In this paper we present a method for calculating the entire hedge surface of a derivative who’s future underlying asset has been simulated by a market simulator for example with the Monte Carlo method. Our method is built from work on penalized filtering techniques and is applied on a grid of...

The effective management of uncertainty and complexity in premium pricing and reserve accumulation processes provide new challenges to the decision- and policy- makers. In this regard, the implementation of complex mathematical tools and advanced statistical techniques is highly acquired. Over...

In the Input-Output Analytic framework, production (X) is related to final demand (C) through the B [while B= INV(I-A), where A is the technical coefficients matrix and INV(.) means inverted (.)], such that X=BC. Generally, the elements of A and C are considered to be non-stochastic and...

We present a stochastic simulation forecasting model to stress-test banks' capital adequacy and to estimate probability of infringement of regulatory capital ratios and default probability. The stochastic methodology proposed is based on a simplified reduced model that provides a manageable...

American Monte Carlo is a solution to the puzzle of calculating the value of derivatives with the right to an early exercise, when using Monte Carlo simulation. One of the technique uses regression of some suitable basis functions, which is a bit arbitrary, and could if made wrong render in...

We present a stochastic simulation forecasting model for stress testing aimed at assessing banks' capital adequacy, financial fragility and probability of default. The paper provides a theoretical presentation of the methodology and the essential features of the forecasting model on which it is...

Many water allocation agreements in transboundary river basins are inherently unstable. Due to stochastic river flow, agreements may be broken in case of drought. The objective of this paper is to analyze whether water allocation agreements can be self-enforcing, or sustainable. We do so using...

In this note, we propose an estimator for continuous-choice dynamic structural models. Our approach expands the class of models that can be estimated using the GMM methods in Hansen and Singleton (1982) by leveraging a theoretical result on stochastic Euler equations from Acemoglu (2009). We...

Strategies for constructing a Markov decision chain approximating a continuous-time finite-horizon optimal control problem are investigated. Some simple, analytically soluble, examples are treated and low computational complexity is reported. Extensions to the method and implementation are...

Many developing nations are in transition from non-renewable to renewable energy in electricity generation. This research analyzes this type of changing investment environment for renewable energy projects such as wind farms and solar-thermal plants with the application of real options theory....