Performance evaluation of modified adaptive Kalman filters, least means square and recursive least square methods for market risk beta and VaR estimation
Adaptive Kalman Filters (AKFs) are well known for their navigational applications. This work bridges the gap in the evolution of AKFs to handle parameter inconsistency problems with adaptive noise covariances. The focus is to apply proposed techniques for beta and VaR estimation of assets. The empir...
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| Format: | Article |
| Language: | English |
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AIMS Press
2019-03-01
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| Series: | Quantitative Finance and Economics |
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| Online Access: | https://www.aimspress.com/article/10.3934/QFE.2019.1.124/fulltext.html |
| _version_ | 1818029579298668544 |
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| author | Atanu Das |
| author_facet | Atanu Das |
| author_sort | Atanu Das |
| collection | DOAJ |
| description | Adaptive Kalman Filters (AKFs) are well known for their navigational applications. This work bridges the gap in the evolution of AKFs to handle parameter inconsistency problems with adaptive noise covariances. The focus is to apply proposed techniques for beta and VaR estimation of assets. The empirical performance of the proposed filters are compared with the standard least square family and KF with respect to VaR backtesting, expected shortfall analysis and in-sample forecasting performance analysis using Indian market data. Results show that the Modified AKFs are performing at par with the bench mark even with these adaptive noise covariance assumptions. |
| first_indexed | 2024-12-10T05:21:56Z |
| format | Article |
| id | doaj.art-f3cf588d3fc44fdda4e41e1b1d7acda8 |
| institution | Directory Open Access Journal |
| issn | 2573-0134 |
| language | English |
| last_indexed | 2024-12-10T05:21:56Z |
| publishDate | 2019-03-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Quantitative Finance and Economics |
| spelling | doaj.art-f3cf588d3fc44fdda4e41e1b1d7acda82022-12-22T02:00:47ZengAIMS PressQuantitative Finance and Economics2573-01342019-03-013112414410.3934/QFE.2019.1.124Performance evaluation of modified adaptive Kalman filters, least means square and recursive least square methods for market risk beta and VaR estimationAtanu Das0Department of Computer Science and Engineering, Netaji Subhash Engineering College, Kolkata, IndiaAdaptive Kalman Filters (AKFs) are well known for their navigational applications. This work bridges the gap in the evolution of AKFs to handle parameter inconsistency problems with adaptive noise covariances. The focus is to apply proposed techniques for beta and VaR estimation of assets. The empirical performance of the proposed filters are compared with the standard least square family and KF with respect to VaR backtesting, expected shortfall analysis and in-sample forecasting performance analysis using Indian market data. Results show that the Modified AKFs are performing at par with the bench mark even with these adaptive noise covariance assumptions.https://www.aimspress.com/article/10.3934/QFE.2019.1.124/fulltext.htmladaptive estimation| noise covariance adaptation| recursive least square| least mean square| modified AKF| market risk| beta| value-at-Risk |
| spellingShingle | Atanu Das Performance evaluation of modified adaptive Kalman filters, least means square and recursive least square methods for market risk beta and VaR estimation Quantitative Finance and Economics adaptive estimation| noise covariance adaptation| recursive least square| least mean square| modified AKF| market risk| beta| value-at-Risk |
| title | Performance evaluation of modified adaptive Kalman filters, least means square and recursive least square methods for market risk beta and VaR estimation |
| title_full | Performance evaluation of modified adaptive Kalman filters, least means square and recursive least square methods for market risk beta and VaR estimation |
| title_fullStr | Performance evaluation of modified adaptive Kalman filters, least means square and recursive least square methods for market risk beta and VaR estimation |
| title_full_unstemmed | Performance evaluation of modified adaptive Kalman filters, least means square and recursive least square methods for market risk beta and VaR estimation |
| title_short | Performance evaluation of modified adaptive Kalman filters, least means square and recursive least square methods for market risk beta and VaR estimation |
| title_sort | performance evaluation of modified adaptive kalman filters least means square and recursive least square methods for market risk beta and var estimation |
| topic | adaptive estimation| noise covariance adaptation| recursive least square| least mean square| modified AKF| market risk| beta| value-at-Risk |
| url | https://www.aimspress.com/article/10.3934/QFE.2019.1.124/fulltext.html |
| work_keys_str_mv | AT atanudas performanceevaluationofmodifiedadaptivekalmanfiltersleastmeanssquareandrecursiveleastsquaremethodsformarketriskbetaandvarestimation |