International FinancialManagement 3国际财务管理课件课件

1、Part IIExchange Rate Risk ManagementInformation on existing and anticipated economic conditions of various countries and on historical exchange rate movementsInformation on existing and anticipated cash flows in each currency at each subsidiaryMeasuring exposure to exchange rate fluctuationsForecast

2、ing exchange ratesManaging exposure to exchange rate fluctuations2Chapter 3 Forecasting Exchange Rates3Objectives This chapter stresses the value of reliable forecasts, but suggests that reliable forecasts cant always be obtained. Because no technique has been singled out as superior, various techni

3、ques are mentioned. Whatever techniques the MNC chooses, it should monitor performance over time. The specific objectives are to:4 Objectives explain how firms can benefit from forecasting exchange rates; describe the common techniques used for forecasting; explain how forecasting performance can be

4、 evaluated.5Why Firms ForecastExchange Rates MNCs need exchange rate forecasts for their: hedging decisions, short-term financing decisions, short-term investment decisions, capital budgeting decisions (long-term investment decisions), long-term financing decisions, and earnings assessment.6 Forecas

5、ting Techniques The numerous methods available for forecasting exchange rates can be categorized into four general groups: technical, fundamental, market-based,and mixed.7Technical Forecasting Technical forecasting involves the use of historical data to predict future values. It includes statistical

6、 analysis and time series models. Speculators may find the models useful for predicting day-to-day movements. However, since they typically focus on the near future and rarely provide point/range estimates, they are of limited use to MNCs.8Fundamental Forecasting Fundamental forecasting is based on

7、the fundamental relationships between economic variables and exchange rates. A forecast may arise simply from a subjective assessment of the factors that affect exchange rates. A forecast may be based on quantitative measurements ( with the aid of regression models and sensitivity analysis) too. 9Fu

8、ndamental Forecasting Example 1: Assume that the corporate objective is to forecast the percentage change in the British pound with respect to U.S. dollar during the next quarter. For simplicity, assume that the firms forecast for the British pound is dependent on only two factors that affect the po

9、unds value: 1. Inflation in the United States relative to inflation in the United Kingdom. 2. Income growth in the United States relative to income growth in the United Kingdom.10 Fundamental Forecasting * The first step is to determine how these variables have affected the percentage change in the

10、pounds value based on historical data. The regression equation can be defined as BPt =b0 + b1INFt-1 + b2INCt-1 + t Where BP is the quarterly percentage change in the British pound value INFt-1 is the previous quarterly percentage change in the inflation differential (U.S. inflation rate minus Britis

11、h inflation rate) INCt-1 is the previous quarterly percentage change in the income growth differential (U.S. Income growth minus British income growth) b0 is a constant b1 measures the sensitivity of BPt to changes in INFt-1 b2 measures the sensitivity of BPt to changes in INCt-1 t represents an err

12、or term 11Fundamental Forecasting * The second step is to generate the values of regression coefficients (b0, b1, and b2) by using the historical data of BP, INF and INC. To illustrate, assume the following values: b0 = .002 b1 = .8 b2 =1.012Fundamental Forecasting *The third step: use the coefficie

13、nts to forecast. (Assume the most recent quarterly percentage change in INFt-1 is 4 percent and INCt-1 is 2 percent.) The forecast for BPt is BPt =b0 + b1INFt-1 + b2INCt-1 = .002 + .8(4%) + 1(2%) = .2% + 3.2% + 2% = 5.4%13Fundamental Forecasting * Conclusion: given the current figures for inflation

14、rates and income growth, the pound should appreciate by 5.4 percent during the next quarter. * Note that this example is simplified to illustrate how fundamental analysis can be implemented for forecasting. A full-blown model might include more than two factors, but the application would still be si

15、milar.14Fundamental Forecasting Use of sensitivity analysis for fundamental forecasting. Example 2: Phoenix Corp. develops a regression model to forecast the percentage change in the Mexican pesos value. It believes that the real interest rate differential and the inflation differential are the only

16、 two factors that affect exchange rate movements, as shown in this regression model:15Fundamental Forecasting et = a0 + a1INTt + a2INFt-1 + t where et = percentage change in the pesos exchange rate over period t INTt = real interest rate differential over period t INFt-1= inflation differential in t

17、he previous period a0, a1, a2 = regression coefficients t = error term16Fundamental Forecasting * Assume that regression analysis has provided the following estimates for the regression coefficients: a0 = .001 a1 = -.7 a2 = .6 * To forecast the pesos percentage change over the upcoming period, INTt

18、and INFt-1 must be estimated. Assume that INFt-1 was 1 percent. However, INTt is not known at the beginning of the period and must therefore be forecasted. Assume that Phoenix Corp. has develop the following probability distribution for INTt:17Fundamental Forecasting Probability Possible Outcome 20%

19、 -3% 50% -4% 30% -5% * A separate forecast of et can be developed from each possible outcome of INTt as follows:Forecast of INT Forecast of et Probability -3% .1%+(-.7)(-3%)+.6(1%)=2.8% 20% -4% .1%+(-.7)(-4%)+.6(1%)=3.5% 50% -5% .1%+(-.7)(-5%)+.6(1%)=4.2% 30%18Fundamental Forecasting Use of PPP for

20、fundamental forecasting. Known relationships like the PPP can be used for forecasting Example 3: The U.S. inflation rate is expected to be 1 percent over the next year, while the Australian inflation rate is expected to be 6 percent. According to PPP, the Australian dollars exchange rate should chan

21、ge as follows: ef = (1 + IU.S. ) / (1 + If) -1 = 1.01 / 1.06 1 -4.7%19Fundamental Forecasting This forecast of the percentage change in the Australian dollar can be applied to its existing spot rate to forecast the future spot rate at the end of the year. If the existing spot rate of the Australian

22、dollar is $.50, the expected spot rate at the end of one year will be : E(St+1) = St (1 + ef ) = $.50 1 + (-.047) = $.476520Fundamental ForecastingNote that in reality, the inflation rates of two countries over an upcoming period are uncertain and would have to be forecasted when using PPP to foreca

23、st future exchange rate. This complicates the use of PPP to forecast future exchange rates. Even if the inflation rates were known with certainty, problems may arise for the following reasons: the timing of the impact of inflation on trade behavior is not known for sure, prices may be measured inacc

24、urately, trade barriers may disrupt the trade patterns that should emerge, and other influential factors may exist.21*Comparison of IRP, PPP, and IFE Theories The IRP theory focuses on why the forward rate differs from the spot rate and on the degree of difference that should exist. The PPP theory a

25、nd IFE theory focuses on how a currencys spot rate will change over time. PPP theory suggests that the spot rate will change in accordance with inflation differential; IFE theory suggests that it will change in accordance with interest rate differential.22Fundamental Forecasting In general, fundamen

26、tal forecasting is limited by : the uncertain timing of the impact of the factors, the need for forecasts of factors with instantaneous impact, the possibility that other relevant factors may be omitted from the model, and changes in the sensitivity of currency movements to each factor over time.23M

27、arket-Based Forecasting Market-based forecasting involves developing forecasts from market indicators. Usually, either the spot rate or the forward rate is used, since speculation should push the rates to the level that reflect the market expectation of the future exchange rate.24Market-Based Foreca

28、sting Long-term exchange rate forecasts can be derived from long-term forward rates. Since long-term forward contracts have low trading volumes and are not widely quoted, the interest rates on risk-free instruments can be used to determine what the forward rates should be according to IRP for long-t

29、erm forecasting.25Market-Based Forecasting * Example: The U.S. five-year interest rate is currently 10 percent annualized, while the British five-year interest rate is 13 percent. The five-year compounded return on investments in each of these countries is computed as follows: Country Five-year Comp

30、ounded Return U.S. (1.10) 1 = 61% U.K. (1.13) 1 = 84%5526Market-Based Forecasting Thus, the appropriate five-year forward rate premium (or discount ) of the British pound would be p = (1+ iU.S.) / (1 + iU.K.) 1 = 1.61 / 1.84 1 = -.125, or 12.5% The results suggests that the five-year forward rate of

31、 the pound should contain a 12.5 percent discount. 27Mixed Forecasting Mixed forecasting refers to the use of a combination of forecasting techniques. The actual forecast is a weighted average of the various forecasts developed.28Evaluation of Forecast Performance An MNC that forecasts exchange rate

32、s should monitor its performance over time to determine whether its forecasting procedure is satisfactory. The MNC may also want to compare the various forecasting methods.29Evaluation of Forecast Performance One measure of forecast performance is the absolute forecast error as a percentage of the r

33、ealized value: | forecasted value realized value | realized value Over time, MNCs are likely to have more confidence in their forecasts when they know the mean error for their past forecasts.30Evaluation of Forecast Performance The ability to forecast currency values may vary with the currency of co

34、ncern. In particular, the value of a less volatile currency is likely to be forecasted more accurately.31Forecast Bias If the forecast errors are consistently positive or negative over time, then there is a bias in the forecasting procedure.32Forecast Bias The following regression model can be used

35、to test for forecast bias: realized = a0 + a1 forecast + m m Where a0 = intercept a1 = regression coefficient m = = error term33Forecast Bias*If the predictor is unbiased, the intercept should equal zero, and the regression coefficient should equal 1.0.*If a0 = 0 and a1 is significantly less than 1.

36、0, this implies the predictor is systematically overestimating the spot rate, for example, if a0 = 0 and a1 = .90, the realized value is estimated to be 90 percent of the forecasted value. Vice versa.*If a predictor is found to be biased, the estimated a0 and a1 values can be used to correct the sys

37、tematic error.34Graphic Evaluationof Forecast Performance Forecast performance can be examined with the use of a graph that compares forecasted values with the realized values for various time periods.35Graphic Evaluationof Forecast PerformanceRegion of upward bias (overestimating) Region of downwar

38、d bias (underestimating)Perfect forecast line$.10 $.12 $.14 $.16 $.18 $.20 $.22 $.24 $.26 $.28 $.30$.28$.26$.24$.22$.20$.18$.16$.14$.12$.10Predicted Value (in U.S. dollars)Realized Value (in U.S. dollars) . . . . . .36Graphic Evaluationof Forecast Performance If the points appear to be scattered eve

39、nly on both sides of the perfect forecast line, then the forecasts are said to be unbiased. Note that a more thorough assessment can be conducted by separating the entire period into subperiods.37Comparison ofForecasting Techniques The different forecasting techniques can be evaluated graphically -

40、by comparing the distances from the perfect forecast line, or statistically - by computing the mean of the absolute forecast errors, and then using a t-test or a nonparametric test to determine whether there is a significant difference in the accuracy of the forecasting techniques. 38Exchange Rate V

41、olatility MNCs also forecast exchange rate volatility. This enables them to specify a range (confidence interval) and develop best-case and worst-case scenarios along with their point estimate forecasts. Popular methods for forecasting volatility include:the use of recent exchange rate volatility,39

42、Exchange Rate Volatilitythe use of a historical time series of volatilities (there may be a pattern in how the exchange rate volatility changes over time), andthe derivation of the exchange rates implied standard deviation from the currency option pricing model.40Questions and Applications *1.You ar

43、e hired as a consultant to assess a firms ability to forecast. The firm has developed a point forecast for two different currencies, presented in the table below. The firm asks you to determine which currency was forecasted with greater accuracy. Period Yen Forecast Actual Yen Value Pound Forecast A

44、ctual Pound Value 1 $.0050 $.0051 $1.50 $1.51 2 .0048 .0052 1.53 1.50 3 .0053 .0052 1.55 1.58 4 .0055 .0056 1.49 1.5241Questions and Applications*2. Assume that the four-year annualized interest rate in the United States is 9 percent and the four-year annualized Interest rate in Singapore is 6 perce

45、nt. Assume interest rate parity holds for a four-year horizon. Assume that the spot rate of the Singapore dollar is $.60. If the forward rate is used to forecast exchange rates, what will be the forecast for the Singapore dollars spot rate in four years? What percentage appreciation or depreciation

46、does this forecast imply over the four-year period?42Questions and Applications 3. If the euro appreciates substantially against the dollar during a specific period, would market-based forecasts have overestimated or underestimated the realized values over this period? Explain. 43Questions and Applications 4