Economist

Barclays
New York - United States
S: Competitive

Barclays Capital Inc. seeks an Economist for its New York, NY location.

Duties:
Utilize structural default risk and recovery rate models to forecast default risk and default tracking error volatility. Utilize macroeconomics knowledge along with quantitative tools to build cross asset class liquidity risk models. Develop, implement, and monitor quantitative models for portfolio management applications for cash and derivative securities across various asset classes. Apply advanced econometric and statistical analysis techniques including cross-sectional regressions, high frequency time series analysis, bootstrap, GARCH, mixed data sampling, and robust estimation to evaluate various risk factors and develop multi-factor risk models across various time horizons. Employ time-series analysis and mixed data sampling to forecast risk factor exposures and estimate a multi-asset class covariance matrix combining high and low frequency data. Manipulate large datasets used for research and implementation phases of risk models using Compustat, IBES, Worldscope, Fame, and OptionMetrics. Support and adapt the trading desk's pricing models and analytics to meet client requirements. Use SAS, SQL, MATLAB, and Java to conduct quantitative analysis and calibrate financial models. Perform statistical analysis of multi-dimensional distributions and simulation engines to estimate full distributions and perform scenario analysis. Implement curve construction tools based on non-linear optimization to generate term structure models. Prepare and publish internal and external publications on research and models, including portfolio modeling. Utilize macroeconomics and financial markets knowledge to communicate and market research related to complex financial models to sophisticated financial clients including asset managers through presentations, seminars, and conferences. Supervise junior Quantitative Researcher.

Requirements:
Requires PhD or foreign equivalent in Economics, Finance, or closely related field. Doctoral research or thesis must include: Experience with default and liquidity risk modeling; Using optimization and curve construction techniques to support term structure models; Using advanced econometrics and statistical techniques including high-frequency time series, cross sectional, non-parametric estimation, and bootstrap methods; Utilizing SAS, SQL, MATLAB and Java; Manipulating large databases including Compustat, TAQ and OptionMetrics to conduct quantitative analysis and calibrate financial models; and Knowledge of various asset classes including Equities, Fixed Income, and Credit. FINRA Series 7 & 63 certifications required within 6 months of hire.

Job summary