---
title: Heterogeneous Tail Common Factor Modeling
url: https://www.ml-quant.com/papers/repec/spr-digfin-v-5-y-2023-i-2-d-10-1007-s42521-023-00083-z/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:spr:digfin:v:5:y:2023:i:2:d:10.1007_s42521-023-00083-z
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs42521-023-00083-z%3Bh%3Drepec%3Aspr%3Adigfin%3Av%3A5%3Ay%3A2023%3Ai%3A2%3Ad%3A10.1007_s42521-023-00083-z
featured: 2023-08-02
citations: unknown
topic: Asset Pricing & Factors
---


# Heterogeneous Tail Common Factor Modeling

The proposed Factor-HGH model, which handles non-Gaussian errors, shows promise in modeling financial factors and asset returns, especially for cryptocurrencies with highly heterogeneous tails.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs42521-023-00083-z%3Bh%3Drepec%3Aspr%3Adigfin%3Av%3A5%3Ay%3A2023%3Ai%3A2%3Ad%3A10.1007_s42521-023-00083-z
- Identifier: RePEc:spr:digfin:v:5:y:2023:i:2:d:10.1007_s42521-023-00083-z
- Released: 2023-08-02
- First featured: Quant Letter No. 10 (2023-08-02): https://www.ml-quant.com/issues/2023-08-02/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Asset Pricing & Factors

## Related

- [Alpha Now, Taxes Later: Tax-Efficient Long-Only Factor Investing](https://www.ml-quant.com/papers/ssrn/4538712/): Despite high turnover, factor investing can yield significant pre-tax and post-tax alphas, especially with value, quality, and safety buy-and-hold portfolios, making it a viable option for tax-aware investors.
- [Power Sorting](https://www.ml-quant.com/papers/ssrn/4552208/): The article suggests a new method for creating characteristic-based equity factors called power sorting, showing its superior performance and applicability to multifactor strategies.
- [A comparative study of factor models for different periods of the electricity spot price market](https://www.ml-quant.com/papers/arxiv/2306.07731/): A 4-factor model is better at predicting electricity spot prices in non-crisis times, but not during crises.
- [Dynamic Time Warping for Lead-Lag Relationships in Lagged Multi-Factor Models](https://www.ml-quant.com/papers/arxiv/2309.08800/): A new technique using dynamic time warping has been created to identify lead-lag relationships in multivariate time series systems, demonstrated in financial markets.
- [HireVAE: An Online and Adaptive Factor Model Based on Hierarchical and Regime-Switch VAE](https://www.ml-quant.com/papers/arxiv/2306.02848/): HireVAE is a deep learning-based model that outperforms previous methods in terms of active returns in stock market benchmarks.
- [Robust Detection of Lead-Lag Relationships in Lagged Multi-Factor Models](https://www.ml-quant.com/papers/arxiv/2305.06704/): A methodology for detecting lead-lag relationships in time series systems can be used for control, forecasting, or clustering, and is useful for financial markets or environmental data sets.
