Results 141 to 150 of about 50,283 (214)

Identifying Drivers of Deviations From Rational Expectations: Using a New Irrational Index for Inflation Forecasts

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Most studies on inflation forecasts have studied behavioral biases, informational frictions, or external shocks in isolation, without considering how these factors jointly drive deviations from rational expectations. We therefore adopt an integrated framework that simultaneously estimates the behavioral, informational, and external ...
Belen Chocobar, Peter Claeys
wiley   +1 more source

Exploring the Nexus Between Sustainability Index and Central European Stock Markets Competitiveness: Evidence Through Time–Frequency Analysis and SHAP

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Sustainability has become an important factor shaping financial markets and investor behavior. This paper examines the relationship between sustainability indices and Central European stock markets using a time–frequency approach. Wavelet coherence is employed to capture time‐varying co‐movements between sustainability indices and stock market
Zuzana Janková   +4 more
wiley   +1 more source

Using DSGE and Machine Learning to Forecast Public Debt for France

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Forecasting public debt is essential for effective policymaking and economic stability, yet traditional approaches face challenges due to data scarcity. While machine learning (ML) has demonstrated success in financial forecasting, its application to macroeconomic forecasting remains underexplored, hindered by short historical time series and ...
Emmanouil Sofianos   +4 more
wiley   +1 more source

Evaluating Forecasts at Multiple Horizons: An Extension of the Diebold–Mariano Approach

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Forecast accuracy tests are fundamental tools for comparing competing predictive models. The widely used Diebold–Mariano (DM) test assesses whether differences in forecast errors are statistically significant. However, its standard form is limited to pairwise comparisons at a single forecast horizon.
Andrew Grant   +2 more
wiley   +1 more source

Enhancing Prediction by Incorporating Entropy Loss in Volatility Forecasting. [PDF]

open access: yesEntropy (Basel)
Urniezius R   +9 more
europepmc   +1 more source

The Role of Price‐Volatility Cojumps in Volatility Forecasting

open access: yesJournal of Futures Markets, EarlyView.
ABSTRACT This paper investigates whether simultaneous jumps in prices and volatility improve volatility forecasting. Using up‐to‐date high‐frequency S&P 500 and VIX data, we identify price‐volatility cojumps at the intraday granularity and construct upside, downside, and asymmetric measures.
Kefu Liao
wiley   +1 more source

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