Hello! I'm Silvana

I work in financial econometrics and time-series analysis, particularly within high-frequency data, in the estimation of volatilities and betas for risk management and option pricing purposes.

I possess graduate education in Mathematics and I have conducted my work in R and Matlab. Currently, I am interested in expanding my programming skills to Python and hopefully next to C++.

I enjoy teaching and finding new ways to communicate and explain ideas in a simple manner. I also take pleasure from interdisciplinary and challenging work environments, and I am highly-analytical, detail-oriented, curious, and a problem solver.

EDUCATION

2018

Ph.D. in Economics

CREATES, AARHUS UNIVERSITY, DENMARK

I was affiliated to the Center for Research in Econometric Analysis of Time-Series (CREATES), where I conducted research on estimating spot and integrated variances, covariances and correlations of continuos-time Itô semimartingales, both with parametric and non-parametric methods.

2015

M.Sc. in Economics

CREATES, AARHUS UNIVERSITY, DENMARK

During my Master in Economics, while affiliated with CREATES as a Ph.D candidate, I took courses in Measure Theory, Probability Theory, Markov Chains, Mathematical Analysis and Advanced Financial Econometrics, among others.

2013

M.A. in Economics

UNIVERSIDAD DE MONTEVIDEO, URUGUAY

During my Master in Economics, I took courses in Advanced Microeconomics, Macroeconomics, and Econometrics.  I completed all the coursework and I left my thesis pending to start my Ph.D. in Denmark.

2011

B.A in Economics

UNIVERSIDAD DE LA REPÚBLICA, URUGUAY

I ranked in the top 5% of my class and I concluded my Bachelor in Economics with a thesis on a Markov regime switching GARCH model for FX data.

RESEARCH

Using a GARCH(1,1) for High-Frequency Volatility

I analyze an estimator of the integrated variance built on summed high-frequency conditional variances of a GARCH(1,1) over a fixed time interval, relative to the popular non-parametric realized variance estimator. The main advantage of the GARCH parametric approach lies on the possibility of improving foreacasts. Working Paper.

A cDCC-GARCH Filter for Spot Correlations

With Francesco Violante. We suggest a discrete-time filter to draw inference on the parameters of a consistent dynamic conditional correlation diffusion. Inference on such parameters is crucial to option pricing and doing it with a discrete-time model circumvents the many complexities and shortcomings of direct inference on continuous-time processes. Working Paper.

Betas in the Presence of Noise and Asyncrhonicity

With Sebastién Laurent and Orimar Sauri. We develop an estimator for spot and integrated betas of a multi-factor model, based on the Cholesky decomposition of the covariance. The estimation and asymptotic theory for spot betas solve which is the appropiate time-window length under which betas are constant and therefore OLS estimation is consistent. Working Paper. 

TEACHING

 Spring 2016

Aarhus University, Denmark

QUANTITATIVE, QUALITATIVE AND LIMITED DEPENDENT VARIABLES

Course contents on regressions using Stata.

Fall 2015

Aarhus University, Denmark

ECONOMETRICS I

Course contents on time-series, cross-section, and panel data analysis using Stata.

Fall 2015

Aarhus University, Denmark

ECONOMICS

Course contents on an introduction to microeconomics and macroeconomics.

2010-2011

Universidad de la República, Uruguay

MACROECONOMICS

An introduction to macroeconomics.

SKILLS

CV

Here you can find my Curriculum Vitae