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There are several ways to predict exchange rates. But for discussion purposes, we will focus on four most common approaches for predicting currency changes.

Econometric Models

The method includes collating all presumptions that can influence the movement of a currency and formulating a model relative to these factors, which are usually based on economic theory. Also, any variable can be integrated if it is said to substantially impact the currency rates. Sure, using economic models is time-consuming and strenuous. But once the framework is formed, new information can be easily collected and inserted into the model to come up with quick estimations.

Purchasing Power Parity

In essence, the theory seeks to discover the necessary adjustment on the two currencies in order to make the exchange rate at par with their respective purchasing power. Basically, purchasing power parity states the similar products in differing nations should have similar prices. Currency changes occur to counter price changes caused by inflation. To equate prices of goods and services in various nations, a considerable amount of data must be gathered. But data gathering alone is a tedious task. In 1968, the United Nations and the University of Pennsylvania came up with the International Comparisons Program to generate the purchasing power of every country.

Relative Economic Strength

Projecting currency changes entails assimilating the sturdiness of economic growth in many countries. The supposition is foreign investors prefer venturing in a nation exhibiting strong economic environment and likely high growth. Relative economic strength approach evaluates all investment flows as well. Whilst it does not forecast exchange rate, it gives an idea of whether a specific currency is going to rise or fall and its overall strength.

Time Series Model

Technical in nature, time series model is trend prediction that is not based on any economic concept. Autoregressive moving average model is one of the most popular time series processes utilized. The system accounts past performance and price trends to anticipate future price movements and patterns. A software can be used to input a series of details to gauge the parameters and figure out the model.