Dependency modelling Data Challenge 12 July 2007.

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Presentation transcript:

Dependency modelling Data Challenge 12 July 2007

Welcome!  Short introduction to  Quantitative Finance Network  Lighthill Risk Network  Launch of the Data Challenge  Next Steps  Pub?  Counts as 1.5 hours CPD! “Harness collective intelligence”

Quantitative Finance Network  Quant & Mammon Study (1999)  Centre for the Study of Financial Innovation (CSFI)  Quantitative Finance Initiative (QFI)  Engineering & Physical Sciences Research Council (EPSRC)  Faculty and Institute of Actuaries  Four Rounds of Funding (2001 to 2004)  EPSRC’s Sustainability Objective  Switch from Directed to Responsive Mode  To build a Network “Pick the best tool for the job”

Quantitative Finance Network Objectives:  To build a sustainable network  linking researchers and practitioners  to support the UK’s Financial Services sector  To identify challenges and opportunities  to initiate and support research  to present funding opportunities  To foster collaboration  Branding for Profession’s knowledge transfer activities  CPD, research groups and workshops “Search out and use prior art”

Quantitative Finance Network “If you find a useful tool…”

Lighthill Risk Network “…post it and tell the world”  Major initiative with other core members  Lloyd’s, Benfield, RMS, Guy Carpenter, Catlin  Bridge between academia and industry  Offers “expert panels” on various risk areas of interest to insurers:  Catastrophe modelling  Climate Change 

Lighthill Risk Network  Not for profit, set up Jan 2006, launched at Lloyd’s in April 2007  Based at the Lighthill Institute of Mathematical Sciences (LIMS) and administered within UCL  Role as a facilitator not a sponsor of research  No equivalent organisation exists, nearest are:  QFN (Quantitative Finance Network) funded by EPSRC and run by Institute of Actuaries  RPI (Risk Prediction Initiative) which sponsors research from Bermuda “We need a new relationship with IT”

Lighthill Risk Network “Harness collective intelligence”

Dependency modelling  Timetable  12 July 2007 : Launch Pseudo Data  28 September 2007 : Solutions submitted to us  30 October : Climb the learning curve  8 November : Results and Keynote Speech “Pick the best tool for the job”

The data challenge  10 years aggregate claims experience  Psuedo classes of business  Property - Direct  Property - Treaty  Directors & Officers/Professional indemnity  Workers Compensation/Employers Liability  Aviation  Marine  Terrorism “Pick the best tool for the job”

The data challenge  The data will be provided as five tables  each a separate realisation  each model slightly more complex  labelled A, B, C, D and E.  Assume aggregate claims’ figures are  accurate and final  not subject to any estimation error. “Pick the best tool for the job”

The data challenge  E.g model A “Pick the best tool for the job”

The data challenge  what is 99.5% Aggregate VaR? (across all lines of business)  what is 99.5% Aggregate TVaR (E(X|X>VaR(X))  what is Mean for each line of business individually?  what is the Price for each line of business individually? “Pick the best tool for the job”

The data challenge  Methods  Purpose = illustrate different approaches  Any techniques may therefore be applied  As long as participants are prepared to describe these and present them at the autumn seminars. “Pick the best tool for the job”

The data challenge Submissions  Answers should be presented using the template to be supplied  Accompanied by a written description of the approach  submissions used to select who will be invited to present  identify and understand broadly the methods used  without being overly long or going into great technical depth!  1,000 words (ish)  Longer descriptions also welcome as attachments.  The completed answer templates and written submissions should be  sent to Nicky Wilkinson at  by 28 th September  include full identification and contact details  or upload yourself to the wiki and send a link to Nicky… “Pick the best tool for the job”

The data challenge Prizes (just for fun…)  Answers ranked on absolute difference from the organisers’ calculated estimates (OCE).  this will give 15 rank figures for each submission  the participant with the lowest sum of these ranks will be judged the winner.  Missing answers will be given the lowest rank  Equally good answers across participants will be given the same rank.  The prize for the best submission will be something.  The winner and two runners-up will be announced at the autumn event and their names will be published in The Actuary magazine. “Pick the best tool for the job”

 Pick the best tool for the job  Search out and use Prior Art  If you find a useful tool, post it and tell the World  Harness collective intelligence  We need a new relationship with IT The Toolkit Manifesto