Applicability of Random Forests Forecasting to International Currency Trade: An Investigation Through Language

Abstract

The goal of this research is to study the performance of foreign exchange trade in both India and China. India and China raised rapidly in recent times and there is abundant of speculation that these countries might reach to the level of few other developed nations as far as international trade is concerned. Whereas there isn’t any doubt that these countries emerging as economic powers in the Asia-Pacific region, a lot of effort is required at international platform with respect to trade and commerce. One of such areas of competition is international currency trade. The aim of this study is to understand trends of currency trade in order to predict how likely these countries are going to emerge as best in the region. The study used certain secondary datasets from very reliable and authenticated sources. As far as statistical techniques are concerned, random walk forecasting methods were employed to test the study hypothesis. The study gathered certain evidence that though there are similarities in present and past performance, it is not likely to be the same in the future. However, the study concludes that random forests forecasting as a methodology is highly useful in studying trends in the data.

Keywords: Asia-Pacific Region, Currency Trade, International Trade, Random Walk Forecasting, Time Series Analysis

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