Agent-based computational economics (ACE) has been attracting attention in recent years. This method, however, is challenging because of the complexity of the model’s structure due to the coexistence of systems for decision-making and those involved in financial transactions. Further, ACE...

We present a new fast calibration technique where we propose to train neural networks to directly perform the orthogonal projection of simulated payoffs of the calibration instrument with randomized model parameters and we enrich the learning task by including path-wise sensitivities of the...

We present an alternative derivation of the transition density in the Cox-Ingersoll-Ross (CIR) model. Applying methods developed in elementary quantum mechanics we show that the transition density can be determined from the eigenvalue problem of a second order differential operator with...

In this paper, we examine an agent-based model and an equation-based model in the form of a mean field model. We show how the mean field model is a small, fast model that identifies the high level properties of a subject, in this case financial time series’ stylized facts. The agent based...

We introduce a new approach to model the market smile for inflation-linked derivatives by defining the Quadratic Gaussian Year-on-Year inflation model -- the QGY model. We directly define the model in terms of a year-on-year ratio of the inflation index on a discrete tenor structure, which,...

When the central bank sets monetary policy according to a conventional or modified Taylor rule (which is known as the Taylor Principle), does this deliver the best outcome for the mac-roeconomy as a whole? This question is addressed by extending the wavelet-based control (WBC) model of Crowley...

In this study, we consider multi-period portfolio optimization model that is formulated as a mixed-integer second-order cone programming problems (MISOCPs). The Markowitz (1952) mean/variance framework has been extended by including transaction costs, conditional value-at-risk (CVaR),...

This paper is concerned with reconstructing weighted directed networks from the total in- and out-weight of each node. This problem arises for example in the analysis of systemic risk of partially observed financial networks. Typically a wide range of networks is consistent with this partial...

Klein (2000) advocates the use of the Schur decomposition of a matrix pencil to solve linear rational expectations (RE) models. Meanwhile his algorithm has become a center piece in several computer codes that provide approximate solutions to (non-linear) dynamic stochastic general equilibrium...

This paper will give a brief overview of the work of introducing machine learning intelligence in the Kineta e-markets system, to facilitate auto-hedging, smart price engine algorithms and proprietary automatic positioning within the foreign exchange market. In this paper we will give a brief...