Introduction to time series preprocessing and forecasting in Python using AR, MA, ARMA, ARIMA, SARIMA and Prophet model with forecast evaluation.

scores: Metrics for the verification, evaluation and optimisation of forecasts, predictions or models.

Utilities for Scoring and Assessing Predictions

AI-assisted XAUUSD daily research workflow with Research Skill, Agent Harness, LangGraph, Tool Calling, and free public data sources.

Comparing sequential forecasters via confidence sequences & e-processes

Easily evaluate your forecasts with (multivariate) Diebold-Mariano and (multivariate) Giacomini-White tests of equal predictive ability and MCS.

A verification pipeline for evaluating models and forecasts.

Multi Horizon Superior Predictive Ability (SPA) test proposed by Quaedvlieg (2021)

This code mainly computes the forecast of headline inflation using different aproaches. Likewise presents the forecast evaluation for each model along different points in a span period.

Temporal adaptation of the gamma index for time series forecast evaluation under joint amplitude and timing tolerances, with applications to renewable energy forecasting.

USDA Food Price Outlook forecast evaluation using CPI data, analyzing forecast accuracy, category-level errors, and long-term food inflation relative to overall CPI trends.

Forecast Evaluation Package for gretl

self archived publications

Analysis on the quality and determinants of economic forecasts during the Covid 19 pandemic

Reference implementation of the Relative Utility Value metric for forecast value assessment

Standalone AR forecasting workflow for the Sentiment–Volatility Ratio capstone project, using UMCSI and VIX data with expanding-window evaluation.

End-to-End Python replication of Iadisernia & Camassa’s LLM macroeconomic forecasting methodology (ICAIF 2025). Implements: 2,368 synthetic economist profiles, 120,000+ GPT-4o forecasts across 50 European Central Bank (ECB) SPF rounds, a rigorous ablation study with Monte Carlo & binomial hypothesis testing.

Analysis on the quality and determinants of economic forecasts pre-Covid 19

Reference scoreboard for probabilistic forecasts. Deterministic evaluation, SHA256 snapshot integrity, and attestation for public and institutional use.

Supplementary materials for the following publication: Davydenko, A., & Goodwin, P. (2021). Assessing point forecast bias across multiple time series: Measures and visual tools. International Journal of Statistics and Probability, 10(5), 46-69. https://doi.org/10.5539/ijsp.v10n5p46