Wenying Yao

Senior Lecturer

Department of Economics
Deakin Business School
Deakin University
Burwood, VIC 3125 Australia

wenying.yao@deakin.edu.au

About Me

Welcome to my page!

I am a Senior Lecturer in Economics at the Department of Economics, Deakin University. My research expertise lies in time series econometrics theory and methods, and the applications of innovative econometric tools to financial and macroeconomic time series data.

I have previously worked at Monash University and the University of Tasmania as a Research Fellow since I obtained my PhD degree from the Department of Econometrics and Business Statistics, Monash University in December 2013. I have published in top field journals in econometrics, including Journal of Econometrics, Journal of Business & Economic Statistics, Journal of Applied Econometrics, among other outlets.

News and updates

Nov.2020 My project "New Insights on Modelling Time Trends with Panel Data: Theory and Practice" has been funded by the Australian Research Council Discovery Project. I will be working with Dr. Bin Peng (Monash University) and Prof. Joakim Westerlund(Deakin University and Lund University) on this project in 2021-2023.
Sep.2018 My promotion application to Senior Lecturer is successful, effective from January 2019.
Aug.2016 I joined Deakin University as a Lecturer in Economics.
Apr.2016 I've started working at Monash University as a Research Fellow until July 2016.
Dec.2015 I will be attending the ASSA/AEA meeting in San Francisco during 3-5 January 2016.
Nov.2015 My application to the "Australia-Germany Joint Research Co-operation Scheme" has been successful. I will be working with Dr Lars Winkelmann (Free University of Berlin) on the project "Identifying Financial Market Contagion in Real Time" in 2016-2017.
Apr.2015 My paper "The role of intra-day volatility pattern in jump detection" has been accepted by the 11th World Congress of the Econometric Society, to be held in August 2015 in Montreal, Canada.
Dec.2013 I attended the graduation ceremony on 18th December 2013 at Monash University and obtained my doctoral degree in Econometrics.
Apr.2013 I started to work as a post-doctoral research fellow at School of Economics and Finance, University of Tasmania, Australia.
Feb.2013 I submitted my PhD dissertation titled "Vector ARMA Model and Macroeconomic Modeling: Some New Methodology and Algorithms".
Dec.2012 I presented my paper "Forecasting with Error Correction VARMA Models" in the seminar series at the School of Economics and Finance, University of Tasmania.
Apr.2010 I won Econometric Game 2010 held in Amsterdam with other 4 teammates representing Monash University. (Monash news link)

Curriculum Vitae

Positions Held

Jan.2019---Now Senior Lecturer, Department of Economics, Deakin University
Aug.2016---Dec.2018 Lecturer, Department of Economics, Deakin University
Apr.2016---Jul.2016 Research Fellow, Department of Econometrics and Business Statistics, Monash University
Apr.2013---Mar.2016 Research Fellow, Tasmanian School of Business and Economics, University of Tasmania

Education

Dec.2013 PhD in Econometrics, Department of Econometrics and Business Statistics, Monash Universityy
Jun.2008 Bachelor of Economics, Bachelor of Science (Mathematics), Double-degree program, School of Economics, Renmin University of China

PhD Dissertation

Vector ARMA Model and Macroeconomic Modelling: Some New Methodology and Algorithms

Advisory Panel: Farshid Vahid (main), Don Poskitt, Heather Anderson, George Athanasopoulos

Research Interests

Financial econometrics High frequency financial econometrics; Jumps and cojumps; Financial contagion; Volatility modelling; Empirical finance.
Multivariate time series Vector ARMA model; Structural VAR; Cointegration analysis; Forecasting.
Macroeconometrics Business cycle analysis; Fiscal and monetary policy; Structural econometric methodology; Empirical macroeconometrics.

Publications

  • Forecasting the volatility of asset returns: The informational gain from option prices (with Vance Martin and Chrismin Tang), International Journal of Forecasting, forthcoming.
  • Modelling financial contagion using high frequency data (with Mardi Dungey and Vitali Alexeev), Economic Record, 2020.
  • Jump risk in the US financial sector (with Dinesh Gajurel, Mardi Dungey and Nagaratnam Jeyasreedharan), Economic Record, 2020.
  • High-dimensional predictive regression in the presence of cointegration (with Heather Anderson, Bonsoo Koo and Myung Hwan Seo), Journal of Econometrics, 2020.
  • Asymmetric jump beta estimation with implications for portfolio risk management (with Vitali Alexeev and Giovanni Urga), International Review of Economics and Finance, 2019.
  • News and expected returns in east Asian equity markets: The RV-GARCHM model (with Vance Martin and Chrismin Tang), Journal of Asian Economics, 2018.
  • High frequency characterization of Indian banking stocks (with Mohammad Sayeed and Mardi Dungey), Journal of Emerging Markets Finance, 2018.
  • Vector autoregressions and macroeconomic modelling: An error taxonomy (with Don Poskitt), Journal of Business and Economic Statistics, 2017.
  • On weak identification in structural VAR(MA) models (with Timothy Kam and Farshid Vahid), Economics Letters (lead article), 2017.
  • Time-varying continuous and jump betas: The role of firm characteristics and periods of stress (with Vitali Alexeev and Mardi Dungey), Journal of Empirical Finance (lead article), 2017.
  • Determination of long-run and short-run dynamics in EC-VARMA models via canonical correlations (with George Athanasopoulos, Don Poskitt and Farshid Vahid), Journal of Applied Econometrics, 2016.
  • Continuous and jump betas: Implications for portfolio diversification (with Vitali Alexeev and Mardi Dungey), Econometrics, 2016.

Working Papers

  • Cojump anchoring (with Lars Winkelmann).
  • Do market-wide circuit breakers calm markets or panic them? Evidence from COVID-19 pandemic (with Xiaoyang Li).
  • A Nonparametric Test of Dynamical Income Distributions with Application (with Vance Martin, Jialu Shi and Yang Song).
  • The Impact of Forward Guidance and Large-scale Asset Purchase Programs on Commodity Markets (with Pedro Gomis- Porqueras and Shuddhasattwa Rafiq).
  • Characterizing financial crises through the spectrum of high frequency data (with Mardi Dungey, Jet Holloway and Abdullah Yalaman).
  • The role of intra-day volatility pattern in jump detection: Empirical evidence on how financial markets respond to macroeconomic news announcements (with Jing Tian).

Invited Seminars

Sep.2020 Melbourne Online Seminar, University of Melbourne/Monash University
Jul.2019 Department of Economics, University of Hamburg
Apr.2019 Institute of Economics, Academia Sinica
Mar.2019 School of Economics, University of Adelaide
May.2017 School of Economics, University of Queensland
Nov.2016 School of Business and Economics, Free University of Berlin
Sep.2016 Tasmanian School of Business and Economics, University of Tasmania
Apr.2016 Department of Economics, University of Melbourne
Oct.2015 Department of Economics, Macquarie University
Sep.2015 Research School of Finance, Actuarial Studies and Applied Statistics, Australian National University
Jul.2015 Hanqing Advanced Institute of Economics and Finance, Renmin (People's) University of China
Jun.2015 School of Business and Economics, Free University of Berlin
May.2015 Department of Econometrics and Business Statistics, Monash University
Sep.2014 QUT Business School, Queensland University of Technology
May.2014 School of Accounting, Economics and Finance, Deakin University
Apr.2014 Reserve Bank of New Zealand
Dec.2012 School of Economics and Finance, University of Tasmania

Conference Presentations

Feb.2020 Australia New Zealand Econometrics Study Group Conference, Melbourne Australia
Dec.2019 International Conference on Computational and Financial Econometrics, London UK
Dec.2019 Workshop of the Australasian Macroeconomic Society, Hobart Australia
Nov.2019 Time Series and Forecasting Symposium, Sydney Australia
Jun.2019 International Symposium on Forecasting, Thessaloniki Greece
Jun.2019 International Symposium on Econometric Theory and Applications, Osaka Japan
Feb.2019 Deakin Business School Centre for Banking and Financial Stability Workshop, Melbourne Australia
Dec.2018 International Conference on Computational and Financial Econometrics, Pisa Italy
Dec.2018 (EC)^2 Conference on Big Data Econometrics with Applications, Rome Italy
Jun.2017 Society of Financial Econometrics Annual Conference, New York USA
Mar.2017 Midwest Finance Association Annual Meeting, Chicago USA
Dec.2016 International Conference on Computational and Financial Econometrics, Seville Spain
Jul.2016 Conference on Financial Econometrics & Empirical Asset Pricing, Lancaster UK
Jun.2016 Conference of the International Association of Applied Econometrics, Milan Italy
Nov.2015 SIRCA Young Researcher Workshop, Sydney Australia
Aug.2015 World Congress of the Econometric Society, Montreal Canada
Jun.2015 Society of Financial Econometrics Annual Conference, Aarhus Denmark
Jun.2015 International Workshop on Financial Markets and Nonlinear Dynamics, Paris France
Feb.2015 New Zealand Econometrics Study Group Meeting, Brisbane Australia
Jan.2015 Western Economic Association International Conference, Wellington New Zealand
Jul.2014 Econometric Society Australasian Meeting, Hobart Australia
Jun.2014 China Meeting of Econometric Society, Xiamen China
Dec.2013 Auckland Finance Meeting, Auckland New Zealand
Nov.2013 FIRN Annual Conference, Sydney Australia
Nov.2013 SIRCA Young Researcher Workshop, Sydney Australia
Oct.2013 Annual Meeting of the Midwest Econometrics Group, Bloomington Indiana USA
Feb.2013 Young Statistician Conference, Melbourne Australia
Jul.2012 Econometric Society Australasian Meeting, Melbourne Australia
Jun.2012 International Symposium on Forecasting, Boston USA
May.2012 International Symposium on Econometric Theory and Applications, Shanghai China
Jul.2011 Workshop on Macroeconomic Dynamics, Brisbane Australia
Jul.2011 Monash Macro Workshop, Melbourne Australia
Jul.2011 Australian Conference of Economists, Canberra Australia
Jul.2011 Econometric Society Australasian Meeting, Adelaide Australia

Other Research Experience:

Nov.2012---Dec.2012 Research Assistant, Associate Professor George Athanasopoulos Benefits of bicycle commuting and policy related factors of promoting bicycle, literature review and data search.
Nov.2009---Jan.2010 Research Assistant, Professor Farshid Vahid and Professor Heather Anderson Cointegration and Common Cycle Restrictions (Oxford Handbook on Economic Forecasting) Model Selection, Estimation and Forecasting in VAR Models with Short-run and Long-run Restrictions (Journal of Econometrics)
Jul.2009---Nov.2009 Case Study Project supervised by Professor Steve Dorwick Estimating Inter-country Inequality and Testing for Sensitivity to Different Methods of Computing Purchasing Power Parity

Honors and Awards

  • Department of Economics Research Award, Deakin University, 2019
  • Department of Economics Ambassador Award, Deakin University, 2019
  • Female-led Research Study Seed Funding, Deakin Business School, 2019
  • Faculty Research Grant, Deakin Business School, Deakin University, 2018
  • Start-up Research Grant, Department of Economics, Deakin University, 2017
  • Start-up Research Grant, Department of Economics, Deakin University, 2016
  • Australia-Germany Joint Research Co-operation Scheme, 2016--2017
  • Econometric Society World Congress 2015 Travel Grant, 2015
  • Career Development Scholarship, University of Tasmania, 2015
  • Conference Travel Grant, Tasmanian School of Business and Economics, University of Tasmania, 2015
  • Small Research Grant, Tasmanian School of Business and Economics, University of Tasmania, 2014
  • Career Development Scholarship, University of Tasmania, 2014
  • Conference Travel Grant, Tasmanian School of Business and Economics, University of Tasmania, 2014
  • Postgraduate Publication Award, Monash Institute of Graduate Research, Monash University, 2013
  • Winner of Econometric Game 2010 (representing Monash University), Amsterdam, 2010
  • Faculty of Business and Economics Postgraduate Research Scholarship, Monash University, 2010--2013
  • Monash Graduate Scholarship, Monash University, 2010--2013
  • Ph.D. International Scholarship, The Australian National University, 2009--2012
  • Ph.D. Supplementary Scholarship, The Australian National University, 2009--2012
  • 100% Tuition Fee Scholarship, School of Economics, The Australian National University, 2009--2012
  • 1st Class Scholarship of Academic Merit (top 5% students), Renmin University of China, 2007
  • 2nd Class Scholarship of Social Work and Volunteer Merit, Renmin University of China

Computer Skills

  • Matlab
  • GAUSS
  • Eviews
  • R
  • Julia
  • Stata
  • Maple

Internships

May.2008---Sep.2008 JPMorgan Chase Bank, Beijing China
Jul.2007---Aug.2007 Summer Internship, Guangdong Development Bank, Beijing China

Publications

Forecasting the volatility of asset returns: The informational gain from option prices (with Vance Martin and Chrismin Tang), International Journal of Forecasting, forthcoming.

Published version

Abstract: A new class of forecasting models is proposed that extends the Realized GARCH class of models through the inclusion of option prices to forecast the variance of asset returns. The VIX is used to approximate option prices resulting in a set of cross-equation restrictions on the model's parameters. The full model is characterized by a nonlinear system of three equations containing asset returns, the realized variance and the VIX, with estimation of the parameters based on maximum likelihood methods. The forecasting properties of the new class of forecasting models, as well as a number of special cases, are investigated and applied to forecasting the daily S&P500 index realized variance using intra-day and daily data from September 2001 to November 2017. The forecasting results provide strong support for including the realized variance and the VIX to improve variance forecasts, with linear conditional variance models performing well for short-term 1-day ahead forecasts, whereas log-linear conditional variance models tend to perform better for intermediate 5-day ahead forecasts.

Modelling financial contagion using high frequency data (with Mardi Dungey and Vitali Alexeev), Economic Record, 2020.

Published version

Abstract: This paper develops a methodology for detecting and measuring contagion using high frequency data which disentangles continuous and discontinuous price movements. We demonstrate its finite sample properties using Monte-Carlo simulation, focusing on the empirically plausible parameter space. Decisions to extend the role of financial regulation around the world to the supervision of insurers post-GFC has been met with literature which supports both the systemic importance of insurers and contrasting evidence that insurers are rather the 'victims' of shocks transmitted via banks. We contribute to this debate by considering the time-varying evidence for contagion at both the firm level and the sectorial level impacts. A number of insurance companies exhibits bank-like characteristics. Our evidence for contagion effects from banks to the real economy, with similar impact from the insurers, supports the view that financial regulation on banks does need to be extended to the insurance sector.

Jump risk in the US financial sector (with Dinesh Gajurel, Mardi Dungey and Nagaratnam Jeyasreedharan), Economic Record, 2020.

Published version

Abstract: In this paper, we establish empirical evidence for the relationship between the systematic jump betas of financial institutions and two types of systemic risk indices: a capital shortfall index and a interconnectedness index. Using high-frequency data for US financial sector stocks, we show that equity market jumps are related positively to capital shortfall and negatively to interconnectedness. Higher potential capital shortfall measures of systemic risk lead to a greater sensitivity to systematic jumps, while increased interconnectedness leads to greater resistance. Our findings, along with indicators such as size and leverage, provide a means to identify the possible trade-offs that regulators might face when assessing the systemic risks of financial institutions, particularly in the context of the cross-multiple influences within the sector.

High-dimensional predictive regression in the presence of cointegration (with Heather Anderson, Bonsoo Koo and Myung Hwan Seo), Journal of Econometrics, 2020.

Published version

Abstract: We propose a Least Absolute Shrinkage and Selection Operator (LASSO) estimator of a predictive regression in which stock returns are conditioned on a large set of lagged covariates, some of which are highly persistent and potentially cointegrated. We establish the asymptotic properties of the proposed LASSO estimator and validate our theoretical findings using simulation studies. The application of this proposed LASSO approach to forecasting stock returns suggests that a cointegrating relationship among the persistent predictors leads to a significant improvement in the prediction of stock returns over various competing forecasting methods with respect to mean squared error.

Asymmetric jump beta estimation with implications for portfolio risk management (with Vitali Alexeev and Giovanni Urga), International Review of Economics and Finance, 2019.

Published version

Abstract: We evaluate the impact of extreme market shifts on equity portfolios and study the difference in negative and positive reactions to market jumps with implications for portfolio risk management. Employing high-frequency data for the constituents of the S&P500 index over the period 2 January 2003 to 30 December 2017, we investigate to what extent the portfolio exposure to the downside and upside jumps can be mitigated. We contrast the risk exposure of individual stocks with those of the portfolios as the number of holdings increases. Varying the jump identification threshold, we show that the number of holdings required to stabilise portfolios’ sensitivities to negative jumps is higher than when positive jumps are considered and that the asymmetry is more prominent for more extreme events. Ignoring this asymmetry results in under-diversification of portfolios and increases exposure to sudden extreme negative market shifts.

News and expected returns in east Asian equity markets: The RV-GARCHM model (with Vance Martin and Chrismin Tang), Journal of Asian Economics, 2018.

Published version

Abstract: Using intraday data to construct realized variance estimates combined with daily data on equity returns from January 1996 to May 2017, equity markets in East Asia are found to be relatively more risky than other markets. The framework uses an intertemporal capital asset pricing model with conditional moments based on realized volatility and a GARCH-in-mean specification to study the impact of news. Significant non-linear dynamics are also identified, with a positive relationship between expected returns and news associated with small shocks, and a negative relationship for large shocks. A similar relationship is found for the Australian market, but not for the US and UK equity markets.

High frequency characterization of Indian banking stocks (with Mohammad Sayeed and Mardi Dungey), Journal of Emerging Markets Finance, 2018.

Published version

Abstract: Using high-frequency stock returns in the Indian banking sector, we find that the beta on jump movements substantially exceeds that on the continuous component, and that the majority of the information content for returns lies with the jump beta. We contribute to the debate on strategies to decrease systemic risk, showing that increased bank capital and reduced leverage reduce both jump and continuous beta with slightly stronger effects for capital on continuous beta and stronger effects for leverage on jump beta. However, changes in these firm characteristics need to be large to create an economically meaningful change in beta.

Vector autoregressions and macroeconomic modelling: An error taxonomy (with Don Poskitt), Journal of Business and Economic Statistics, 2017.

Published version

Abstract: In this article, we investigate the theoretical behavior of finite lag VAR(n) models fitted to time series that in truth come from an infinite-order VAR(∞) data-generating mechanism. We show that the overall error can be broken down into two basic components, an estimation error that stems from the difference between the parameter estimates and their population ensemble VAR(n) counterparts, and an approximation error that stems from the difference between the VAR(n) and the true VAR(∞). The two sources of error are shown to be present in other performance indicators previously employed in the literature to characterize, so-called, truncation effects. Our theoretical analysis indicates that the magnitude of the estimation error exceeds that of the approximation error, but experimental results based upon a prototypical real business cycle model and a practical example indicate that the approximation error approaches its asymptotic position far more slowly than does the estimation error, their relative orders of magnitude notwithstanding. The experimental results suggest that with sample sizes and lag lengths like those commonly employed in practice VAR(n) models are likely to exhibit serious errors of both types when attempting to replicate the dynamics of the true underlying process and that inferences based on VAR(n) models can be very untrustworthy.

On weak identification in structural VAR(MA) models (with Timothy Kam and Farshid Vahid), Economics Letters (lead article), 2017.

Published version

Abstract: We simulate synthetic data from known data generating processes (DGPs) that arise from economic theory, and compare the performance of fitted VAR and VARMA models in estimating the true impulse responses to structural shocks. We show that while the VARMA structures implied by these DGPs are theoretically identified and lead to precise estimates of impulse responses given enough data, their parameters are close to the non-identified ridge in the parameter space, and that makes precise estimation of the impulse responses in small samples typical of macroeconomic data improbable. As a result, VARMA models barely show any advantage over VARs in characterizing the known DGPs in small samples. This is a refinement of the conjecture that near non-stationarity, near non-invertibility or weak identification could be possible reasons for the failure of structural VARMA models in providing good estimates of theoretical impulse responses of particular DSGE models.

Time-varying continuous and jump betas: The role of firm characteristics and periods of stress (with Vitali Alexeev and Mardi Dungey), Journal of Empirical Finance (lead article), 2017.

Published version

Abstract: Using high frequency data we decompose the time-varying beta for stocks into beta for continuous systematic risk and beta for discontinuous systematic risk. Estimated discontinuous betas for S & P500 constituents over 2003-2011 generally exceed the corresponding continuous betas. Smaller stocks are more sensitive to discontinuities than their larger counterparts, and during periods of financial distress, high leverage stocks are more exposed to systematic risk. Higher credit ratings and lower volatility are each associated with smaller betas. Industry effects are also apparent. We use the estimates to show that discontinuous risk carries a significantly positive premium, but continuous risk does not.

Determination of long-run and short-run dynamics in EC-VARMA models via canonical correlations (with George Athanasopoulos, Don Poskitt and Farshid Vahid), Journal of Applied Econometrics, 2016.

Published version

Abstract: This article studies a simple, coherent approach for identifying and estimating error-correcting vector autoregressive moving average (EC-VARMA) models. Canonical correlation analysis is implemented for both determining the cointegrating rank, using a strongly consistent method, and identifying the short-run VARMA dynamics, using the scalar component methodology. Finite-sample performance is evaluated via Monte Carlo simulations and the approach is applied to modelling and forecasting US interest rates. The results reveal that EC-VARMA models generate significantly more accurate out-of-sample forecasts than vector error correction models (VECMs), especially for short horizons.

Continuous and jump betas: Implications for portfolio diversification (with Vitali Alexeev and Mardi Dungey), Econometrics, 2016.

Published version

Abstract: Using high-frequency data, we decompose the time-varying beta for stocks into beta for continuous systematic risk and beta for discontinuous systematic risk. Estimated discontinuous betas for S&P500 constituents between 2003 and 2011 generally exceed the corresponding continuous betas. We demonstrate how continuous and discontinuous betas decrease with portfolio diversification. Using an equiweighted broad market index, we assess the speed of convergence of continuous and discontinuous betas in portfolios of stocks as the number of holdings increase. We show that discontinuous risk dissipates faster with fewer stocks in a portfolio compared to its continuous counterpart.

Working Papers

Cojump anchoring (with Lars Winkelmann).

Working paper

Do market-wide circuit breakers calm markets or panic them? Evidence from COVID-19 pandemic (with Xiaoyang Li).

Working paper

A Nonparametric Test of Dynamical Income Distributions with Application (with Vance Martin, Jialu Shi and Yang Song).

The Impact of Forward Guidance and Large-scale Asset Purchase Programs on Commodity Markets (with Pedro Gomis- Porqueras and Shuddhasattwa Rafiq).

Working paper

Characterizing financial crises through the spectrum of high frequency data (with Mardi Dungey, Jet Holloway and Abdullah Yalaman).

The role of intra-day volatility pattern in jump detection: Empirical evidence on how financial markets respond to macroeconomic news announcements (with Jing Tian).

Teaching

2020

  • Analytical Methods in Economics and Finance, 2nd year undergrad, Department of Economics, Deakin University
  • Econometrics II, 1st year PhD, Department of Economics, Deakin University

2017---2019

  • Advanced Econometrics, 1st year PhD, Department of Economics, Deakin University
  • Applied Econometrics for Economics and Finance, 3rd year undergrad, Department of Economics, Deakin University

2015

  • FIRN masterclass PhD Course---High Frequency Empirical Finance: A Practical Introduction to Time Series Problems, invited by Financial Integrity Research Network (FIRN) in July 2015
  • Econometrics, 3rd year undergrad, Tasmanian School of Business and Economics, University of Tasmania
  • Banking and Financial Institutions (guest lecturer), Tasmanian School of Business and Economics, University of Tasmania

2014

  • Econometrics, 3rd year undergrad, Tasmanian School of Business and Economics, University of Tasmania
  • Honours Finance (guest lecturer), Tasmanian School of Business and Economics, University of Tasmania
  • Honours Econometrics (guest lecturer), Tasmanian School of Business and Economics, University of Tasmania

2010---2012

  • Introductory Econometrics (tutor), Department of Econometrics & Business Statistics, Monash University

2009

  • Econometric Modeling (tutor), School of Economics, The Australian National University