International Banking and Finance - Example

International Banking and Finance Student’s Name Institution of Learning Date of submission 1. Graphs of Australian Dollar against various currencies Figure1. Trends of Australian Dollar against the USD The figure above shows the performance of Australian Dollar against the USD from 2010 to 2014. According to the figure above, it can be observed that in 2010, the USD was weakest against the Australian Dollar with an exchange rate of 0.8400 against 1 Australian Dollar. However, there was improvement from the year 2011 onwards where the highest value of the USD against the Australian Dollar was observed. The contributing factor towards improvement of the USD against the Australian Dollar can be attributed to the change in economic policies in the USA following the change in political regime. In the years 2012 onwards until 2013, the value of the USD against the Australian Dollar remained stable at 1.00 USD against 1 Australian Dollar. However, from the year 2013 to 2014, there was a low performance of the USD against the Australian Dollar with a value as low as 0.9 against 1 Australian Dollar. This change can be attributed to improvement of economic performance of Australia in international trade compared to the US between 2013 and 2014. Figure2. Trends of Australian Dollar against the European Euro From the figure above, it can be observed that the European Euro exchanged at 0.7 against 1 Australian Dollar. However, there was a gradual improvement in the value of the European euro between the years 2011 and 2013 with the highest value of the European euro being 0.83 against 1 Australian Dollar. This improvement can be attributed to a number of factors in the European foreign banking and financing policies such as increased trade with other countries and trade liberalization which resulted into high value of the European Euro. It can also be contributed by changes in banking policies that enabled international institutions to bank in the European countries thus improving the value of the Euro. However, between 2013 and 2014, it was observed that there was a drastic reduction in the value of the European euro against the Australian Dollar with the lowest value being 0.63 against 1 Australian Dollar in mid 2013. This can be attributed to improved economic performance in Australian in 2013 and improved economic policies in the country which resulted into increased trade and exchange with its partners. This resulted into an increase in value of its currency. Figure3. Trends of Australian Dollar against the Chinese Yuan The figure above shows that the performance of the Chinese Yuan was not very high in the year 2010 but improved steadily between mid 2010 and 2011 with the highest value of the Chinese Yuan being 7.00 against 1 Australian Dollar. This improvement can be explained to have been contributed by increased economic performance of China between 2011 and 2013. However, from 2012 onwards, it was observed that the Chinese yen reduced in value against the Australian Dollar with the value moving between 6.5 and 6.0 against 1 Australian Dollar. This can be explained to have resulted from economic reforms in Australia such as investments in international banking that resulted into improvement of the value of its currency. It can also be contributed by economic sanctions against China such as limit on international banking that affected its cooperation with partners in the banking sector. Figure4. Trends of Australian Dollar against the Indian Rupees According to the figure above, the value of Indian Rupee was 39.41 against 1 Australian Dollar. From 2010 until 2012, the value of Indian Rupee increased steadily reaching a maximum value of 59.6 against 1 Australia Dollar. This condition can be explained by the fact that India intensified its banking services in 2010 compared to subsequent years. As a result of reduced international banking between India and other countries, the value of its currency reduced compared with that of Australian Dollar. On the other hand, Australian government improved its international banking policies such as freedom of investment in foreign countries. This contributed to improved performance of the currency against the Indian rupee. Figure5. Trends of Australian Dollar against the South Korean Won The figure above shows that the South Korean Won exchanged at about 1030 against 1 Australian Dollar in 2010. This implies that in 2010, South Korean did not perform well in foreign exchange compared with Australia. However, there was a slight improvement then stagnation of the value of the South Korean Won with a value of 1200 against 1 Australian Dollar. This improvement can be attributed to improved international trade between South Korea and other countries that resulted into improvement in the value of its currency. Between 2012 and 2014, there was a decline in the value of South Korean Won with a value as low as 900 against 1 Australian dollar observed in 2014. This can be attributed to improved economic performance and international trade in Australia which boosted the value of its currency. Figure6. Trends of Australian Dollar against the Malaysian Ringgit According to the figure above, the value of Malaysian Rinngit was 2.75 against 1 Australian Dollar in 2010. There was a slight improvement in the value of this currency with the highest value being 3.2 against 1 Australian Dollar between 2011 and 2013. This value remained stagnant until 2013 because the economic performance of both Malaysia and Australia improved at the same pace. However, between 2013 and 2014, there was a slight reduction the performance of Malaysian Rinngit against the Australian Dollar. This is because Australia intensified foreign trade in 2014 thus improving the value of its currency. 2. Estimates of average FX rates for each currency in the four year period and standard deviation of the FX rate change were calculated and tabulated as shown below. USD Euro Yuan Rupee Won Rinngit Average 0.0001 0.0004 0.0000 0.0000 0.0000 0.0000 Std Deviation 0.007003441 0.013114624 0.006768397 0.006796476 0.005307149 0.005377843 Figure 7. Average and Standard deviation for various currencies 3. Estimates of one day loss of each currency under a 5% confidence level. Estimates of the potential maximum one-day loss of each currency under a 5% confidence level Currency SD Amount of Loss USD 0.007003441 0.000350172 Euro 0.013114624 0.000655731 Yuan 0.006768397 0.00033842 Rupee 0.007003441 0.000350172 Won 0.013114624 0.000655731 Rinngit 0.006768397 0.00033842 For the USD it will be 0.05*0.007003441=0.000350172. This shows that the value of Australian Dollar will reduce by 0.000350172 in a one-day loss. For Euro it will be 0.05*0.013114624=0.000655731. This shows that the value of Australian Dollar will reduce by 0.000655731 in a one-day loss. For Chinese Yuan it will be 0.05*0.006768397=0.00033842. This shows that the value of Australian Dollar will reduce by 0.000338421in a one-day loss. For Indian Rupee will be 0.05*0.007003441=0.000350172. This shows that the value of Australian Dollar will reduce by 0.000350172 in a one-day loss. For South Korean Won, it will be 0.05*0.013114624=0.000655731. This shows that the value of Australian Dollar will reduce by 0.000655731 in a one-day loss. For Malaysian Rinngit will be 0.05*0.006768397=0.00033842. This shows that the value of Australian Dollar will reduce by 0.00033842 in a one-day loss. 4. The correlation matrix of daily FX rates changes and the possible lessons from the correlation coefficients From Ms Excel, various values of correlation matrix were obtained as shown below.   USD Euro Yen Rupee Won Rinngit USD 1.0000 0.8040 0.9105 -0.0174 0.8559 0.91828798 Euro 0.803965759 1.0000 0.705345787 0.18440847 0.846606404 0.79285742 Yen 0.910533837 0.705345787 1.0000 -0.394255667 0.884032861 0.76850379 Rupee -0.017394217 0.18440847 -0.394255667 1.0000 -0.21790762 0.21267694 Won 0.8559 0.846606404 0.884032861 -0.217907617 1.0000 0.76932569 Rinngit 0.918287977 0.79285742 0.768503793 0.212676935 0.769325688 1.0000 Figure 8. Correlation between various currencies From the figure above, it can be observed that there is a positive correlation between most currencies except a few areas. Cases with negative correlation include the correlation between the USD and Indian rupee, the correlation between Yuan and Rupee and the correlation between Rupee and Won. 5. The use of Standard Deviation and Correlation coefficients to determine the SD of each currency scenario for cash flow. a. The case of USD 50% and Euro 50%   Standard Deviation Correlation Composition of cash flow USD 0.007003441 0.803965759 50% Euro 0.013114624 0.803965759 50% SD 0.358283544 b. The case of Chinese Yuan 40% and Indian Rupee 60%   Standard Deviation Correlation Composition of cash flow Yen 0.006768397 -0.394255667 40% Rupee 0.007003441 -0.39425567 60% SD 0.40558917 c. The case of South Korean Won and Malaysian Rinngit   Standard Deviation Correlation Composition of cash flow Won 0.013114624 0.769325688 70% Rinngit 0.006768397 0.769325688 30% SD 0.366858407 In the above currency combinations, the currency combination that is more risky is the combination of rupee and yen. This is because it has the greatest standard deviation of 0.40558917 which is higher than the SD for other combinations. 6. Using Purchasing Power Parity (PPP) and International Fischer Effect (IFE) to estimate exchange rates of USD, MYR, CYN and KRW for each six month period based on sot exchange rates on 2nd July 2012 as shown in the table below. In order to calculate the actual exchange rates of the countries in various cases using PPP the formula: S1/So= (Iy+1)/(Ix+1) was used. In the above formula: S1 is the actual exchange rate So is the spot exchange rate Iy is the inflation rate in the foreign country Ix is the inflation rate in the home country which in this case is Australia.   USD Australia Malaysia China South Korea Inflation Rates 0.025 0.012 0.032 0.0242 0.0141 Iy+1 1.025 1.012 1.032 1.0242 1.0141 Ix+1 1.012 1.012 1.012 1.012 1.012 (Iy+1)/(Ix+1) 1.01284585 1 1.019763 1.012055 1.002075099 So 1.0468 1 3.1817 6.5295 114.16 Making S1 the subject of the formula, we obtain S1=So(Iy+1)/Ix+1)Actual exchange rates as at 2nd January 2013 is obtained by: For USD, S1=1.0468*1.01284585= 1.060247036 For MYR, S1=3.1817*1.019763=3.244579447 For CYN,S1=6.5295*1.012055=6.608215316 For KRW, S1= 114.16*1.002075099=13032.5056 This process was repeated to obtain actual exchange rates as at 2nd July 2013, 2nd January 2014 and 2nd July 2014. The results were as shown in the excel worksheet 7 of workbook 2. Using International fischer effect (IFE), the formula used to get actual exchange rate will be S1/So= (Iy+1)/ (Ix+1) was used. In the above formula: S1 is the actual exchange rate So is the spot exchange rate Iy is the interest rate in the foreign country Ix is the interest rate in the home country which in this case is Australia   USD Australia Malaysia China South Korea Interest rates (Iy) 0.063 0.049 0.044 0.056 0.032 (Iy+1) 1.063 1.049 1.044 1.056 1.032 (Ix+1) 1.049 1.049 1.049 1.049 1.049 (Iy+1)/(/Ix+1) 1.013346044 1 0.995234 1.006673 0.98379409 So 1.0468 1 3.1817 6.5295 114.16 Making S1 the subject of the formula, we obtain S1=So(Iy+1)/Ix+1)Actual exchange rates as at 2nd January 2013 is obtained by substituting the respective values of So and (Iy+1)/(Ix+1) into the above equation. For USD, S1=1.0468*1.013346044=1.060770639 For MYR, S1=3.1817*0.995234=3.166534604 For CYN,S1=6.5295*1.006673= 6.573071497 For KRW, S1= 114.16*0.98379409=112.3099333 The same process was used to find actual exchange rates as at 2nd July 2013, 2nd January 2014 and 2nd July 2014. The results were as shown in the excel worksheet 7 of workbook 2. Report From the results of the use of Purchasing Power parity and International Fischer Effect method, the following observations were made. In countries whose inflation rates were higher than that of Australia, there was a reduction in the value of Foreign exchange rate compared with the spot exchange rates while in countries whose inflation rates was lower than that of Australia, the value of actual foreign exchange rate increased more than the spot exchange rate. This leads to the conclusion that the higher the inflation rate, the lower the power of a currency with respect to other currencies (Madura, 2013). From the results of the International Fischer Effect, it was found that countries whose interest rates were higher than that of Australia had higher actual exchange rates than the spot exchange rates. On the other hand, countries that had lower interest rates in comparison to Australia had lower actual exchange rates than the spot exchange rate. This implies that if a country has a higher interest rate, the value of its currency appreciates with respect to another country with a lower interest rate. This is in compliance with the Fischer effect which states that the higher the interest rate of a country, the more its currency appreciates with respect to a currency to which it is compared (Mullineux, 1987). 7. Comparison of Estimated spot Exchange rates and corresponding actual exchange rates When the Purchasing Power Parity method was used to compare the spot exchange rates with the corresponding actual exchange rates, it was found that in a case where the inflation rates in Australia was higher than the inflation rates in a country with which it was compared, the actual exchange rate was lower than the spot exchange rates. This can be explained by the fact that when a country has a higher inflation rate than the country of comparison, its currency loses value in foreign trade with the currency of the country of comparison. This resulted into a lower actual exchange rate compared to spot exchange rate. It was also found that if inflation rate in Australia was lower than a country with which it was compared, the actual exchange rate was higher than the spot exchange rate. This can be explained by the argument of Purchasing power parity which states that when a country has a lower inflation rate than the country of comparison, it has a higher purchasing power thus, resulting into a greater value of its currency in comparison to the currency of the other country. References De Rosa, L., & Fazio, A. 2003. International banking and financial systems: evolution and stability. Aldershot [u.a.], Ashgate. English for international banking and finance. 2002. Cambridge [u.a.]: Cambridge Univ. Press. Hassan, K., & Lewis, M. 2007. Handbook of Islamic banking. Cheltenham, UK, Edward Elgar. Machiraju, H. R. 2002. International financial markets and India. New Delhi [u.a.], New Age Internat. Madura, J. 2013. International financial management. Mason, OH, South-Western/Cengage Learning. McDonald, F., & Burton, F. 2002. International business. London [u.a.], Thomson Learning. Mullineux, A. W. 1987. International banking and financial systems: a comparison. 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