Search Results for author:
Found 8 papers, 0 papers with code
Towards Enhanced Local Explainability of Random Forests: a Proximity-Based Approach
We initiate a novel approach to explain the out of sample performance of random forest (RF) models by exploiting the fact that any RF can be formulated as an adaptive weighted K nearest-neighbors model.
Towards reducing hallucination in extracting information from financial reports using Large Language Models
For a financial analyst, the question and answer (Q\&A) segment of the company financial report is a crucial piece of information for various analysis and investment decisions.
Company Similarity using Large Language Models
Identifying companies with similar profiles is a core task in finance with a wide range of applications in portfolio construction, asset pricing and risk attribution.
Quantifying Outlierness of Funds from their Categories using Supervised Similarity
Mutual fund categorization has become a standard tool for the investment management industry and is extensively used by allocators for portfolio construction and manager selection, as well as by fund managers for peer analysis and competitive positioning.
Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey
In this article, we present a comprehensive survey on domain specification techniques for large language models, an emerging direction critical for large language model applications.
Learning Embedded Representation of the Stock Correlation Matrix using Graph Machine Learning
In particular, the algorithm compresses the network into a lower dimensional continuous space, called an embedding, where pairs of nodes that are identified as similar by the algorithm are placed closer to each other.
Learning Mutual Fund Categorization using Natural Language Processing
Categorization of mutual funds or Exchange-Traded-funds (ETFs) have long served the financial analysts to perform peer analysis for various purposes starting from competitor analysis, to quantifying portfolio diversification.
Supervised similarity learning for corporate bonds using Random Forest proximities
Financial literature consists of ample research on similarity and comparison of financial assets and securities such as stocks, bonds, mutual funds, etc.
