Fundamental analysis Macroeconomic indicators

The Relation between Countries’ Trade Balance and Currency Rates

Elena Berseneva 25 January 2022 253 3

The subject of the research is the influence of foreign trade on currency rates. Let us assess the influence of the dynamics of export and import volumes on national currencies.


We will start the article with the definition of the trade balance:


The Balance of Trade (BoT), also known as the trade balance, is an annual (quarterly or monthly) indicator of the country’s foreign transactions. If the trade balance has a surplus, this means that in monetary terms the volume of exported goods was greater than imported goods from other countries.

If the trade balance shows a trade deficit, the volume of imported goods prevails over export. A trade surplus indicates a stronger demand of goods of the country in the international market, and also that the country does not consume everything that produces.

Hypothesis
To conclusion

Growth of the trade balance causes strengthening of the national currency’s exchange rate.

To conclusion

The following liaison mechanism is expected:

Growth in exports of the country indicates that importing countries have to obtain the national currency to carry out transactions. Growing demand for the national currency raises its exchange rate.

Moreover, a trade surplus leads to a rise in income and expenses of the government budget which contributes to economic development and strengthens the national currency’s exchange rate.


We will test this hypothesis with different methods relying on actual data of ten greatest economies of the world for the last 10 years.

Data used

For the analysis, we will use values of the trade balance 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 listed countries.


We will compare the dynamics of changes of the trade balance for every country and quotes changes of 5 currency pairs that incorporate the currency of the country.

To estimate the 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 size of the sample is 91 455 values.


The name of the indicator and data source of the BoT reports:


Country
Currency
Data Source
Source website
The USA
The US Dollar (USD)
The Bureau of Economic Analysis
https://www.bea.gov/
China
Chinese Yuan (CNY)
National Bureau of Statistics of China
http://www.stats.gov.cn/
Japan
Japanese Yen (JPY)
Ministry of Finance Japan
https://www.mof.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)
Ministry of Finance
http://lekiosque.finances.gouv.fr/
Brazil
Brazilian Real (BRL)
Ministry of Industry, Foreign Trade and Services
http://www.mdic.gov.br/index.php/english
Canada
Canadian Dollar (CAD)
Statistics Canada
https://www.statcan.gc.ca/
South Korea
South Korean won (KRW)
Statistics Korea
http://kostat.go.kr/
Australia
Australian Dollar (AUD)
Australian Bureau of Statistics
https://www.abs.gov.au/



Definition of volatility


Before we move on to the assessment of the direct impact of publication of the BoT statistics on the direction of currency rate changes, we will consider the influence of new publications of the BoT on volatility of the Forex market.


For this reason, 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 concerning the BoT data releases for 10 years in 10 countries.



Daily volatility, %


Country
On the day of publication
Average for the preceding week
Average for three preceding weeks
The USA
0.98
0.93
0.94
Australia
1.22
1.13
1.13
Brazil
1.64
1.51
1.51
The United Kingdom
1.16
1.01
1.01
Germany
1.01
1.01
0.99
Canada
1.06
1.01
1.01
China
0.84
0.80
0.80
France
1.04
1.00
0.99
South Korea
1.01
0.97
0.97
Japan
1.19
1.14
1.16
Average value
1.12
1.05
1.05


From the table values, we can conclude that on the day of data publication the volatility is 6.25% higher compared to the average volatility of the preceding week and three weeks periods.



Volatility assessment


Volatility
Value, %
Interpretation
The USA
+4.49
Lack of increase on volatility
Australia
+7.58
Weak increase on volatility
Brazil
+8.80
Weak increase on volatility
The United Kingdom
+15.06
Strong increase on volatility
Germany
+1.33
Lack of influence on volatility
Canada
+4.86
Lack of influence on volatility
China
+4.64
Lack of influence on volatility
France
+4.95
Lack of influence on volatility
South Korea
+4.35
Lack of influence on volatility
Japan
+3.16
Lack of influence on volatility



We will now move straight into the next stage of testing the hypothesis that growth of the BoT results in strengthening of the national currency rate of the country.


We suggest carrying out the calculation with two methods:


The first method involves assessing the correlation between the BoT changes of the country and changes of the national currency’s exchange rate.


The calculation is carried out on the following timeframes of observation:

  • with a one-week delay following the publication of the indicator;
  • with a delay until the day of the next publication of the indicator;



Correlation between changes of currency rates and the BoT value changes:


Country
1 week
1 month
The USA
0.04
0.01
Australia
0.1
0.07
Brazil
0.08
0.05
The United Kingdom
0.08
-0.06
Germany
-0.07
-0.03
Canada
0.11
0.1
China
0.12
0.15
France
-0.01
0.02
South Korea
0.01
0.09
Japan
-0.02
0.08
Average value
0.04
0.05



As can be noticed from the obtained results, there is a weak correlation between the following currency pairs: AUDJPY, AUDKRW, CADKRW, CADCNY, EURCNY, GBPCNY, GBPCAD, EURJPY, GBPAUD, EURBRL, EURUSD, USDJPY.


The rest of the pairs have insignificant coefficients of the correlation (detailed information on correlations for every currency pairs is shown in the application).


The second method of correlation determination between the BoT changes and currency rates changes involves calculating the average probability of profit-making.


Calculations will be carried out with a test from the trade terminal using historical data of the currency quotes quotes.



Description of the testing algorithm:

If a published indicator of the BoT 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 indicator of the BoT is lower than the preceding one, it is the opposite, we open a short position for the country’s currency. For example, if the United Kingdom BoT demonstrates an increase, we open buys for GBPJPY, GBPAUD, GBPKRW, GBPKRW, and etc.


Positions are opened with the opening price of a daily candlestick on the next day following data publication. Positions are closed similarly at the opening price of a daily candlestick upon the expiry of specified time periods for position hold.


In total, the result of 6510 positions will be analyzed.


In this method, the magnitude of difference of the BoT’s 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 positions, %


Country
1 week
1 month
The USA
56.96
51.46
Japan
52.13
53.82
Germany
50.36
49.86
The United Kingdom
52.6
52.46
France
52.12
51.18
Brazil
52.23
52.14
Canada
50.89
52.17
South Korea
51.47
51.43
Australia
53.02
53.34
China
52.86
48.00
Average value of profitable positions
52.46
51.59



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 prevalence of the number of profitable transactions which indicates a lack of a well-pronounced regularity of the distribution of transactions results.

Conclusion

Correlation:

The total average value of the correlation coefficients speaks a lack of a well-pronounced 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 results of closed positions signifies a lack of a well-pronounced regularity in distribution of profitable and non-profit transactions.


Volatility on the day of publication of the indicator:

The volatility value on the day of publication exceeds its value for the preceding week and the preceding three weeks.

From the data presented, the publication of the BoT values has the greatest impact on the growth of volatility of the Pound Sterling. A weak increase in volatility occurs in the currencies of Brazil and Australia.

For the rest of the countries, the influence of the publication on volatility is missing.



The influence of the publication of the trade balance data of the countries on the direction of the market has not been identified.

XLSX (0.02 MB)Trade Balance.xlsx

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