42 citations · 82 across the 9 of their papers we have counts for
12 papers
When Does "Post-Call" Begin? An Availability Contract for Earnings-Call NLP Benchmarks
Xiaoyu Ma, Kelvin J. L. Koa, Yuncong Liu +1
Corporate financial disclosures often unfold over time, with announcements, prepared remarks, and discussion spanning multiple high-frequency return intervals. Financial NLP benchm…
Retrieval-Augmented Diffusion Modeling for Stochastic Discount Factor Portfolios
Kelvin J. L. Koa, Xinyang Li, Ke-Wei Huang
In this work, we study portfolio optimization under the stochastic discount factor (SDF) framework by learning market state representations that capture the underlying risk structu…
Self-Evolving Multi-Agent Symbolic Discovery for Financial Fundamental Analysis
Kelvin J. L. Koa, Filip Orestav, Shengqiong Wu +2
While symbolic regression (SR) has been successfully used in science to discover new equations, its use in financial valuation is hindered by several limitations. Whereas the natur…
AnalysisBank: An Expert Analysis Pattern Library for Financial Report Generation
Yajing Yang, Yunshan Ma, Kelvin J. L. Koa +1
We argue that financial report generation should operate at the analytical rather than structural level, composing content from data-derived insights rather than high-level topics…
SPACE: Sample-cloud Predictive Adaptive Conformal Ellipsoids for Multivariate Time-Series Forecasting
Baishi Li, Kelvin J. L. Koa, Ke-Wei Huang
Modern probabilistic time-series forecasters often express uncertainty through forecast samples. While typically converted into nominal prediction regions using empirical quantiles…
FinStressTS: A Parametric Synthetic Benchmark for Time-Series Forecasting in Finance
Jiaze Sun, Kelvin J. L. Koa, Ruiyang Ni +3
Financial forecasting is difficult due to low signal-to-noise ratios, latent factors, heavy tails, regime shifts, and jumps. Real-world benchmarks offer limited failure attribution…
The Proxy Presumption: From Semantic Embeddings to Valid Social Measures
Baishi Li, Ta Yu, Kelvin J. L. Koa +1
Natural Language Processing is rapidly evolving into a primary instrument for Computational Social Science, with researchers increasingly using embeddings to measure latent constru…
FinDeepForecast: A Live Multi-Agent System for Benchmarking Deep Research Agents in Financial Forecasting
Xiangyu Li, Xuan Yao, Guohao Qi +16
Deep Research (DR) Agents powered by advanced Large Language Models (LLMs) have fundamentally shifted the paradigm for completing complex research tasks. Yet, a comprehensive and l…
Reasoning on Time-Series for Financial Technical Analysis
Kelvin J. L. Koa, Jan Chen, Yunshan Ma +2
While Large Language Models have been used to produce interpretable stock forecasts, they mainly focus on analyzing textual reports but not historical price data, also known as Tec…
Temporal Relational Reasoning of Large Language Models for Detecting Stock Portfolio Crashes
Kelvin J. L. Koa, Yunshan Ma, Yi Xu +3
Stock portfolios are often exposed to rare consequential events (e.g., 2007 global financial crisis, 2020 COVID-19 stock market crash), as they do not have enough historical inform…
Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models
Kelvin J. L. Koa, Yunshan Ma, Ritchie Ng +1
Explaining stock predictions is generally a difficult task for traditional non-generative deep learning models, where explanations are limited to visualizing the attention weights…
Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction
Kelvin J. L. Koa, Yunshan Ma, Ritchie Ng +1
Multi-step stock price prediction over a long-term horizon is crucial for forecasting its volatility, allowing financial institutions to price and hedge derivatives, and banks to q…