FX Carry Trade Analytic Report
International Finance
Submitted by, Taijas Kumar – s3496493
Table of Contents List of figures ........................................................................................................................ 1 Abstract ................................................................................................................................ 2 Introduction ......................................................................................................................... 2 Assumptions ......................................................................................................................... 2 Theoretical framework ......................................................................................................... 3 Qualitative and Current Issues affecting Currency ............................................................... 4 1. 2. 3. 4.
Qualitative factors affecting exchange rate determination ................................................... 4 Carry Trade and Interest rate parity current news and information...................................... 5 RPPP current news and information ..................................................................................... 6 Other news impacting exchange rate .................................................................................... 7
Data and Methodology......................................................................................................... 7 Regression Output and interpretation ............................................................................... 11 Single equation model & Results ........................................................................................ 13 Forecasting ......................................................................................................................... 14 Profit and Loss Calculation - Carry Trade ............................................................................ 15 Limitations .......................................................................................................................... 16 Conclusion .......................................................................................................................... 17 Reference List ..................................................................................................................... 18
List of tables Table 1: Currency valuation ranking (Sydney Morning Herald 2013) .................................... 7 Table 2: Regression of 3 variables ....................................................................................... 11 Table 3: Regression of 2 variables ....................................................................................... 12 Table 4: Final regression coefficients .................................................................................. 12 Table 5: Auto-correlation test between cash rate, exchange rate and CPI ............................. 13 Table 6: Forecasted values for the model ............................................................................. 14
List of figures Figure 1: Spot rate percentage of AUD/USD ......................................................................... 9 Figure 2: Interest rate differential of AUD/USD .................................................................... 9 Figure 3: CPI differential of AUD/USD .............................................................................. 10 Figure 4: GDP differential of AUD/USD............................................................................. 10 Figure 5: Carry trade portfolio for AUD and USD ............................................................... 15 1|Page
Abstract This report provides an analysis and evaluation of a carry trade strategy between AUD and USD between 2nd October 2015 to 18th December 2015. Methods include various regression analysis such as autocorrelation and ordinary least squares using the e-views software. Recommendations include, going long on AUD against USD and evaluating the analyses from time to time for constant accurate forecasts. This report also has certain limitations which has eventually helped in tying up the whole report together. The key factors are discussed in detail below.
Introduction Our investment strategy is to use the carry trade model to make a profit. We have chosen to go long in AUD and short in USD for the last financial quarter in 2015. The carry trade strategy is based on borrowing money using a currency with a low cash rate, in this case the U.S (0.25%). Then we must invest it in a country with a higher cash rate; in our instance the Australian cash rate of (2%). Furthermore, we expect the AUD to appreciate against the USD in the last quarter. Thereby using regression testing for the cash rate, the CPI and GDP. We have also utilized the interest rate parity and also the purchasing power parity theoretical frameworks to assist us in explaining the expected currency spot price. In addition, by using current news, it would support why we believe our strategy will be profitable in the AUD/USD currency pair.
Assumptions To perform the carry trade strategies, several facts have been assumed for smoothing the forecast of future spot rate of AUD/USD. The relative purchasing power parity(RPPP) and interest rate parity(IRP) conditions are applied here. Here, the RPPP assumes that there are no transportation costs between Australia and USA due to efficient market and the percentage change in CPI or inflation affects the movement in exchange rate (AUD/USD). While under IRP condition, the interest rate differentials between Australia and USA are assumed to be a better unbiased predictor of future spot rate. For constructing our single equation, we used 2|Page
short-term rates for USD and cash rate for AUD because our carry trade portfolio considers a time frame of only 3 months (77 days). Furthermore, if we would have considered long term rates, our analysis would have deterred us from forecasting our carry trade accordingly. In developing a single equation model, multiple linear regression theory is utilized to forecast the change in future spot rate at the end of our carry trade period. To run the regression model, three variables are selected; Interest rate (INT), Consumer price index (CPI) and GDP growth rate based on their underlying effects (Eiteman, Stonehill & Moffett 2013). It is anticipated that these variables can offer some substantial prediction or explanation on the movement of AUD/USD rate using the linearity between them. However, the final model will only consider variables that are more meaningful based on their respective significance of coefficients. Moreover, in developing our regression model, we did not consider the residuals or error since our determinants are constrained towards 2 variables towards our model. For E-views below are the assumptions (Kahane, 2008), 1. The residuals are normally distributed. 2. There is no perfect multicollinearity i.e., no exact linear relationship between 2 or more independent variables. 3. All independent variables are quantitative or dichotomous and dependent variables are quantitative, continuous, and unbounded.
Theoretical framework This paper aims at finding the perfect carry trade strategies. Currency carry trade is a very prevalent investment strategy in foreign exchange market. Egbers and Swinkels (2015) defined carry trade as a speculative position where somebody borrows money from low interest bearing country, converts that to high interest bearing country and invest there for more returns. This strategy is applicable where there is a significant deviation under interest rate parity condition between two countries (Cenedese, Sarno & Tsiakas 2014). Here the underlying approach implicates earning profits by taking short position in low-interest currencies, named funding currencies and then taking long position in high interest currencies named investment currencies (Laborda, Laborda & Olmo 2014). To construct the carry trade strategies, speculators need to forecast the expected future movement in exchange rate between two countries. Several core impulses are actually impacting on the persistency in exchange rates such as the deviations in purchasing power parity and interest rate parity. 3|Page
Sarno and Valente (2006) delineated the law of PPP where the exchange rate between two countries is determined by the ratio of the price level between domestic and foreign market. In absolute term, such exchange rate behavior between two countries is prevalent on when certain conditions are met such as single price, fully competitive market, no transaction cost and no trade barrier (Aoki 2007). Thus theoretically such linearity between nominal exchange rate and price levels of two countries will be stationary in long term. However, any deviation from current PPP theorem or change in domestic and foreign price level will eventually translate in the change in their respective exchange rate, causing overvalued or undervalued domestic currency (Sulku 2010). Relative purchasing power parity formula: % exchange rate change
=
% change in home (x) prices - % change in foreign (y)
prices Interest rate parity is another theorem that impacts on the determination of foreign exchange rate between two countries. Guender (2014) denotes that any differentials in interest rate between domestic and foreign market will affect the underlying movement in exchange rate between two countries. Theoretically any positive or negative disparities in interest rate will be compensated by depreciation or appreciation of domestic currencies which would be visible in our model. Chang-Chiang and Huei-Mei (2009) further added that empirically IRP assists speculators in determining future spot rate with the increase or decrease of interest rate. This ultimately help them devise their trading strategy. Interest rate parity formula:
Qualitative and Current Issues affecting Currency 1.
Qualitative factors affecting exchange rate determination
In developing our model to forecast future exchange rate, we only considered interest rate and CPI (inflation). However, from a rational and practical point of view, there are several other aspects in relation to our model that would affect our independent variables as well as exchange rate in both short and long run. Relevant qualitative factors together with their impacts on exchange rate are discussed below: 4|Page
Fiscal policy Due to the global financial crisis (GFC), many advanced counters especially USA has experienced a prolonged economic weakness which forced them to keep their short term interest rate near zero (0.15%). However, with significant improvement in economic condition, USA is now expecting to increase their interest rate while Australia is cutting their cash rates. Any further change of interest rates in fiscal policy would affect the interest rate differentials and thereby appreciate or depreciate AUD/USD exchange rate. Government debt and economic growth rate With mining boom, Australia was enjoying a superior rating of AAA (Financial review 2015) in their government debt position while USA was rated AA+ under this factor (Bloomberg 2015). However, with higher budget deficit, and enhancing unemployment rates, Australia is experiencing a lower forecasted economic growth (from 3.25 to 3%). In contrast, USA is stabilizing their economic growth and government debt position. There factors will eventually affect the balance of payment and foreign investment in both countries and cause the exchange rate to move in different directions.
2.
Carry Trade and Interest rate parity current news and information
As cited in the Sydney Morning Herald (2015) the RBA decision in August 2015 not to decrease the current cash rate of 2%, it illustrated in the matter of hours after the announcement the AUD appreciated from 0.729 USD per AUD to 0.739 USD per dollar, thus demonstrating the impact of cash rate and supporting the interest rate parity and carry trade theoretical frameworks. The significance of a country's cash rate is pivotal to the currency spot rate. According to Bloomberg (2015), investors believed that the uncertainty demonstrated by the United States FED reduced the market view that the anticipated U.S cash rate hike had a lower probability of occurring was reflected by the depreciation of the U.S dollar. However, in the practical terms, currency exchange prices and the interest rate parity framework do not always reflect an absolute linear correlation. Apart from interest rate, some other factors as stated in the Financial Express (2015) also influence the future spot rate: â—? Political compulsions â—? Monetary policy interventions â—? Interdependence and volatility in different markets 5|Page
●
Property market
●
Consumer spending
● General inflation ● Economic growth rate ● Domestic compulsion Even though the interest rate parity framework is an excellent model, we must remember that we cannot deduce expectations on currency futures rates using this model alone; as factors stated above also play a critical role in the determination of currency exchange.
3.
RPPP current news and information
The relative purchasing power parity is an important theory in determining whether some currencies may be undervalued or overvalued, as illustrated in the graph below (Sunday Morning Herald, 2013). The Australian dollar at that time was one of the most overvalued currencies based on PPP, the Big Mac Index and REER levels. In early February of 2013 the Australian dollar was trading at an astonishing price of $US 1.03. In contrast currently in October 2015 the Australian dollar is trading at $US 0.73. This data demonstrates in the long term the purchasing power parity will adjust the currency to its underlying fair value. However, in the short term, it is possible for currency traders to cash in a profit, as news and market sentiment impact on the currency exchange prices.
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Table 1: Currency valuation ranking (Sydney Morning Herald 2013)
4.
Other news impacting exchange rate
Current news is also a major influence of the currency exchange rate. As reported in The Australian (2015) when Malcolm Turnbull had taken office as Australian prime minister over Tony Abbott, the Australian dollar was trading at USD 71.14 cents appreciating from USD 70.90 cents the previous day. The market has indicated that Malcolm Turnbull will bring the Australian economy to a greater prosperous level than under the former prime minister.
Data and Methodology For the assessment and evaluation of data, it is imperative that the data collected are from reliable sources for the attainment of concrete results. All our sources have been collected from Organization for Economic Co-operation and Development (OECD) database, Reuters FX Polls, Reserve Bank of Australia (RBA) and the Federal Reserve website. Our research work consists of independent determinants as mentioned below that affect the foreign exchange rate, namely,
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For AUD CURRENCY (20 years data), 1. Consumer price index (CPI) - Data collected from Reuters. 2. Gross Domestic Product (GDP) - Data collected from Reuters. 3. Cash Rate - Data collected from Reuters. For USD CURRENCY (20 years data) 1. CPI - Data collected from Reuters. 2. GDP - Data collected from Federal Reserve. 3. Cash Rate (Short-term interest rate) - Data collected from OECD. Note - Forecasted rate for AUD was taken from RBA (cash rate) and Reuters(CPI) website whereas for USD from Federal Reserve (cash rate) and OECD (CPI). The above was analyzed by collecting data on a quarterly basis between 1995 Q2 to 2015 Q3. Large sample size was taken to make our sample observations more reliable. Using all the independent variables mentioned above, we calculated the differentials of the cash rate, GDP and CPI. As far as the dependent determinant i.e., the percentage change between the USD and AUD goes, the data was collected from the Reuters as well. After assembling all the data with correct configurations we used the multiple regressions method of ordinary least squares using the EViews software. We could had used the maximum likelihood method but according to Ryan (2013) this method is not the best suited for estimation of the same as the estimators tend to vary for every regression. By regressing the 3 independent (CPI, GDP and cash rate) and 1 dependent variable (spot rate between AUD/USD) together, we got certain outputs which highlight the factors that show significant effects on the percentage change in the exchange rate. Using the 2 most significant effects out of the three, we did another regression until the best model was achieved. Moreover, tests like autocorrelation and ordinary least squares were used to test the best fit and its strength with regards to the regression. Below you will observe the findings of our research considering the factors that play a role in determining the exchange rate between AUD and USD.
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Figure 1: Spot rate percentage of AUD/USD
Figure 2: Interest rate differential of AUD/USD
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Figure 3: CPI differential of AUD/USD
Figure 4: GDP differential of AUD/USD
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Regression Output and interpretation Below you will find our regression based on the 3 variables, where, ● FGDP - Differential gross domestic product ● FCPI - Differential consumer price index ● FCR - Differential cash rate ● FSR - Percentage change between USD and AUD
Table 2: Regression of 3 variables
From above we find that the cash rate differential is significant as the p-value is 0.0000 which is less than the critical value of 0.05 (5%) with a coefficient value of 0.049291. CPI was also significant as it had the p-value of 0.0254 which is less than the critical value of 0.05 with a coefficient value of -0.028768. The negative sign showcases that the CPI has a negative correlation towards the exchange rate whereas the cash rate showed direct correlation w.r.t exchange rate. Now we select the 2 significant variables and put them in another regression towards the exchange rate change as per below,
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Table 3: Regression of 2 variables
As per our interpretation, from above (table 3) we see that both the variables are again significant as per their joint impact towards the exchange rate with slight changes in the coefficients. According to the adjusted-R2, our model explains 30% of the data indicating that there could be other factors that could influence the exchange rate. Below is our final regression output as per our requirement. CPI and Cash Rate → Independent variables Exchange rate change → Dependent variable
COEFFICIENTS
FSR
FCR
FCPI
0.049375
-0.030014
Table 4: Final regression coefficients
As stated by Rupert et al., (2015), the correlation in regression does not necessarily imply causation but indicates linkages in sequence of events, furthermore, the CPI and exchange rate behave inversely (table 4). Therefore, since correlation doesn’t exactly have a predictable ability (Rupert et. al., 2015), we have to analyze CPI, cash rate and exchange rate data simultaneously. 12 | P a g e
Now we check for serial correlation for cash rate, CPI w.r.t exchange rate as per table 5,
Table 5: Auto-correlation test between cash rate, exchange rate and CPI
As per our observation, there is no serial correlation between dependent and independent variables as the p-values are more than 5% (critical value). This means that the variables evolve in a random process rather than it’s related prior values. Hence, they are not affected by the past variable patterns.
Single equation model & Results Based on the final regression analysis and our group decision, only interest rate and CPI are used to predict the future spot rate of AUD/USD. The final single equation model, AUD/USD (% change)
= = 0.690888 + 0.049375 INT – 0.030014 CPI
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Here, = 0.690888; this indicates that based on the trend on AUD/USD movement, without any percentage change in interest rate and CPI differentials, the AUD/USD exchange rate will change by 0.690888% = 0.049375; For every unit percentage change (increase/decrease) in interest rate differentials, AUD will change (increase/decrease) by 0.049375%, considering ceteris paribus or other things remain constant. = -0.030014; For every unit percentage change (increase/decrease) in consumer price index differentials, AUD will change (increase/decrease) by -0.030014%, considering ceteris paribus or other things remain constant.
Forecasting Now, based on the forecasted information of quarter 4 on interest rate and CPI, we can estimate the possible rate of AUD/USD. The following predicted information are collected from Reuter FxPoll, Wall street journals, Reserve Bank of Australia and Federal Reserve system USA web pages. Australia
USA
Interest rate
2.0%
0.25%
CPI
0.8%
0.4%
Table 6: Forecasted values for the model
Thereby, AUD/USD (% change) = 0.690888 + 0.049375 (2% - 0.25%) – 0.030014 (0.8% - 0.4%) = 0.76528865 or approx. 0.77 Thus, as per the model, AUD is expected to appreciate by 0.77% during the quarter 4 in 2015. Since the current spot rate on quarter 3 is 0.7117 AUD/USD, it implies that the forecasted exchange rate for quarter 4 would be, {0.7117 * (1+0.77%)} = 0.7172 AUD/USD.
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Profit and Loss Calculation - Carry Trade Based on our analysis to forecast the spot rate, in this section. we will perform our carry trade. Using the underlying notion of carry trade, we will borrow money from one country and invest it to other. Since the forecasted interest rate of USA (0.25%) is considerably lower than that of Australia (2%) in quarter 4, there is a huge possibility of arbitrage. Furthermore (Figure 1), at the end of quarter 3, we will borrow $1,000,000 from USA, which will be paid back at the end of our carry trade period with 0.25% interest rate per annum. Then we will convert the borrowed amount to AUD with current spot rate (0.7117 AUD/USD) and invest in Australia with cash rate 2% per annum (these will be converted to per quarter basis for our calculations). At the end of quarter 4, we will convert back our investment proceeds to USD using our forecasted spot rate (0.7172 AUD/USD) for quarter 4 and pay back the borrowed amount along with the interest for that period. Any difference between the payback amount and the investment proceeds will be our profit and loss.
Figure 5: Carry trade portfolio for AUD and USD
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Profit/loss calculation At the end of Q3, Borrowed amount = USD 1,000,000 Amounts to be paid back at the end of Q4 = USD 1,000,000 * (1 + (0.25% * 77/360)) = USD 1,000,534.72 Current spot rate = 0.7117 AUD/USD Converting borrowed amount to AUD = 1,000,000/0.7117 = AUD 1,405,086.41 At the end of Q4, Investment proceeds = AUD 1,405,086.41 * (1 + (2% * 77/360)) = AUD 1,411,097.06 Forecasted spot rate = 0.7172 AUD/USD Converting investment proceeds to USD = 1,411,097.06 * 0.7172 = USD 1,012,038.81 Profit after paying back the owning amount = USD (1,012,038.81 - 1,000,534.72) = USD 11,504.09
Limitations 1. Parameter Instability - Relationships between CPI, cash rate and exchange rate have a tendency to alter overtime towards the changes seen in the economy. Therefore, more parameters would be needed as the number of variables are relatively low to attain an accurate regression. 2. The main limitation is that we can only ascertain relationships of variables rather than the underlying causal factor. For example, from our single equation model (table 3) we found that cash rate has direct correlation towards the exchange rate which doesn’t necessarily mean that the cash rate causes changes to the exchange rate. 3. Further testing such as the heteroskedasticity, chow breakpoint tests would help in generating the variable pattern flow towards the data used. However, these could not be done as sufficient accurate data was not present to analyze for the same. 4. There was limited time available during our dealing sessions which resulted in the limited information being considered as statistically perfect for our research. 5. In the single equation model, the explanatory variables are difficult to determine as the coefficients used may not remain constant over the period of time. 6. Measurement and calculation errors may be present which might affect the forecast. 7. Our regression model based on RPPP is expected to hold up for more than 77 days if and only if the market efficiency of this theory remain true, which is quite unlikely. 16 | P a g e
Conclusion There are various factors that are responsible for the determination of exchange rate changes, mainly, the cash rate and the CPI. However, on the basis of RPPP, IRP and the single equation model, we forecasted that the AUD would rise against the USD between 0.75% to 1.5% till 18th December. Since our data regressed is not serially correlated, it gives us a better accuracy for our forecasted estimation of the same. However, the limitations on the model and theories may reorient our forecast. The data would be needed to be constantly reevaluated and re-adjusted due to the fluctuating nature of economic factors and current news to always give an accurate forecast. In conclusion, we would recommend on going long on AUD against the USD for the last quarter of 2015.
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Reference List Aoki, T 2007, 'Some remarks on purchasing power parity and exchange rate determination mechanism', Applied Economics Letters, vol. 14, no. 3, pp. 179-182 Bloomberg 2015, ‘Dollar bull-herd exposed’, <http://www.bloomberg.com/news/articles/2015-08-20/dollar-bull-herd-exposed-again-asseptember-fed-rate-odds-shrink> Cenedese, G, Sarno, L, & Tsiakas, I 2014, 'Foreign exchange risk and the predictability of carry trade returns', Journal of Banking & Finance, vol. 42, pp. 302-313 Chang-Chiang, C, & Huei-Mei, L 2009, 'The long-run uncovered interest rate parity in view of a trading strategy', Applied Economics, vol. 41, no. 21, pp. 2727-2739 Egbers, T, & Swinkels, L 2015, 'Can implied volatility predict returns on the currency carry trade?', Journal of Banking & Finance, vol. 59, pp. 14-26 Eiteman, DK, Stonehill, AI and Moffett, MH 2013, ‘Multinational business finance’, ed. 13, Pearson Education Inc., London Financial Express 2015, ‘How interest rate parity affects investments’, <http://www.financialexpress.com/article/personal-finance/how-interest-rate-parity-affectsthose-who-invest-abroad/153728/> Guender, AV 2014, 'Monetary Policy and the Uncovered Interest Rate Parity Puzzle: Theory and Empirical Results for Oceania', Economic Record, vol. 90, no. 289, pp. 207-219 Kahane LH 2008, ‘Regression Basics’, Library of Cataloging-in Publications, ed. 2nd, pp. 31 Laborda, J, Laborda, R, & Olmo, J 2014, 'Optimal currency carry trade strategies', International Review of Economics & Finance, vol. 33, pp. 52-66 Ryan P. 2013, ‘Sample size determination and power’, Institute for Statistics education, pp 57-63. Rupert D, Matteson D 2015, ‘Statistics and Data analysis for Financial Engineering’,Business Media LLC New York, 2nd edition, pp 379. Sarno, L, & Valente, G 2006, 'Deviations from purchasing power parity under different exchange rate regimes: Do they revert and, if so, how?', Journal of Banking & Finance, vol. 30, no. 11, pp. 3147-3169
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Sulku, SN 2010, 'Econometric testing of purchasing power parity in less developed countries: fixed and flexible exchange rate regime experiences', Applied Economics, vol. 42, no. 20, pp. 2617-2630 Sydney Morning Herald 2013, ‘ The most overvalued currency’, <http://www.smh.com.au/business/markets/dollar-the-most-overvalued-currency-201302152eho2.html > Sydney Morning Herald 2015,’RBA keeps cash rate at 2%’, <http://www.smh.com.au/business/the-economy/rba-keeps-cash-rate-at-2-per-cent-at-augustmeeting-20150804-gir5m4.html > The Australian 2015, ‘Australian dollar jumps after pm spill’, <http://www.theaustralian.com.au/business/markets/australian-dollar-jumps-after-pmspill/story-e6frg916-1227527623312 >
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