NYU Faculty Digital Archive
metadata only
Semiparametric vector MEM
In financial time series analysis we encounter several instances of non–negative valued processes (volumes, trades, durations, realized volatility, daily range, and so on) which exhibit clustering and can be modeled as the product of a vector of conditionally autoregressive scale factors and a mul
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
- Clustering of Time Series Data: Measures, Methods, and Applications#492525
- Advanced spectral clustering for heterogeneous data in credit risk monitoring systems#1061624
- Cross-Sectional Asset Retrieval via Future-Aligned Soft Contrastive Learning#1013508
- Rigidity of the Black–Scholes Valuation Operator Representative-Invariant Local Valuation under Fixed One-Factor Market Data#694234
- Retrieval-Augmented Diffusion Modeling for Stochastic Discount Factor Portfolios#1129687
Record · ID 942880
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