Invesco Quantitative Strategies PhD Studentship: Advancing Factor Investing in the Face of Big Data

Lancaster University - Lancaster University Management School, Department of Accounting and Finance

This is a 1+3 years studentship between the Department of Accounting and Finance at Lancaster University Management School (LUMS) and our industry partner Invesco, funded by Invesco and LUMS. The PhD Studentship includes payment of full tuition fees and an annual maintenance grant sponsored by Invesco of £20,000 (tax-free) in years 1, 2, 3 and 4. The start date is 1st October 2018 and the supervisors are:

  1. Prof Ingmar Nolte (Professor of Finance and Econometrics, Director of the Centre for Financial Econometrics, Asset Markets and Macroeconomic Policy, LUMS)
  2. Dr Sandra Nolte (Lecturer in Finance, Director of the MSc in Quantitative Finance, the MSc in Finance and the MSc in Accounting and Financial Management, LUMS)
  3. Dr Alberto Martin-Utrera (Lecturer in Finance, LUMS)
  4. Dr Harald Lohre (Senior Research Analyst, Invesco Quantitative Strategies)

Description of the project:

In the prevailing low interest rate environment many investors embrace the possibility to systematically structure their investments along transparent and unique risk and return drivers, akin to a systematic factor investing approach as pursued by quantitative investment managers. In parallel to the rise of factor investing the notion of big data, especially the advent and availability of high-frequency news analytics, will fundamentally change the way with which information is processed in capital markets. In turn, the nature and relevance of any given factor might be considerably altered and it is crucial to further the understanding and modelling of the underlying economic dynamics. At the heart of this research project the PhD candidate will thus investigate the importance and impact of big data analytics for major risk and return factors across various asset classes, such as equities, fixed income, commodities, and currencies. In a related vein, the PhD candidate will draw from big data and machine learning techniques to aid optimal allocation across factors to enable efficient harvesting of the associated premia. The PhD Candidate will enjoy the unique opportunity to pursue a first-class formal finance education while keeping close ties to the investment management industry. In particular, the PhD student will get comprehensive insight into the Invesco Quantitative Strategies Team with more than 50 investment professionals managing over USD 36bn within a broad range of investment strategies and asset classes.

Application details:

The successful candidate will automatically be enrolled into the department’s 4 year PhD programme in Accounting and Finance. The admission criteria are:

  • Applicants are normally expected to hold a relevant Master’s degree in finance (with a substantial quantitative component), Master (MSci or MSc) in Mathematics, Statistics or in a related quantitative/econometric cognate subject area.
  • We will usually require a performance at distinction level at Master’s degree, typically averaging above 70% overall, which may also be required in a suitable dissertation element.
  • Our English language requirements (where required) are for IELTS at 7.0.
  • Applicants are advised that a GMAT score may be required. 

How to apply:

Please send your CV (including marks’ transcripts) and a motivation letter directly to Dr Sandra Nolte (S.Nolte@lancaster.ac.uk) and Dr Harald Lohre (harald.lohre@invesco.com); and apply formally to the department’s PhD programme. More details can be found under www.lancaster.ac.uk/lums/our-departments/accounting-and-finance/phd/

Please apply before 15th April 2018. 

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Type / Role:

PhD

Location(s):

Northern England