In this paper, we introduce a clustering method to approximate the solution to a general Backward Stochastic Differential Equation with Jumps (BSDEJ). We show the convergence of the sequence of approximate solutions to the true one. The method is implemented for an application in finance....

In this paper, we provide insights on the prediction of asset returns via novel machine learning methodologies. Machine learning clustering-enhanced classification and regression techniques to predict future asset return movements are proposed and compared. Numerical experiments show good...

In this paper, we document a novel machine learning based bottom-up approach for static and dynamic portfolio optimization on, potentially, a large number of assets. The methodology overcomes many major difficulties arising in current optimization schemes. For example, we no longer need to...

Since the formation of intermetallic compounds at the copper-side interface for the duration of the copper/aluminum brazing process leads to a reduction in the mechanical properties of the brazing joint, and the diffusion and reaction process between the molten filler metal and the base material...

This paper proposes a novel bond return (price or yield curve) prediction methodology, unifying the classical no arbitrage pricing framework, which is ubiquitous and serves as the fundamental theoretical building block in mathematical finance, and empirical asset (bond) pricing methodologies,...

Stock market index enhancement is a popular strategy among hedge funds. The algorithm tries to adjust the weights of individual stocks of a benchmark index to boost performance of the target portfolio with respect to the original benchmark. Therefore, the key to success of this strategy is the...