지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2020.6
- 수록면
- 133 - 144 (12page)
- DOI
- 10.33162/JAR.2020.6.20.2.133
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Purpose: Recently, the art market has been attracting several investors owing to growing interest toward alternative investment. In this study, to enhance our understanding of the art market, we test the pricing difference in artwork under various segments and further study the return on investment.
Methods: The hedonic pricing approach investigates the relation between characteristics of artworks and their corresponding prices. Thus, our model, based on hedonic quantile regression, considers a complete characterization of the conditional distribution for the response variables.
Results: We used segmented art market data collected between 2014 and 2018 from South Korea. The results of hedonic quantile regression show no evidence that more expensive artworks tend to generate higher returns. The artworks traded in the online art market follow a different pricing mechanism compared to those in the offline art market. The return on investment for arts in general shows a downward trend, and online auctions result in lower financial returns.
Conclusion: We investigate the relation between art pricing factors and financial returns in the segmented art market using hedonic quantile regression empirically. We may consider the absence of masterpiece artworks, which generate the “masterpiece effect” in auctions, for further research.
Methods: The hedonic pricing approach investigates the relation between characteristics of artworks and their corresponding prices. Thus, our model, based on hedonic quantile regression, considers a complete characterization of the conditional distribution for the response variables.
Results: We used segmented art market data collected between 2014 and 2018 from South Korea. The results of hedonic quantile regression show no evidence that more expensive artworks tend to generate higher returns. The artworks traded in the online art market follow a different pricing mechanism compared to those in the offline art market. The return on investment for arts in general shows a downward trend, and online auctions result in lower financial returns.
Conclusion: We investigate the relation between art pricing factors and financial returns in the segmented art market using hedonic quantile regression empirically. We may consider the absence of masterpiece artworks, which generate the “masterpiece effect” in auctions, for further research.
목차
1. 서론
2. 방법론
3. 데이터 및 변수
4. 분석 결과
5. 결론
References
참고문헌 (38)
참고문헌 신청
C. McAndrew / 2007 / The collateral value of fine art / J. of Banking & Finance 31(3):589~607
J. Mei / 2002 / Are investors credulous? some preliminary evidence from art auctions
A. C. Worthington / 2006 / A note on financial risk, return and asset pricing in australian modern and contemporary art / J. of Cultural Econ. 30(1):73~84
W. J. Baumol / 1986 / Unnatural value: or art investment as floating crap game / Am. Econ. Rev. 76(2):10~14
B. S. Frey / 1995 / On the return of art investment return analyses / J. of Cultural Econ. 19(3):207~220
J. Mei / 2002 / Are investors credulous? some preliminary evidence from art auctions
A. C. Worthington / 2006 / A note on financial risk, return and asset pricing in australian modern and contemporary art / J. of Cultural Econ. 30(1):73~84
W. J. Baumol / 1986 / Unnatural value: or art investment as floating crap game / Am. Econ. Rev. 76(2):10~14
B. S. Frey / 1995 / On the return of art investment return analyses / J. of Cultural Econ. 19(3):207~220
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