3 Common Ways to Forecast Currency Exchange Rates

Using a currency exchange rate forecast can help brokers and businesses make informed decisions to help minimize risks and maximize returns. Many methods of forecasting currency exchange rates exist. Here, we’ll look at a few of the most popular methods: purchasing power parity, relative economic strength, and econometric models.

Purchasing Power Parity

The purchasing power parity (PPP) is perhaps the most popular method due to its indoctrination in most economic textbooks. The PPP forecasting approach is based on the theoretical law of one price, which states that identical goods in different countries should have identical prices.

According to purchasing power parity, a pencil in Canada should be the same price as a pencil in the United States after taking into account the exchange rate and excluding transaction and shipping costs. In other words, there should be no arbitrage opportunity for someone to buy inexpensive pencils in one country and sell them in another for a profit.

The PPP approach forecasts that the exchange rate will change to offset price changes due to inflation based on this underlying principle. To use the above example, suppose that the prices of pencils in the U.S. are expected to increase by 4% over the next year while prices in Canada are expected to rise by only 2%. The inflation differential between the two countries is:

$\begin{aligned} &4\% – 2\% = 2\% \\ \end{aligned}$​4%−2%=2%​

This means that prices of pencils in the U.S. are expected to rise faster relative to prices in Canada. In this situation, the purchasing power parity approach would forecast that the U.S. dollar would have to depreciate by approximately 2% to keep pencil prices between both countries relatively equal. So, if the current exchange rate was 90 cents U.S. per one Canadian dollar, then the PPP would forecast an exchange rate of:

$\begin{aligned} &( 1 + 0.02 ) \times ( \text{US \$}0.90 \text{ per CA \$}1 ) = \text{US \$}0.92 \text{ per CA \$}1 \\ \end{aligned}$​(1+0.02)×(US $0.90 per CA $1)=US $0.92 per CA $1​

Meaning it would now take 92 cents U.S. to buy one Canadian dollar.

One of the most well-known applications of the PPP method is illustrated by the Big Mac Index, compiled and published by The Economist. This lighthearted index attempts to measure whether a currency is undervalued or overvalued based on the price of Big Macs in various countries. Since Big Macs are nearly universal in all the countries they are sold, a comparison of their prices serves as the basis for the index.

Relative Economic Strength

As the name may suggest, the relative economic strength approach looks at the strength of economic growth in different countries in order to forecast the direction of exchange rates. The rationale behind this approach is based on the idea that a strong economic environment and potentially high growth are more likely to attract investments from foreign investors. And, in order to purchase investments in the desired country, an investor would have to purchase the country’s currency—creating increased demand that should cause the currency to appreciate.

This approach doesn’t just look at the relative economic strength between countries. It takes a more general view and looks at all investment flows. For instance, another factor that can draw investors to a certain country is interest rates. High interest rates will attract investors looking for the highest yield on their investments, causing demand for the currency to increase, which again would result in an appreciation of the currency.

Conversely, low interest rates can also sometimes induce investors to avoid investing in a particular country or even borrow that country’s currency at low interest rates to fund other investments. Many investors did this with the Japanese yen when the interest rates in Japan were at extreme lows. This strategy is commonly known as the carry trade.

The relative economic strength method doesn’t forecast what the exchange rate should be, unlike the PPP approach. Rather, this approach gives the investor a general sense of whether a currency is going to appreciate or depreciate and an overall feel for the strength of the movement. It is typically used in combination with other forecasting methods to produce a complete result.

Econometric Models of Forecasting Exchange Rates

Another common method used to forecast exchange rates involves gathering factors that might affect currency movements and creating a model that relates these variables to the exchange rate. The factors used in econometric models are typically based on economic theory, but any variable can be added if it is believed to significantly influence the exchange rate.

As an example, suppose that a forecaster for a Canadian company has been tasked with forecasting the USD/CAD exchange rate over the next year. They believe an econometric model would be a good method to use and has researched factors they think affect the exchange rate. From their research and analysis, they conclude the factors that are most influential are: the interest rate differential between the U.S. and Canada (INT), the difference in GDP growth rates (GDP), and income growth rate (IGR) differences between the two countries. The econometric model they come up with is shown as:


$\begin{aligned} &\text{USD/Cad(1 – Year)} = z + a( \text{INT} ) + b( \text{GDP} ) + c( \text{IGR} ) \\ &\textbf{where:} \\ &z = \text{Constant baseline exchange rate} \\ &a, b \text{ and } c = \text{Coefficients representing relative} \\ &\text{weight of each factor} \\ &\text{INT} = \text{Difference in interest rates between} \\ &\text{U.S. and Canada} \\ &\text{GDP} = \text{Difference in GDP growth rates} \\ &\text{IGR} = \text{Difference in income growth rates} \\ \end{aligned}$​USD/Cad(1 – Year)=z+a(INT)+b(GDP)+c(IGR)where:z=Constant baseline exchange ratea,b and c=Coefficients representing relativeweight of each factorINT=Difference in interest rates betweenU.S. and CanadaGDP=Difference in GDP growth ratesIGR=Difference in income growth rates​

After the model is created, the variables INT, GDP and IGR can be plugged in to generate a forecast. The coefficients a, b, and c will determine how much a certain factor affects the exchange rate and direction of the effect (whether it is positive or negative). This method is probably the most complex and time-consuming approach, but once the model is built, new data can be easily acquired and plugged in to generate quick forecasts.

Forecasting exchange rates is a very difficult task, and it is for this reason that many companies and investors simply hedge their currency risk. However, those who see value in forecasting exchange rates and want to understand the factors that affect their movements can use these approaches as a good place to begin their research.