. http://repub.eur.nl/res/pub/38773/ 2013-01-18T00:00:00Z The purpose of this paper is to examine the asymmetric relationship between price and implied volatility and the associated extreme quantile dependence using linear and non linear quantile regression approach. Our goal in this paper is to demonstrate that the relationship between the volatility and market return as quantified by Ordinary Least Square (OLS) regression is not uniform across the distribution of the volatility-price return pairs using quantile regressions. We examine the bivariate relationship of six volatility-return pairs, viz. CBOE-VIX and S&P-500, FTSE-100 Volatility and FTSE-100, NASDAQ-100 Volatility (VXN) and NASDAQ, DAX Volatility (VDAX) and DAX-30, CAC Volatility (VCAC) and CAC-40 and STOXX Volatility (VSTOXX) and STOXX. The assumption of a normal distribution in the return series is not appropriate when the distribution is skewed and hence OLS does not capture the complete picture of the relationship. Quantile regression on the other hand can be set up with various loss functions, both parametric and non-parametric (linear case) and can be evaluated with skewed marginal based copulas (for the non linear case). Which is helpful in evaluating the non-normal and non-linear nature of the relationship between price and volatility. In the empirical analysis we compare the results from linear quantile regression (LQR) and copula based non linear quantile regression known as copula quantile regression (CQR). The discussion of the properties of the volatility series and empirical findings in this paper have significance for portfolio optimization, hedging strategies, trading strategies and risk management in general. Allen, D.E. Singh, A.K. Powell, R.J. McAleer, M.J. Taylor, J. Thomas, L. http://repub.eur.nl/res/pub/38750/ 2013-01-17T00:00:00Z This paper features an analysis of the relationship between the S&P 500 Index and the VIX using daily data obtained from both the CBOE website and SIRCA (The Securities Industry Research Centre of the Asia Pacific). We explore the relationship between the S&P 500 daily continuously compounded return series and a similar series for the VIX in terms of a long sample drawn from the CBOE running from 1990 to mid 2011 and a set of returns from SIRCA's TRTH datasets running from March 2005 to-date. We divide this shorter sample, which captures the behaviour of the new VIX, introduced in 2003, into four roughly equivalent sub-samples which permit the exploration of the impact of the Global Financial Crisis. We apply to our data sets a series of non-parametric based tests utilising entropy based metrics. These suggest that the PDFs and CDFs of these two return distributions change shape in various subsample periods. The entropy and MI statistics suggest that the degree of uncertainty attached to these distributions changes through time and using the S&P 500 return as the dependent variable, that the amount of information obtained from the VIX also changes with time and reaches a relative maximum in the most recent period from 2011 to 2012. The entropy based non-parametric tests of the equivalence of the two distributions and their symmetry all strongly reject their respective nulls. The results suggest that parametric techniques do not adequately capture the complexities displayed in the behaviour of these series. This has practical implications for hedging utilising derivatives written on the VIX, which will be the focus of a subsequent study. Allen, D.E. McAleer, M.J. Powell, R.J. Singh, A.K. http://repub.eur.nl/res/pub/38230/ 2013-01-08T00:00:00Z This paper examines the size effects of volatility spillovers for firm performance and exchange rates with asymmetry in the Taiwan tourism industry. The analysis is based on two conditional multivariate models, BEKK-AGARCH and VARMA-AGARCH, in the volatility specification. Daily data from 1 July 2008 to 29 June 2012 for 999 firms are used, which covers the Global Financial Crisis. The empirical findings indicate that there are size effects on volatility spillovers from the exchange rate to firm performance. Specifically, the risk for firm size has different effects from the three leading tourism sources to Taiwan, namely USA, Japan, and China. Furthermore, all the return series reveal quite high volatility spillovers (at over sixty percent) with a one-period lag. The empirical results show a negative correlation between exchange rate returns and stock returns. However, the asymmetric effect of the shock is ambiguous, owing to conflicts in the significance and signs of the asymmetry effect in the two estimated multivariate GARCH models. The empirical findings provide financial managers with a better understanding of how firm size is related to financial performance, risk and portfolio management strategies that can be used in practice. Chang, C.L. Hsu, H-K. McAleer, M.J. http://repub.eur.nl/res/pub/38233/ 2013-01-08T00:00:00Z The Basel II Accord requires that banks and other Authorized Deposit-taking Institutions (ADIs) communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more risk models to measure Value-at-Risk (VaR). The risk estimates of these models are used to determine capital requirements and associated capital costs of ADIs, depending in part on the number of previous violations, whereby realised losses exceed the estimated VaR. In this paper we define risk management in terms of choosing from a variety of risk models, and discuss the selection of optimal risk models. A new approach to model selection for predicting VaR is proposed, consisting of combining alternative risk models, and we compare conservative and aggressive strategies for choosing between VaR models. We then examine how different risk management strategies performed during the 2008-09 global financial crisis. These issues are illustrated using Standard and Poor’s 500 Composite Index. McAleer, M.J. Jimenez-Martin, J-A. http://repub.eur.nl/res/pub/38222/ 2013-01-01T00:00:00Z The paper proposes a general asymmetric multifactor Wishart stochastic volatility (AMWSV) diffusion process which accommodates leverage, feedback effects and multifactor for the covariance process. The paper gives the closed-form solution for the conditional and unconditional Laplace transform of the AMWSV models. The paper also suggests estimating the AMWSV model by the generalized method of moments using information not only of stock prices but also of realized volatilities and co-volatilities. The empirical results for the bivariate data of the NASDAQ 100 and S&P 500 indices show that the general AMWSV model is preferred among several nested models. Asai, M. McAleer, M.J. http://repub.eur.nl/res/pub/38775/ 2013-01-01T00:00:00Z Research papers in empirical finance and financial econometrics are among the most widely cited, downloaded and viewed articles in the discipline of Finance. The special issue presents several papers by leading scholars in the field on “Recent Developments in Financial Economics and Econometrics”. The breadth of coverage is substantial, and includes original research and comprehensive review papers on theoretical, empirical and numerical topics in Financial Economics and Econometrics by leading researchers in finance, financial economics, financial econometrics and financial statistics. The purpose of this special issue on “Recent Developments in Financial Economics and Econometrics” is to highlight several novel and significant developments in financial economics and financial econometrics, specifically dynamic price integration in the global gold market, a conditional single index model with local covariates for detecting and evaluating active management, whether the Basel Accord has improved risk management during the global financial crisis, the role of banking regulation in an economy under credit risk and liquidity shock, separating information maximum likelihood estimation of the integrated volatility and covariance with micro-market noise, stress testing correlation matrices for risk management, whether bank relationship matters for corporate risk taking, with evidence from listed firms in Taiwan, pricing options on stocks denominated in different currencies, with theory and illustrations, EVT and tail-risk modelling, with evidence from market indices and volatility series, the economics of data using simple model free volatility in a high frequency world, arbitrage-free implied volatility surfaces for options on single stock futures, the non-uniform pricing effect of employee stock options using quantile regression, nonlinear dynamics and recurrence plots for detecting financial crisis, how news sentiment impacts asset volatility, with evidence from long memory and regime-switching approaches, quantitative evaluation of contingent capital and its applications, high quantiles estimation with Quasi-PORT and DPOT, with an application to value-at-risk for financial variables, evaluating inflation targeting based on the distribution of inflation and inflation volatility, the size effects of volatility spillovers for firm performance and exchange rates in tourism, forecasting volatility with the realized range in the presence of noise and non-trading, using CARRX models to study factors affecting the volatilities of Asian equity markets, deciphering the Libor and Euribor spreads during the subprime crisis, information transmission between sovereign debt CDS and other financial factors for Latin America, time-varying mixture GARCH models and asymmetric volatility, and diagnostic checking for non-stationary ARMA models with an application to financial data. Chang, C.L. Allen, D.E. McAleer, M.J. http://repub.eur.nl/res/pub/38225/ 2012-12-31T00:00:00Z Jaskowski, M. McAleer, M.J. http://repub.eur.nl/res/pub/38216/ 2012-12-12T00:00:00Z We assess the effect of aggregate stock market illiquidity on U.S. Treasury bond risk premia. We find that the stock market illiquidity variable adds to the well established Cochrane-Piazzesi and Ludvigson-Ng factors. It explains 10%, 9%, 7%, and 7% of the one-year-ahead variation in the excess return for two-, three-, four-, and ve-year bonds respectively and increases the adjusted R2 by 3-6% across all maturities over Cochrane and Piazzesi (2005) and Ludvigson and Ng (2009) factors. The effects are highly statistically and economically significant both in and out of sample. We find that our result is robust to and is not driven by information from open interest in the futures market, long-run inflation expectations, dispersion in beliefs, and funding liquidity. We argue that stock market illiquidity is a timely variable that is related to " right-to-quality" episodes and might contain information about expected future business conditions through funding liquidity and investment channels. Bouwman, K.E. Sojli, E. Tham, W.W. http://repub.eur.nl/res/pub/38199/ 2012-11-12T00:00:00Z This paper documents that speed is crucially important for high frequency trading strategies based on U.S. macroeconomic news releases. Using order level data of the highly liquid S&P500 ETF traded on NASDAQ from January 6, 2009, to December 12, 2011, we find that a delay of 300 milliseconds (1 second) significantly reduces returns by 3.08% (7.33%) compared to instantaneous execution over all announcements in the sample. This reduction is stronger in case of high impact news and on days with high volatility. In addition, we assess the effect of algorithmic trading on market quality around macroeconomic news. Increases in algorithmic trading activity have a positive (mixed) effect on market quality measures when we use algorithmic trading proxies that capture the top of the orderbook (full orderbook). Scholtus, M.L. Dijk, D.J.C. van Frijns, B.P.M. http://repub.eur.nl/res/pub/38949/ 2012-11-01T00:00:00Z The effectiveness of any sanction depends on the costs of avoiding its restrictions. We examine whether bearish option strategies were substitutes for short sales during the September 2008 short-sale ban. We find a significant diminution in option volumes and a significant increase in option bid-ask spreads for banned stock relative to unbanned stock during the ban period. Apparent violations of the put-call parity bound became significantly more frequent for banned stocks during the ban period. We conclude that the ban acted as an effective restriction on trading in options. Grundy, B.D. Lim, B. Verwijmeren, P. http://repub.eur.nl/res/pub/17699/ 2012-10-29T00:00:00Z The promotion and support of small and medium-sized enterprises (SMEs) forms an essential ingredient of the policies designed to help improve Europe’s economic performance. A key issue is whether SMEs face difficulty obtaining bank loans. Using pre-crisis survey data from 2005 and 2006 for nearly 3,500 SMEs (firms with fewer than 250 employees) in the European Union (EU), we investigate the determinants of perceived bank loan accessibility at the firm level and at the country level. Based on hierarchical (multi-level) binomial logit regressions, our findings show that the youngest and smallest SMEs have the worst perceptions regarding access to bank loans. The SMEs in nations with concentrated banking sectors are more positive about loan accessibility. In addition, a high fraction of foreign-owned banks is associated with improved perceptions regarding loan accessibility in the EU 15 but not in the EU 10. Canton, E.J.F. Grilo, I. Monteagudo, J. Zwan, P.W. van der http://repub.eur.nl/res/pub/37538/ 2012-10-25T00:00:00Z We introduce a heuristic bias-adjustment for the transaction price-based realized range estimator of daily volatility in the presence of bid-ask bounce and non-trading. The adjustment is an extension of the estimator proposed in Christensen et al. (2009). We relax the assumption that all intra-day high (low) transaction prices are at the ask (bid) quote. Using data-based simulations we obtain estimates of the probability that a given intraday range is (upward or downward) biased or not, which we use for a more refined bias-adjustment of the realized range estimator. Both Monte Carlo simulations and an empirical application involving a liquid and a relatively illiquid S&P500 constituent demonstrate that ex post measures and ex ante forecasts based on the heuristically adjusted realized range compare favorably to existing bias-adjusted (two time scales) realized range and (two time scales) realized variance estimators. Bannouh, K. Martens, M.P.E. Dijk, D.J.C. van http://repub.eur.nl/res/pub/37871/ 2012-10-25T00:00:00Z The promotion and support of small and medium-sized enterprises (SMEs) is an essential component of policies designed to help improve Europe's economic performance. A crucial issue is whether SMEs face difficulty obtaining bank loans. Using pre-crisis survey data from 2005 and 2006 for nearly 3,500 SMEs (firms with fewer than 250 employees) in the European Union (EU), we investigate the determinants of perceived bank loan accessibility at the firm level and at the country level. Based on hierarchical (multi-level) binomial logit regressions, our findings show that the youngest and smallest SMEs have the worst perception of access to bank loans. The SMEs in nations with concentrated banking sectors are more positive about loan accessibility. In addition, a high fraction of foreign-owned banks is associated with improved perception of loan accessibility in the EU 15 but not in the EU 10. Canton, E.J.F. Grilo, I. Monteagudo, J. Zwan, P.W. van der http://repub.eur.nl/res/pub/37470/ 2012-10-23T00:00:00Z We introduce a Mixed-Frequency Factor Model (MFFM) to estimate vast dimensional covari- ance matrices of asset returns. The MFFM uses high-frequency (intraday) data to estimate factor (co)variances and idiosyncratic risk and low-frequency (daily) data to estimate the factor loadings. We propose the use of highly liquid assets such as exchange traded funds (ETFs) as factors. Prices for these contracts are observed essentially free of microstructure noise at high frequencies, allowing us to obtain precise estimates of the factor covariances. The factor loadings instead are estimated from daily data to avoid biases due to market microstructure effects such as the relative illiquidity of individual stocks and non-synchronicity between the returns on factors and stocks. Our theoretical, simulation and empirical results illustrate that the performance of the MFFM is excellent, both compared to conventional factor models based solely on low-frequency data and to popular realized covariance estimators based on high-frequency data. Bannouh, K. Martens, M.P.E. Oomen, R.C.A. Dijk, D.J.C. van