Bighead's Algorithm Notes
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Bighead's Algorithm Notes

Focused on AI applications in the fintech sector

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Bighead's Algorithm Notes
Bighead's Algorithm Notes
Nov 9, 2025 · Artificial Intelligence

How Heuristic‑Guided Inverse Reinforcement Learning Boosts Portfolio Optimization

The article presents a heuristic‑guided inverse reinforcement learning framework that generates expert strategies respecting industry diversification and correlation constraints, employs a multi‑objective reward to balance return and risk, and uses a heterogeneous graph attention network to model stock relationships, achieving superior risk‑adjusted returns on CSI‑300, CSI‑500, NASDAQ‑100 and S&P‑500 benchmarks.

financial AIgraph neural networkheuristic expert policy
0 likes · 13 min read
How Heuristic‑Guided Inverse Reinforcement Learning Boosts Portfolio Optimization
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Nov 8, 2025 · Artificial Intelligence

Time-Series Paper Digest: Nov 1‑7 2025 Highlights

This digest summarizes three recent AI papers—DoFlow, Forecast2Anomaly, and ForecastGAN—detailing their causal generative flow model for interventions, a retrieval‑augmented framework for zero‑shot anomaly prediction, and a decomposition‑based adversarial approach that improves multi‑horizon forecasting across diverse datasets.

anomaly detectioncausal inferencedeep learning
0 likes · 8 min read
Time-Series Paper Digest: Nov 1‑7 2025 Highlights
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Nov 7, 2025 · Artificial Intelligence

Weekly AI Finance Paper Digest (Nov 1‑7 2025)

This digest summarizes three recent AI‑driven finance papers—DeltaLag’s dynamic lead‑lag detection, MS‑HGFN’s multi‑scale graph network for stock movement, and LiveTradeBench’s real‑time LLM trading benchmark—highlighting their methods, datasets, and performance gains.

Large Language Modelfinancial AIgraph neural network
0 likes · 8 min read
Weekly AI Finance Paper Digest (Nov 1‑7 2025)
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Nov 4, 2025 · Artificial Intelligence

Key Quantitative Finance Papers from WWW2025 – Summaries & Insights

This article compiles concise English summaries of recent AI-driven quantitative finance papers presented at WWW2025, covering novel stock‑price forecasting frameworks such as CSPO, MERA, Ploutos, DINS, HedgeAgents, HRFT, and IDED, with links to the original PDFs, code repositories, authors, and abstracts.

deep learningfinancial AImachine learning
0 likes · 13 min read
Key Quantitative Finance Papers from WWW2025 – Summaries & Insights
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Nov 1, 2025 · Artificial Intelligence

Recent Time-Series Research Summaries (Oct 25‑31 2025)

This article presents concise summaries of five newly released arXiv papers on time‑series forecasting and causal discovery, highlighting each work’s objectives, proposed methods such as FreLE, selective learning, TempoPFN, and DOTS, and the reported experimental improvements.

causal discoveryselective learningspectral bias
0 likes · 8 min read
Recent Time-Series Research Summaries (Oct 25‑31 2025)
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Oct 31, 2025 · Artificial Intelligence

Weekly Quantitative Paper Digest (Oct 25‑31 2025)

This article summarizes six recent arXiv papers that explore how large language models, graph‑theoretic methods, generative frameworks, hypergraph multimodal architectures, GroupSHAP‑enhanced forecasting, and multi‑agent LLM workflows can improve financial signal extraction, portfolio optimization, and stock‑price prediction, providing empirical results on S&P 500 data.

LLMMultimodal Learningfinancial AI
0 likes · 13 min read
Weekly Quantitative Paper Digest (Oct 25‑31 2025)
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Oct 30, 2025 · Artificial Intelligence

FinSearchComp: ByteDance’s Expert‑Level Financial Search and Reasoning Benchmark for Real‑World Scenarios

FinSearchComp is the first fully open‑source benchmark that evaluates large‑language‑model agents' search and reasoning abilities in realistic financial workflows, featuring 635 expert‑annotated questions across three task types, built with 70 finance experts, and revealing that web‑enabled models with financial plugins markedly outperform API‑only models.

AI evaluationFinSearchCompLLM agents
0 likes · 12 min read
FinSearchComp: ByteDance’s Expert‑Level Financial Search and Reasoning Benchmark for Real‑World Scenarios
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Oct 28, 2025 · Artificial Intelligence

Paper Review: THEME – Thematic Investing via Stock Semantic Embeddings and Temporal Dynamics

The article reviews the THEME framework, which tackles static and coverage limitations of traditional thematic investing by constructing a large Thematic Representation Set (TRS) and applying a two‑stage hierarchical contrastive learning process that first aligns stock text embeddings with theme semantics and then refines them with short‑term return dynamics, achieving superior retrieval and portfolio performance across extensive experiments.

financial AIhierarchical contrastive learningportfolio optimization
0 likes · 12 min read
Paper Review: THEME – Thematic Investing via Stock Semantic Embeddings and Temporal Dynamics
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Oct 26, 2025 · Artificial Intelligence

How Shapelet-Based Patterns Predict Financial Market Direction

The article presents a two‑stage framework—SIMPC for invariant multivariate pattern clustering and JISC‑Net for shape‑subclass detection—that achieves accurate and interpretable financial market direction forecasts, outperforming strong baselines on Bitcoin and S&P 500 datasets across most metric‑dataset combinations.

DTWDirection PredictionInterpretability
0 likes · 11 min read
How Shapelet-Based Patterns Predict Financial Market Direction
Bighead's Algorithm Notes
Bighead's Algorithm Notes
Oct 25, 2025 · Artificial Intelligence

Time Series Paper Digest: Extreme Event Prediction, Multimodal Fusion & Anomaly Detection

This article summarizes four recent arXiv papers on time‑series forecasting, covering a hierarchical knowledge‑distillation framework for extreme events, a graph‑enhanced multimodal fusion network, an interpretable unsupervised anomaly detector, and an adaptive masking loss that improves prediction accuracy.

adaptive maskinganomaly detectionexpert mixture
0 likes · 10 min read
Time Series Paper Digest: Extreme Event Prediction, Multimodal Fusion & Anomaly Detection