Pin-Huang Chou Robin K. Chou Kuan-Cheng Ko National Central University

Slides:

Advertisements

Similar presentations

Dummy Variables. Introduction Discuss the use of dummy variables in Financial Econometrics. Examine the issue of normality and the use of dummy variables.

Advertisements

F-tests continued.

Introduction Describe what panel data is and the reasons for using it in this format Assess the importance of fixed and random effects Examine the Hausman.

Ordinary least Squares

Input Selections Matching Procedure Objectives Stock Performance Analyst Estimates OLS Regression Robustness Check Conclusions Viessmann European Research.

Data organization.

Motivation Hard to believe that productivity shocks drive the whole cycle We want to know their importance relative to demand shocks.

1 V. Simplifying the Portfolio Process. 2 Simplifying the Portfolio Process Estimating correlations Single Index Models Multiple Index Models Average.

MBA & MBA – Banking and Finance (Term-IV) Course : Security Analysis and Portfolio Management Unit I : Introduction to Security analysis Lesson No. 1.2-

Capital Asset Pricing Model and Single-Factor Models

Econometric Details -- the market model Assume that asset returns are jointly multivariate normal and independently and identically distributed through.

LECTURE 9 : EMPRICIAL EVIDENCE : CAPM AND APT

1 MF-852 Financial Econometrics Lecture 12 Case Studies in Financial Econometrics Roy J. Epstein Fall 2003.

Empirical Financial Economics The Efficient Markets Hypothesis Review of Empirical Financial Economics Stephen Brown NYU Stern School of Business UNSW.

The Role of Financial System in Economic Growth Presented By: Saumil Nihalani.

KYIV SCHOOL OF ECONOMICS Financial Econometrics (2nd part): Introduction to Financial Time Series May 2011 Instructor: Maksym Obrizan Lecture notes III.

McGraw-Hill/Irwin Copyright © 2005 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 10 Index Models.

Chapter 12 Jones, Investments: Analysis and Management

Comm W. Suo Slide 1. Comm W. Suo Slide 2 Diversification  Random selection  The effect of diversification  Markowitz diversification.

The Theory of Capital Markets Rational Expectations and Efficient Markets.

McGraw-Hill/Irwin Copyright © 2005 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 10 Index Models.

Chapter 9 CAPITAL ASSET PRICING AND ARBITRAGE PRICING THEORY The Risk Reward Relationship.

Market Efficiency.

Run length and the Predictability of Stock Price Reversals Juan Yao Graham Partington Max Stevenson Finance Discipline, University of Sydney.

1 Risk Changes Following Ex-Dates of Stock Splits Shen-Syan Chen National Taiwan University Robin K. Chou National Central University Wan-Chen Lee Ching.

Team member  Team manager: Lili Ma  Speaker: Liang Gao Chuan Sun  Technical support: Xiangyu Zheng Zhewei Gu.

1 Prospect theory, mental accounting, and momentum Grinblatt and Han JFE (2005)

1 Arbitrage risk and the book- to-market anomaly Ali, Hwang and Trombley JFE (2003)

Fixed Effects Model (FEM)

Negative underwriting loss turning into positive profit — Explore the role of investment income for U.S. Property and Casualty insurers Shuang Yang Department.

Does Academic Research Destroy Stock Return Predictability. R

Topic 3 (Ch. 8) Index Models A single-factor security market

F-tests continued.

Bounds and Prices of Currency Cross-Rate Options

Momentum and Reversal.

QM222 Class 9 Section A1 Coefficient statistics

Market Efficiency Chapter 12

Seasonality of Stock Market Returns

Equilibrium Asset Pricing

Vera Tabakova, East Carolina University

Unit 3 Hypothesis.

When does the market matter?

Author: Konstantinos Drakos Journal: Economica

Simposio de Análisis Económico - Diciembre 2008

Momentum Effect (JT 1993).

The Multiple Regression Model

Journal of Economics and Finance(2017) 41:311–329

Extrapolative Beliefs in the Cross-section

Efficient Market Hypothesis The Empirics

Introduction to Econometrics, 5th edition

Techniques for Data Analysis Event Study

Jump Processes and Trading Volume

Interval Estimation and Hypothesis Testing

Ch. 13. Pooled Cross Sections Across Time: Simple Panel Data.

Introduction to Time Series

Corporate governance, chief executive officer compensation, and firm performance 刘铭锋

Private Placements, Cash Dividends and Interests Transfer: Empirical Evidence from Chinese Listed Firms Source: International review of economics & finance,

Econometrics Analysis

Chapter 7: The Normality Assumption and Inference with OLS

Even-Tov O Journal of Accounting & Economics, 2017, 64(1).

Political uncertainty and cash holdings: Evidence from China

Lecturer Dr. Veronika Alhanaqtah

Behavioral Finance Economics 437.

Chapter 9 Dummy Variables Undergraduated Econometrics Page 1

Ch. 13. Pooled Cross Sections Across Time: Simple Panel Data.

Options Trading Activity and Firm Valuation

Measuring Exposure to Exchange Rate Fluctuations

Global Market Inefficiencies

Presentation transcript:

Pin-Huang Chou Robin K. Chou Kuan-Cheng Ko National Central University Empirical Determinants of Limit-hit Durations: Rational and Behavioral Perspectives Pin-Huang Chou Robin K. Chou Kuan-Cheng Ko National Central University

Introduction Definition of price limits. Pro and cons of price limits. Cool-off period. Market might be hurt. The limit-hit durations.

Introduction Kim and Limpaphayom (2000): determinants of limit-hit frequency. Complements Kim and Limpaphayom (2000) in: The impact of price-limit rule. Rational and behavioral perspectives. We empirically examine various determinants of limit-hit duration using censored duration models.

Limit-hit durations Definition: limit-hit duration is the length of period during which the trading price is locked at a limit price. Types of limit-hit durations: True duration. Left censored duration. Right censored duration. Two-sided censored duration.

Data Data source: Taiwan Economic Journal. Sample period: January 1997 to August 2000. The price limits are fixed at 7%. The thirty component stocks of the Taiwan Composite Index are selected as the sample.

The determinants Three categories of variables are considered: Cross-sectional determinants: Beta and Resi-var: GMM Beta estimator and the error term from market model. ME: the nature logarithm of the market capitalization. Lag daily information: Lag-ret: the daily return of previous trading day. Lag-turn: the daily turnover of previous trading day. Lag-pr: the daily price range of previous trading day. Lag-sr: the daily square return of previous trading day.

The determinants Self-related determinants: NHDUR: the previous non-hit duration. PHSIGN: a dummy variable of previous hit sign. PR: the price range between the opening of the trading day and the time of hit occurrence. PCTO: cumulative turnover up to the time of hit occurrence. CTO: cumulative turnover during the limit hit. NHDUR×PHSIGN.

Hypotheses Does systematic risk or firm’s specific risk matter? The sentiment effect (negative ME). Triggered by non-fundamental, transitory shocks (negative PR). The magnet effect (Negative PCTO). Overreaction hypothesis (Negative CTO).

Econometric model Let denote the true duration, where The censored duration model takes the regression form of , where is assumed to follow the Weibull distribution.

Empirical results Negative coefficient of ME supports the sentiment effect. Lag-ret and Lag-turn have significantly positive coefficients. NHDUR is positive.

Empirical results Negative coefficient of PR is supportive of transitory shocks. Negative PCTO is consistent with the magnet effect. Negative CTO indirectly supports the overreaction hypothesis.

Conclusion Limit-hit durations are affected by both rational and behavioral factors. Also, limit hits may have been triggered by magnet effect which suggests that limit hits are triggered by non-fundamental, transitory trades.