Article ID: | iaor20013139 |
Country: | United Kingdom |
Volume: | 19 |
Issue: | 4 |
Start Page Number: | 299 |
End Page Number: | 311 |
Publication Date: | Jul 2000 |
Journal: | International Journal of Forecasting |
Authors: | Taylor James W. |
Keywords: | neural networks |
This paper presents a new approach to estimating the conditional probability distribution of multiperiod financial returns. Estimation of the tails of the distribution is particularly important for risk management tools, such as Value-at-Risk models. A popular approach is to assume a Gaussian distribution, and to use a theoretically derived variance expression which is a non-linear function of the holding period,