Introduction of AI Quant Investment

Jul 19, 2026·
Yao Tung Huang (Don HUANG)
Yao Tung Huang (Don HUANG)
· 1 min read
Abstract
This lecture covers three modules: quantitative investment and market anomalies (value, quality, momentum, low-volatility, size, and reversal factors), behavioral biases and institutional dynamics (prospect theory, disposition effect, anchoring, overconfidence, and herd behavior), and an AI Agent demo showing how to audit data, challenge backtests, and build disciplined investment workflows.
Date
Jul 19, 2026
Event
Online Live Lecture
Location

Online

课程简介

本次线上直播课程面向个人投资者,以"别和机器拼手速"为主题,系统讲解如何借鉴量化投资思维、识别行为误区、善用 AI 工具来提升投资决策质量。课程分为三大模块:第一模块介绍量化投资的基本框架与六类经典投资因子(价值、质量、动量、低波动、规模、短期反转),结合 A 股真实案例讲解因子的适用场景、失效风险与回测陷阱;第二模块通过六个互动测验,剖析前景理论、处置效应、锚定效应、过度自信、羊群效应等行为偏误如何影响交易决策,并介绍 Pre-mortem 等纪律工具;第三模块现场演示 AI Agent 在投资研究中的应用,包括数据质量审查、因子解释与冲突分析、回测审计、多角色投资委员会模拟,以及 Human-in-the-loop 决策流程。

Course Overview

This two-hour online lecture, themed “Don’t Race Against Machines,” equips individual investors with a scientific, reproducible investment decision framework. Module 1 introduces quantitative investing fundamentals and six classic factor families (value, quality, momentum, low-volatility, size, and short-term reversal), illustrated with real A-share market cases covering factor applicability, failure risks, and backtest pitfalls. Module 2 uses six interactive quizzes to dissect behavioral biases—prospect theory, disposition effect, anchoring, overconfidence, and herding—and presents disciplinary tools such as Pre-mortem analysis. Module 3 demonstrates AI Agent applications in investment research, including data quality auditing, factor interpretation and conflict analysis, backtest review, multi-role investment committee simulation, and Human-in-the-loop decision workflows.

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