Please refer to JobSuchmaschine in your application
Duration: up to 6 months, starting immediately
The thesis will focus on the estimation of high-frequency covariance dynamics for financial assets, with the purpose of developing a methodology to assess intraday portfolio risk figures. Potential applications can be found in the context of intraday trading or intraday margining systems.
Given the nature of the problem, a covariance estimator relying on tick-by-tick time series should theoretically benefit from their data abundancy and lead to better statistical properties. However, tick data analysis poses specific challenges, most notably: time inhomogeneity, presence of market micro -structure noise and time-series asynchronicity. Furthermore, to be of any practical value the estimation procedure will have to satisfy tight computational time constraints. Recently, new methods to tackle these issues relying on different (kernel, Fourier, Bayesian ) techniques have been published. Aim of the thesis is to investigate these approaches and, based on them, analyse intraday covariance dynamics and develop an intraday portfolio risk methodology.
Further details are available upon request.
Implement a covariance estimation methods for inhomogeneous, asynchronous and noisy data
Based on this covariance estimation model determine a methodology for portfolio risk figures estimation over different intra-day horizons
Benchmark this approach against standard econometric approaches both on artificial and real data
We are looking for a highly motivated student willing to focus his/her Master thesis on quant modeling in the context of the financial industry. The following qualifications are prerequisites:
Good knowledge of time-series analysis, Bayesian statistics and signal-processing
Comfortable with Python, R or Matlab
Flexible and self-motivated personality
Registration in a master’s thesis program at a recognized Swiss university; subsequent Supervisor approval
Interested? Please register and upload your cover letter and CV/Recommendations in PDF format via www.swissquant.com.Master Thesis - Intraday (PDF, 169 kb)