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					                          Career Opportunities for PhDs in
                          Investment Banking
                          Algorithmic Trading




Giuseppe Nuti: Deutsche Bank - Electronic Market-Making Desk
Introduction


Algorithmic Trading - Outline


 Overview of Algorithmic Trading in Investment Banking
     – Algorithmic Trading across asset classes

     – Proprietary Trading

     – Other applications

 The Perfect Candidate & The Application Process




Giuseppe Nuti · Apr-11 · page 2
Algorithmic Trading


Algorithmic Trading in Investment Banking
 Each area of Investment Banking has a different understandings of Algorithmic Trading:

    – Equities: primarily Order Management & Order Routing

    – Foreign Exchange & Commodities: High Frequency Market-Making, Speed Optimization & Gamma
        Hedging

    – Fixed Income: Market-Making & Gamma Hedging

    – Proprietary Trading (across asset classes): various applications & techniques.



 The most commonly known category is Proprietary Trading; this is also the principal focus
    of academic research.

 The remaining categories of Algorithmic Trading have received much less attention but can
    provide very rewarding careers!




Giuseppe Nuti · Apr-11 · page 3
Algorithmic Trading


Proprietary Algorithmic Trading
 Proprietary Trading: the Holy Grail of Algorithmic Trading
     – Anyone & any firm can try their hand at it with (generally) minimal entry costs

     – Successful systems span a variety of trading styles & techniques: form High Frequency pattern
         recognition to News Scanning for stock forecasting (on the Internet, Bloomberg, etc.)

     – Cheap entry to this kind of trading has created a fiercely competitive market for Model Trading. As a
         general rule, aim for differentiation from the rest of the market participants, e.g.: use a little know (or
         little understood) AI technique; use data that nobody else has; focus on a time horizon that most
         other model traders find too short or too long; etc.

     – Simple Algorithms should nevertheless be examined as they can
         be surprisingly successful if applied to a market whit little
         competition from other Algorithmic traders

     – Simple & profitable algorithms seldom have a long lifespan

     – Academic research is often applied without realistic bid/ask
         spreads, PL constrains, etc.




                                              Bloomberg® Markets Magazine, June 2007


Giuseppe Nuti · Apr-11 · page 4
Algorithmic Trading


Algorithmic Trading & the Credit Crunch

 The credit Crunch has taken some of the lustre out of Algo Trading:

        Monday, 26 November 2007…




        Monday, 26 November 2007…




 …although there are some optimists around!
        Sunday, 1 June 2008…




Giuseppe Nuti · Apr-11 · page 5
Algorithmic Trading


Other Applications Algorithmic Trading
 The remaining applications of Algorithmic Trading can be broadly grouped in three categories:

 Order Management & Order Routing:
    – this is probably the most mature discipline within Algorithmic Trading

    – banks have recently moved from providing execution services with proprietary order management
        algorithms to selling the execution algorithms directly!

 Electronic Market-Making & Risk Management:
    – this is a relatively newer field, with little academic research

    – in depth understanding of the specific market structure is crucial

 Gamma Trading:
    – this area overlaps considerably with Proprietary Trading

    – it has great potential for growth as options markets become more mature & electronic execution becomes
        widely available




Giuseppe Nuti · Apr-11 · page 6
Career Opportunities in Algorithmic Trading


The Perfect Candidate


 There is, in general, a limited number of opportunities to join a successful Algorithmic Trading
     team.

 These desks tend to be manned by individuals with excellent IT skills (programming &
     theoretical computation) and a deep understanding of the Financial Markets.

 Although the theoretical aspect is often the most stimulating, remember to stay focused on the
     results: PL! Research done on any area of Algorithmic Trading (except Prop. Trading) will be
     very well received by the Banks.

 In general, candidates form a Front Office Graduate Programme are not interested in the ‘IT
     side’ of Algorithmic Trading, whilst IT Graduates generally do not have the necessary
     understanding of Financial Markets.

     This is fertile ground for PhD candidates!




Giuseppe Nuti · Apr-11 · page 7
Career Opportunities in Algorithmic Trading

The Application Process for PhD students
    Deutsche Bank runs the following programs in Global Markets for PhD students:
     –   Summer Internship Program – for penultimate year students only

         – 10 weeks programme

         – 1 week of training; 2 x 4.5 weeks rotation (including product event, community service days, etc.)

         – Candidates are assessed during the rotations, a trading simulation and a final presentation

         – There are currently (2008) 30 associates interns

         – Application deadline: mid Jan., apply from Sept onwards

     –   Full Time Graduate Program

         – Initial training is held in the US from Mid July to end of Aug.

         – Back in the UK: one week of desks’ presentations and FSA exams

         – 4 x 4 week rotations

         – Application deadline: mid Nov., apply from Sept onwards

    PhD students are hired as Associates

    Deutsche Bank dose not hire PhD students for research positions only

    Please apply on line at www.db.com/careers with a CV and Thesis Abstract. Ensure you are clear about your
     expected completion date

    There will be 2 rounds of interviews with representatives from Global Markets

    Please ensure you apply early!


Giuseppe Nuti · Apr-11 · page 8

				
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