| Grant number: | 13/22930-0 |
| Support Opportunities: | Research Projects - Thematic Grants |
| Start date: | April 01, 2014 |
| End date: | March 31, 2017 |
| Field of knowledge: | Applied Social Sciences - Economics - Quantitative Methods Applied to Economics |
| Principal Investigator: | Pedro Luiz Valls Pereira |
| Grantee: | Pedro Luiz Valls Pereira |
| Host Institution: | Escola de Economia de São Paulo (EESP). Fundação Getúlio Vargas (FGV). São Paulo , SP, Brazil |
| Pesquisadores principais: | Marcelo Fernandes |
| Associated researchers: | Cristina Mabel Scherrer ; Emerson Fernandes Marçal ; Flavio Augusto Ziegelmann ; Gustavo Fruet Dias ; João Filipe Bernardes Volkmann de Mendonça Mergulhão ; Luiz Koodi Hotta ; Marcelo Cunha Medeiros ; Pedro Alberto Chauffaille Saffi |
| Associated scholarship(s): | 16/18599-4 - Modeling and forecasting volatility of high dimensional financial series,
BP.PD 14/26448-0 - Contribution of temporal variation for price discovery in high-dimensional arbitrage portfolios, BP.PD |
Abstract
This research project aims to extend the standard methodology for price discovery to tackle more general arbitrage situations in which the underlying assets trade at different markets and/or platforms. Hasbrouck's (1995) information share measure is problematic because, in the presence of contemporaneous correlation between the innovations, it depends heavily on the ordering we attribute to prices in the system. To remain agnostic about which are the leading asset and market within the arbitrage portfolio, one could in principle compute some weighted average information share across all possible orderings. However, this is extremely inconvenient given that there are n! possible permutations in a system with n prices, implying averaging over thousands of permutations within the context of high-dimensional systems. The principal investigator has been developing a novel methodology to carry out price discovery analyses that does not impose any ex-ante assumption about which asset or trading platform conveys more information about shocks in the fundamental price. As such, it yields a single measure of information share, which does not depend on the ordering of the variables in the system. This project endeavors to apply such methods to different arbitrage situations in order to gather as much information as possible about a given latent common factor. For instance, apart from a dual-class premium, common and preferred shares provide information about the fundamental value of the underlying company as given by the present value of the expected cash flows, whereas the covered interest rate parity relates future and spot exchange rates to interest rate differentials. In addition, these projects will also attempt to contrive a price discovery methodology that allows for a stochastic covariance matrix and for irregularly-spaced-in-time data. The extant methods assume that the covariance matrix is constant and that we record prices at some fixed sampling frequency (say, 30 seconds or 5 minutes).The advantage of employing tick data is that trade duration, as measured by the time interval between transactions, reveals relevant information about how timely the different asset prices in the arbitrage portfolio react to news and hence about the price discovery process. (AU)
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