BAFI3200 ASM2 Exchange-Rate-Forecasting Asm 2 PDF

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Subject code BAFISubject name International FinanceCampus SGSAssessment name Exchange Rate ForecastingLecturerStudent name & ID:GroupTable of Contents Executive Summary ..............................................................................................................................

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Subject code

BAFI3200

Subject name

International Finance

Campus Assessment name Lecturer Student name & ID: Group

SGS Exchange Rate Forecasting

Table of Contents Executive Summary.............................................................................................................................0 Introduction.........................................................................................................................................1 Task 1: Exchange rate forecasting models.........................................................................................1 Data Source......................................................................................................................................1 Purchasing power parity.................................................................................................................2 PPP Model construction.............................................................................................................2 PPP Regression result & analysis:.............................................................................................3 PPP Residual Plot:......................................................................................................................4 PPP Forecasting for Q1/2021:....................................................................................................4 Uncover Interest rate Parity (UIP).................................................................................................5 UIP Model Construction:...........................................................................................................5 UIP Regression result & analysis:..............................................................................................5 UIP Residual Plot:.......................................................................................................................6 UIP Forecasting for Q1202:........................................................................................................6 Macro-based Model.........................................................................................................................7 Macro-based Model construction..............................................................................................9 Macro-based regression result & analysis:................................................................................9 Macro-based Model forecasting for Q1/2021:.........................................................................10 Task 2: Composite Forecasting.........................................................................................................11 Task 3: Qualitative Factors...............................................................................................................12 Sweden policy in terms of QE program.......................................................................................12 Sweden’s labour market................................................................................................................12 Economic Growth in Covid-19 Pandemic....................................................................................13 Sweden import and export policy.................................................................................................13 References:.........................................................................................................................................14

Executive Summary The purpose of this report is to calculate and forecast the exchange rate of EUR/SEK for Quarter 1 in 2021. The data set used in this report is collected from Quarter 2 of 2003 to Quarter 3 of 2020. By applying regression analysis for Purchasing Power Parity model, Uncovered Interest Rate Parity, and Macro-based model, we come up with the forecasted exchange rate EUR/SEK based on each model, with 10.6964, 10.388 and 10.5353, respectively. The results derived from 3 models indicates that the exchange rate of EUR/SEK will be depreciating. To generate a more trustful forecasted exchange rate EUR/SEK, we decided to construct Composite Forecasting Model, which is the combination of 3 models above, and produce the final exchange rate EUR/SEK in Q1/2021, with the result of 10.5415. To support the forecasting results from the models, we also discuss the qualitative factors and events affecting the depreciation of EUR/SEK, which are Sweden policy in terms of QE program, Sweden’s labour market, Economic Growth in Covid-19 Pandemic, Sweden import and export policy.

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Introduction According to Reinhart and Reinhart (2001), the exchange rate is determined as the value of a currency of a nation in terms of the other country’s currency. Having a deep understanding about the causes affected by the exchange rate, investors could seize opportunities and receive profit by predicting how it will change in future. In this report, the exchange rate of SEK/EUR in Q1 2020 is forecasted by applying quantitative and qualitative methods. In quantitative methods, there are four models used in order to anticipate the exchange rate. The first model, we used the inflation rate differential between Sweden and Euro area, known as PPP theory. The next model is interest rate parity that uses the differential of interest rate of two countries. The third model attached six macro factors including inflation, interest rate, oil price, GDP growth rate, money supply and current account balance. Thus, in the last model, the most significant variables will be chosen by using the backward elimination. In terms of qualitative, the movement Sweden and Euro area exchange would be forecasted by analyzing the relevant economic events

Task 1: Exchange rate forecasting models Data Source

Table 1: Data sources used in our report

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Purchasing power parity Purchasing power parity (PPP) is an economic theory which uses the “basket of goods” approach in order to compare different countries. Purchasing Power Parity (PPP) tends to center around the aggregate price levels whereas the law of one price (LOP) focuses on an individual level (basing on Sorkin 2012). According to International Monetary Fund Research (1976), PPP among two countries includes two versions such as absolute PPP and relative PPP. Absolute PPP is considered as the ratio of the countries' price levels or the product of the exchange rate in a base period. Relative PPP is the ratio of the countries’ price indices. According to Flood and Taylor (2005), absolute PPP supposes that the exchange rate is the same with the ratio of 2 national price levels while relative PPP shows that the shift in the exchange rate accompanies the shift in relative national prices. Therefore, a country suffering higher inflation will hope to decrease its currency. The formula for absolute PPP: st = (pt - pt*) + t The formula for relative PPP: st = (pt - pt*) + t In which: St : The spot exchange rate (Domestic price of foreign currency) at time t pt : The domestic price level at time t pt*: The foreign price level at time t PPP Model construction Basing Alastair J.Waithe (2010), the relative PPP be tried utilizing bivariate regression analysis by estimating the equation. %

S = 0 + 1 * (Inf Euro Area + Inf Sweden) +

In which: %

S: The percentage change in the spot exchange rate

%

P: The percentage change in the domestic price level (Domestic Inflation)

%

P*: The percentage change in the foreign price level (Foreign Inflation) 0

: The arbitrary constant term (the intercept)

1

: The coefficient of the regressors

: The error (residual) term Apply to this case, considering the domestic currency is Euro (EUR) and the foreign currency is Sweden (SEK), the regression model would be indicated in terms of difference inflations between the Euro Area (Home country) and Sweden (Foreign country) (basing on Hauner, Lee and Takizawa, 2010): %

EUR/SEK =

0+

1*

(Inf Euro Area + Inf Sweden) +

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In which: Inf Eu: Inflation rates in the Euro Area Inf Sweden: Inflation rates in Sweden

Figure 1: Regression result of PPP PPP Regression result & analysis: According to figure 1, the relationship between percentage change of exchange rate and inflation rate of Euro area and Sweden is:

-

The intercept coefficients �0 is 0.0045 that is expected that the value of exchange rate between two countries will be 0.0045 when there is no different between their inflation.

-

The slope of coefficients is - 0.00537 has showed the negative relationship between the exchange rate of EUR/SEK and inflation rate differentials. It will be explained that a 1% increase in inflation rate will lead to an increase in % change of spot rate by 0.00537%.

-

The R-square is 0.031 which means there are only 3.1% of percentage change of exchange rate variation is explained by inflation rate differentials between Sweden and Euro area.

-

The P-value is extremely high (14.5%), much higher than 0.05 implies that the null hypothesis is true. The results were not statistically significant. Hence, there is no relationship between two variables.

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PPP Residual Plot:

Figure 2: Inflation differenntial residual plot The residual plot diagram displays the most of errors are randomly dispersed around the horizontal axis and fluctuate around -0.08 and 0.006 which is relatively low, indicating a good fit model. PPP Forecasting for Q1/2021:

Time 2020 - Q4 2021 - Q1

Inflation

Predicted % change of EUR/SEK

differential exchange rate -0.6052 0.00776198 -0.7 0.00827106 Table 2: PPP model exchange rate forecast

10.6086096 10.696354

(Data adapted from Trading Economics (2020)) To predict the exchange rate in Q1 – 2020, we use the differentials of inflation rate in Q3 2020 plugging to regression equation:

Based on above equation, exchange rate in Q4 2020 is predicted increase by 0.77%. Hence the expected ER of Sweden and Euro area is 10.61. According to Trading Economics (2020), the differences of inflation between Sweden and Euro area are predicted slowly increase from -0.7 to 0.2 in the first three quarters in 2021. IN case of PPP model is truth, the exchange rate of EUR/SEK is sightly increase following the differential inflation. However, the p-value of this model is too high, the forecasting exchange rate is not reliable due to the unclear relationship between the change of EUR/SEK and the inflation difference. Uncover Interest rate Parity (UIP) The general concept of the Interest Rate Parity (IRP) explains the changes of the exchange rate related to the nominal interest rate differential between two countries. Furthermore, we have two different

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covered and uncovered interest arbitrage. With the uncovered interest arbitrage, we will predict the future spot rate and also use that future sport market to exchange currency. Hence, due to we are not hedged against possible risk, our profit gain or loss will be affected by market exchange rate. Otherwise, with covered interest arbitrage, after having the prediction for future exchange rate, we will have a forward contract at which we will sell currency in the future. Nevertheless, using a covered interest arbitrage can limit the potential risk and make profits from the market. UIP Model Construction: The equation of UIP model to be examine will be:

UIP Regression result & analysis:

Figure3. UIP Regression Model The Equation for UIP Regression is that:

S EUR´/ SEKt =−0.006617827+0.00821196 ×(i EUR −iSEK )t It can be analysed from the UIP regression result that: 

The intercept

β0

is

−0.006617827 , expressing that the difference between the

interest rates of both regions valued at 0 at time t will lead to the fall in the change of exchange rate EUR/SEK by −0.66 %

in the same period.

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

The coefficient β 1

is 0.00821196

acts the indicator that if the interest rate differential

of the both interest rates increases by 1% at time t, the change of the exchange rate will also increase by 0.82% in the same period. 

The R-squared is calculated at 0.039796375 , showing that about 3.97% of the variations of the change of the Exchange rate between EUR and SEK can be explained by the change of the both interest rates. This can be inferred that there is an insignificant relationship between change in exchange rate and interest rate differential between EUR and SEK.



The p-value is recorded at

0.097784411 (approximately 9.77%, which is higher than the

significant level 5%) illustrate that there is no specific relationship between the change of the exchange rate and interest rate differential between EUR and SEK. UIP Residual Plot:

Figure 4. IR differentials Residual Plot. From the UIP regression model, the IR differential Residual Plot is provided for testing whether or not the model is good fitted. According to the data from the figure, the residuals value ranging from -0.05 to 0.08, which is considered relatively low rate, represents the UIP model is highly accurate. UIP Forecasting for Q1202: Expected Time (Quarterly)

Forecast Inflation Euro Area

2020 Q4 2021 Q1

Sweden

Inflation

% change

Expected

differential

EUR/SE

Spot rate

K 0.0% 0.0% 0.0% -0.66% 0.0% 0.0% 0.0% -0.66% Table 3. The UIP model exchange rate forecast.

10.4572 10.388

Due to the booming of the COVID-19 around the world, which leads most of the European region suffering from one the worst recession in the economy. This urged the European Central Bank decisively reduce the interest rate down to 0% or lower in order to minimize the loss from the sudden

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pandemic. Also, from the data provided by Trading Economics, they predicted that the interest rate will remain 0% until 2021, causing interest rate differential of EUR and SEK will remain 0. Therefore, the change of EUR/SEK will maintain at decreasing rate at –0.66% for each quarter until the end of 2021. From the calculating, EUR/SEK is predicted to fall at the value of 10.5269, as the EUR is expected to depreciate against SEK. Macro-based Model Apart from the PPP and UIP models for forecasting the exchange rate (ER), there have been several studies on forecasting the ER using monetary fundamentals. According to Mark and Sul (2001), there is an increasing magnitude of ER return regression slope coefficients and R squared as the prediction horizon increases. Simultaneously, there is also an improvement in forecast accuracy using out-ofsample monetary fundamentals relative to the random walk under the same condition (Faust, J et al., 2002, p. 36). Based on the two statements, we have constructed a multifactor regression model using the following variables:

1) Short term Interest rate: The effect of interest rate on ER can be expressed through either Chicago view (asset market approach) and Keynesian approach (international goods market approach) (Hüseyin Şen et al., 2019). Regarding the Chicago view, under perfectly flexible prices, a change in market interest rate is primarily affected by the expected rate of inflation. If domestic interest rates were higher than the rest of the world, the increases in expected rate of inflation would also be expected by the market participants, putting pressure on the exchange rate to increase (due to the depreciation effect of inflation). On the other hand, the Keynesian view suggests that a higher interest rate would create an attractive market for capital inflows into the host country (as the returns for investment of foreigners increases), leading to an appreciation of the domestic currency through a rise in demand of the domestic currency.

2) Inflation rates: Several studies conducted by Giavazzi and Giovannini (1989), Velasco (1996), and Dornbusch (2001) have proved that in a stable exchange rate regime, not only the price is stable, but the efficiency of monetary policy is also increased. Under that condition, a country with a relatively higher inflation rate against the rest of the world is likely to suffer from external deficits, leading to a fall in its foreign exchange reserves (Hüseyin Şen et al., 2019).

3) Percentage change in oil prices:

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The connection between the oil market and currency market has long been established. Early research on the role of oil prices by Golub (1983) and Krugman (1983) revealed that when oil prices rise (fall), an oil-exporting (oil-importing) country may witness an appreciation (depreciation) in its currency (Reboredo, J. C 2011, p. 420). Furthermore, study on oil price movements’ impacts on exchange rate by Bloomberg and Harris (1995) based on the law of one price highlighted that since oil is homogenous and internationally traded in USD, a depreciation in USD reduces the oil price in foreigners’ perspective, hence increasing their purchasi ng power and oil demand, pushing up the crude oil price in USD (Reboredo, J. C 2011, p. 420).

4) Relative change in real GDP: The effect of real GDP has a different effect on the exchange rate, depending on which channel is considered (trade balance or capital flows). In terms of trade balance, if the growth rate of domestic income were faster than foreign income, the imports would also grow with a faster pace, leading to a higher demand for foreign currency (in order to make imports payment). As a result, the domestic currency will witness a depreciation. On the other hand, a faster economic growth is associated with a higher return in domestic assets. Therefore, foreign investors will seek an opportunity to invest in domestic assets, pushing up the demand for domestic currency, hence decrease the exchange rate (appreciation) (Moosa, I, A 2009, p. 106).

5) Change in money supply:

The justification for the impact of change in money supply to ER can be expressed through inflation. Theoretically, when a substantial amount of money is injected to the market, it would lead to an increase in inflation, depreciating the value of domestic currency against other foreign currencies (Sean, M et al, 2018, p. 64).

6) Current account (CA) to GDP ratio: There have been many developments since the original study about exchange rate adjustment to CA imbalances with the price-specific-flow adjustment mechanism under the gold standard by David Hume in the 18th century. In all of these models, regardless of the exchange rate regime, the real exchange rate (RER) movement is found to accompany the adjustment to current account imbalance. For example, a CA surplus following a demand shock will enable the RER to appreciate, either through nominal exchange rate appreciation or through a rise in domestic inflation, reducing competitiveness and exports while favouring imports (Gervais et al., 2015, p. 87).

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Macro-based Model construction The model is constructed based on the data in Q1/2003 to Q3/2020 (all variables are at time t-1, except percentage change in EUR/SEK exchange rate), the regression equation of change in EUR/SEK exchange rate is written as below:

EUR /SEK)t ¿ ¿ S¿ ´¿

(1)

Where:

EUR /SEK)t ¿ ¿ S¿

at time t

( ∆ % iEUR−∆ %iSEK )t −1 :relative change in short term interest rate at time t-1 ( ∆ %π EUR −∆ %π SEK )t−1 :relative change in inflation rate at time t-1 ∆ %oilpricet −1 : percentage ...