• Marcel Ndengo Rugengamanzi (with a talk),

12th International Conference on Stochastic Programming, August 16-20, Dalhousie University, Canada

Title: Optimal Investment in the Fixed-Income Market using the Heath-Jarrow-Morton Framework
Abstract: A good estimation of expected returns is imperative when optimal investments are determined with Stochastic Programming. In this paper, we develop an interest rate model which is consistent with the observations from the market with respect to how interest rates change. This is done by studying expected changes and randomness in forwards rates. Considering that market interest rate data contains noise and therefore is of poor quality, a previously developed method to determine smooth forward rates is used. Having the forward rates at hand, these are modelled using the Heath-Jarrow-Morton framework. We use Stochastic Programming to determine optimal investments for xed-income instruments. We present preliminary results using historical data where the Stochastic Programming model has been back-tested.

  • Japhet Niyobuhungiro, Joseph Nzabanita (without a talk),

Workshop on Inverse Problems, Data and Mathematical Statistics and Ecology, May 20-21, Linköping, Sweden

  • Lydie Mpinganzima (with a talk),

Inverse problems and applications, May 3, Norrköping, Sweden

Title: A data assimilation approach to coefficient identification
Abstract: The thermal conductivity properties of a material can be determined experimentally by using temperature measurements taken at specified lo- cations inside the material. We examine a situation where the properties of a (previously known) material changed locally. Mathematically we aim to find the coeffient k(x) in the stationary heat equation (kTx)x = 0; under the assumption that the function k(x) can be parametrized using only a few degrees of freedom. The coeffient identiffation problem is solved using a least squares approach; where the (non-linear) control functional is weighted according to the distribution of the measurement locations. Though we only dis- cuss the 1D case the ideas extend naturally to 2D or 3D. Experiments demonstrate that the proposed method works well.


  • Marcel Ndengo Rugengamanzi (without a talk),

3rd Nordic Optimization Symposium, March 13-14, Stockholm, Sweden