Forecasting Report Report Samples

Investments

Introduction
In this section, there will elemental information concerning the entire report. First, this report will present the Forecast Report on the Prices and Yields of Amtrak. The following link provides the original data from which the information used in the Forecast Report was sourced. https://www.quandl.com/BTS_MM/AMTRAKPRICES-Amtrak-Ticket-Prices-and-Yields. The exact information used in the report included the data from 12/1/2008 to 2012-07-01. This information contains the various aspects required in the analysis of this forecast report. This report will discuss the methods and the assumptions of the forecast data. The methods will encompass a detailed explanation of the methodology employed in the in the forecast report. On the other hand, the assumptions will be formulated based on the methodology and will encompass aspects such as the accuracy of the data. The results will follow the methods and assumptions. The results will document the results of the forecast on the yields and prices. This section will encompass different graphical presentation of the raw data itself, the raw data across the forecast, and a table of forecasted values of the errors. The results will document and present information for discussion. Discussion will encompass evaluation of the behavior of the forecast data over time. This report will also have the error analysis that will present the weaknesses of the model and the discussion of the errors. Last, this report will provide recommendations from the analysis of the forecast data. These recommendations will be the basis for some managerial actions.

Methods and Assumptions

The TSF was employed in this forecast report. The methodology is involved collection of the information on the yields and prices of Amtrak from 12/1/2008 to 2012-07-01. The data on these prices and yields was recorded in Excel for analysis. These results were then evaluated to for discussion and drawing of recommendations. The assumptions made in this section were those of this method. The first assumption made was that the future will be an extension of the past. That is; all events that had been happening at Amtrak will continue happening, at least across the horizon of the forecast. Second, all the causative factors of variation, regardless of their form are all imbedded in the forecast data. These causative factors of the variation, regardless of what they are, are assumed to cause the interest variables to shift or react the way it did. Another assumption was that the Amtrak yields and prices changed with a constant degree or percentage over a given period. In addition, it was assumed that these changes were influenced by both the internal and external factors Nevertheless, these factors were assumed to remain constant over the period over which the forecast results were collected and documented. In addition, it was assumed that these prices and yields of Amtrak were progressive over the time intended for the evaluation. It was also assumed that there external and internal factors contributed to the probable errors in the report.

Discussion and Results

The Raw Data with the Model Extended Across the Forecast Horizon and With the 2σ Error Bands Added To the Extended Trend

Forecast Values without the error bands

Raw Data
Error Analysis
The weak point in this model is the instances where the data provided in the MAPE allow for inadvertent calculations. These errors are random because they vary with time. That is, the percentage error is not consistent with time. The errors vary with time. The percentage of the error shows the validity and reliability of the forecast results. The highest error value is 3.28% experienced in 2011-05-01, which makes data during that time less reliable. On the other hand, the lowest error value was -3.24% experienced in 2009-01-01, which makes information during that period reliable for reference. The numeric results of the run tests were as follows:

The distribution of the errors is random as presented in the graph below:

Conclusion
This model was used in the forecasting of the yields and prices of Amtrak. The data collected is indicative that there is a fluctuating trend in the prices and yields of Amtrak. This model predicts a rise in the yields during 2011-11-01. The findings of the model, especially with reference to the MAPE suggests that the highest value is expected on 2011-11-01
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