Hedge Fund returns are often highly serially correlated mainly due to illiquidity exposures given that investments in such securities tend to be inactively traded and associated market prices are not always readily available. Following that, observed returns of such alternative investments tend...

In recent years both equity and bond markets have been afflicted by high volatility. In order to build up a portfolio on a quantitative basis, several models may be used, such as minimum variance portfolio or equally weighted portfolio. In 2008/09 another way to deal with diversification came...

We improve on our Vigilant Asset Allocation (VAA) by the introduction of a separate “canary” universe for signaling the need for crash protection, using the concept of breadth momentum. The amount of cash is now governed by the number of canary assets with bad (non-positive) momentum. The...

Understanding variance risk is of key importance in mathematical finance since it affects risk management, asset allocation and derivative pricing. Variance risk is priced in financial markets by the so-called variance risk premium (VRP), which refers to the premium demanded for holding assets...

Macroeconomic data is often noisy, contradictory and lagging. These limitations render the data difficult to integrate into a robust quantitative investment strategy that generates excess returns. This paper outlines a new approach to macro investing that removes these inherent limitations in...

Our aim is to develop a very offensive (‘aggressive’) tactical asset allocation strategy, by combining some of our previous models like Protected- (PAA), Vigilant- (VAA) and Defensive (DAA) Asset Allocation. We will call this new strategy the ‘Bold Asset Allocation’ (BAA). BAA combines a...

Pricing kernels implicit in option prices play a key role in assessing the risk aversion over equity returns. We deal with nonparametric estimation of the pricing kernel (Empirical Pricing Kernel) given by the ratio of the risk-neutral density estimator and the subjective density estimator. The...

Classical asset allocation methods have assumed that the distribution of asset returns is smooth, well behaved with stable statistical moments over time. The distribution is assumed to have constant moments with e.g., Gaussian distribution that can be conveniently parameterised by the first two...

The persistent nature of equity volatility is investigated by means of a multi-factor stochastic volatility model with time varying parameters. The parameters are estimated by means of a sequential matching procedure which adopts as auxiliary model a time-varying generalization of the HAR model...

Long term investments in bonds offer known returns, but with risks corresponding to defaults of the underwriters. The excess return for a risky bond is measured by the spread between the expected yield and the risk-free rate. Similarly, the risk can be expressed in the form of a default yield,...