Schedule Fall 2014
Tse-Chun Lin (Hong Kong University)
4 September 2014
How do short-sale costs affect put options trading? Evidence from separating hedging and speculative shorting demands
We find that put options bid-ask spread and put options trading volume both increase with equity lending fees. However, we also find that put options trading volume decreases with lending fees for banned stocks during the 2008 Short-Sale Ban period when only options market makers can short. By separating the speculative demand of short sellers from the hedging demand of options market makers in the lending market, our results provide a thorough analysis on the interaction between options market and equity lending market. We also reconcile the debate in the literature regarding the substitutability/complementarity between put options and short sales.
Christian Brownlees (Pompeu Fabra)
18 September 2014
Bank Credit Risk Networks: Evidence from the Eurozone Crisis
Co-authors: Christina Hans (Universitat Pompeu Fabra), Eulalia Nualarte (Universitat Pompeu Fabra)
The European financial crisis has shown that the credit risk of large financial institutions is highly interconnected as a results of a number of linkages between entities like exposure to common assets and interbank lending. In this work we propose a novel methodology to study credit risk interdependence in large panels of financial institutions. We introduce a credit risk model in which bank defaults can be triggered both by systematic economy wide and idiosyncratic bank specific shocks. The idiosyncratic shocks are assumed to have a sparse conditional dependence structure that we call the bank credit risk network. An estimation strategy based on CDS data and Lasso-type regression allows to estimate the parameters of the model and to recover the bank credit risk network structure. We apply this technique to analyse the interdependence of large European financial institutions between 2006 and 2013. Results show that the credit risk network captures a substantial amount of de pendence on top of what can be explained by systematic factors.
Andrea Carriero (Queen Mary London)
25 September 2014
No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates
Co-authors: Todd E. Clark (Federal Reserve Bank of Cleveland), Massimiliano Marcellino (Bocconi University, IGIER and CEPR)
We propose a method to produce density forecasts of the term structure of government bond yields that accounts for (i) the possible mispecification of an underlying Gaussian Affine Term Structure Model (GATSM) and (ii) the time varying volatility of interest rates. For this, we derive a Bayesian prior from a GATSM and use it to estimate the coefficients of a BVAR for the term structure, specifying a common, multiplicative, time varying volatility for the VAR disturbances. Results based on U.S. data show that this method significantly improves the precision of point and density forecasts of the term structure. While this paper focuses on term structure modelling, the proposed method can be applied for a wide range of alternative models, including DSGE models, and is a generalization of the method of Del Negro and Schorfheide (2004) to VARs featuring drifting volatilities. Our results show that both time variation in volatilities, and a hierarchical specification for the prior means, improve model fit and forecasting performance.
Michael Massmann (WHU)
16 October 2014
Estimating Structural Parameters in Regression Models with Adaptive Learning
Co-author: Norbert Christopeit (Universität Bonn)
This paper investigates the asymptotic properties of the ordinary least squares (OLS) estimator of structural parameters in a stylised macroeconomic model in which agents are boundedly rational and use an adaptive learning rule to form expectations of the endogenous variable.
In particular, when the learning recursion is subject to so-called decreasing gain sequences the model does not satisfy, in general, any of the sufficient conditions for consistent estimability available in the literature. The paper demonstrates that, for appropriate parameter sets, the OLS estimator nevertheless remains strongly consistent and asymptotically normally distributed.
Anthony Garratt (Warwick Business Chool)
6 November 2014
Information Rigidities and the News-Adjusted Output Gap
Co-authors: Kevin Lee and Kalvinder Shields
A vector-autoregressive model of actual output and expected output obtained from surveys is used to test for information rigidities and to provide a characterisation of output dynamics that accommodates these information structures. News on actual and expected outputs is decomposed to identify innovations understood to have short-lived effects and these are used with the model to derive a `news-adjusted output gap' measure. The approach is applied to US data over 1970q1-2014q2 and the gap measure is shown to provide a good leading indicator of inflation and to capture inflationary pressures well through estimated New Keynesian Phillips curves.
Björn Hagströmer (Stockholm Business School)
20 November 2014
Trading Fast and Slow: Colocation and Liquidity
Co-authors: Jonathan Brogaard, Lars Nordén and Ryan Riordan
We exploit an optional colocation upgrade at NASDAQ OMX Stockholm to assess how speed affects market liquidity. Liquidity improves for the overall market and even for non-colocated trading entities. We find that the upgrade is pursued mainly by market-maker-type participants. Those that upgrade use their enhanced speed to reduce their exposure to adverse selection and to relax their inventory constraints. In particular, the upgraded trading entities remain competitive at the best bid and offer even when they are inventory constrained. Our results suggest that increasing the speed of market making participants can have benefits for market liquidity.
Paulo Rodrigues (Bank of Portugal)
27 November 2014 ****CANCELLED****
Stefan Straetmans (Maastricht University)
4 December 2014
Financial crises and the state of the real economy: an Extreme Value approach
Financial crises typically occur both during economic recessions and expansions. The objective of this paper is to quantify the likelihood of financial crises and crisis spill-overs across the business cycle in order to assess whether and to what extent economic recession episodes are more inclined towards financial crises and crisis co-movements than expansion periods. Statistical extreme value analysis (EVT) is put at work to calculate these marginal and joint tail likelihoods for recessions and expansion subsamples. We find that tail risk increases during recessions for most financial assets. The same seems to happen with extreme linkages between financial markets. Moreover, cross-asset crisis spillovers like flight-to-quality effects between stocks, bonds or gold become more pronounced during recessions. Finally, we show that diversifying portfolio tail risk becomes more difficult during recessions. To our knowledge, applying EVT techniques to economically meaningful sample partitions is novel to the literature on financial extremes and extreme value analysis. From a statistical point of view, neglecting the existence of regimes in tail behaviour biases full sample estimates of measures of tail fatness or tail dependence because the presence of regimes induces higher order tail behaviour. EVT measures can also be made dependent on multiple regimes and regime determination can be made endogenous.
Christine Baumeister (Bank of Canada)
11 December 2014
Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information
It has become common in empirical macroeconomics to use numerical Bayesian methods to form structural inference in vector autoregressions that are identified solely on the basis of sign restrictions. Because sign restrictions only provide set-identification of structural parameters, over certain regions of the parameter space all that these procedures can do is reproduce the researcher's implicit prior distribution. In this paper we characterize these regions, explicate the prior that is implicit in popular methods, provide an analytical characterization of the full posterior distribution for arbitrary priors, and analyze the asymptotic properties of this posterior distribution. We show that in a simple bivariate supply and demand example, if the population correlation between reduced-form residuals is negative, then even if one has available an infinite sample of data, any inference about the supply elasticity is simply a restatement of the implicit prior distributions. More generally, the asymptotic posterior distribution of contemporaneous coefficients in an n-variable VAR is confined to the set of values that orthogonalize the population variance-covariance matrix of OLS residuals, with the height of the posterior proportional to the height of the prior at any point within that set. We suggest that researchers should use explicit rather than implicit prior distributions and should routinely report the difference between prior and posterior distributions for key magnitudes of interest. We illustrate these methods with a simple macroeconomic model.