Munich Personal RePEc Archive
metadata only
Autoregressive Conditional Heteroskedasticity Models and the Dynamic Structure of the Athens Stock Exchange
Autoregressive Conditional Heteroskedasticity (ARCH) models have been applied in modeling the relation between conditional variance and asset risk premium. The most important theoretical regularities that govern the dynamic structure of financial time series are presented. A model named Exponential
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Estimating conditional volatility with neural networks#1194090
- Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH#942356
- Chasing El Dorado: gold under shifting geopolitical and financial conditions#1210432
- Forecasting volatility: Evidence from the Macedonian stock exchange#1276372
- GARCH-Informed Neural Networks for Volatility Prediction in Financial Markets#1115467
Record · ID 1276942
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive