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Understanding and Exploiting Commodity Currencies a Study Using Time Series Regression

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Understanding and Exploiting Commodity Currencies a Study Using Time Series Regression DEGREE PROJECT IN TECHNOLOGY, FIRST CYCLE, 15 CREDITS STOCKHOLM, SWEDEN 2017 Understanding and Exploiting commodity currencies A Study using time series Regression DYLAN DEHOKY EDWARD SIKORSKI KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF ENGINEERING SCIENCES Understanding and Exploiting commodity currencies A Study using time series Regression DYLAN DEHOKY EDWARD SIKORSKI Degree Projects in Applied Mathematics and Industrial Economics Degree Programme in Industrial Engineering and Management KTH Royal Institute of Technology year 2017 Supervisors at KTH: Henrik Hult, Pontus Braunerhjelm Examiner at KTH: Henrik Hult TRITA-MAT-K 2017:04 ISRN-KTH/MAT/K--17/04--SE Royal Institute of Technology School of Engineering Sciences KTH SCI SE-100 44 Stockholm, Sweden URL: www.kth.se/sci Abstract This thesis within Industrial Economics and Applied Mathematics examines the term commodity currency. The thesis delves into analysing the characteristics and consequences of such a currency through a macroeconomic perspective while discussing previous studies within the matter. The applied mathematical statis- tics section audits the correlation between the currency and the commodities of the exporting country through a time series regression. The regression is based on the currency as the dependent variable and the commodities represent the covariates. Furthermore, a trading strategy is developed to see if a profit can be made on the foreign exchange market when looking at the commodity price movements. Key words: Commodity currencies, regression analysis, time series regression, Dutch disease and trading strategy Att f¨orst˚aoch utnyttja r˚avaruvalutor En statistisk analys baserat p˚atidsserieregression Sammanfattning Det h¨arkandidatexamensarbetet ¨arskrivet inom industriell ekonomi och till¨ampad matematik och granskar termen r˚avaruvaluta (commodity currency). Upp- satsen analyserar, utifr˚anett makroekonomiskt perspektiv, karakt¨arsdragen och konsekvenserna av en s˚adanvaluta, samtidigt som den diskuterar tidigare studier inom ¨amnet.Delen inom till¨ampadmatematik unders¨oker korrelationen mellan valutan och r˚avarorna som landet exporterar genom en tidsserieregres- sion. Regressionen ¨arbaserad p˚avalutan som responsvariabel samtidigt som r˚avarorna representerar kovariaterna. Den f¨ardigamodellen anv¨andssedan i en handelsstrategi som f¨ors¨oker f¨orutsp˚av¨axelkursensr¨orelsergenom att titta p˚a r˚avarornas r¨orelser. Preface This Bachelor's thesis was written in the spring of 2017 by Edward Sikorski and Dylan Dehoky, during their five-year master's degree program within Industrial Engineering and Management at KTH Royal Institute of Technology. The the- sis combines both aspects from industrial economics and applied mathematical statistics. These aspects were integrated into one report, although the economi- cal and mathematical theories were separated under section 2 and 3 respectively. We would also like to take the opportunity to thank Joel Berhane, Sara Alexis, Graziella El-Ghorayeb, and Dalill Arafat for their never-withering belief in us. Lastly, we would like to express our appreciation to our supervisors Henrik Hult and Pontus Braunerhjelm for allowing us to write this thesis together, despite Edward being on the other side of the globe. Contents 1 Background 1 1.1 Aim . .2 1.2 Research Question and Problem Statement . .2 1.3 Limitations . .2 1.4 Previous Research . .3 2 Theoretical Background 4 2.1 Understanding Exchange Rates . .4 2.1.1 Floating or pegged? . .4 2.1.2 Nominal exchange rate (NER) . .5 2.1.3 Real exchange rate (RER) . .5 2.1.4 Overshooting . .6 2.1.5 Purchasing power parity (PPP) . .6 2.1.6 PPP puzzle . .7 2.1.7 Factors influencing the exchange rate . .7 2.2 Commodity Pricing . .8 2.2.1 Supply and demand . .8 2.3 Commodity Currencies . .9 2.3.1 Commodity currencies through PPP . .9 2.3.2 Consequences of a commodity currency . 10 2.4 Dutch Disease . 10 2.4.1 Historical events . 11 2.4.2 Consequences . 11 2.4.3 Other theories . 12 2.4.4 Mitigation of the phenomenon . 13 3 Mathematical Theory 14 3.1 Multiple Linear Regression . 14 3.2 Ordinary Least Squares . 14 3.2.1 Key assumptions . 15 3.2.2 Lagged variables . 15 3.2.3 Interpretation of the coefficents . 15 3.2.4 Logarithmic transformation of variables . 16 3.3 Time Series Regression . 16 3.3.1 Similarity measure . 17 3.3.2 The Autoregressive model . 18 3.4 Validating the Model . 18 3.4.1 Hypothesis testing . 18 3.4.2 F-test statistics and t-test . 19 3.4.3 p-value . 19 3.4.4 R2 and Adjusted R2 ..................... 20 3.4.5 Akaike Information Criterion . 20 3.5 Errors . 20 3.5.1 Heteroscedasticity . 21 3.5.2 Multicollinearity . 22 3.5.3 Endogenity . 23 3.5.4 Normality . 23 3.5.5 Autocorrelation and cross-correlation . 24 3.5.6 Spurious regression . 25 4 Method 27 4.1 Data Collection . 27 4.2 Literature Study . 28 4.3 Choice of Country . 28 4.4 The Regression Model . 29 4.5 Outline . 31 5 Results 33 5.1 Preliminary analysis of the data and unit root analysis . 33 5.2 Cointegration analysis . 35 5.3 Regressions without lag . 36 5.4 Regressions with lag . 38 5.4.1 Smoothed data . 40 5.5 Analysis of models . 42 5.6 Trading results . 46 6 Discussion 49 7 Further Research 53 8 References 54 9 Appendices 58 9.1 Graphs . 58 9.2 Regression outputs . 67 9.3 Nominal Commodity Prices . 68 1 Background The relationship between macroeconomic fundamentals and the real exchange rate is among the more controversial in the field of international macroeco- nomics. Attempts to model the behaviour of the real exchange rate empirically has repeatedly proven to be unsuccessful. This was most noticeably demon- strated by Meese and Rogoff [1983], where they found a random walk model performing as well as any of their models in predicting the exchange rate. This random walk contradicts the Purchasing Power Theory, which claims that ex- change rates should converge towards an equilibrium level, such that price lev- els are equal once converted to a common currency [Rogoff, 1996]. Voices have been raised that real shocks in macroeconomic fundamentals could prove to be decisive in resolving these empirical puzzles. However, what these price shocks might be, or how to identify and measure them remains to be answered [Chen & Rogoff, 2012]. In contrast, commodity prices have generally been shown to drive real exchange rates in major commodity-exporting countries, giving birth to the term "com- modity currencies". One of the first people to discover the correlation between a commodity exporting country and its currency was Paul Krugman [1980], as he observed how oil prices affected different exchange rates. More extensive re- search was made, and economists could confirm the correlation. In 2003, Cashin looked at currencies among developing countries and saw that the correlation was not as robust as with developed countries. The reasons to this was that inflation and capital controls in developing countries in turmoil are constantly fluctuating [Cashin et al. , 2003]. There are several commodity currencies, but studies have shown that the Cana- dian dollars (oil), Australian dollars (gold) and New Zealand dollars (agricul- tural products, e.g. wheat) are the three currencies among developed countries with high correlation to their commodities [Chen & Rogoff, 2002]. Other cur- rencies worth mentioning are the South African Rand (metals, e.g. platinum), Norwegian Krone (oil) and Brazilian Real (oil, soybeans, iron). When the price of a commodity rises, the cost of goods sold increases, thus, resulting in an in- crease of the price. Consequently, this raises inflation. The response to a rise in inflation is a rise in interest rates, in order to strengthen the currency. In essence, appreciation of commodity prices results in a strengthened currency. However, macroeconomic problems arise along with a commodity currency. The Dutch disease is such an implication, which in simple terms regards how a natu- ral resource boom can cause other sectors, often manufacturing, to experience a decline. The term was coined in the journal The Economist in 1977, describing the decline in The Netherlands' manufacturing sector following the discovery of oil in the country. This is as the increased commodity export drives up the value of the currency, making the other sectors less competitive on the international market. 1 Another complication that a commodity currency bears is the sensitivity to fluctuations in the price of the commodity. In the case of developing countries, where a commodity is their main source of income, a fall in the price of their commodity can have dire consequences. For instance, 60% of Mali's export is gold, leaving them vulnerable to fluctuations in gold prices [OEC, 2015]. However, despite considerable research having been conducted in the field, the majority of the literature concerning the relationship between commodity prices and exchange rates focus on a longer time horizon. This begs the question, from an investors point of view, whether there exists a relationship over a shorter time period. Hence, this thesis differs from previous studies in the field by seeking to conclude whether there exists a relationship between the nominal exchange rate, instead of the real exchange rate, and commodity prices in selected major commodity currencies on a short term. 1.1 Aim This thesis aims to assess the short-term relationship between nominal exchange rates and commodities in countries where the majority of the total export con- stitutes of one, or a few, commodities. It further aims to examine, both from a macroeconomic and statistical point of view, the reasons behind the results. 1.2 Research Question and Problem Statement The aim culminates in the following two problem statements: • Is there a short-term relationship between commodity prices and nominal exchange rates? • Is it possible to profit from this relationship? An Ordinary Least Squares (OLS) estimation will be used for one country, using data from January 2009 until December 2016, to give a robust empirical underpinning to these questions.
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