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...

With the exception of naive methods for portfolio selection, such as the equal weighted approaches, all other methods of portfolio allocation are more or less sensitive to the quality of the inputs considered in constructing the models and risk measures utilised in the allocation framework. The...

In this paper we assume a multivariate risk model has been developed for a portfolio and its capital derived as a homogeneous risk measure. The Euler (or gradient) principle, then, states that the capital to be allocated to each component of the portfolio has to be calculated as an expectation...

Following the Loss Distributional Approach (LDA), this article develops two procedures for simulation of an annual loss distribution for modeling of Operational Risk. First, we provide an overview of the typical compound-process LDA used widely in Operational Risk modeling, before expanding upon...

The focus of this work involves a comparison of the performance of a covariance regression model (CovReg) and a vector heterogeneous autoregressive (VHAR) model for the development of a dynamic portfolio allocation framework in equity index strategies. The performance of each method is assessed...

This paper introduces DivFolio, a multi-period portfolio selection and analytic software application that incorporates automated and user-determined divestment practices accommodating Environmental Social Governance (ESG) and portfolio carbon footprint considerations. This freely available...

Mechanisms to develop divestment strategies are an essential component of carbon reduction strategies. The rate at which investors should divest has become a critical aspect of effective divestment, which has shifted from the periphery to a movement of over a thousand major investors, totaling...

A time-series basis decomposition and trend extraction technique known as Empirical Mode Decomposition (EMD), designed for multi-scale time-frequency decomposition in non-stationary time-series settings, will be combined with Regularised Covariance Regression (RCR) methods to produce a framework...

In this work we study numerous aspects that pertain to an exploration around the significance of green bonds in funding the transition to a low carbon economy. We begin by exploring why green bonds are an emerging and critical component of financial markets contribution to the funding of...