1 citations · 1 across the 6 of their papers we have counts for
6 papers
What Makes a Peer? Valuation-Anchored Similarity in Private Markets
Sebastian Frank, Jingrao Lyu, Max Jarmey +5
As more investors contemplate private markets and contend with limited transparency, sparse disclosures, and infrequent transactions, identifying economically meaningful peer compa…
STRAPSim: A Portfolio Similarity Metric for ETF Alignment and Portfolio Trades
Mingshu Li, Dhruv Desai, Jerinsh Jeyapaulraj +4
Accurately measuring portfolio similarity is critical for a wide range of financial applications, including Exchange-traded Fund (ETF) recommendation, portfolio trading, and risk a…
Explainable Unsupervised Anomaly Detection with Random Forest
Joshua S. Harvey, Joshua Rosaler, Mingshu Li +2
We describe the use of an unsupervised Random Forest for similarity learning and improved unsupervised anomaly detection. By training a Random Forest to discriminate between real d…
How to Choose a Threshold for an Evaluation Metric for Large Language Models
Bhaskarjit Sarmah, Mingshu Li, Jingrao Lyu +4
To ensure and monitor large language models (LLMs) reliably, various evaluation metrics have been proposed in the literature. However, there is little research on prescribing a met…
Case-based Explainability for Random Forest: Prototypes, Critics, Counter-factuals and Semi-factuals
Gregory Yampolsky, Dhruv Desai, Mingshu Li +2
The explainability of black-box machine learning algorithms, commonly known as Explainable Artificial Intelligence (XAI), has become crucial for financial and other regulated indus…
Quantile Regression using Random Forest Proximities
Mingshu Li, Bhaskarjit Sarmah, Dhruv Desai +4
Due to the dynamic nature of financial markets, maintaining models that produce precise predictions over time is difficult. Often the goal isn't just point prediction but determini…