Week 4 Homework Assignment This assignment is due by 6 p.m. eastern time on Sunday, September 17.When
Question:
Week 4 Homework Assignment
This assignment is due by 6 p.m. eastern time on Sunday, September 17.When you turn it in, please:
(1) Include your team number and assignment number in the filename(s).
(2) List all team members in the file.
(3) Remember to send me a separate email with feedback on the contribution of the members of your team (see syllabus).
Problem 1
Open the Excel file called "interest rates from 1982 to 2017" which contains annualized yields on zero-coupon bond of various maturities (3 and 6 months, 1, 2, 3, 5, and 10 years) over the last 35 years.
a.Calculate the mean and standard deviation for each column of data (i.e., each type of bond) and compare these statistics across different types of bonds.What is the relation between the average yield and maturity? What is the relation between the volatility of yields and maturity? Is this the pattern you would expect to observe?Why or why not?
b. The real purpose of working with these numbers is to test the expectations hypothesis of the term structure of interest rates.Remember that this hypothesis says that forward rates are unbiased predictors of future spot rates.
Clearly if you are testing whether forward rates predict future spot rates, you have to begin by taking the data you have and calculate the forward rates implied by the spot rates at any moment in time.You have monthly yields on 7 different securities, and from those there are many different forward rates you could compute.For example, in January, 1982, the three-month and six-month spot rates were 12.92% and 13.90% respectively. From these two numbers we could calculated the forward rate on a three-month bond three months into the future. To do that, remember that we want to find the return on the 3-month bond, 3 months from now, that would make an investor indifferent between holding the 6-month bond that pays 13.90% and a sequence of two, 3-month bonds. Since these are annual rates, but we are looking at investments with maturities as short as 3 months, we use quarterly compounding like this:
(1+0.1390/4)2 = (1+0.1292/4)(1+f/4)
Here "f" stands for the annualized three-month forward rate three months from now. The term on the left means you earn (13.90/4)% for two quarters if you buy the 6-month bond.On the right, you can (12.92%/4) for one quarter, and then you earn (f/4)% for one quarter.If my algebra is correct, I find that f = 14.88%.Now, to test the expectations hypothesis, I would want to compare this number to the interest rate that it is supposed to predict, which is the three-month spot rate in April 1982.
Forward rate - spot rate = forecast error
14.88 - 13.34 = 1.54
So for this particular month, the forward rate predicted a higher spot rate than what actually prevailed in the market three months later.To conduct a general test of the expectations hypothesis, I want to repeat this comparison every three months (do not use overlapping periods) throughout my sample period.My next step then would be to use data in April 1982 to calculate the three-month forward rate three months ahead, then compare that forward rate to the spot rate in July 1982 to get the forecast error for that period.Just repeat this process until you've gone all the way through the data.Once your calculations are complete, you could ask questions like:
(1) Is the three-month forward rate an unbiased predictor of the three-month spot rate three months into the future (remember, an unbiased predictor is one that has a zero forecast error on average)?If not, what is the size and direction of the bias, and what does that imply about different theories of the yield curve?
(2) How much volatility is there in the forecast error (remember, a biased forecast can be quite useful if the bias is predictable)?
(3) If you run a regression in which the Y (dependent) variable is the three-month spot rate at a particular time and the X (independent) variable is the three-month forward rate calculated three months earlier, what do the regression results tell you?
Y = a + bX
Spot rate at time (t) = a + b(forward rate three months earlier)
What value do you expect for "a" and "b" if the expectations hypothesis is true?What values for "a" and "b" do you expect if the forecast error is biased (remember, the bias could be positive or negative)?What does the regression R-square value tell you?
(4) Investors in bonds are particularly interested in changes in interest rates.Go back to my original example in which I calculated the three-month forward rate starting in January 1982.That rate was 14.88%.Given that the three-month spot rate in January 1982 was 12.92%, the forward rate was predicting an interest rate increase of 1.96%.Three months later, the three-month spot rate was 13.34%, so the actual change in interest rates was an increase of 0.42% (three-month rates went up from 12.92% to 13.34%).Now think about running your regression again, except this time let Y be the actual change in the three-month spot rate over some period (so + 0.42% in my example) and let X be the predicted change (from forward rates) from three months ago (+1.96% in my example).
Y = a + bX
Actual change in spot rate = a + b(forecasted change in spot rates)
Again, if the expectations hypothesis is true what values do you expect for a and b in this regression?How does the R-square value compare here to the previous regression?
In all of the analysis above, I've started with the example of using current three-month and six-month spot rates to calculate a three-month forward rate and compare that to a subsequent three-month spot rate.You can and should do the same kind of analysis with different forward rates.For example, you could (A) use the current one-year and two-year spot rates to calculate a one-year forward rate one year ahead and compare that to the one-year spot rate one year into the future. You could (B) use the current two-year and three-year spot rates to calculate a one-year forward rate two years into the future and compare that to the one-year spot rate that arises two years later.So if you do both (A) and (B) above, you are testing the ability of current interest rates to predict one-year bond rates one year ahead and two years ahead.Similarly, if you compare your analysis in (A) to the analysis of the three-month spot rate, you can get a sense of whether the predictability of short-term rates is different from the predictability of longer term rates.
The point is I want you to do some broad analysis of the expectations hypothesis using different forward rates to predict different spot rates at different horizons. Then write few paragraphs characterizing what you find.
Economists often refer to the term "random walk."There are two main implications when some economic variable like stock prices, exchange rates, or interest rates follows a random walk.The first is that the future is basically unpredictable...random.The second is that if you must guess what the future value of some quantity will be, the most reasonable forecast is the current value.For example, if the US dollar follows a random walk relative to other currencies, then my best guess for the exchange rate between dollars and euros one year in the future is just today's exchange rate.When evaluating the quality of your interest rate forecasts based upon forward rates, try to assess whether forward rates provide a forecasting tool that is superior to simple random walk estimates.Remember, "superior" in forecasting has several dimensions including unbiasedness and reliability.Think about different ways you could measure reliability.
Problem 2
The figure below lists the price, maturity (in years), and coupon rate (stated in annual terms) for several bonds, all of which pay interest semiannually.
Bond Price
Maturity
Coupon Rt.
1007.78
1
5.000%
1036.87
1
8.000%
1046.57
1
9.000%
1048.58
2
7.250%
1065.15
2
8.125%
1119.60
2
11.000%
1136.35
3
10.000%
1122.52
3
9.500%
1246.97
3
14.000%
1046.86
4
6.750%
1208.16
4
11.250%
1308.81
5
13.000%
972.15
5
5.250%
1086.61
6
7.875%
992.00
6
6.000%
1352.84
7
12.500%
1003.08
7
6.375%
Use regression analysis to estimate the term structure.Your deliverable is a series of spot interest rates at 6-month intervals going out 7 years.State each spot rate as an annual rate.Also calculate the YTM for each bond and compare that to the spot rate for the year in which the bond matures.
Let me give you some significant hints about how to set up and interpret the regression.In regression analysis, we usually write equations like this:
Y = a + B1X1 + B2X2 + B3X3 + ....
Here, X1, X2, and X3 are variables that influence Y, and B1, and B2, and B3 are coefficients that measure the extent to which the variables affect Y.In the present context, Y is the price of a bond.We want to know what determines bond prices.That's easy, it's just cash flows and discount rates, and it is the discount rates, the spot rates, which we are after here.
Set up a spreadsheet where each bond is a separate row.The first column is the bond's price.The second column is the cash payment that the bond makes in 6 months.The 3rd column is the cash payment that the bond makes in 12 months.The 4th column is the cash payment that the bond makes in 18 months, and so on.You keep adding data to columns until you have gone far enough out to capture all 14 payments that a 7-year bond would make.Note, after a bond matures, you enter a zero for all payment dates after maturity.For example, the first row of the spreadsheet would look like this:
1007.78251025000000000000
Now, use Data Analysis in Excel or some other method to run a multiple linear regression.Price is the Y variable and cash flows in each of the 14 payment periods are the X variables.That is, there are 14 explanatory variables here, and you will get 14 Beta coefficients.Each coefficient is telling you how much an additional dollar of cash flow at a given time period adds to the price of the bond.Notice, I did not say that there should be an intercept term in this regression.There should not be (i.e., no little "a" as in the regression equation above).You have to instruct Excel or whatever statistical software you are using to force the intercept through zero.Why are we doing this?
Once you have the beta coefficients, you'll have to use them to "back out" what the spot rates are at each point on the yield curve.You'll have to derive the spot rates algebraically.By convention, let's all assume the usual semi-annual compounding for bonds where the denominator of the bond pricing equation would look like (1 + r/2)^t.
Problem 3
Suppose the expectations hypothesis is true and you have the following series of spot rates.
1-year1.25%2-year1.75%3-year 2.25%4-year 2.75%
a.Calculate the price of a bond that has a $1,000 par value, pays a $30 coupon once a year, and matures in four years.You can assume the first coupon is one year away.
b. Assuming the expectations hypothesis is true, what is the expected price of this bond in one year just after it makes its first coupon payment?
c.If you buy the bond today and sell it in one year (just after getting the first coupon payment), what is your expected rate of return.
d.You buy the bond today and hold it to maturity.After you receive a coupon payment, you reinvest it in a zero-coupon bond maturing at the same time (4 years from now) as the coupon-paying bond.How much total cash do you expect to have after 4 years?Given that estimate, what compound annual rate of return do you earn over the 4 years?
e.Go back to the beginning of this problem (use the spot rates given), and assume that investors require a liquidity premium of 0.25% per year to invest in an N-year bond instead of a bond maturing in year N-1.For example, investors want to earn 0.25% more per year if they invest in a two-year bond than they expect to earn if they buy a one-year bond and then roll that over into another one-year bond.Does your answer to part (a) change?Why or why not?If you are now asked to predict the bond's price in one year, is your answer different than in part (b)?Note that I am not asking you to derive a price.Just tell me if it would be different or not and explain why.If you think it would be different, would be the price be higher or lower than your answer to part (b)?
f.Considering the information given in part (e), what is the expected interest rate on a one-year bond one year from today?
Problem 4
The current 1-year spot rate is 3%, and 1f1 is 3.5%.Investors require a liquidity premium on short-term bonds such that the expected annual return on a 2-year bond is 0.25% per year lower than the expected return on a series of two, 1-year bonds.What is the current market price of a 2-year bond that pays a 4% coupon rate (annual payments) and what is the expected price of this bond one year from today? If you buy the bond today, hold it for one year, collect its first coupon payment, then immediately resell it at the expected selling price, what is your expected return?
Problem 5
Calculate the duration, in years, of a bond that matures in 5 years, pays $60 in interest twice a year (e.g., 12% coupon rate), and sells for $997.55.Explain how you can use duration (or modified duration) to estimate the change in the price of a bond when the yield to maturity changes.Estimate how much the price of this bond will change if rates go up one percentage point, and then calculate an exact price assuming a one percentage point jump in the YTM.Why doesn't the duration approach give you an exact answer.
Problem 6
A bond sells at par and pays an annual coupon of 5% (assume annual payments).Calculate the duration of this bond at various maturities including 1, 2, 3, 4, 5, 10, 20, 50, and 100 years.Plot a graph showing how the duration changes as maturity changes.Explain why the graph is shaped the way it is.Be careful to draw to scale.
Problem 7
Your firm is obligated to make payments to a supplier according to the following schedule:
Year 1$1 million
Year 2$1.5 million
Year 3$10 million
You want to immunize this liability investing in some combination of a 2-year bond with a 10% coupon and a 4-year bond with a 12% coupon.You can assume these bonds pay interest annually, and have a par value of $1,000.Use a discount rate / YTM of 6% throughout this problem.How many (in terms of numbers of bonds) of each type of bond do you need to purchase to immunize your liability?
SUMMARY OUTPUT Regression Statistics Multiple R 0.977135 R Square 0.954793 Adjusted R 0.954442 Standard Er0.006515 Observatio 131 ANOVA df Regression Residual Total SS MS F Significance F 1 0.11566 0.11566 2724.525 1.31E-088 129 0.005476 4.25E-005 130 0.121136 Coefficients Standard Error t Stat P-value Lower 95%Upper 95% Lower 95.0% Upper 95.0% Intercept 0.000342 0.000993 0.344061 0.731361 -0.001623 0.002306 -0.001623 0.002306 X Variable 0.890494 0.01706 52.19699 1.31E-088 0.85674 0.924248 0.85674 0.924248 0.03592 fwd 0 0.02 0.03 0.03 0.03 0.04 0.04 0.04 0.05 0.06 0.06 0.06 0.07 0.07 0.08 0.1 0.1 0.13 0.13 0.15 0.16 0.16 0.16 0.18 0.69 0.9 0.92 0.94 0.96 1.15 1.19 1.31 1.36 1.61 1.66 1.68 1.71 1.75 1.79 2.2 2.37 2.82 2.84 2.93 2.93 3.04 3.07 3.09 3.11 3.28 3.29 3.59 3.78 3.79 3.84 3.91 3.97 4 4.07 4.34 0.0009 0.0012 0.0008 0.001 0.0007 0.0018 0.0012 0.0011 0.001 0.0025 0.0021 0.0015 0.0038 0.002 0.0011 0.002 0.002 0.017707 0.0024 0.0023 0.004701 0.0024 0.0032 0.005401 0.023003 0.011 0.0119 0.0102 0.0108 0.0125 0.0157 0.0286 0.012601 0.0177 0.018502 0.0214 0.022101 0.0186 0.020403 0.0353 0.023102 0.043201 0.029902 0.0348 0.034101 0.0335 0.033301 0.034101 0.0319 0.041601 0.034402 0.0401 0.034601 0.037701 0.0411 0.0538 0.0501 0.0512 0.0537 0.044703 spot Y 0 0.0002 0.0003 0.0003 0.0003 0.0004 0.0004 0.0004 0.0005 0.0006 0.0006 0.0006 0.0007 0.0007 0.0008 0.001 0.001 0.0013 0.0013 0.0015 0.0016 0.0016 0.0016 0.0018 0.0069 0.009 0.0092 0.0094 0.0096 0.0115 0.0119 0.0131 0.0136 0.0161 0.0166 0.0168 0.0171 0.0175 0.0179 0.022 0.0237 0.0282 0.0284 0.0293 0.0293 0.0304 0.0307 0.0309 0.0311 0.0328 0.0329 0.0359 0.0378 0.0379 0.0384 0.0391 0.0397 0.04 0.0407 0.0434 X 4.41 4.45 4.46 4.69 4.72 4.96 5.01 5.02 5.05 5.08 5.08 5.09 5.09 5.1 5.11 5.11 5.12 5.14 5.15 5.17 5.18 5.19 5.29 5.3 5.3 5.32 5.44 5.5 5.58 5.59 5.75 5.82 5.82 5.83 5.84 5.88 5.9 6 6 6.08 6.14 6.24 6.29 6.35 6.41 6.95 7.3 7.32 7.4 7.4 7.6 7.87 7.9 7.9 7.97 8.02 8.04 8.12 8.15 8.22 8.51 0.0453 0.0433 0.047205 0.0467 0.046 0.0513 0.0519 0.0481 0.054601 0.0528 0.050801 0.0511 0.054401 0.054406 0.0547 0.0519 0.057401 0.061901 0.0568 0.055201 0.054901 0.059002 0.0635 0.054501 0.0545 0.0624 0.0565 0.053801 0.056401 0.062601 0.061301 0.0576 0.060202 0.067501 0.071209 0.065603 0.061407 0.0648 0.077312 0.071208 0.063202 0.077601 0.064 0.062201 0.0766 0.069204 0.080202 0.092006 0.078202 0.0797 0.077504 0.085001 0.0787 0.0816 0.137421 0.109204 0.0802 0.092911 0.093801 0.088805 0.085401 0.0441 0.0445 0.0446 0.0469 0.0472 0.0496 0.0501 0.0502 0.0505 0.0508 0.0508 0.0509 0.0509 0.051 0.0511 0.0511 0.0512 0.0514 0.0515 0.0517 0.0518 0.0519 0.0529 0.053 0.053 0.0532 0.0544 0.055 0.0558 0.0559 0.0575 0.0582 0.0582 0.0583 0.0584 0.0588 0.059 0.06 0.06 0.0608 0.0614 0.0624 0.0629 0.0635 0.0641 0.0695 0.073 0.0732 0.074 0.074 0.076 0.0787 0.079 0.079 0.0797 0.0802 0.0804 0.0812 0.0815 0.0822 0.0851 8.56 8.96 8.99 9.26 9.45 10.07 10.12 10.53 11.86 13.34 0.082002 0.091402 0.102504 0.097904 0.090502 0.098602 0.120113 0.108704 0.144007 0.148823 0.0856 0.0896 0.0899 0.0926 0.0945 0.1007 0.1012 0.1053 0.1186 0.1334 SUMMARY OUTPUT Regression Statistics Multiple R 0.052513 R Square 0.002758 Adjusted R -0.009404 Standard Er0.007154 Observatio 84 ANOVA df Regression Residual Total SS MS 1 1.16E-005 1.16E-005 82 0.004197 5.12E-005 83 0.004209 F Significance F 0.22675 0.63521 Coefficients Standard Error t Stat P-value Lower 95%Upper 95% Lower 95.0% Upper 95.0% Intercept -0.00098 0.001173 -0.835573 0.405823 -0.003312 0.001353 -0.003312 0.001353 X Variable -0.088156 0.185131 -0.476183 0.63521 -0.45644 0.280128 -0.45644 0.280128 0.019623 0.010607 0.018821 0.013211 0.004201 0.005402 0.008004 0.008004 0.006002 0.008004 0.014813 0.008004 0.008605 0.009806 0.005002 0.006202 0.004601 0.0024 0.0024 0.003201 0.0018 0.007403 0.003401 0.013812 0.011208 0.008404 0.008004 0.006002 0.005802 0.004201 -0.0028 0.0026 0.0012 0.004601 0.001 0.0026 0.003401 0.003001 0.004401 0.0024 0.002 0.003201 0.002 0.004001 0.003401 0.0026 0.003001 0.0026 0.004201 0.009405 0.009806 0.010407 0.012209 0.004201 0.0006 0.0024 -0.0004 0.003601 0.004401 0.0042 -0.0148 -0.0389 0.0015 0.0039 0.0094 -0.0046 0.0027 0.0081 0.0046 -0.0041 -0.021 0.002 -0.009 0.0008 -0.001 -0.0106 -0.0024 -0.0068 0.0026 0.0024 0.0006 0.0047 -0.0035 0.0008 0.0087 0.0065 0.0096 0.004 -0.0081 -0.0025 0 0.0014 -0.0017 -0.0047 -0.0099 -0.0058 -0.0008 -0.0061 -0.0123 -0.0007 -0.0056 -0.0035 0.0014 -0.0014 0.0018 -0.0002 -0.0005 0.0074 0.0068 0.0064 0.008 -0.0006 -0.0025 -0.0015 -0.0029 -0.0006 0.0021 -0.0018 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 -0.052513 0.004001 0.0028 0.006002 0.0028 0.003801 0.001 0.003601 0.0028 0.0026 0.0008 0.0026 0.0012 0.003601 0.005202 0.005002 0.0026 0.0006 -0.0028 0.0004 -0.0006 -0.0006 0.0018 0.004601 0.0006 -0.0004 0.0005 0.0013 -0.0011 -0.0008 0.0007 -0.001 0.0001 -0.0102 0.0038 -0.0004 0.0028 0.0033 0.0048 0.0032 0.0032 0.0015 -0.01 -0.0132 -0.0038 -0.0139 -0.0052 0.0007 -0.0004 -0.001 -0.0042 0.0004 0.001 0.0016 0.0018 0.003001 0.006803 0.005202 0.006202 0.006002 0.004801 0.006803 0.0026 0.003601 0.003801 0.0014 0.0008 0.0012 0.0016 0.003201 0.0004 0.005402 0.006403 0.010807 0.003401 0.003801 0.002 0.0018 0.0018 0.0016 0.0008 0.001 0.0006 0.0012 0.0008 0.0006 -0.0023 0.0002 -0.0004 0.0006 0.004 0.0043 0.0058 0.0047 0.0045 0.005 0.0055 0.0038 0.0036 -0.0003 0.0006 -0.001 -0.0005 -0.0096 -0.0118 -0.0151 0.0035 -0.0097 -0.0056 0.0003 0.0002 -0.0011 -0.0001 0.001 0 -0.0003 0.0002 -0.0009 -0.0002 -0.0002 0.0001 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 0.0008 0.0012 0.001 0.001 0.0008 0.0006 0.0006 0.0006 0.0006 0.0004 0.0005 0.0002 0 -0.0003 -0.0001 -0.0002 0.0001 -0.0001 -0.0001 0 121 122 123 124 125 126 127 128 129 130 0.0006 -0.0003 Three Six One Two Three Five Ten Month Month Year Year Year Year Year DATE Spot Spot Spot Spot Spot Spot Spot 1982-01-01 12.92 13.90 14.32 14.57 14.64 14.65 14.59 1982-02-01 14.28 14.81 14.73 14.82 14.73 14.54 14.43 1982-03-01 13.31 13.83 13.95 14.19 14.13 13.98 13.86 1982-04-01 13.34 13.87 13.98 14.20 14.18 14.00 13.87 1982-05-01 12.71 13.13 13.34 13.78 13.77 13.75 13.62 1982-06-01 13.08 13.76 14.07 14.47 14.48 14.43 14.30 1982-07-01 11.86 12.80 13.24 13.80 14.00 14.07 13.95 1982-08-01 9.00 10.51 11.43 12.32 12.62 13.00 13.06 1982-09-01 8.19 9.83 10.85 11.78 12.03 12.25 12.34 1982-10-01 7.97 8.63 9.32 10.19 10.62 10.80 10.91 1982-11-01 8.35 8.80 9.16 9.80 9.98 10.38 10.55 1982-12-01 8.20 8.59 8.91 9.66 9.88 10.22 10.54 1983-01-01 8.12 8.33 8.62 9.33 9.64 10.03 10.46 1983-02-01 8.39 8.65 8.92 9.64 9.91 10.26 10.72 1983-03-01 8.66 8.86 9.04 9.66 9.84 10.08 10.51 1983-04-01 8.51 8.78 8.98 9.57 9.76 10.02 10.40 1983-05-01 8.50 8.70 8.90 9.49 9.66 10.03 10.38 1983-06-01 9.14 9.44 9.66 10.18 10.32 10.63 10.85 1983-07-01 9.45 9.85 10.20 10.69 10.90 11.21 11.38 1983-08-01 9.74 10.16 10.53 11.07 11.30 11.63 11.85 1983-09-01 9.36 9.73 10.16 10.79 11.07 11.43 11.65 1983-10-01 8.99 9.39 9.81 10.57 10.87 11.28 11.54 1983-11-01 9.11 9.48 9.94 10.66 10.96 11.41 11.69 1983-12-01 9.36 9.76 10.11 10.84 11.13 11.54 11.83 1984-01-01 9.26 9.56 9.90 10.64 10.93 11.37 11.67 1984-02-01 9.46 9.77 10.04 10.79 11.05 11.54 11.84 1984-03-01 9.89 10.27 10.59 11.31 11.59 12.02 12.32 1984-04-01 10.07 10.47 10.90 11.69 11.98 12.37 12.63 1984-05-01 10.22 11.02 11.66 12.47 12.75 13.17 13.41 1984-06-01 10.26 11.24 12.08 12.91 13.18 13.48 13.56 1984-07-01 10.53 11.27 12.03 12.88 13.08 13.27 13.36 1984-08-01 10.90 11.37 11.82 12.43 12.50 12.68 12.72 1984-09-01 10.80 11.19 11.58 12.20 12.34 12.53 12.52 1984-10-01 10.12 10.52 10.90 11.60 11.85 12.06 12.16 1984-11-01 8.92 9.34 9.82 10.65 10.90 11.33 11.57 1984-12-01 8.34 8.76 9.33 10.18 10.56 11.07 11.50 1985-01-01 8.02 8.45 9.02 9.93 10.43 10.93 11.38 1985-02-01 8.56 8.87 9.29 10.17 10.55 11.13 11.51 1985-03-01 8.83 9.45 9.86 10.71 11.05 11.52 11.86 1985-04-01 8.22 8.71 9.14 10.09 10.49 11.01 11.43 1985-05-01 7.73 8.07 8.46 9.39 9.75 10.34 10.85 1985-06-01 7.18 7.46 7.80 8.69 9.05 9.60 10.16 1985-07-01 7.32 7.57 7.86 8.77 9.18 9.70 10.31 1985-08-01 7.37 7.71 8.05 8.94 9.31 9.81 10.33 1985-09-01 7.33 7.64 8.07 8.98 9.37 9.81 10.37 1985-10-01 7.40 7.71 8.01 8.86 9.25 9.69 10.24 1985-11-01 7.48 7.68 7.88 8.58 8.88 9.28 9.78 1985-12-01 7.33 7.50 7.67 8.15 8.40 8.73 9.26 1986-01-01 7.30 7.53 7.73 8.14 8.41 8.68 9.19 1986-02-01 7.29 7.47 7.61 7.97 8.10 8.34 8.70 1986-03-01 6.76 6.89 7.03 7.21 7.30 7.46 7.78 1986-04-01 1986-05-01 1986-06-01 1986-07-01 1986-08-01 1986-09-01 1986-10-01 1986-11-01 1986-12-01 1987-01-01 1987-02-01 1987-03-01 1987-04-01 1987-05-01 1987-06-01 1987-07-01 1987-08-01 1987-09-01 1987-10-01 1987-11-01 1987-12-01 1988-01-01 1988-02-01 1988-03-01 1988-04-01 1988-05-01 1988-06-01 1988-07-01 1988-08-01 1988-09-01 1988-10-01 1988-11-01 1988-12-01 1989-01-01 1989-02-01 1989-03-01 1989-04-01 1989-05-01 1989-06-01 1989-07-01 1989-08-01 1989-09-01 1989-10-01 1989-11-01 1989-12-01 1990-01-01 1990-02-01 1990-03-01 1990-04-01 1990-05-01 1990-06-01 1990-07-01 1990-08-01 1990-09-01 6.24 6.33 6.40 6.00 5.69 5.35 5.32 5.50 5.68 5.58 5.75 5.77 5.82 5.85 5.85 5.88 6.23 6.62 6.35 5.89 5.96 6.00 5.84 5.87 6.08 6.45 6.66 6.95 7.30 7.48 7.60 8.03 8.35 8.56 8.84 9.14 8.96 8.74 8.43 8.15 8.17 8.01 7.90 7.94 7.88 7.90 8.00 8.17 8.04 8.01 7.99 7.87 7.69 7.60 6.36 6.47 6.56 6.12 5.79 5.57 5.48 5.64 5.78 5.67 5.83 5.86 6.19 6.35 6.28 6.05 6.46 6.99 7.04 6.50 6.68 6.56 6.21 6.18 6.50 6.89 7.04 7.35 7.79 7.82 7.90 8.30 8.70 8.85 9.05 9.39 9.17 8.91 8.38 8.01 8.17 8.16 8.03 7.89 7.81 7.96 8.12 8.28 8.27 8.19 8.05 7.92 7.77 7.70 6.44 6.65 6.73 6.27 5.93 5.77 5.72 5.80 5.87 5.78 5.96 6.03 6.50 7.00 6.80 6.68 7.03 7.67 7.59 6.96 7.17 6.99 6.64 6.71 7.01 7.40 7.49 7.75 8.17 8.09 8.11 8.48 8.99 9.05 9.25 9.57 9.36 8.98 8.44 7.89 8.18 8.22 7.99 7.77 7.72 7.92 8.11 8.35 8.40 8.32 8.10 7.94 7.78 7.76 6.70 7.07 7.18 6.67 6.33 6.35 6.28 6.28 6.27 6.23 6.40 6.42 7.02 7.76 7.57 7.44 7.75 8.34 8.40 7.69 7.86 7.63 7.18 7.27 7.59 8.00 8.03 8.28 8.63 8.46 8.35 8.67 9.09 9.18 9.37 9.68 9.45 9.02 8.41 7.82 8.14 8.28 7.98 7.80 7.78 8.09 8.37 8.63 8.72 8.64 8.35 8.16 8.06 8.08 6.86 7.27 7.41 6.86 6.49 6.62 6.56 6.46 6.43 6.41 6.56 6.58 7.32 8.02 7.82 7.74 8.03 8.67 8.75 7.99 8.13 7.87 7.38 7.50 7.83 8.24 8.22 8.44 8.77 8.57 8.43 8.72 9.11 9.20 9.32 9.61 9.40 8.98 8.37 7.83 8.13 8.26 8.02 7.80 7.77 8.13 8.39 8.63 8.78 8.69 8.40 8.26 8.22 8.27 7.05 7.52 7.64 7.06 6.80 6.92 6.83 6.76 6.67 6.64 6.79 6.79 7.57 8.26 8.02 8.01 8.32 8.94 9.08 8.35 8.45 8.18 7.71 7.83 8.19 8.58 8.49 8.66 8.94 8.69 8.51 8.79 9.09 9.15 9.27 9.51 9.30 8.91 8.29 7.83 8.09 8.17 7.97 7.81 7.75 8.12 8.42 8.60 8.77 8.74 8.43 8.33 8.44 8.51 7.30 7.71 7.80 7.30 7.17 7.45 7.43 7.25 7.11 7.08 7.25 7.25 8.02 8.61 8.40 8.45 8.76 9.42 9.52 8.86 8.99 8.67 8.21 8.37 8.72 9.09 8.92 9.06 9.26 8.98 8.80 8.96 9.11 9.09 9.17 9.36 9.18 8.86 8.28 8.02 8.11 8.19 8.01 7.87 7.84 8.21 8.47 8.59 8.79 8.76 8.48 8.47 8.75 8.89 1990-10-01 1990-11-01 1990-12-01 1991-01-01 1991-02-01 1991-03-01 1991-04-01 1991-05-01 1991-06-01 1991-07-01 1991-08-01 1991-09-01 1991-10-01 1991-11-01 1991-12-01 1992-01-01 1992-02-01 1992-03-01 1992-04-01 1992-05-01 1992-06-01 1992-07-01 1992-08-01 1992-09-01 1992-10-01 1992-11-01 1992-12-01 1993-01-01 1993-02-01 1993-03-01 1993-04-01 1993-05-01 1993-06-01 1993-07-01 1993-08-01 1993-09-01 1993-10-01 1993-11-01 1993-12-01 1994-01-01 1994-02-01 1994-03-01 1994-04-01 1994-05-01 1994-06-01 1994-07-01 1994-08-01 1994-09-01 1994-10-01 1994-11-01 1994-12-01 1995-01-01 1995-02-01 1995-03-01 7.40 7.29 6.95 6.41 6.12 6.09 5.83 5.63 5.75 5.75 5.50 5.37 5.14 4.69 4.18 3.91 3.95 4.14 3.84 3.72 3.75 3.28 3.20 2.97 2.93 3.21 3.29 3.07 2.99 3.01 2.93 3.03 3.14 3.11 3.09 3.01 3.09 3.18 3.13 3.04 3.33 3.59 3.78 4.27 4.25 4.46 4.61 4.75 5.10 5.45 5.76 5.90 5.94 5.91 7.53 7.39 7.03 6.58 6.19 6.20 5.98 5.87 6.02 5.97 5.63 5.48 5.26 4.80 4.26 4.01 4.08 4.33 4.00 3.88 3.90 3.38 3.31 3.04 3.13 3.44 3.47 3.24 3.16 3.15 3.06 3.17 3.29 3.26 3.24 3.15 3.22 3.36 3.34 3.25 3.53 3.92 4.25 4.79 4.72 4.95 5.08 5.24 5.62 5.98 6.50 6.51 6.31 6.17 7.55 7.31 7.05 6.64 6.27 6.40 6.24 6.13 6.36 6.31 5.78 5.57 5.33 4.89 4.38 4.15 4.29 4.63 4.30 4.19 4.17 3.60 3.47 3.18 3.30 3.68 3.71 3.50 3.39 3.33 3.24 3.36 3.54 3.47 3.44 3.36 3.39 3.58 3.61 3.54 3.87 4.32 4.82 5.31 5.27 5.48 5.56 5.76 6.11 6.54 7.14 7.05 6.70 6.43 7.88 7.60 7.31 7.13 6.87 7.10 6.95 6.78 6.96 6.92 6.43 6.18 5.91 5.56 5.03 4.96 5.21 5.69 5.34 5.23 5.05 4.36 4.19 3.89 4.08 4.58 4.67 4.39 4.10 3.95 3.84 3.98 4.16 4.07 4.00 3.85 3.87 4.16 4.21 4.14 4.47 5.00 5.55 5.97 5.93 6.13 6.18 6.39 6.73 7.15 7.59 7.51 7.11 6.78 8.07 7.74 7.47 7.38 7.08 7.35 7.23 7.12 7.39 7.38 6.80 6.50 6.23 5.90 5.39 5.40 5.72 6.18 5.93 5.81 5.60 4.91 4.72 4.42 4.64 5.14 5.21 4.93 4.58 4.40 4.30 4.40 4.53 4.43 4.36 4.17 4.18 4.50 4.54 4.48 4.83 5.40 5.99 6.34 6.27 6.48 6.50 6.69 7.04 7.44 7.71 7.66 7.25 6.89 8.33 8.02 7.73 7.70 7.47 7.77 7.70 7.70 7.94 7.91 7.43 7.14 6.87 6.62 6.19 6.24 6.58 6.95 6.78 6.69 6.48 5.84 5.60 5.38 5.60 6.04 6.08 5.83 5.43 5.19 5.13 5.20 5.22 5.09 5.03 4.73 4.71 5.06 5.15 5.09 5.40 5.94 6.52 6.78 6.70 6.91 6.88 7.08 7.40 7.72 7.78 7.76 7.37 7.05 8.72 8.39 8.08 8.09 7.85 8.11 8.04 8.07 8.28 8.27 7.90 7.65 7.53 7.42 7.09 7.03 7.34 7.54 7.48 7.39 7.26 6.84 6.59 6.42 6.59 6.87 6.77 6.60 6.26 5.98 5.97 6.04 5.96 5.81 5.68 5.36 5.33 5.72 5.77 5.75 5.97 6.48 6.97 7.18 7.10 7.30 7.24 7.46 7.74 7.96 7.81 7.78 7.47 7.20 1995-04-01 1995-05-01 1995-06-01 1995-07-01 1995-08-01 1995-09-01 1995-10-01 1995-11-01 1995-12-01 1996-01-01 1996-02-01 1996-03-01 1996-04-01 1996-05-01 1996-06-01 1996-07-01 1996-08-01 1996-09-01 1996-10-01 1996-11-01 1996-12-01 1997-01-01 1997-02-01 1997-03-01 1997-04-01 1997-05-01 1997-06-01 1997-07-01 1997-08-01 1997-09-01 1997-10-01 1997-11-01 1997-12-01 1998-01-01 1998-02-01 1998-03-01 1998-04-01 1998-05-01 1998-06-01 1998-07-01 1998-08-01 1998-09-01 1998-10-01 1998-11-01 1998-12-01 1999-01-01 1999-02-01 1999-03-01 1999-04-01 1999-05-01 1999-06-01 1999-07-01 1999-08-01 1999-09-01 5.84 5.85 5.64 5.59 5.57 5.43 5.44 5.52 5.29 5.15 4.96 5.10 5.09 5.15 5.23 5.30 5.19 5.24 5.12 5.17 5.04 5.17 5.14 5.28 5.30 5.20 5.07 5.19 5.28 5.08 5.11 5.28 5.30 5.18 5.23 5.16 5.08 5.14 5.12 5.09 5.04 4.74 4.07 4.53 4.50 4.45 4.56 4.57 4.41 4.63 4.72 4.69 4.87 4.82 6.05 5.93 5.66 5.62 5.65 5.54 5.56 5.51 5.35 5.13 4.97 5.16 5.27 5.33 5.46 5.52 5.34 5.45 5.32 5.27 5.24 5.31 5.27 5.48 5.60 5.53 5.34 5.33 5.40 5.30 5.30 5.38 5.45 5.23 5.27 5.25 5.26 5.36 5.32 5.23 5.15 4.81 4.20 4.59 4.57 4.49 4.61 4.65 4.54 4.75 5.03 4.75 5.09 5.08 6.27 6.00 5.64 5.59 5.75 5.62 5.59 5.43 5.31 5.09 4.94 5.34 5.54 5.64 5.81 5.85 5.67 5.83 5.55 5.42 5.47 5.61 5.53 5.80 5.99 5.87 5.69 5.54 5.56 5.52 5.46 5.46 5.53 5.24 5.31 5.39 5.38 5.44 5.41 5.36 5.21 4.71 4.12 4.53 4.52 4.51 4.70 4.78 4.69 4.85 5.10 5.03 5.20 5.25 6.57 6.17 5.72 5.78 5.98 5.81 5.70 5.48 5.32 5.11 5.03 5.66 5.96 6.10 6.30 6.27 6.03 6.23 5.91 5.70 5.78 6.01 5.90 6.22 6.45 6.28 6.09 5.89 5.94 5.88 5.77 5.71 5.72 5.36 5.42 5.56 5.56 5.59 5.52 5.46 5.27 4.67 4.09 4.54 4.51 4.62 4.88 5.05 4.98 5.25 5.62 5.55 5.68 5.66 6.68 6.27 5.80 5.89 6.10 5.89 5.77 5.57 5.39 5.20 5.14 5.79 6.11 6.27 6.49 6.45 6.21 6.41 6.08 5.82 5.91 6.16 6.03 6.38 6.61 6.42 6.24 6.00 6.06 5.98 5.84 5.76 5.74 5.38 5.43 5.57 5.58 5.61 5.52 5.47 5.24 4.62 4.18 4.57 4.48 4.61 4.90 5.11 5.03 5.33 5.70 5.62 5.77 5.75 6.86 6.41 5.93 6.01 6.24 6.00 5.86 5.69 5.51 5.36 5.38 5.97 6.30 6.48 6.69 6.64 6.39 6.60 6.27 5.97 6.07 6.33 6.20 6.54 6.76 6.57 6.38 6.12 6.16 6.11 5.93 5.80 5.77 5.42 5.49 5.61 5.61 5.63 5.52 5.46 5.27 4.62 4.18 4.54 4.45 4.60 4.91 5.14 5.08 5.44 5.81 5.68 5.84 5.80 7.06 6.63 6.17 6.28 6.49 6.20 6.04 5.93 5.71 5.65 5.81 6.27 6.51 6.74 6.91 6.87 6.64 6.83 6.53 6.20 6.30 6.58 6.42 6.69 6.89 6.71 6.49 6.22 6.30 6.21 6.03 5.88 5.81 5.54 5.57 5.65 5.64 5.65 5.50 5.46 5.34 4.81 4.53 4.83 4.65 4.72 5.00 5.23 5.18 5.54 5.90 5.79 5.94 5.92 1999-10-01 1999-11-01 1999-12-01 2000-01-01 2000-02-01 2000-03-01 2000-04-01 2000-05-01 2000-06-01 2000-07-01 2000-08-01 2000-09-01 2000-10-01 2000-11-01 2000-12-01 2001-01-01 2001-02-01 2001-03-01 2001-04-01 2001-05-01 2001-06-01 2001-07-01 2001-08-01 2001-09-01 2001-10-01 2001-11-01 2001-12-01 2002-01-01 2002-02-01 2002-03-01 2002-04-01 2002-05-01 2002-06-01 2002-07-01 2002-08-01 2002-09-01 2002-10-01 2002-11-01 2002-12-01 2003-01-01 2003-02-01 2003-03-01 2003-04-01 2003-05-01 2003-06-01 2003-07-01 2003-08-01 2003-09-01 2003-10-01 2003-11-01 2003-12-01 2004-01-01 2004-02-01 2004-03-01 5.02 5.23 5.36 5.50 5.73 5.86 5.82 5.99 5.86 6.14 6.28 6.18 6.29 6.36 5.94 5.29 5.01 4.54 3.97 3.70 3.57 3.59 3.44 2.69 2.20 1.91 1.72 1.68 1.76 1.83 1.75 1.76 1.73 1.71 1.65 1.66 1.61 1.25 1.21 1.19 1.19 1.15 1.15 1.09 0.94 0.92 0.97 0.96 0.94 0.95 0.91 0.90 0.94 0.95 5.20 5.43 5.68 5.76 6.00 6.11 6.07 6.39 6.24 6.27 6.35 6.25 6.32 6.34 5.92 5.15 4.89 4.44 3.99 3.74 3.56 3.56 3.39 2.71 2.17 1.92 1.82 1.77 1.86 2.06 1.98 1.91 1.83 1.74 1.64 1.64 1.59 1.30 1.27 1.22 1.20 1.16 1.17 1.11 0.94 0.97 1.05 1.03 1.02 1.04 1.01 0.99 1.01 1.01 5.43 5.55 5.84 6.12 6.22 6.22 6.15 6.33 6.17 6.08 6.18 6.13 6.01 6.09 5.60 4.81 4.68 4.30 3.98 3.78 3.58 3.62 3.47 2.82 2.33 2.18 2.22 2.16 2.23 2.57 2.48 2.35 2.20 1.96 1.76 1.72 1.65 1.49 1.45 1.36 1.30 1.24 1.27 1.18 1.01 1.12 1.31 1.24 1.25 1.34 1.31 1.24 1.24 1.19 5.86 5.86 6.10 6.44 6.61 6.53 6.40 6.81 6.48 6.34 6.23 6.08 5.91 5.88 5.35 4.76 4.66 4.34 4.23 4.26 4.08 4.04 3.76 3.12 2.73 2.78 3.11 3.03 3.02 3.56 3.42 3.26 2.99 2.56 2.13 2.00 1.91 1.92 1.84 1.74 1.63 1.57 1.62 1.42 1.23 1.47 1.86 1.71 1.75 1.93 1.91 1.76 1.74 1.58 5.94 5.92 6.14 6.49 6.65 6.53 6.36 6.77 6.43 6.28 6.17 6.02 5.85 5.79 5.26 4.77 4.71 4.43 4.42 4.51 4.35 4.31 4.04 3.45 3.14 3.22 3.62 3.56 3.55 4.14 4.01 3.80 3.49 3.01 2.52 2.32 2.25 2.32 2.23 2.18 2.05 1.98 2.06 1.75 1.51 1.93 2.44 2.23 2.26 2.45 2.44 2.27 2.25 2.00 6.03 5.97 6.19 6.58 6.68 6.50 6.26 6.69 6.30 6.18 6.06 5.93 5.78 5.70 5.17 4.86 4.89 4.64 4.76 4.93 4.81 4.76 4.57 4.12 3.91 3.97 4.39 4.34 4.30 4.74 4.65 4.49 4.19 3.81 3.29 2.94 2.95 3.05 3.03 3.05 2.90 2.78 2.93 2.52 2.27 2.87 3.37 3.18 3.19 3.29 3.27 3.12 3.07 2.79 6.11 6.03 6.28 6.66 6.52 6.26 5.99 6.44 6.10 6.05 5.83 5.80 5.74 5.72 5.24 5.16 5.10 4.89 5.14 5.39 5.28 5.24 4.97 4.73 4.57 4.65 5.09 5.04 4.91 5.28 5.21 5.16 4.93 4.65 4.26 3.87 3.94 4.05 4.03 4.05 3.90 3.81 3.96 3.57 3.33 3.98 4.45 4.27 4.29 4.30 4.27 4.15 4.08 3.83 2004-04-01 2004-05-01 2004-06-01 2004-07-01 2004-08-01 2004-09-01 2004-10-01 2004-11-01 2004-12-01 2005-01-01 2005-02-01 2005-03-01 2005-04-01 2005-05-01 2005-06-01 2005-07-01 2005-08-01 2005-09-01 2005-10-01 2005-11-01 2005-12-01 2006-01-01 2006-02-01 2006-03-01 2006-04-01 2006-05-01 2006-06-01 2006-07-01 2006-08-01 2006-09-01 2006-10-01 2006-11-01 2006-12-01 2007-01-01 2007-02-01 2007-03-01 2007-04-01 2007-05-01 2007-06-01 2007-07-01 2007-08-01 2007-09-01 2007-10-01 2007-11-01 2007-12-01 2008-01-01 2008-02-01 2008-03-01 2008-04-01 2008-05-01 2008-06-01 2008-07-01 2008-08-01 2008-09-01 0.96 1.04 1.29 1.36 1.50 1.68 1.79 2.11 2.22 2.37 2.58 2.80 2.84 2.90 3.04 3.29 3.52 3.49 3.79 3.97 3.97 4.34 4.54 4.63 4.72 4.84 4.92 5.08 5.09 4.93 5.05 5.07 4.97 5.11 5.16 5.08 5.01 4.87 4.74 4.96 4.32 3.99 4.00 3.35 3.07 2.82 2.17 1.28 1.31 1.76 1.89 1.66 1.75 1.15 1.11 1.33 1.64 1.70 1.76 1.91 2.05 2.32 2.50 2.68 2.85 3.09 3.14 3.17 3.22 3.53 3.78 3.79 4.13 4.30 4.33 4.47 4.69 4.79 4.90 5.01 5.17 5.27 5.17 5.08 5.12 5.15 5.07 5.15 5.16 5.10 5.07 4.98 4.95 5.04 4.55 4.20 4.16 3.58 3.34 2.84 2.10 1.51 1.58 1.86 2.19 1.98 1.97 1.64 1.43 1.78 2.12 2.10 2.02 2.12 2.23 2.50 2.67 2.86 3.03 3.30 3.32 3.33 3.36 3.64 3.87 3.85 4.18 4.33 4.35 4.45 4.68 4.77 4.90 5.00 5.16 5.22 5.08 4.97 5.01 5.01 4.94 5.06 5.05 4.92 4.93 4.91 4.96 4.96 4.47 4.14 4.10 3.50 3.26 2.71 2.05 1.54 1.74 2.06 2.42 2.28 2.18 1.91 2.07 2.53 2.76 2.64 2.51 2.53 2.58 2.85 3.01 3.22 3.38 3.73 3.65 3.64 3.64 3.87 4.04 3.95 4.27 4.42 4.40 4.40 4.67 4.73 4.89 4.97 5.12 5.12 4.90 4.77 4.80 4.74 4.67 4.88 4.85 4.57 4.67 4.77 4.98 4.82 4.31 4.01 3.97 3.34 3.12 2.48 1.97 1.62 2.05 2.45 2.77 2.57 2.42 2.08 2.57 3.10 3.26 3.05 2.88 2.83 2.85 3.09 3.21 3.39 3.54 3.91 3.79 3.72 3.69 3.91 4.08 3.96 4.29 4.43 4.39 4.35 4.64 4.74 4.89 4.97 5.09 5.07 4.85 4.69 4.72 4.64 4.58 4.79 4.75 4.51 4.60 4.69 5.00 4.82 4.34 4.06 4.01 3.35 3.13 2.51 2.19 1.80 2.23 2.69 3.08 2.87 2.70 2.32 3.39 3.85 3.93 3.69 3.47 3.36 3.35 3.53 3.60 3.71 3.77 4.17 4.00 3.85 3.77 3.98 4.12 4.01 4.33 4.45 4.39 4.35 4.57 4.72 4.90 5.00 5.07 5.04 4.82 4.67 4.69 4.58 4.53 4.75 4.71 4.48 4.59 4.67 5.03 4.88 4.43 4.20 4.20 3.67 3.49 2.98 2.78 2.48 2.84 3.15 3.49 3.30 3.14 2.88 4.35 4.72 4.73 4.50 4.28 4.13 4.10 4.19 4.23 4.22 4.17 4.50 4.34 4.14 4.00 4.18 4.26 4.20 4.46 4.54 4.47 4.42 4.57 4.72 4.99 5.11 5.11 5.09 4.88 4.72 4.73 4.60 4.56 4.76 4.72 4.56 4.69 4.75 5.10 5.00 4.67 4.52 4.53 4.15 4.10 3.74 3.74 3.51 3.68 3.88 4.10 4.01 3.89 3.69 2008-10-01 2008-11-01 2008-12-01 2009-01-01 2009-02-01 2009-03-01 2009-04-01 2009-05-01 2009-06-01 2009-07-01 2009-08-01 2009-09-01 2009-10-01 2009-11-01 2009-12-01 2010-01-01 2010-02-01 2010-03-01 2010-04-01 2010-05-01 2010-06-01 2010-07-01 2010-08-01 2010-09-01 2010-10-01 2010-11-01 2010-12-01 2011-01-01 2011-02-01 2011-03-01 2011-04-01 2011-05-01 2011-06-01 2011-07-01 2011-08-01 2011-09-01 2011-10-01 2011-11-01 2011-12-01 2012-01-01 2012-02-01 2012-03-01 2012-04-01 2012-05-01 2012-06-01 2012-07-01 2012-08-01 2012-09-01 2012-10-01 2012-11-01 2012-12-01 2013-01-01 2013-02-01 2013-03-01 0.69 0.19 0.03 0.13 0.30 0.22 0.16 0.18 0.18 0.18 0.17 0.12 0.07 0.05 0.05 0.06 0.11 0.15 0.16 0.16 0.12 0.16 0.16 0.15 0.13 0.14 0.14 0.15 0.13 0.10 0.06 0.04 0.04 0.04 0.02 0.01 0.02 0.01 0.01 0.03 0.09 0.08 0.08 0.09 0.09 0.10 0.10 0.11 0.10 0.09 0.07 0.07 0.10 0.09 1.23 0.74 0.26 0.30 0.46 0.43 0.35 0.30 0.31 0.28 0.27 0.21 0.16 0.15 0.17 0.15 0.18 0.23 0.24 0.22 0.19 0.20 0.19 0.19 0.18 0.18 0.19 0.18 0.17 0.16 0.12 0.09 0.10 0.08 0.06 0.04 0.05 0.05 0.05 0.07 0.12 0.14 0.14 0.15 0.15 0.15 0.14 0.14 0.15 0.14 0.12 0.11 0.12 0.11 1.42 1.07 0.49 0.44 0.62 0.64 0.55 0.50 0.51 0.48 0.46 0.40 0.37 0.31 0.37 0.35 0.35 0.40 0.45 0.37 0.32 0.29 0.26 0.26 0.23 0.25 0.29 0.27 0.29 0.26 0.25 0.19 0.18 0.19 0.11 0.10 0.11 0.11 0.12 0.12 0.16 0.19 0.18 0.19 0.19 0.19 0.18 0.18 0.18 0.18 0.16 0.15 0.16 0.15 1.61 1.21 0.82 0.81 0.98 0.93 0.93 0.93 1.18 1.02 1.12 0.96 0.95 0.80 0.87 0.93 0.86 0.96 1.06 0.83 0.72 0.62 0.52 0.48 0.38 0.45 0.62 0.61 0.77 0.70 0.73 0.56 0.41 0.41 0.23 0.21 0.28 0.25 0.26 0.24 0.28 0.34 0.29 0.29 0.29 0.25 0.27 0.26 0.28 0.27 0.26 0.27 0.27 0.26 1.86 1.51 1.07 1.13 1.37 1.31 1.32 1.39 1.76 1.55 1.65 1.48 1.46 1.32 1.38 1.49 1.40 1.51 1.64 1.32 1.17 0.98 0.78 0.74 0.57 0.67 0.99 1.03 1.28 1.17 1.21 0.94 0.71 0.68 0.38 0.35 0.47 0.39 0.39 0.36 0.38 0.51 0.43 0.39 0.39 0.33 0.37 0.34 0.37 0.36 0.35 0.39 0.40 0.39 2.73 2.29 1.52 1.60 1.87 1.82 1.86 2.13 2.71 2.46 2.57 2.37 2.33 2.23 2.34 2.48 2.36 2.43 2.58 2.18 2.00 1.76 1.47 1.41 1.18 1.35 1.93 1.99 2.26 2.11 2.17 1.84 1.58 1.54 1.02 0.90 1.06 0.91 0.89 0.84 0.83 1.02 0.89 0.76 0.71 0.62 0.71 0.67 0.71 0.67 0.70 0.81 0.85 0.82 3.81 3.53 2.42 2.52 2.87 2.82 2.93 3.29 3.72 3.56 3.59 3.40 3.39 3.40 3.59 3.73 3.69 3.73 3.85 3.42 3.20 3.01 2.70 2.65 2.54 2.76 3.29 3.39 3.58 3.41 3.46 3.17 3.00 3.00 2.30 1.98 2.15 2.01 1.98 1.97 1.97 2.17 2.05 1.80 1.62 1.53 1.68 1.72 1.75 1.65 1.72 1.91 1.98 1.96 2013-04-01 2013-05-01 2013-06-01 2013-07-01 2013-08-01 2013-09-01 2013-10-01 2013-11-01 2013-12-01 2014-01-01 2014-02-01 2014-03-01 2014-04-01 2014-05-01 2014-06-01 2014-07-01 2014-08-01 2014-09-01 2014-10-01 2014-11-01 2014-12-01 2015-01-01 2015-02-01 2015-03-01 2015-04-01 2015-05-01 2015-06-01 2015-07-01 2015-08-01 2015-09-01 2015-10-01 2015-11-01 2015-12-01 2016-01-01 2016-02-01 2016-03-01 2016-04-01 2016-05-01 2016-06-01 2016-07-01 2016-08-01 2016-09-01 2016-10-01 2016-11-01 2016-12-01 2017-01-01 2017-02-01 2017-03-01 2017-04-01 2017-05-01 2017-06-01 2017-07-01 0.06 0.04 0.05 0.04 0.04 0.02 0.05 0.07 0.07 0.04 0.05 0.05 0.03 0.03 0.04 0.03 0.03 0.02 0.02 0.02 0.03 0.03 0.02 0.03 0.02 0.02 0.02 0.03 0.07 0.02 0.02 0.13 0.23 0.26 0.31 0.30 0.23 0.28 0.27 0.30 0.30 0.29 0.33 0.45 0.51 0.52 0.53 0.75 0.81 0.90 1.00 1.09 0.09 0.08 0.09 0.07 0.07 0.04 0.08 0.10 0.10 0.07 0.08 0.08 0.05 0.05 0.06 0.06 0.05 0.04 0.05 0.07 0.11 0.08 0.07 0.11 0.09 0.08 0.09 0.12 0.22 0.18 0.11 0.33 0.50 0.43 0.45 0.47 0.37 0.42 0.40 0.40 0.45 0.47 0.48 0.58 0.64 0.62 0.65 0.89 0.95 1.04 1.11 1.13 0.12 0.12 0.14 0.12 0.13 0.12 0.12 0.12 0.13 0.12 0.12 0.13 0.11 0.10 0.10 0.11 0.11 0.11 0.11 0.10 0.13 0.21 0.20 0.22 0.25 0.23 0.24 0.28 0.30 0.38 0.37 0.26 0.48 0.65 0.54 0.53 0.66 0.56 0.59 0.55 0.51 0.57 0.59 0.66 0.74 0.87 0.83 0.82 1.01 1.04 1.12 1.20 1.22 0.23 0.25 0.33 0.34 0.36 0.40 0.34 0.30 0.34 0.39 0.33 0.40 0.42 0.39 0.45 0.51 0.47 0.57 0.45 0.53 0.64 0.55 0.62 0.64 0.54 0.61 0.69 0.67 0.70 0.71 0.64 0.88 0.98 0.90 0.73 0.88 0.77 0.82 0.73 0.67 0.74 0.77 0.84 0.98 1.20 1.21 1.20 1.31 1.24 1.30 1.34 1.37 0.34 0.40 0.58 0.64 0.70 0.78 0.63 0.58 0.69 0.78 0.69 0.82 0.88 0.83 0.90 0.97 0.93 1.05 0.88 0.96 1.06 0.90 0.99 1.02 0.87 0.98 1.07 1.03 1.03 1.01 0.93 1.20 1.28 1.14 0.90 1.04 0.92 0.97 0.86 0.79 0.85 0.90 0.99 1.22 1.49 1.48 1.47 1.59 1.44 1.48 1.49 1.54 0.71 0.84 1.20 1.40 1.52 1.60 1.37 1.37 1.58 1.65 1.52 1.64 1.70 1.59 1.68 1.70 1.63 1.77 1.55 1.62 1.64 1.37 1.47 1.52 1.35 1.54 1.68 1.63 1.54 1.49 1.39 1.67 1.70 1.52 1.22 1.38 1.26 1.30 1.17 1.07 1.13 1.18 1.27 1.60 1.96 1.92 1.90 2.01 1.82 1.84 1.77 1.87 1.76 1.93 2.30 2.58 2.74 2.81 2.62 2.72 2.90 2.86 2.71 2.72 2.71 2.56 2.60 2.54 2.42 2.53 2.30 2.33 2.21 1.88 1.98 2.04 1.94 2.20 2.36 2.32 2.17 2.17 2.07 2.26 2.24 2.09 1.78 1.89 1.81 1.81 1.64 1.50 1.56 1.63 1.76 2.14 2.49 2.43 2.42 2.48 2.30 2.30 2.19 2.32 Week 4 Homework Assignment This assignment is due by 6 p.m. eastern time on Sunday, September 17. When you turn it in, please: (1) Include your team number and assignment number in the filename(s). (2) List all team members in the file. (3) Remember to send me a separate email with feedback on the contribution of the members of your team (see syllabus). Problem 1 Open the Excel file called \"interest rates from 1982 to 2017\" which contains annualized yields on zero-coupon bond of various maturities (3 and 6 months, 1, 2, 3, 5, and 10 years) over the last 35 years. a. Calculate the mean and standard deviation for each column of data (i.e., each type of bond) and compare these statistics across different types of bonds. What is the relation between the average yield and maturity? What is the relation between the volatility of yields and maturity? Is this the pattern you would expect to observe? Why or why not? b. The real purpose of working with these numbers is to test the expectations hypothesis of the term structure of interest rates. Remember that this hypothesis says that forward rates are unbiased predictors of future spot rates. Clearly if you are testing whether forward rates predict future spot rates, you have to begin by taking the data you have and calculate the forward rates implied by the spot rates at any moment in time. You have monthly yields on 7 different securities, and from those there are many different forward rates you could compute. For example, in January, 1982, the three-month and six-month spot rates were 12.92% and 13.90% respectively. From these two numbers we could calculated the forward rate on a threemonth bond three months into the future. To do that, remember that we want to find the return on the 3-month bond, 3 months from now, that would make an investor indifferent between holding the 6-month bond that pays 13.90% and a sequence of two, 3-month bonds. Since these are annual rates, but we are looking at investments with maturities as short as 3 months, we use quarterly compounding like this: (1+0.1390/4)2 = (1+0.1292/4)(1+f/4) Here \"f\" stands for the annualized three-month forward rate three months from now. The term on the left means you earn (13.90/4)% for two quarters if you buy the 6-month bond. On the right, you can (12.92%/4) for one quarter, and then you earn (f/4)% for one quarter. If my algebra is correct, I find that f = 14.88%. Now, to test the expectations hypothesis, I would want to compare this number to the interest rate that it is supposed to predict, which is the three-month spot rate in April 1982. Forward rate - spot rate = forecast error 14.88 - 13.34 = 1.54 So for this particular month, the forward rate predicted a higher spot rate than what actually prevailed in the market three months later. To conduct a general test of the expectations hypothesis, I want to repeat this comparison every three months (do not use overlapping periods) throughout my sample period. My next step then would be to use data in April 1982 to calculate the three-month forward rate three months ahead, then compare that forward rate to the spot rate in July 1982 to get the forecast error for that period. Just repeat this process until you've gone all the way through the data. Once your calculations are complete, you could ask questions like: (1) Is the three-month forward rate an unbiased predictor of the three-month spot rate three months into the future (remember, an unbiased predictor is one that has a zero forecast error on average)? If not, what is the size and direction of the bias, and what does that imply about different theories of the yield curve? (2) How much volatility is there in the forecast error (remember, a biased forecast can be quite useful if the bias is predictable)? (3) If you run a regression in which the Y (dependent) variable is the three-month spot rate at a particular time and the X (independent) variable is the three-month forward rate calculated three months earlier, what do the regression results tell you? Y = a + bX Spot rate at time (t) = a + b(forward rate three months earlier) What value do you expect for \"a\" and \"b\" if the expectations hypothesis is true? What values for \"a\" and \"b\" do you expect if the forecast error is biased (remember, the bias could be positive or negative)? What does the regression R-square value tell you? (4) Investors in bonds are particularly interested in changes in interest rates. Go back to my original example in which I calculated the three-month forward rate starting in January 1982. That rate was 14.88%. Given that the three-month spot rate in January 1982 was 12.92%, the forward rate was predicting an interest rate increase of 1.96%. Three months later, the three-month spot rate was 13.34%, so the actual change in interest rates was an increase of 0.42% (three-month rates went up from 12.92% to 13.34%). Now think about running your regression again, except this time let Y be the actual change in the three-month spot rate over some period (so + 0.42% in my example) and let X be the predicted change (from forward rates) from three months ago (+1.96% in my example). Y = a + bX Actual change in spot rate = a + b(forecasted change in spot rates) Again, if the expectations hypothesis is true what values do you expect for a and b in this regression? How does the R-square value compare here to the previous regression? In all of the analysis above, I've started with the example of using current three-month and six-month spot rates to calculate a three-month forward rate and compare that to a subsequent three-month spot rate. You can and should do the same kind of analysis with different forward rates. For example, you could (A) use the current one-year and twoyear spot rates to calculate a one-year forward rate one year ahead and compare that to the one-year spot rate one year into the future. You could (B) use the current two-year and three-year spot rates to calculate a one-year forward rate two years into the future and compare that to the one-year spot rate that arises two years later. So if you do both (A) and (B) above, you are testing the ability of current interest rates to predict one-year bond rates one year ahead and two years ahead. Similarly, if you compare your analysis in (A) to the analysis of the three-month spot rate, you can get a sense of whether the predictability of short-term rates is different from the predictability of longer term rates. The point is I want you to do some broad analysis of the expectations hypothesis using different forward rates to predict different spot rates at different horizons. Then write a few paragraphs characterizing what you find. Economists often refer to the term \"random walk.\" There are two main implications when some economic variable like stock prices, exchange rates, or interest rates follows a random walk. The first is that the future is basically unpredictable...random. The second is that if you must guess what the future value of some quantity will be, the most reasonable forecast is the current value. For example, if the US dollar follows a random walk relative to other currencies, then my best guess for the exchange rate between dollars and euros one year in the future is just today's exchange rate. When evaluating the quality of your interest rate forecasts based upon forward rates, try to assess whether forward rates provide a forecasting tool that is superior to simple random walk estimates. Remember, \"superior\" in forecasting has several dimensions including unbiasedness and reliability. Think about different ways you could measure reliability. Problem 2 The figure below lists the price, maturity (in years), and coupon rate (stated in annual terms) for several bonds, all of which pay interest semiannually. Bond Price 1007.78 1036.87 1046.57 1048.58 1065.15 1119.60 1136.35 1122.52 Maturity 1 1 1 2 2 2 3 3 Coupon Rt. 5.000% 8.000% 9.000% 7.250% 8.125% 11.000% 10.000% 9.500% 1246.97 1046.86 1208.16 1308.81 972.15 1086.61 992.00 1352.84 1003.08 3 4 4 5 5 6 6 7 7 14.000% 6.750% 11.250% 13.000% 5.250% 7.875% 6.000% 12.500% 6.375% Use regression analysis to estimate the term structure. Your deliverable is a series of spot interest rates at 6-month intervals going out 7 years. State each spot rate as an annual rate. Also calculate the YTM for each bond and compare that to the spot rate for the year in which the bond matures. Let me give you some significant hints about how to set up and interpret the regression. In regression analysis, we usually write equations like this: Y = a + B1X1 + B2X2 + B3X3 + .... Here, X1, X2, and X3 are variables that influence Y, and B1, and B2, and B3 are coefficients that measure the extent to which the variables affect Y. In the present context, Y is the price of a bond. We want to know what determines bond prices. That's easy, it's just cash flows and discount rates, and it is the discount rates, the spot rates, which we are after here. Set up a spreadsheet where each bond is a separate row. The first column is the bond's price. The second column is the cash payment that the bond makes in 6 months. The 3rd column is the cash payment that the bond makes in 12 months. The 4th column is the cash payment that the bond makes in 18 months, and so on. You keep adding data to columns until you have gone far enough out to capture all 14 payments that a 7-year bond would make. Note, after a bond matures, you enter a zero for all payment dates after maturity. For example, the first row of the spreadsheet would look like this: 1007.78 25 1025 0 0 0 0 0 0 0 0 0 0 0 0 Now, use Data Analysis in Excel or some other method to run a multiple linear regression. Price is the Y variable and cash flows in each of the 14 payment periods are the X variables. That is, there are 14 explanatory variables here, and you will get 14 Beta coefficients. Each coefficient is telling you how much an additional dollar of cash flow at a given time period adds to the price of the bond. Notice, I did not say that there should be an intercept term in this regression. There should not be (i.e., no little \"a\" as in the regression equation above). You have to instruct Excel or whatever statistical software you are using to force the intercept through zero. Why are we doing this? Once you have the beta coefficients, you'll have to use them to \"back out\" what the spot rates are at each point on the yield curve. You'll have to derive the spot rates algebraically. By convention, let's all assume the usual semi-annual compounding for bonds where the denominator of the bond pricing equation would look like (1 + r/2)^t. Problem 3 Suppose the expectations hypothesis is true and you have the following series of spot rates. 1-year 1.25% 2-year 1.75% 3-year 2.25% 4-year 2.75% a. Calculate the price of a bond that has a $1,000 par value, pays a $30 coupon once a year, and matures in four years. You can assume the first coupon is one year away. b. Assuming the expectations hypothesis is true, what is the expected price of this bond in one year just after it makes its first coupon payment? c. If you buy the bond today and sell it in one year (just after getting the first coupon payment), what is your expected rate of return. d. You buy the bond today and hold it to maturity. After you receive a coupon payment, you reinvest it in a zero-coupon bond maturing at the same time (4 years from now) as the coupon-paying bond. How much total cash do you expect to have after 4 years? Given that estimate, what compound annual rate of return do you earn over the 4 years? e. Go back to the beginning of this problem (use the spot rates given), and assume that investors require a liquidity premium of 0.25% per year to invest in an N-year bond instead of a bond maturing in year N-1. For example, investors want to earn 0.25% more per year if they invest in a two-year bond than they expect to earn if they buy a one-year bond and then roll that over into another one-year bond. Does your answer to part (a) change? Why or why not? If you are now asked to predict the bond's price in one year, is your answer different than in part (b)? Note that I am not asking you to derive a price. Just tell me if it would be different or not and explain why. If you think it would be different, would be the price be higher or lower than your answer to part (b)? f. Considering the information given in part (e), what is the expected interest rate on a one-year bond one year from today? Problem 4 The current 1-year spot rate is 3%, and 1f1 is 3.5%. Investors require a liquidity premium on short-term bonds such that the expected annual return on a 2-year bond is 0.25% per year lower than the expected return on a series of two, 1-year bonds. What is the current market price of a 2-year bond that pays a 4% coupon rate (annual payments) and what is the expected price of this bond one year from today? If you buy the bond today, hold it for one year, collect its first coupon payment, then immediately resell it at the expected selling price, what is your expected return? Problem 5 Calculate the duration, in years, of a bond that matures in 5 years, pays $60 in interest twice a year (e.g., 12% coupon rate), and sells for $997.55. Explain how you can use duration (or modified duration) to estimate the change in the price of a bond when the yield to maturity changes. Estimate how much the price of this bond will change if rates go up one percentage point, and then calculate an exact price assuming a one percentage point jump in the YTM. Why doesn't the duration approach give you an exact answer. Problem 6 A bond sells at par and pays an annual coupon of 5% (assume annual payments). Calculate the duration of this bond at various maturities including 1, 2, 3, 4, 5, 10, 20, 50, and 100 years. Plot a graph showing how the duration changes as maturity changes. Explain why the graph is shaped the way it is. Be careful to draw to scale. Problem 7 Your firm is obligated to make payments to a supplier according to the following schedule: Year 1 Year 2 Year 3 $1 million $1.5 million $10 million You want to immunize this liability investing in some combination of a 2-year bond with a 10% coupon and a 4-year bond with a 12% coupon. You can assume these bonds pay interest annually, and have a par value of $1,000. Use a discount rate / YTM of 6% throughout this problem. How many (in terms of numbers of bonds) of each type of bond do you need to purchase to immunize your liability Expert Answer:
