Results 221 to 230 of about 28,205 (317)

Optimal Variance Forecasting in a Trading Context

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT In financial trading, the economic value of return and variance forecasts arises from three key components: an investor's risk preference, the quality of return predictions, and the accuracy of risk estimates. This study isolates the third component—risk knowledge—and demonstrates that its contribution is a non‐linear function of realized and ...
Nick Taylor
wiley   +1 more source

Investigation of Social Media Metrics With Respect to Demand Modeling for Promotional Products

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Social media (SM) has revolutionized the way companies connect with customers, enabling more personalized marketing strategies and enhancing engagement. With platforms like Facebook offering detailed user data, businesses can create more targeted advertising campaigns. This paper proposes an approach to categorizing SM variables based on their
Yvonne Badulescu   +3 more
wiley   +1 more source

Seasonal Decomposition‐Enhanced Deep Learning Architecture for Probabilistic Forecasting

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Time series decomposition as a general preprocessing method has been widely used in the field of time series forecasting. However, since the future is unknown, this preprocessing practice is limited in realistic forecasting, especially in real‐time forecasting scenarios.
Keyan Jin   +1 more
wiley   +1 more source

UK Forecasts of Annual GDP: Their Accuracy and the Information Categories Underlying Their Revisions

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Policy makers are concerned with the accuracy of GDP forecasts and want to understand the reasons for the revision of forecasts. We study these issues by examining forecasts of annual UK GDP growth by a panel of agents, published monthly by HM Treasury. We focus on two main issues: the developing accuracy of the group‐mean forecast as horizons
Nigel Meade, Ciaran Driver
wiley   +1 more source

When Are Statistical Forecast Gains Economically Relevant? Evidence From Bitcoin Returns

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT We study how statistical forecast gains for Bitcoin translate into trading profits. Using real‐time out‐of‐sample forecasts from daily bivariate VARs from October 2021 to February 2024, we show that Bitcoin returns are forecastable and that seven predictive indices yield significant gains in directional accuracy (DA).
Rehan Arain, Stephen Snudden
wiley   +1 more source

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