Long-term behavior of non-ferrous metal price models with jumps

Jun Peng,Jianbai Huang

doi:10.1186/1687-1847-2014-210

Abstract

In this paper, we study the long-term behavior of a class of stochastic non-ferrous metal prices with jumps. Suppose that is a stochastic model for some metal price with Poisson jumps. For a suitable , we prove that converges almost surely as . Finally, the model is applied to forecast the behavior of a two-factor affine model. MSC:60H15, 86A05, 34D35.

Highlights

1 Introduction Non-ferrous metal resources commodity producers, consumers and investors face problems resulting from the great variability in metal prices over time
In order to capture the properties of empirical data, Brennan and Schwartz [ ] proposed a geometric Brownian motion (GBM) model for forecasting natural resources commodity prices Yt: dYt = θ Yt dt + σ Yt dWt, t ≥, y =, where dWt is the increment in a Gauss-Wiener process with drift θ and instantaneous standard deviation σ
It is applicable to mathematical modeling of some phenomena in financial markets

Summary

Introduction

Non-ferrous metal resources commodity producers, consumers and investors face problems resulting from the great variability in metal prices over time. It is very useful to study and to model the long-time behavior in a mathematical way. In order to capture the properties of empirical data, Brennan and Schwartz [ ] proposed a geometric Brownian motion (GBM) model for forecasting natural resources commodity prices Yt: dYt = θ Yt dt + σ Yt dWt, t ≥ , y = , where dWt is the increment in a Gauss-Wiener process with drift θ and instantaneous standard deviation σ .

Results

Conclusion