Project CEMAPRE internal
| Title | MTD-Probit Model |
| Participants | João Nicolau (Principal Investigator), Flávio Ivo Riedlinger |
| Summary | One of the most complex tasks in finance is to forecast stock market. The main challenge is how to choose a methodology that is theoretically consistent and feasible when applied in the real world in the presence of market inefficiencies. Usually, the best choice should be suggested by the underlined theoretical background; however, the model is often selected by its capacity to reproduce the key data series characteristics. The main goal of this project is to study financial market behavior using the multivariate Markov chain (MMC, hereafter) modelling framework. To the best of our knowledge, this is the first time that the MMC methodology is applied in finance to forecast stock markets. Indeed, the Markov chain research in this area, is based on the standard discrete-time univariate state-space case, adopting the restrictive hypothesis that a security price behavior depends only on its own past price information. In this context, we proposed to use a new MMC forecast methodology: the MTD-Probit model. This model has very attractive features since it is not only completely free of constraints, but also it is more precise in estimating the transition probabilities than the standard MMC models. We believe that our project must leverage new lines of research in a variety of fields. |