Question-3 The spot price of an investment asset is $30 and the risk-free rate for all maturities is 10% with continuous compounding. The asset provides an income of $2 at the end of the first year and at the end of the second year. What is the three-year forward price? (2 mark) Question-4 On March 1 a commodity’s spot price is $60 and its August futures price is $59. On July 1 the spot price is $64 and the August futures price is $63.50. A company entered into futures contracts on March 1 to hedge its
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B. Y,S,Z,P C. K. Use regression to estimate K. Log S=logK + logY + logX – logP To find the antilog of K, use the exponential logK. 5. Use Excel. Fill in the numbers. Look under 5 year moving average. Click on exponential smoothing tab. Look at the smoothing factor. Look at MSE for each mean squared errors. Use the MSE to choose the one that will give you the best focus and that would be the one with the smallest MSE. 6. A
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After changing the periods for the moving forecast to 1,2,3,4,5 I found that the lowest MAD is at 1 period. This is because our deviation in the demand is very small and a more receptive moving average would work more efficiently than a larger one. c). The new demand totals had a higher deviation, after placing the different moving averages in I have concluded that the lowest MAD results at 5. This is because of the higher deviated demand which makes a longer moving average better with less error.
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Mgt 2070 Assignment 2 – Solutions 4.13 As you can see in the following table, demand for heart transplant surgery at Washington General Hospital has increased steadily in the past few years: |Year |1 |2 |3 |4 |5 |6 | |Heart Transplants |45 |50 |52 |56 |58 |? | The
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10 Sales Volume 10000 12400 14250 15750 20500 18500 15750 20500 21500 22550 6. Using Data Set E1, what would be the forecast for period 7 using a four period moving average: (Choose the closest answer.) a. 17625 b. 15225 c. 15300 d. 17250 7. Using Data Set E1, what would be the forecast for period 6 using a five period weighted moving average? The weights for each period are 0.05,
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how the forecasted item behaves. This would be used by companies would do not have access to historical data therefore they would use a competitors available data. What are some of the problems and drawbacks of the moving average forecasting model? One problem with the moving average method is that it does not take into account data
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Running Head: PARKER EARTH MOVING COMPANY RECOMMENDATION Parker Earth Moving Company Recommendation Amanda Duarte ISCOM 305 August 18, 2011 R. Sell Parker Earth Moving Company (PEMC) is in the business of providing high-quality small earthmoving equipment for home and small business consumers. In an effort to grow its business, PEMC has developed a new navigational device called the Ultramover. The Ultramover was designed for personal and small business use and is intended
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machine capacity. Our goal was to buy additional machines whenever a station reached about 80% of capacity. Day 50 Once the initial first 50 days of data became available, we plotted the data against different forecasting methods: Moving average, weighted moving average, exponential smoothing, exponential smoothing with trend, and exponential smoothing with trend and season. Out of these five options, exponential smoothing with trend displayed the best values of MSE (2.3), MAD (1.17), and MAPE
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Forecasting Models: Associative and Time Series Forecasting involves using past data to generate a number, set of numbers, or scenario that corresponds to a future occurrence. It is absolutely essential to short-range and long-range planning. Time Series and Associative models are both quantitative forecast techniques are more objective than qualitative techniques such as the Delphi Technique and market research. Time Series Models Based on the assumption that history will repeat
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4.9 (a, b) The computations for both the two- and three-month averages appear in the table; the results appear in the figure below. [pic] (c) MAD (two-month moving average) = .750/10 = .075 MAD (three-month moving average) = .793/9 = .088 Therefore, the two-month moving average seems to have performed better. |Table for Problem 4.9 (a, b, c) | | | | |Forecast
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