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http://dx.doi.org/10.13088/jiis.2022.28.3.105

Analysis of the relationship between interest rate spreads and stock returns by industry  

Kim, Kyuhyeong (College of Business Administration, Seoul National University of Science and Technology)
Park, Jinsoo (College of Business Administration, Seoul National University)
Suh, Jihae (College of Business Administration, Seoul National University of Science and Technology)
Publication Information
Journal of Intelligence and Information Systems / v.28, no.3, 2022 , pp. 105-117 More about this Journal
Abstract
This study analyzes the effects between stock returns and interest rate spread, difference between long-term and short-term interest rate through the polynomial linear regression analysis. The existing research concentrated on the business forecast through the interest rate spread focusing on the US market. The previous studies verified the interest rate spread based on the leading indicators of business forecast by moderating the period of long-term/short-term interest rates and analyzing the degree of leading. After the 7th reform of composite indices of business indicators in Korea of 2006, the interest rate spread was included in the items of composing the business leading indicators, which is utilized till today. Nevertheless, there are a few research on stock returns of each industry and interest rate spread in domestic stock market. Therefore, this study analyzed the stock returns of each industry and interest rate spread targeting Korean stock market. This study selected the long-term/short-term interest rates with high causality through the regression analysis, and then understood the correlations with each leading period and industry. To overcome the limitation of the simple linear regression analysis, polynomial linear regression analysis is used, which raised explanatory power. As a result, the high causality was verified when using differences between returns of corporate bond(AA-) without guarantee for three years by leading six months and call rate returns as interest rate spread. In addition, analyzing the stock returns of each industry, the relation between the relevant interest rate spread and returns of the automobile industry was the closest. This study is significant in the aspect of verifying the causality of interest rate spread, business forecast, and stock returns in Korea. Even though it could be limited to forecast the stock price by using only the interest rate spread, it would be working as a strong factor when it is properly utilized with other various factors.
Keywords
Interest Rate Spread; Stock Returns; Polynomial Linear Regression Analysis; Domestic Stock Market;
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1 Saraiva Catarina, Matthews Steve and Marte Jonnelle(2022. Jul 13)Fed could weigh historic 100 Basis-Point hike after inflation scorcher. Bloomberg. https://www.bloomberg.com/news/articles/2022-07-13/fed-could-weigh-historic100-basis-point-hike-after-cpi-scorcher
2 김민국, & 이한식. (2019). 금리스프레드의 경기예측력 비교분석. 통계연구, 24(1), 1-25.   DOI
3 김용찬, 박진수, & 서지혜. (2018). 엔티티 간의 관계명을 생성하는 알고리즘: 반자동화된 스키마 통합. 지능정보연구, 24(3), 243-262.   DOI
4 김원기 & 곽노선. (2012). Leading Behavior of Interest Rate Term Spreads and Credit Risk Spreads in Korea. 금융연구, 26(4), 1-25.
5 김재경, 서지혜, 안도현, & 조윤호. (2002). 협업 필터링 기법을 활용한 개인화된 상품 추천 방법론 개발에 관한 연구. 지능정보연구, 8(2), 139-157 .
6 지호준, & 박상규. (2002). 금리 스프레드의 경기 예측력 평가. 재무관리연구, 19(2), 233-251.
7 오정근. (1997). 金利스프레드와 通貨政策. 한국은행
8 이근영. (2013). 금융변수의 불황예측력 비교. 금융연구, 27(1), 29-69.
9 허찬국, 김창배, & 남광희. (2014). 미국의 양적 완화 축소가 국내 금리, 환율, 자본유입에 미치는 영향분석. 한국경제연구, 32(3), 49-77.
10 Estrella, A., & Hardouvelis, G. A. (1991). The term structure as a predictor of real economic activity. The journal of Finance, 46(2), 555-576.   DOI
11 Falk, R. F., & Miller, N. B. (1992). A primer for soft modeling. University of Akron Press.
12 Ross Jenna(2002. Jul 4) Interest rate hikes vs inflation:How are different countries doing it?. World Economic Forum. https://www.weforum.org/agenda/2022/07/interest-rate-hikes-inflation-rate-economy/
13 김기범, & 구본일. (2019). 우리나라 기간 스프레드의 경기예측력 증가 원인. 금융연구, 33(1), 69-103.
14 김유성, 박영석, 엔티티 간의 관계명을 생성하는 알고리즘: 반자동화된 스키마 통합이정진. (2004). 장단기 금리 스프레드를 이용한 주식시장 마켓타이밍 전략의 유용성에 관한 실증분석. 한국증권학회지, 33(4), 135-173.
15 조미현(2022. Jul 13) 한은, 사상 첫 빅스텝...기준금리 8년 만에 연 2.25%. 한국경제신문. https://www.hankyung.com/economy/article/202207134538i
16 오정은(2022. Jul 13)"환율 1300원에 금리까지 뛴다" 2300선'맴맴 코스피 향방은... 머니투데이. https://news.mt.co.kr/mtview.php?no=2022071310080342878
17 은희문 & 백재승. (2020). 금리 스프레드의 경제 예측력에 관한 비교 연구: 스프레드 구간과 금융위기 전후 분석을 중심으로. 기업경영연구, 27(2), 107-127.
18 이창선. (2001). 금리 스프레드의 경기예측력에 관한 연구. LG 경제연구원 연구보고서.
19 Bernanke, B. S. (1990). On the predictive power of interest rates and interest rate spreads.
20 Estrella, A., & Mishkin, F. S. (1996). The yield curve as a predictor of US recessions. Current issues in economics and finance, 2(7).
21 James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 112, p. 18). New York: springer.
22 이정. (2022). 대선 관련 인터넷 뉴스의 댓글과 대댓글 간 비교를 통해 살펴본 온라인 토론의 진행 가능성. 지능정보연구, 28(2), 33-55   DOI
23 Stock, J. H., & Watson, M. W. (1989). New indexes of coincident and leading economic indicators. NBER macroeconomics annual, 4, 351-394.   DOI
24 Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of financial economics, 116(1), 1-22.   DOI
25 Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Routledge.