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Found 7 papers, 2 papers with code
The Adaptive Multi-Factor Model and the Financial Market
Modern evolvements of the technologies have been leading to a profound influence on the financial market.
Clustering Structure of Microstructure Measures
This paper builds the clustering model of measures of market microstructure features which are popular in predicting stock returns.
A News-based Machine Learning Model for Adaptive Asset Pricing
The paper proposes a new asset pricing model -- the News Embedding UMAP Selection (NEUS) model, to explain and predict the stock returns based on the financial news.
Time-Invariance Coefficients Tests with the Adaptive Multi-Factor Model
We show that for nearly all time periods with length less than 6 years, the beta coefficients are time-invariant for the AMF model, but not for the FF5 model.
The Low-volatility Anomaly and the Adaptive Multi-Factor Model
The paper provides a new explanation of the low-volatility anomaly.
FrequentNet: A Novel Interpretable Deep Learning Model for Image Classification
This paper has proposed a new baseline deep learning model of more benefits for image classification.
High-Dimensional Estimation, Basis Assets, and the Adaptive Multi-Factor Model
The paper proposes a new algorithm for the high-dimensional financial data -- the Groupwise Interpretable Basis Selection (GIBS) algorithm, to estimate a new Adaptive Multi-Factor (AMF) asset pricing model, implied by the recently developed Generalized Arbitrage Pricing Theory, which relaxes the convention that the number of risk-factors is small.
