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Econometrics 2018, 6(3), 34; https://doi.org/10.3390/econometrics6030034

Financial Big Data Solutions for State Space Panel Regression in Interest Rate Dynamics

1
Department of Statistical Science, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
2
Department of Actuarial Mathematics and Statistics, Heriot-Watt University, Colin Maclaurin Building, Heriot-Watt University, Edinburgh EH14 4AS, UK
3
Man Institute of Quantitative Finance, University of Oxford, Oxford OX1 3BD, UK
4
Systemic Risk Center, The London School of Economics and Political Science, Houghton Street, London WC2A 2AE, UK
*
Author to whom correspondence should be addressed.
Received: 12 February 2018 / Revised: 19 June 2018 / Accepted: 7 July 2018 / Published: 18 July 2018
(This article belongs to the Special Issue Big Data in Economics and Finance)

Abstract

A novel class of dimension reduction methods is combined with a stochastic multi-factor panel regression-based state-space model in order to model the dynamics of yield curves whilst incorporating regression factors. This is achieved via Probabilistic Principal Component Analysis (PPCA) in which new statistically-robust variants are derived also treating missing data. We embed the rank reduced feature extractions into a stochastic representation for state-space models for yield curve dynamics and compare the results to classical multi-factor dynamic Nelson–Siegel state-space models. This leads to important new representations of yield curve models that can be practically important for addressing questions of financial stress testing and monetary policy interventions, which can incorporate efficiently financial big data. We illustrate our results on various financial and macroeconomic datasets from the Euro Zone and international market. View Full-Text
Keywords: feature extraction; yield curve modelling; panel regression; heavy tail distribution; multivariate state-space models; robust dimensionality reduction; Expectations-Maximisation algorithm; macroeconomic and financial datasets feature extraction; yield curve modelling; panel regression; heavy tail distribution; multivariate state-space models; robust dimensionality reduction; Expectations-Maximisation algorithm; macroeconomic and financial datasets
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Toczydlowska, D.; Peters, G.W. Financial Big Data Solutions for State Space Panel Regression in Interest Rate Dynamics. Econometrics 2018, 6, 34.

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