Dissertations, Theses, and Capstone Projects
Date of Degree
6-2026
Document Type
Doctoral Dissertation
Degree Name
Doctor of Philosophy
Program
Business
Advisor
Robert A. Schwartz
Committee Members
Jian Hua
Jun Wang
Nazli Sila Alan
Subject Categories
Business
Abstract
This dissertation provides empirical tests of both the weak and semi-strong forms of market efficiency by examining how prices adjust across different market structures and information environments. It proposes a reinterpretation of technical analysis that shifts the focus away from short-term return prediction toward the economic role of technical signals in the price-discovery process. Rather than viewing technical trading as inherently trend-following and liquidity-taking, this dissertation argues that technical signals can be understood as indicators of price-discovery noise arising from heterogeneous investor expectations and market frictions. Within this framework, technical trading strategies can be designed to function as liquidity-supplying mechanisms that stabilize prices while remaining profit-seeking.
The dissertation develops a contrarian, correlation-based technical trading strategy that conditions trade timing and size on indicators including the variance ratio, return autocorrelation, momentum, and order imbalance. These signals are designed to identify market states characterized by elevated short-horizon volatility, price overshooting, and an increased likelihood of subsequent reversal. By trading against short-term price pressure during such periods and unwinding positions as prices revert, the strategy supplies liquidity when it is most needed while exploiting mean-reversion dynamics.
Chapter 1 introduces the dissertation and outlines its central research question and framework. Chapter 2 reviews the literature on the Efficient Market Hypothesis (EMH) and technical analysis. Chapters 3 and 4 empirically test the weak form of the EMH by implementing the strategy in two distinct market settings: call auction markets and continuous trading markets. In call auctions, where orders are pooled and executed at discrete clearing prices, the batching mechanism naturally filters short-term noise and concentrates liquidity provision. The strategy generates positive and statistically significant mark-to-market cash flows across exchanges and sample years, with profitability strengthening during periods of heightened volatility. In continuous markets, where prices evolve sequentially as orders arrive, the strategy is implemented using limit orders to maintain its liquidity-providing role. The results show that the strategy continues to deliver positive and economically meaningful cash flows, particularly during volatile periods. Together, these findings challenge the weak form of market efficiency by demonstrating that past price dynamics contain economically meaningful information about liquidity needs and price overshooting.
Chapter 5 extends the analysis to the semi-strong form of the EMH by examining price dynamics around stock split announcements. Using the variance ratio as a proxy for price-discovery noise, the results show that short-horizon volatility is elevated prior to the announcement, remains elevated and often intensifies during the announcement-to-effective window, and then declines toward the random-walk benchmark after implementation. This pattern indicates that price discovery around public news is noisy rather than instantaneous, contradicting the semi-strong form of market efficiency and suggesting that correlation-based technical signals remain informative in the presence of publicly available information.
Overall, this dissertation demonstrates that departures from both weak and semi-strong market efficiency are closely linked to non-instantaneous price discovery. By grounding technical analysis in the economics of price formation, this work provides a unified framework for testing market efficiency, understanding liquidity dynamics, and designing trading strategies that both stabilize markets and generate sustainable profits. The dissertation concludes by outlining future research directions, including controlled market-simulation experiments and the potential role of artificial intelligence in adaptive liquidity provision.
Recommended Citation
Kong, Lingyi, "Studies in the Efficient Market Hypothesis, Technical Analysis, and Return Autocorrelation" (2026). CUNY Academic Works.
https://academicworks.cuny.edu/gc_etds/6668
