Analyzing the Determinants of Long-Run Stock Returns

• 발행기관: 한국자료분석학회
• 저자명: Seung Doo Choi
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.5 No.4, 695~703쪽, 전체 9쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2003.12.30

영문 초록

This paper investigates the methods of analyzing the determinants of long-run stock returns using a sample of 204 privatization initial public offerings(IPOs) from 37 countries. The evidence indicates that an inference made without adjusting the effect of outlier tends to draw some false inference. This is because outliers tend to exaggerate the estimated levels of skewness or kurtoisis and thus require caution in using conventional parametric tests. In contrast, the quality of estimation tends to be improved by simply adjusting the effect of outliers on the inference, since the procedure serves to solve the heavy tail problems which have serious contaminations in estimations and tests. Specifically, the explanatory power of the test is much improved if we adopt outlier detection technique or the variance stabilization transformation of dependent variable.

목차

1. Introduction

2. Test of Long-run Returns

3. Data and Methodology

4. Analyzing the Determinants of Long-Run Returns

5. Conclusion

REFERENCES

키워드

Privatization IPO Long-run stock returns Outlier detection Variance smoothing