Drop in your Binance or Bybit CSV export. An AI agent identifies revenge trading, overleverage, FOMO entries, and other psychological errors — with dollar attribution per error class. Runs locally. No API keys. No account linking.

A bot that scrapes open-interest and liquidation heatmaps to alert traders when a "Short Squeeze" or "Long Squeeze" is imminent.

众人的因子回测框架 stock factor test

An explainable modeling system that analyzes cryptocurrency prices as equilibrium outcomes shaped by market forces. This simulator computes force decompositions, equilibrium bands, tension scores, and scenario-based what-if simulations to reveal how demand, supply, volatility, liquidity, and speculation negotiate price.

A deep research study introducing the Gene Drift Hypothesis: a framework explaining how tokenomics mutate across market cycles. Analyzes evolutionary forces, selective pressures, behavioral traits, and economic genes that rise, fall, or mutate through bull/bear phases, shaping token species over time.

A research-grade exploration of the Tokenomics Ecological Framework, analyzing how tokens behave as predator, prey, parasite, and symbiotic species. Examines ecosystem interactions, evolutionary pressures, species population cycles, and the dynamics of economic predation, mutation, drift, and long-term survival across market cycles.

Replicate Barberis, Jin, and Wang (2021)

An end-to-end Python implementation of Cao et al.'s (2025) HLPPL methodology for the identification of financial (asset price) bubbles. Implements 7-parameter Log-Periodic Power Law model fitting, confidence-weighted sentiment analysis, regime-dependent 'BubbleScore' fusion, and Transformer-based forecasting with a backtesting framework.

Agent banking SDK with Agent FICO credit scoring (300-850), Merkle-anchored ledger integrity, behavioral finance, EWMA anomaly detection. Memory + payments + identity + fraud in one package. npm i @mnemopay/sdk

Replication of tables and figures of (BGLS, 2020) in Stata, R and Python. Not 100% perfectly the same as the original paper due to probable data misusage, ambiguous descriptions of some datasets in the paper or other reasons.

Rule-based NLP system for real-time cognitive bias detection (FOMO, loss aversion, confirmation bias) in Indonesian retail investor text. 94.7% accuracy, outperforms Gemini 3 Flash by 18.3pp. Dataset: 1,193 real posts from 5 platforms.

An analytical study of how Bitcoin market sentiment (Fear vs Greed Index) influences trading volume, leverage behavior, and profitability using historical data.

Pre-investment psychological checklist based on Munger's cognitive biases and behavioral finance research. Identify your blind spots before they cost you money.

A practical guide to recognizing and overcoming the 12 most dangerous cognitive biases in investing

AI Trading Psychology Coach inspired by "Billions" - Multi-agent behavioral finance coaching system

AI-powered Market Sentiment & Narrative Intelligence Platform

This repo contains the most important snippets of my masters thesis on the predictive power of Twitter emotions in the early months of the Covid-19 global health emergency

End-to-End Python implementation of Dávila-Fernández & Sordi's (2025) methodology for FX-constrained growth modeling (in emerging markets). Features Bayesian state-space estimation via Gibbs sampling with FFBS algorithm, heterogeneous agent simulation (fundamentalists/chartists), and nonlinear dynamics analysis.

University of Pennsylvania Senior Thesis (2021)

Research study exploring how behavioral biases like overconfidence, loss aversion, and herding influence investors’ decisions in the Indian securities market. It reveals why even smart investors make irrational choices, and how financial literacy transforms emotions into rational, informed investing.