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Quant Finance

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last update : 30/11/2015

Predictive Analytics and Filtering for Finance (delivered over 4 evenings)

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Predictive Analytics & Filtering in Finance, London -  8, 9, 15 & 16 February; Time: 17:00 – 20:30

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This program has been approved by GARP and qualifies for 12 GARP CPD credit hours. If you are a Certified ERP or FRM, please record this activity in your credit tracker at http://www.garp.org/cpd

 

Objectives:Scope and Purpose

The application of regime-switching models and filtering techniques gain in importance in financial modelling. Financial variables, like e.g. asset price dynamics, interest rates or asset volatilities can be modelled within a regime-switching framework to allow for switching market conditions. These conditions are typically unobservable, therefore filtering techniques are applied for a predictive analysis of financial variables.The aim of this workshop is to introduce the regime-switching framework and filtering techniques like e.g., Kalman Filters and the EM-algorithm. In addition Particle Filters are shortly presented. The use of these methods in the calibration of dynamic state space models as well as in the prediction of unobservable variables is discussed. States of the market are filtered and utilized to estimate parameters and calibrate financial models to market data. The predictions of future volatility and asset price distributions are explained with examples. Switching ARCH/ GARCH models for volatility modelling are introduced.

Learning Outcomes:

After successful completion of the workshop, the participants will

  • be able to:
    • apply standard filtering techniques to financial data sets,
    • apply concepts from time series modelling with regime shifts
    • utilize regime-switching models for a predictive analysis of asset prices and volatilities.
  • have acquired a good knowledge of regime-switching models and their applications and benefits in changing market situations.

Target Audience:

The workshop is designed to provide insight for a wide range of individuals such as financial quantitative analysts, risk analysts, consultants, and academics.

Workshop Format:

The workshop is well balanced between Theory and Practical Sessions. Attendee numbers are limited to ensure that personalised interaction can take place. The workshop comprises of eight sessions which are spread over four evenings.

Practical sessions:

In the practical sessions, the statistical software R is briefly introduced. It is utilized to demonstrate the filtering techniques and models with regime shifts in some examples. Practical application of basic filter techniques are demonstrated.

Presenters:

Dr. Christina Erlwein-Sayer is a visiting researcher working on the topic of financial analytics in general and models and tools for portfolio construction and Asset and Liability Management in particular. Dr Erlwein-Sayer is sponsored under a joint project between OptiRisk Systems and its partner Fraunhofer ITWM in Kaiserslautern, Germany. She completed her PhD in Mathematics at Brunel University, London in 2008. Prior to the current assignment Dr Erlwein-Sayer had presented workshops on behalf of OptiRisk at the IIM Calcutta Financial Research and Trading Laboratory in Kolkata, and also in Mumbai. Dr Erlwein-Sayer was also the lead member of the training partnership between OptiRisk Systems and Fraunhofer ITWM and presented at many of the workshops; notable of these was the training delivered to the World Bank in Washington.

Prof.Enza Messina is a Professor in Operations Research at the Department of Informatics Systems and Communications, University of Milano-Bicocca, where she leads the research Laboratory MIND (Models in decision making and data            analysis). She holds a PhD in Computational Mathematics and Operations Research from the University of Milano. Her research activity is mainly focused on decision models under uncertainty and more recently on statistical relational models for data analysis and knowledge extraction. In particular, she developed relational classification and clustering models that finds applications in different domains such as systems biology, e-justice, text mining and social network analysis. She is a co-founder of Sharper Analytics a spin-off of the University of Milano Bicocca.

Registration Fees: £500 + VAT

Delegates are also welcome to participate online at a discounted rate. This workshop will be streamed live online to delegates all around the world. Discounted rates for group bookings can be also arranged on request.

 

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