Early Stage Researcher (ESR) PhD Studentship in Marie Sklodowska-Curie ITN BigDataFinance
Position available (36 months) at AllianceBernstein
Job Description
ESR11
Research Project: Smart Beta Investing – A Data-Driven Strategy to Exploit Systematic Risk Factors in the Financial Markets
Objectives: Systematic risk factors, such as size, value, quality and momentum, exist within the capital markets. An active approach to smart beta investing adds value by varying the exposure to these risk factors to exploit temporary risk and return opportunities. This project is expected to encompass the identification of new data to create new risk factor indices, where each new index has exposure to the newly identified risk factor. Research using big-data techniques would then follow to understand risk and return characteristics of these new indices, including the relationship between existing and other new factors. Of particular interest is the integration of micro-economic data as early indicators for macro-economic-driven strategies. Finally, the potential application of any findings to active management should be evaluated taking into account real life considerations such as investment constraints and transaction costs.
Expected Results: “Pure” smart-beta indices, portfolio construction, and risk management tools will be built from big-data analytics of market data, macro-economic data, and select micro-economic data for carry, value, and momentum risk factors. These “pure” smartbeta indices do not suffer style contamination or style drift. Overall, we expect to develop risk management tools that monitor spikes in volatility and contagion across risk factors so as to minimise portfolio risk.
How to Apply?
Applications must be submitted to Paula Dawson by the 5th April 2016 by e-mail at paula.dawson(at)abglobal.com
The application should include the following annexes (if not clearly stated in the application form):
– Letter of motivation
– CV (including names and contact details of at least two references, one of which is preferably the MSc or current PhD thesis supervisor)
– Copy of MSc degree certificate
– List of publications
– Abstract on Research Proposal
Research Fields
Signal processing, machine learning, pattern recognition, statistics, quantitative financial analysis.
Career Stage
Early stage researcher or 0-4 yrs (Post graduate)
First Stage Researcher (R1)
Requirements
| · We are looking for talented, creative and highly motivated researchers. A suitable background for this open position includes Signal Processing, Artificial Intelligence, Machine Learning, Econometrics, Finance, Quantitative Finance, Data Engineering, Knowledge Engineering, Statistics, Physics and other related areas. Fluent written and spoken English and solid programming (C/C++/Python/R/Matlab) and sufficient data engineering skills (e.g. SQL, Hadoop or Spark) are required. Excellent skills in statistics, applied mathematics and data science are essential. Skills in financial analysis are acknowledged. If separately asked from a candidate, a suitable English language proficiency test may be required.
· Candidates applying for the doctoral student position must hold Master’s degree in a relevant field and the recruited candidate is expected to enroll as a PhD student at the University of Manchester.
· Applicants shall, at the time of recruitment by the host organization, be in the first four years (full-time equivalent research experience) of their research careers and not yet have been awarded a doctoral degree. Full-Time Equivalent Research Experience is measured from the date when a researcher obtained the degree that would formally entitle him/her to embark on a doctorate.
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Benefits
The salary will be set in accordance with MSCA ESR rates.
Artikkeli ESR POSITION AVAILABLE AT ALLIANCEBERNSTEIN julkaistiin ensimmäisen kerran BigDataFinance.