Dr Rachida Ouysse | UNSW Research

My Expertise

Modelling and forecasting with big data. Applications include forecasting macroeconomic activity ( inflation and GDP), predictability of asset returns, risk aversion and macro activity, and growth prediction in the property market
Nowcasting; Complexity Economics;
Bayesian econometrics as alternative to big data factor models
Dense and sparse predictive models
Opportunities and risks using big data and machine learning

Biography

I completed my PhD in Economics with specialisation in Econometrics at Boston College in 2003. Prior to joining UNSW, I held several teaching and research appointments at Boston College and University of Montreal. I have also been a visiting academic at the Risk Management Institute in Singapore, Department of Economics in San Diego USA, Department of Economics at University College Dublin, Ireland, and European Centre for Applied Research in...view more

My main research expertise is on modelling, estimating and making correct statistical analysis in big systems. Big-data presents technical challenges (hence curse of dimensionality) to the existing statistical tools that are used in economics and finance. My work falls in the new line of research that aims at turning this curse into a blessing. I have been published in top tier field journals. My contribution to the theoretical developments in econometrics has direct empirical implications. For example, a hedge fund manager wants to know what are the drivers of the market risk. Once these risk factors are identified, the hedge fund manager can build a portfolio to diversify away this risk. In big-data world, there are potentially hundreds/thousands of sources of systematic risk. The statistical tool I develop use this large volumes of information and selects the main key risk drivers without the fund manager having to make an uninformed ad-hoc guess. The technique is accurate and reliable and can be applied in many scenarios in Finance and Economics. Currently, I am working on identifying key drivers of growth in the real estate market in Australian Capital cities. For the Sydney area, the work is building a big data spatial econometric model to uncover what drives the high premium some suburbs earn their homeowners.

In another. area interest, I have published in A* journal in Finance where I establish new evidence of dependence of risk aversion on the Business cycle. Aggregate risk aversion it seems does vary with periods of economic booms and busts. Consumers perception of risk and wiliness to engage in risky ventures is conditional of the health of the economy.

Statistical inference sometimes has to be performed in small samples and asymptotic tools are no longer reliable. I have expertise in using simulation methods like the Bootstrap to study the statistical properties of key estimators like the Generalized Method of Moments estimator in models of practical importance in consumer behaviours. These models include the rational expectation model of the consumption asset pricing model.

Research Interests:

Econometric Theory: Statistical Inference in High-Dimensional Factor Models, Bootstrap Methods, GMM Estimation, Bayesian Econometrics
Applied Econometrics: Forecasting with large number of predictors
Financial Econometrics: Arbitrage pricing theory model, Consumption CAPM

ASB Profile: http://www.asb.unsw.edu.au/schools/Pages/RachidaOuysse.aspx

My Grants

Landcom (NSW Government) funded project: Review and development of a predictive model for the Sydney housing market, 2018-2019, ($35, 000)
Business School Research Grant, UNSW, 2018 ($10, 000)
ARC Project Booster Grant, Economics UNSW, 2017 ($5,000)
ARC Application Incentive Funding, ASB, UNSW, 2010-2013-2016 ($2, 000) Contestable Funding for International Strategic Projects, UNSW, 2012 ($30,000)
Australian School of Business Research Grant (ASBRG), UNSW, 2009 ($16,000)
Special Research Grant (SRG), UNSW, 2004-07 ($5,000, $3,000, $4,000, $4,000)
2003: Center for Applied Economic Research CAER, UNSW, $3000
2003: Faculty Research Grant Program (FRGP), UNSW, $ 15,000
Center for Applied Economic Research Grant CAER, 2003
Faculty Research Grant Program (FRGP), UNSW 2003 ($30, 000)
Best Paper Award, V IIth Spring Meeting of Young Economists
Doctoral Fellowship, Boston College, 1997-2002
H. Michael Mann Summer Dissertation Award, Boston College, 2000 Dissertation Award, Boston College, 2001
Thesis Proposal Award, Boston College, 2001
Excellence Bourse, University of Montreal, 1997
Full Scholarship, Canadian International Development Agency, 1995-1997

My Awards

Certificate of Outstanding Contribution in Reviewing, Emerging Markets Review, 2018

Best Paper Award, V IIth Spring Meeting of Young Economists

My Research Activities

Journal Publications
(1) Ouysse, R., 2021. Asset pricing with endogenous beliefs-dependent risk aversion. Journal of Financial Econometrics, Accepted Jan 2021 [A*]

(2) Ouysse, R., 2016. Bayesian model averaging and principal component regression forecasts in a data rich environment. International Journal of Forecasting, 32(3), pages 763-787. [Q1, IF 1.33, 5YIF 1.94, 87/333, cited 5, SSRN 230]

(3) Ouysse, R., 2014. On the performance of block-bootstrap continuously updated GMM for a class of non-linear conditional moment models: Moving block boot- strap infer- ence under weak identification. Computational Statistics, 29(1-2), pages: 233-261.[Q2, IF 0.403, 5YIF 0.558, SSRN 14]

(4) Ouysse, R., 2013. A fast iterated bootstrap procedure for approximating the small- sample bias. Communications in Statistics - Simulation and Computation, 42(7), pages: 1472-1494.

(5) Ouysse, R., 2011. Computationally efficient approximation for the double bootstrap mean bias correction. Economics Bulletin, 31(3) pages: 2388-2403.cited 3

(6) Ouysse, R and Kohn, R., 2010. Bayesian Selection of Risk Factors and Estimation of Factor Betas and Risk Premiums in the APT model. Computational Statistics and Data Analysis, 54, pages: 3249-3268.[Q1, IF 1.40, 5YIF 1.51, 34/122 cited 18, SSRN 791]

(7) Ouysse, R., 2010. Finite Sample Properties of Bootstrap GMM for Nonlinear Con- ditional Moment Models, InterStat Journal.

(8) Ouysse, R., 2006. Consistent Variable Selection in Large Panels when Factors are Observable. Journal of Multivariate Analysis, 97: 946-984.[Q1, IF 0.934 5YIF 1.153, 50/122, cited 12, SSRN 45]

(9) Ouysse, R., 2006. Approximate Factor Models: Finite Sample Distributions. Journal of Statistical Computation and Simulation, 76(4), pages: 279-303. Cited 2.

(10) Ouysse, R. Constrained principal components estimation of large approximate factor models. Journal of Econometrics (A*).

(11) Ouysse, R. Asset pricing with endogenous state-dependent risk aversion. Journal of Financial Econometrics (A*). Revision Due Feb 2020.

(12) Ouysse, R. Constrained principal components estimation of large approximate factor models. Journal of Applied Econometrics (A*)

(13) Ouysse, R. Predictability of Housing Prices in the Australian Capital Cities in a data rich environment. J ournal of Housing Economics (A)

(14) Ouysse, R.& Shi, S. & Mangionia, V. & Ge, J. & Heratha, S. & Rabhi, F. House Price Forecasting from Investment Perspectives

(15) Ouysse, R. & Chang, C. Consistent Estimation and Valid Inference for Dynamic Panel Data Models: Theory and Application to Latent Carbon Emissions Prices.
Note Abstract Submitted to Special Issue of Journal of Econometrics (A*).

(16) Ouysse, R. A Study of the distribution of Model Space under the Ridge and G-prior: Simulation and Application to Growth Data.

In Progress

(17) Ouysse, R., Bayesian Model Selection in Hybrid Factor model: Application to Arbitrage Pricing Theory Model.

(18) Ouysse, R., Consistency of the g-prior in multivariate regression models.

(19) Ouysse, R.& Qian, M., New Test for Endogeneity in Exactly Identified Instru- mental Variable Model.
Book Chapter. Ouysse, R., 2019 Estimation of Common Factors by Principal Com- ponents, Partial Least Squares, and related methods, in M acroeconomic Forecasting in the Era of Big Data. Editors Koop, G., Matyas, L. & Fuleky, P., to be published in the “Ad- vanced Studies in Theoretical and Applied Econometrics” series by Springer.

Ouysse, R., 2006. Book review of “Introduction to the Theory of Econometrics”, by Jan R. Magnus, VU University Press.

Ouysse, R., 2006. Book review on “Introduction to the Mathematical and Statistical Foundations of Econometrics”, Herman J. Bierens, Cambridge University Press, Economic Record, 82, pages:230-231.

Ouysse, R. 2013. Forecasting using a large number of predictors: Bayesian model averag- ing versus principal components regression Ouysse, R. 2009. “Fast Iterated Bootstrap for Mean Bias Correction,” Proceedings of 2009 NZESG Workshop, University of Canterbury, Christchurch, New Zealand.

Ouysse, R., Nicholas, C. 2008. “Time Varying Determinants of Cross-Country Growth,” UNSW School of Economics Discussion paper 2008/03.

Ouysse, R. 2007. “ Finite Sample Properties of the Dependent Bootstrap for Conditional Moment Models,” Proceedings of 36th Australian Conference of Economists, Hobart, Tas- mania.
Ouysse, R. 2005. “Sampling Properties of Block Bootstrap in Non-linear Rational Expec- tations Models: Case of Consumption Asset Pricing Model,” Proceedings of 34th Australian Conference of Economists, Melbourne, Australia.

Invited Seminars

UNU-CRIS (United Nations University Comparative Regional Integration Studies), Bruges, Belgium, 2018
SHERPA (Study Hive for Economic Research and Public Policy Analysis) University of Ghent, Belgium, 2018
UNAM (National Autonomous University of Mexico), Institute of Geography, Mexico, 2018
Department of Econometrics and Business Statistics, Monash University 2017
Department of Economics, Macquarie University 2017
Department of Economics, Auckland University 2017
School of Mathematics and Statistics, UNSW 2017
School of Mathematics and Statistics, UNSW 2016
Department of Economics, University of Ghent, Belgium 2015
Department of Econometrics and Business Statistics, Monash University 2014
School of Mathematics and Statistics, UNSW 2014
Department of Econometrics and Business Statistics, Monash University 2013
Dipartimento di Economiae Finanza, Universit`a di Roma ’Tor Vergata’, Rome, Italy, 2013
European Center for Applied Research in Economics and Statistics (ECARES), Belgium, 2013
European Center for Applied Research in Economics and Statistics (ECARES) 2009 (November)
School of Mathematics and Statistics, UNSW 2009
CentER Applied Research, Tilburg University (October) 2009
Department of Econometrics and Business Statistics, Monash University (September 2009)
Risk Management Institute (NUS, Singapore), Singapore Management University 2008
Rady School of Management (UCSD, USA), 2006
University College Dublin (Ireland), 2006
University of Alicante (Spain), 2006
School of Economics, University of Sydney 2004
Econometrics and Business Statistics (Monash, Australia), 2003
Australian National University, Macquarie University, 2003

Conference Presentations

AFES2019: Africa Meeting of the Econometric Society, Rabat, Morocco 2019
EcoSta2018: 2nd International Conference on Econometrics and Statistics, Hong 2018 Kong
SETA 2018: The 14th International Symposium on Econometric Theory and Applications, University of Sydney
Econometric Society Meetings & North American Winter Meeting at the ASSA, 2018 Philadelphia, USA 2018
World Statistics Congress ISIS-2017, Marrakech, Morocco 2017
International Panel Data Conference (IPDC), Thessaloniki, Greece 2017
10th International Conference on Computational and financial Econometrics (CFE), 2016 Seville
9th International Conference on Computational and financial Econometrics (CFE), 2015 London
8th International Conference on Computational and financial Econometrics (CFE), 2014 Pisa
19th International Panel Data Conference, London 2013
First Vienna Workshop on High-Dimensional Time Series in Macroeconomics and 2013 finance, Vienna
New Zealand Econometric Study Croup Workshop (Christchurch), Econometric 2009
Society Australasian Meeting (Canberra), Computing in Economics and Finance (Sydney) 2009
Far East and South Asia Meeting of the Econometric Society (Tokyo, Japan). 2009
Computational and Financial Econometrics (October Limassol, Cyprus)
Computational and Financial Econometrics (Neuchaˆtel, Switzerland) 2008
Western Economic Association Meeting (Honolulu, Hawaii), Far East Econometric Society Meeting (Singapore). 2008
Australian Conference of Economists (Hobart) 2007
Spring Meeting of Young Economists (Seville, Spain), (E C )2 Conference (Rotterdam, Netherlands), 2007
Econometric Society Australasian Meeting (Alice Spring), 2007
Australian Conference of Economists (Perth), 2007
Australian Conference of Economists (Melbourne) 2005
Econometric Society Australasian Meeting (Melbourne) 2004
Brazilian Econometric Society (Porto Seguro, Brazil) 2003
(EC)2 Conference (Bologna, Italy) 2002

My Research Supervision

Supervision keywords

big data

asset pricing

forecasting and improvement

spatial econometrics

financial market uncertainty

Areas of supervision

Big data models: sparse and dense.models. in economics and finance
State dependent preferences in asset pricing models
Predictability of asset returns
Predicting growth differentials in the Sydney property market in data rich environment
Topics on Consistent estimation and normality in frequentist approach
Bootstrap methods

My Engagement

Professional Service

2020- Master of Commerce Coordinator;
2018-2020 Acting Member of the Academic Integrity Committee;
2017- Acting Chair of the Academic Integrity Committee;
2016- Organizer (sole): 3nd Sydney SERG Econometric Theory Workshop; 2015- Co-organizer of the 2nd Sydney Econometric Theory Workshop;
2012- Organizer (sole): 1th Sydney Econometric Theory Workshop; 2010-Present Co-Founder of the Sydney Econometric Study Group;
2011 Coordinator of Peer Assisted Support Scheme (PASS);
2015, 2013, 2012 Co-organizer of WEE, Workshop on Emerging Economies; 2
003-2005 Internal Seminar organizer. School of Economics, UNSW.

My Teaching

Learning and Teaching Qualifications

(1) UNSW Graduate Certificate in University Learning and Teaching, January 2015- December 2016.

(2) UNSW Foundations of University Learning and Teaching (FULT), 2006

Present. Teaching

Term 1 2021

ECON1203 Business and Economic Statistics
ECON3209 Statistics for Econometrics

Previously

Course Taught	Year	Level
Econometric Analysis ECON6003 Financial Econometrics ECON3206 Business & Economic Statistics ECON1203 Applied Econometric methods ECON3208 Introductory Econometrics ECON2206 S tatistics and Data Analysis ECON5257 S Statistics for Econometrics Econometric Methods ECON3203 Econometric Theory Data, Models and Decisions Business Forecasting Quantitative Methods A	2011-2012 2016-2018 2015-2018 2011-2016 2012-2014 2010 2005, 2007-2010 2010 2002-08 2006-08 2003-05 2007-09	Honours & Ph.D Undergraduate Undergraduate Undergraduate Undergraduate MA Undergraduate Honours MA Undergraduate Undergraduate