The Influence of Inflation on Changes of Currency Pairs Quotes
27 January 2022The subject of this article is the assessment of the correlation between the indices of consumer prices in various countries and quotes of currency pairs.
Brief definition:
Inflation is the increase in the general price level for goods and services. Rising inflation means that with the passage of time, one can buy fewer goods and services than before using the same amount of money. In this case, it is conventional to say that with time the purchasing power of money has declined, i.e. money has depreciated which means a loss of its real value.
The Consumer Price Index, CPI, was created to measure the average price for goods and services of the consumer basket for a certain period of time.
Growth of the CPI causes appreciation of the national currency rate.
The following liaison mechanism is expected:
The generally accepted way of monetary policy to control inflation is through raising interest rates. And expectations of interest rate hikes attracts investments consolidating the currency rate itself.
We try to test this hypothesis with different methods on actual dataof ten greatest economies of the world for the last 10 years.
For the analysis, we will use CPI values of the USA, the United Kingdom, Germany, Canada, Japan, Brazil, South Korea, China, Australia, and France.
The period under consideration is 10 years (2009-2019).
These countries were selected for the analysis because the majority of transactions in Forex trading are carried out with currency pairs that incorporate the currencies of the listed countries. The dynamics of CPI changes for every country will be compared to the quotes’ changes of five currency pairs that contain the currency of the country.
To estimate changes of currency rates, we will use historical values of daily quotes for opening prices.
In total, the dynamics for 50 currency pairs will be analyzed.
The sample size is 91 455 values.
The name of inflation indicators and their sources:
Country |
Currency |
Data source |
Source website |
The USA |
The US Dollar (USD) |
The Bureau of Labor Statistics |
https://www.bls.gov/ |
China |
Chinese Yuan (CNY) |
National Bureau of Statistics of China |
http://www.stats.gov.cn/ |
Japan |
Japanese Yen (JPY) |
The Statistics Bureau |
http://www.stat.go.jp/english/ |
Germany |
Euro (EUR) |
The Federal Statistical Office |
https://www.destatis.de/ |
The United Kingdom |
Pound Sterling (GBP) |
Office for National Statistics |
https://www.gov.uk/ |
France |
Euro (EUR) |
The French National Institute of Statistics and Economic Studies |
https://www.insee.fr/en/accueil |
Brazil |
Brazilian Real (BRL) |
Brazilian Institute of Geography and Statistics |
https://www.ibge.gov.br/ |
Canada |
Canadian Dollar (CAD) |
Statistics Canada |
https://www.statcan.gc.ca/ |
South Korea |
South Korean Won (KRW) |
Statistics Korea |
http://kostat.go.kr/portal/korea/index.action |
Australia |
Australian Dollar (AUD) |
Australian Bureau of Statistics |
https://www.abs.gov.au/ |
Definition of volatility
Before we move to the assessment of the direct impact of publication of CPI statistics on currency rate changes, we will consider the influence of new publications of CPI on volatility of the Forex market.
We suggest comparing the values of daily volatility of currency pairs on the day of data publication with the values of average daily volatility for the preceding week and for three weeks. For the analysis, we will use 1313 news releases of CPI data for 10 years in 10 countries.
Daily volatility of national currencies, %
Country | On the day of publication | Average for the preceding week | Average for three preceding weeks |
The USA | 1.00 | 0.95 | 0.94 |
Australia | 1.38 | 1.13 | 1.13 |
Brazil | 1.69 | 1.53 | 1.53 |
The United Kingdom | 1.09 | 1.03 | 1.02 |
Germany | 1.01 | 0.99 | 0.99 |
Canada | 1.05 | 1.01 | 1.02 |
China | 0.83 | 0.80 | 0.80 |
France | 1.00 | 0.97 | 0.96 |
South Korea | 1.13 | 1.08 | 1.11 |
Japan | 1.17 | 1.18 | 1.21 |
Average value | 1.13 | 1.07 | 1.07 |
From the table values, we can state that on the day of data publication the volatility was on average 6% higher compared to the average volatility of the preceding week period.
Assessment of volatility changes
Volatility |
Value, % |
Interpretation |
The USA |
+5.59 |
Weak increase in volatility |
Australia |
+17.92 |
Large increase in volatility |
Brazil |
+9.65 |
Large increase in volatility |
The United Kingdom |
+5.62 |
Weak increase in volatility |
Germany |
+1.29 |
Lack of influence on volatility |
Canada |
+2.87 |
Lack of influence on volatility |
China |
+3.73 |
Lack of influence on volatility |
France |
+3.71 |
Lack of influence on volatility |
South Korea |
+2.84 |
Lack of influence on volatility |
Japan |
-2.05 |
Lack of influence on volatility |
We will now move straight to the next stage of testing the hypothesis that growth of the CPI results in strengthening in national currency rates of countries.
We suggest that we should carry out the calculation with two methods:
The first method involves assessing the correlation between changes in the CPI of the country and changes in the national currency rate.
The calculation is carried out on the following timeframes of observation:
- with a delay for the following seven days after the publication of the indicator;
- with a delay until one day before the next publication of the indicator.
Correlation between currency rates and CPI changes:
Country | 1 week | 1 month |
The USA | 0.08 | 0.01 |
Australia | 0.07 | -0.1 |
Brazil | -0.1 | -0.02 |
The United Kingdom | -0.05 | -0.12 |
Germany | 0.02 | 0.06 |
Canada | 0.07 | 0.1 |
China | 0.06 | -0.05 |
France | 0.01 | 0.05 |
South Korea | 0.05 | -0.04 |
Japan | 0.05 | 0.03 |
Average value | 0.03 | -0.01 |
As can be noticed from the obtained results, there is no connection between changes of quotes and the dynamics of the CPI (the detailed information on correlation of every currency pairs is shown in the appendix).
The second method of correlation determination between the CPI and currency rates changes involves calculating the average profitability of profit-making.
Calculations will be carried out with a test from the trade terminal using the historical data of the currency pair quotes.
Description of the testing algorithm:
If the published CPI indicator is again higher than the preceding one, we place an open-to-buy position of its relevant national currency with respect to other currencies. If the CPI indicator is lower than the preceding one, it is the opposite, we open a short position for the country’s currency. For example, if Germany’s CPI demonstrates an increase, we open buys for EURUSD, EURAUD, EURJPY, EURGBP, and etc.
Positions are opened with the opening price of the daily candlestick on the next day following data publication. Positions are closed similarly at the opening price of the daily candlestick upon the expiry of specified time periods for position hold.
In total, the result of 6510 positions (deals) will be analyzed.
In this method, the magnitude of the difference of retail CPI values is not considered, nor is the volatility of currency pairs caused by data publication. Instead, we assess only the number of positions closed with a profit.
Share of profitable transactions, %
Country | 1 week | 1 month |
The USA | 46.08 | 47.87 |
Japan | 52.16 | 50.84 |
Germany | 48.59 | 49.52 |
The United Kingdom | 46.04 | 47.88 |
France | 47.76 | 48.64 |
Brazil | 49.39 | 50.61 |
Canada | 47.92 | 47.89 |
South Korea | 48.1 | 47.93 |
Australia | 57.73 | 50.09 |
China | 46.44 | 52.87 |
Average value | 49.02 | 49.41 |
The obtained coefficients demonstrate the probability (in %) of closing the position with a profit, depending on its hold time. The total average value for all currency pairs indicates a low number but, nevertheless, a slight prevalence of non-profit transactions.
Correlation:
The total average value of the correlation coefficients indicates an absence of correlation. This value is 0.03 with a week-long position hold, and -0.01 with a three week-long position hold.
Probability of profit-making:
The average value of the share of profitable positions is slightly more than 49% which means an almost equal distribution of transaction results. No explicit regularity has been identified.
Volatility on the day of CPI publication:
The volatility value on the day of publication of the CPI exceeds its value for the preceding week and the preceding three weeks by 6% on average.
The influence of data publication of inflation on the direction of currency rates has not been identified.
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