This paper proposes a new approach to numerically solving a wide class of heterogeneous agent models in continuous time using adaptive sparse grids. I combine the sparse finite difference method with the sparse finite volume method to solve the Hamilton-Jacobian-Bellman equation and Kolmogorov...

We propose a portfolio construction method that accounts for the regime-dependent behavior of stocks, thereby impacting their expected returns. Using a hidden Markov model (HMM) and a regime-weighted least-squares approach, we estimate forward-looking regime-conditional factors. These factors...

This study develops a hybrid model to integrate climate risks into Côte d'Ivoire’s economic policy, drawing on the work of economists like Keynes, Ostrom, Stiglitz, Sen, and Nordhaus. The model combines decentralized governance, climate risk externalities, and capacity building to address the...

This paper demonstrates that if we intend to optimally rank order n objects (candidates) each of which has m attributes or rank scores awarded by m evaluators, then the ordinal ranking of objects by the conventional principal component based factor scores turns out to be suboptimal. Three...

Rank-ordering of individuals or objects on multiple criteria has many important practical applications. A reasonably representative composite rank ordering of multi-attribute objects/individuals or multi-dimensional points is often obtained by the Principal Component Analysis, although much...

In this paper we have proposed a method to conduct the ordinal canonical correlation analysis (OCCA) that yields ordinal canonical variates and the coefficient of correlation between them, which is analogous to (and a generalization of) the rank correlation coefficient of Spearman. The ordinal...

The classical canonical correlation analysis is extremely greedy to maximize the squared correlation between two sets of variables. As a result, if one of the variables in the dataset-1 is very highly correlated with another variable in the dataset-2, the canonical correlation will be very high...

Portfolio optimisation for a Fund of Hedge Funds (“FoHF”) has to address the asymmetric, non-Gaussian nature of the underlying returns distributions. Furthermore, the objective functions and constraints are not necessarily convex or even smooth. Therefore traditional portfolio optimisation...

In this paper we test a particular variant of the (Repulsive) Particle Swarm method on some rather difficult global optimization problems. A number of these problems are collected from the extant literature and a few of them are newly introduced. First, we introduce the Particle Swarm method of...