A procedure for upgrading linear-convex combination forecasts with an application to volatility predictionOpen Access

Monschang Verena, Wilfling Bernd

Arbeitspapier / Working Paper

Zusammenfassung

We investigate mean-squared-forecast-error (MSE) accuracy improvements for linear-convex combination forecasts, whose components are pretreated by a procedure called 'Vector Autoregressive Forecast Error Modeling' (VAFEM). Assuming that the forecast-error series of the individual forecasts are governed by a stable VAR process under classic conditions, we obtain the following results: (i) VAFEM treatment bias-corrects all individual and linear-convex combination forecasts. (ii) Any VAFEM-treated combination has smaller theoretical MSE than its untreated analogue, if the VAR parameters are known. (iii) In empirical applications, VAFEM gains depend on (1) in-sample sizes, (2) out-of-sample forecast horizons, (3) the biasedness of the untreated forecast combination. We demonstrate the VAFEM capacity for realized-volatility forecasting, using S&P 500 data.

Details zur Publikation

ErscheinungsortUniversity of Muenster
Titel der ReiheCQE-Working-Papers
Nr. in Reihe97/2022
StatusVeröffentlicht
Veröffentlichungsjahr2022 (22.03.2022)
Sprache, in der die Publikation verfasst istEnglisch
StichwörterCombination forecasts; mean-squared-error loss; VAR forecast-error modeling; multivariate least squares estimation

Autor*innen der Universität Münster

Monschang, Verena
Lehrstuhl für Volkswirtschaftslehre, insbesondere empirische Wirtschaftsforschung
Wilfling, Bernd
Professur für Volkswirtschaftslehre, empirische Wirtschaftsforschung (Prof. Wilfling)

Promotionen, aus denen die Publikation resultiert

Contributions to Forecasting and Hypothesis Testing with Application to Financial-Market Data
Promovend*in: Monschang, Verena | Betreuer*innen: Wilfling, Bernd; Trede, Mark | Gutachter*innen: Trede, Mark; Wilfling, Bernd
Zeitraum: 01.04.2017 - 01.07.2022
Promotionsverfahren erfolgt(e) an: Promotionsverfahren an der Universität Münster