AUTOFIM · Automated financial modelling
FP6 — Marie Curie Actions (Human Resources and Mobility)
- Duration
- 2007-09-01 → 2009-08-31
- EU contribution
- €137,015
- Participants
- 1
- Scheme
- EIF
Lines connect the coordinator with its partners. CORDIS does not always give exact coordinates for projects before 2014. These points are placed at city or country level.
Results in brief
Final Activity Report Summary - AUTOFIM (Automated financial modelling)
Most financial models are technically demanding and therefore a challenge to estimate, use and maintain. In particular, automated modelling is infeasible for most types of models if many variables are considered from the outset, as in "General-to-Specific" (GETS) modelling. The objectives of the project 'Automated financial modelling' (AUTOFIM) were to implement and evaluate the usefulness of automated value-at-risk modelling and automated derivative price modelling within a GETS modelling framework. The most important scientific achievements of AUTOFIM are three. First, a very general and flexible model that enables automated financial GETS modelling has been developed and studied. Second, empirical evaluations strongly suggest that automated financial GETS modelling can be useful in derivative pricing and in value-at-risk analysis. Finally, a methodological study suggests that the notion of financial variability is indeed a feasible study object. Contrary to a widespread view among academics, it is feasible to evaluate volatility - i.e. a prediction of financial variability - in terms of their forecast precision of variability.
Data: CORDIS, © European Union
Project objective
Traditionally automated quantitative financial modelling faced great challenges with respect to computation, implementation and maintenance, since most financial models are highly non-linear and thus require rocket science skills, substantial effort and advanced technology. Recently, however, a methodology was proposed and developed in a series of papers which overcomes many of the computational challenges earlier associated with automated financial volatility modelling. Moreover, softwares (for example PcG ets) in which the methodology can be implemented in an automated manner is already available, so that only minor modifications and additions to the methodology are necessary before it can be used in automated financial modelling.The software PcGets implements an econometric methodology called general-to-specific (GETS) modelling, thus the name PcGets, and the modelling framework is sometimes referred to as LSE econometrics after the academic institution (London School of Economics and Political Science) in which it originated. More recently though the approach has become widely associated with David F. Hendry at the University of Oxford. In brief, the methodology consists of starting with a general model that adequately characterises the data, and then simplifying it while paying careful attention to the model properties.The methodology provides a systematic framework for statistical economic hypothesis testing, model development and model evaluation, and the methodology is popular among large- scale econometric model developers. However, it is unused for the purpose of financial econometric modelling. The aim of the project Automated Financial Modelling is to implement and evaluate the usefulness of automated valute-at-risk modelling and automated derivative price modelling within a general-to-specific modelling framework. The main evaluation criterion of the methodology will be its forecast accuracy compared with alternative approaches.
Original text from CORDIS.
Participants
- DEPARTMENT OF ECONOMICS, UNIVERSITY CARLOS III OF MADRID DEPARTAMENTO DE ECONOMIA, UNIVERSIDAD CARLOS III DE MADRID · GETAFE (MADRID)CoordinatorCity levelSpain
Links
Data: CORDIS, © European Union