Quantitative Strategy

TEJ showcases its Factor Library and Earnings Call Transcripts at Neudata Hong Kong 2025, highlighting Taiwan-focused quant data for institutional strategies.

In recent years, the low-volatility anomaly has gained widespread attention for challenging traditional asset pricing theory. This article takes a closer look at one key driver behind the anomaly—Idiosyncratic Volatility (IVOL)—through a comprehensive analysis of the Taiwan stock market. Using point-in-time data from the TEJ Factor Library, we investigate the statistical behavior of IVOL, its relationship with stock characteristics, and its implications for cross-sectional return prediction. 

Building on the statistical foundation presented in Part 1, this article explores how Idiosyncratic Volatility (IVOL) can be effectively applied in investment strategy design. We present two categories of approaches: a single-factor sorting model and a set of filter-enhanced momentum strategies. Through robust backtesting across two decades of Taiwan stock market data, we demonstrate how IVOL can improve risk-adjusted performance when used as a portfolio filter—especially when combined with momentum or dividend-based signals.

Factor Library – TEJ's Factor Database for Quantitative Investing

Discover how TEJ's Taiwan Market Data captivated global investors at the Neudata London Summit 2025, offering unique insights into Asia's financial landscape.

Event-driven investing exploits pricing inefficiencies caused by significant corporate events. Discover common event-driven strategies and examples below.