CV Lattes
ResearcherID
ORCID
Google Scholar Citations
Fundação Getúlio Vargas (FGV). Escola de Economia de São Paulo (EESP) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Pedro Valls has a Habilitation (Livre Docência) from University of São Paulo (1990), PhD in Economics (Statistics) from London School of Economics (1983), MSc in Statistics from IMPA (1978) and BSc in Applied Mathematics from PUC-Rio (1974). At São Paulo School of Economics FGV he is Professor of Financial Econometrics and Director of Centre for Quantitative Studies in Economics and Finance. He is Level I-A Research from CNPq since 2004 and Fellow of São Paulo Academy of Science since 2012, At EESP he was the Director of Graduate Studies from 2011 to 2012. At Insper he was Professor of Economics and Finance, Director of Research, Director of the Professional Master and Director of the Finance Lab. At IME_USP he was Associate and Assistant Professor. At Impa he was Associated Reseraher.. At INPES-IPEA he was senior researcher. He was Academic Visitor at CREATES Aarhus University; INET University of Oxford; School of Economics and Finance at Queen Mary College University of London; Department of Statistics and Department of Economics at London School of Economics; Department of Economics at University of Cambridge and Department of Finance at Cass Business School. He was Associate Member of Nuffield College University of Oxford. He was President of the Brazilian Econometric Society (1986-1988) and Vice-President of the Brazilian Econometric Society (1984-1986). His research interest are Financial Econometrics, Forecasting, Empirical Finance, Computational Finance, Time Series Econometrics (Source: Lattes Curriculum)
| News published in Agência FAPESP Newsletter about the researcher |
| More itemsLess items |
| TITULO |
| Articles published in other media outlets ( ): |
| More itemsLess items |
| VEICULO: TITULO (DATA) |
| VEICULO: TITULO (DATA) |
This project deals with new methodologies for econometric modelling and forecasting in high dimensional and/or frequency setting, as well as mixed-data frequencies setting. One of the challenges in econometrics in high dimensional problems is to deal with complex world, including structural changes, using sparce vector autoregressive models and dense (factors). Applications of these metho…
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…
The aim of the research project is to propose models and forecasting for the volatility for high dimensional financial time series. It will consider methods to obtain point and interval forecasts and density forecast. Comparisons with existing methods will be considered. Monte Carlo experiments will be carried out to evaluate the performance of the proposed procedures. It will also evalua…
This research project aims to extend the standard methodology for price discovery to tackle time-varying information shares. The existent information share measures are constant over time because it assumes a stable contemporaneous correlation between market. However, recent empirical results based on recursive estimates and sample splitting indicate that the contribution to the price dis…
Dimension reduction techniques are being used in the economic and financial literature as an alternative way to modelling and forecasting the volatility and circumvent the curse of dimensionality. Most of procedures proposed in the literature are developed to extract the main features of returns and assume that the principal/common component for volatilities coincide with the volatility …
| 1 / 1 | Ongoing grants |
| 3 / 2 | Completed research grants |
| 3 / 2 | Completed scholarships in Brazil |
| 2 / 1 | Completed scholarships abroad |
| 9 / 6 | All research grants and scholarships |
| Associated processes | |