Robust Estimation and Inference for Multivariate Financial Data
Predicting and forecasting are routine day-to-day activities that guide us in making the best possible choices. They play an integral role in financial analysis. A lot of work has been done on one dimensional geometric Brownian motion (GBM) in stock price prediction. In this line of work, we focus mainly on how to use the one dimensional geometric Brownian motion and the multidimensional geometric Brownian motion in predicting future stock prices. There are several stock prices in the financial market and the multidimensional geometric Brownian motion gives a more realistic prediction compared to the one dimensional GBM. The reason being that, there are inter-relationships between stock prices. We therefore use robust statistics to create statistical procedures which are not influenced by outliers and observations that are not indicative of real stock price data. We perform statistical analysis and simulations to support our work in both one and two dimensions.
Amoako Dadey, Afua Kwakyewaa, "Robust Estimation and Inference for Multivariate Financial Data" (2020). ETD Collection for University of Texas, El Paso. AAI28089663.