@inproceedings{0140354d357745969d980cb48b49953c,
title = "Forecasting covariance for optimal carry trade portfolio allocations",
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.",
keywords = "Covariance Forecasting, Covariance Regression, Currency Carry Trade, Equal Risk Contribution, Markowitz Portfolio",
author = "Matthew Ames and Guillaume Bagnarosa and Peters, \{Gareth W.\} and Pavel Shevchenko and Tomoko Matsui",
year = "2017",
month = jun,
day = "19",
doi = "10.1109/ICASSP.2017.7953290",
language = "English",
series = "IEEE International Conference on Acoustics, Speech and Signal Processing",
publisher = "IEEE",
pages = "5910--5914",
booktitle = "2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",
address = "United States",
note = "42nd IEEE International Conference on Acoustics, Speech, and Signal Processing 2017, ICASSP 2017 ; Conference date: 05-03-2017 Through 09-03-2017",
}