In: Finance
The accompanying table gives the stock market indices for a certain company on the stock market. Use simple linear regression to forecast the data.
Date Index Date (numeric)
9/3/2010 10,446.78 40424
9/7/2010 10,340.24 40428
9/8/2010 10,387.43 40429
9/9/2010 10,416.96 40430
9/10/2010 10,462.14 40431
9/13/2010 10,545.67 40434
9/14/2010 10,525.62 40435
9/15/2010 10,572.66 40436
9/16/2010 10,593.78 40437
9/17/2010 10,606.94 40438
9/20/2010 10,752.82 40441
9/21/2010 10,760.77 40442
9/22/2010 10,740.59 40443
9/23/2010 10,663.99 40444
9/24/2010 10,861.13 40445
9/27/2010 10,812.19 40448
9/28/2010 10,858.73 40449
9/29/2010 10,833.32 40450
9/30/2010 10,788.48 40451
10/1/2010 10,828.31 40452
A. Identify the trend and level for the given data.
(Round the Trend to two decimal places as needed. Round the Level to the nearest integer as needed.)
B. What would be the forecasts for the next three days?
After plotting the points in excel, we see a steady upward trend
We use the forecast function in excel, for which we first calculate the daily price changes in % terms and then extrapolate those values into the future
Our forecast | ||
Stock price | % Chg from previous day | |
9/3/2010 | 10446.78 | |
9/7/2010 | 10340.24 | -1% |
9/8/2010 | 10387.43 | 0% |
9/9/2010 | 10416.96 | 0% |
9/10/2010 | 10462.14 | 0% |
9/13/2010 | 10545.67 | 1% |
9/14/2010 | 10525.62 | 0% |
9/15/2010 | 10572.66 | 0% |
9/16/2010 | 10593.78 | 0% |
9/17/2010 | 10606.94 | 0% |
9/20/2010 | 10752.82 | 1% |
9/21/2010 | 10760.77 | 0% |
9/22/2010 | 10740.59 | 0% |
9/23/2010 | 10663.99 | -1% |
9/24/2010 | 10861.13 | 2% |
9/27/2010 | 10812.19 | 0% |
9/28/2010 | 10858.73 | 0% |
9/29/2010 | 10833.32 | 0% |
9/30/2010 | 10788.48 | 0% |
10/1/2010 | 10828.31 | 0% |
10/2/2010 | 10,944.82 | 1% |
10/3/2010 | 11,061.66 | 1% |
10/4/2010 | 11,232.09 | 2% |