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Estimate the aggregate market for the S&P 500 index and either the Shanghai Composite or Shenzhen Composite Indexes. SHOW ALL WORK. EXAMPLE 13.7 In late

Estimate the aggregate market for the S&P 500 index and either the Shanghai Composite or Shenzhen Composite Indexes. SHOW ALL WORK.

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EXAMPLE 13.7 In late 2014, the S&P 500 was at 2,040. The forecast for 12-month forward earnings per share for the S&P 500 portfolio was about $134. The 10-year Treasury-bond yleld at thls time was about 2.3%, but the yield curve was relatively steep, so a plausible forecast for its value next year would be higher, perhaps 2.8%. As a first approach, we might posit that the spread between the earn- ings yield and the Treasury yield, which was around 3.2% in 2014, will remain at tat level by the end of the year Given the assumed Treasury yleld, this would Imply an earnings yleld for the S&P of 6% and a PE rato of 1/06 = 16.67. Our forecast for the level ofthe S&P index would then be 16.67 x 134-2,233, which would imply a one-year capital gain on the Index of 193/2,040-9.5%. Of course, there is uncertainty regarding all three Inputs Into this analysls: the actual earnings on the S&P 500 stocks, the level of Treasury yields at year-end, and the spread between the Treasury yleld and the earnings yleld. One would wish to perform sensltivity or scenario analysls to examine the Impact of changes In all of these varlables. To illustrate, conslder Table 13.4, which shows a simple scenario analysls treating possible effects of varlation In the Treasury-bond yleld. The sce- narlo analysls shows that the forecast level of the stock market varles Inversely and with dramatic Forecasting the Aggregate Stock Market Some analysts use an aggregate version of the dividend discount model rather than an earnings multiplier approach. All of these models, however, rely heavily on forecasts of such macroeconomic variables as GDP, interest rates, and the rate of inflation, which are difficult to predict accurately. EXAMPLE 13.7 In late 2014, the S&P 500 was at 2,040. The forecast for 12-month forward earnings per share for the S&P 500 portfolio was about $134. The 10-year Treasury-bond yleld at thls time was about 2.3%, but the yield curve was relatively steep, so a plausible forecast for its value next year would be higher, perhaps 2.8%. As a first approach, we might posit that the spread between the earn- ings yield and the Treasury yield, which was around 3.2% in 2014, will remain at tat level by the end of the year Given the assumed Treasury yleld, this would Imply an earnings yleld for the S&P of 6% and a PE rato of 1/06 = 16.67. Our forecast for the level ofthe S&P index would then be 16.67 x 134-2,233, which would imply a one-year capital gain on the Index of 193/2,040-9.5%. Of course, there is uncertainty regarding all three Inputs Into this analysls: the actual earnings on the S&P 500 stocks, the level of Treasury yields at year-end, and the spread between the Treasury yleld and the earnings yleld. One would wish to perform sensltivity or scenario analysls to examine the Impact of changes In all of these varlables. To illustrate, conslder Table 13.4, which shows a simple scenario analysls treating possible effects of varlation In the Treasury-bond yleld. The sce- narlo analysls shows that the forecast level of the stock market varles Inversely and with dramatic Forecasting the Aggregate Stock Market Some analysts use an aggregate version of the dividend discount model rather than an earnings multiplier approach. All of these models, however, rely heavily on forecasts of such macroeconomic variables as GDP, interest rates, and the rate of inflation, which are difficult to predict accurately

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