Forecast Quality Matrix: A Methodological Survey of Judging Forecast Quality of Capital Market Forecasts.

Capital market forecasts sometimes suffer from a too intensive orientation towards the current market situation and lose their future-orientated character. This phenomenon can be referred to as Topical Orientated Trend Adjustment (GOVA). For an individual statistical proof we develop a new instrument called GOVA coefficient. In the second step we combine the GOVA coefficient with the conventional forecast quality measure of Theil's inequality coefficient. The result is the Forecast Quality Matrix. With this instrument, it is possible to verify whether the examined forecast is better or worse than the naive forecast and to exclude Topical Orientated Trend Adjustment. This results in four different possibilities: 1. The forecast considering the future is an ideal case. This forecast is significantly better than a naive forecast and is not influenced by the market situation during the making of the forecast. 2. The quasi-naive forecast is characterized ba a Topical Orientated Trend Adjustment, but is not better than the naive forecast. 3. The wrong forecast does not reflect the past, but unfortunately not even the future. 4. The direction-orientated forecast follows the past, but mostly indicates the correct market trend. This classification facilitates the evaluation of the practicability of forecasts and points out the reasons for a possibly lacking forecast accuracy.