Using big financial data for the price dynamics of U.S. equities, we investigate the impact that market microstructure noise has on modeling volatility of the returns. Based on wavelet transforms (DWT and MODWT) for decomposing the systematic pattern and noise, we propose a new wavelet-based...

Although the practicability of using wavelet neural networks (WNNs) in nonlinear function approximation has been addressed extensively, selecting the optimal number of hidden nodes and their appropriate initial locations remains a great challenge for WNNs' initialization. The cuckoo search...

Paired-switching refers to investing in one of a pair of negatively correlated equities/ETFs/Funds and periodic switching of the position on the basis of either the relative performance of the two equities/ETFs/Funds over a period immediately prior to the switching or some other criterion. It is...

We analyze a methodology for portfolio selection based on the Independent Component Analysis. In this paper parametric and non-parametric approaches are used for capturing the behavior of independent components that generate the distribution of asset returns. Although the setup is quite general,...

This paper is concerned with finding an optimal inventory policy for a finite horizon, two-stage inventory model. In this model, products may be manufactured in two stages. The first stage uses raw material from an external supplier and the second stage uses raw material from defective items...

Here we present a novel approach to how the Chief Investment Office (CIO) can select investment strategies to allocate to and to decide the percentage allocation to them. The method that we outline here is a continuation of our previous research on recommender systems science[13]. The aim of...