Forecasting covariance for optimal carry trade portfolio allocations

Matthew Ames, Guillaume Bagnarosa, Gareth W. Peters, Pavel Shevchenko, Tomoko Matsui

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Abstract

Modelling and forecasting of asset volatility and covariance is of prime importance in the construction of portfolios. In this paper, we present a generalised multi-factor model that incorporates heteroskedasticity and dependence in the idiosyncratic error terms. We apply this model to forecasting the time-varying covariances in a basket of high interest rate and a basket of low interest rate carry trade currencies and then utilise these forecasts for portfolio optimisation. We compare traditional Markowitz portfolio optimisation to the more recently popular risk-based portfolio optimisation. Our model is shown to provide superior risk-adjusted returns for a currency carry trade strategy over the period 1999 - 2014.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages5910-5914
Number of pages5
ISBN (Electronic)9781509041176
DOIs
Publication statusPublished - 16 Jun 2017
Event2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States
Duration: 5 Mar 20179 Mar 2017

Conference

Conference2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
CountryUnited States
CityNew Orleans
Period5/03/179/03/17

Keywords

  • covariance Forecasting
  • covariance Regression
  • currency carry trade
  • equal risk contribution
  • markowitz portfolio

Cite this

Ames, M., Bagnarosa, G., Peters, G. W., Shevchenko, P., & Matsui, T. (2017). Forecasting covariance for optimal carry trade portfolio allocations. In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings (pp. 5910-5914). [7953290] Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICASSP.2017.7953290