DOI QR코드

DOI QR Code

Research on Determine Buying and Selling Timing of US Stocks Based on Fear & Greed Index

Fear & Greed Index 기반 미국 주식 단기 매수와 매도 결정 시점 연구

  • 홍성혁 (백석대학교 첨단IT학부, IoT 전공)
  • Received : 2022.10.07
  • Accepted : 2023.01.20
  • Published : 2023.01.28

Abstract

Determining the timing of buying and selling in stock investment is one of the most important factors to increase the return on stock investment. Buying low and selling high makes a profit, but buying high and selling low makes a loss. The price is determined by the quantity of buying and selling, which determines the price of a stock, and buying and selling is also related to corporate performance and economic indicators. The fear and greed index provided by CNN uses seven factors, and by assigning weights to each element, the weighted average defined as greed and fear is calculated on a scale between 0 and 100 and published every day. When the index is close to 0, the stock market sentiment is fearful, and when the index is close to 100, it is greedy. Therefore, we analyze the trading criteria that generate the maximum return when buying and selling the US S&P 500 index according to CNN fear and greed index, suggesting the optimal buying and selling timing to suggest a way to increase the return on stock investment.

주식 투자에서 매수와 매도의 타이밍을 결정하는 것은 주식 투자의 수익률 올리기 위해 가장 중요한 요인 중에 하나이다. 주식은 싸게 사서 비싸게 팔면 이익이 되지만, 비싸게 사서 싸게 팔면 손해가 된다. 주식의 가격을 결정하는 매수와 매도의 물량에 의해 가격이 결정이 되고, 매수와 매도는 기업실적, 경제지표와도 관련이 있다. CNN에서 제공하는 공포와 탐욕지수는 7가지 요소를 사용하고, 각 요소에 가중치를 부여하여 탐욕과 두려움으로 정의한 가중치 평균을 0~100 사이의 척도로 계산하여 매일 발표하고 있다. 지수가 0에 가까우면 주식시장 심리가 두려운것이고, 100에 가까우면 탐욕스러운 것이다. 따라서 미국 S&P 500 지수를 CNN 공포와 탐욕지수에 따른 매수와 매도를 할 경우 최대 수익률이 발생하는 매매 기준을 분석하여 최적의 매수와 매도 타이밍을 제시하여 주식투자에 수익률을 높일 수 있는 방안을 제시하고자 한다.

Keywords

Acknowledgement

This research was conducted with the support of Baekseok University Research Fund in 2022.

References

  1. Sang-Hoon Lee. (2006). Unilateral sale of treasury stock to specific shareholders, in violation of the principle of shareholder equality. Laws and institutions, 1-4.
  2. Hong, S. (2020). A Research on stock price prediction based on Deep Learning and Economic Indicators. Journal of Digital Convergence, 18(11), 267-272. https://doi.org/10.14400/JDC.2020.18.11.267
  3. Hao, J., & Zhang, J. E. (2013). GARCH option pricing models, the CBOE VIX, and variance risk premium. Journal of Financial Econometrics, 11(3), 556-580. https://doi.org/10.1093/jjfinec/nbs026
  4. Atkins, A. B., & Dyl, E. A. (1997). Market structure and reported trading volume: NASDAQ versus the NYSE. Journal of Financial Research, 20(3), 291-304. https://doi.org/10.1111/j.1475-6803.1997.tb00250.x
  5. Lento, C., & Gradojevic, N. (2021). S&P 500 index price spillovers around the COVID-19 market meltdown. Journal of Risk and Financial Management, 14(7), 330.
  6. Subrahmanyam, A. (2018). Equity market momentum: A synthesis of the literature and suggestions for future work. Pacific-Basin Finance Journal, 51, 291-296. https://doi.org/10.1016/j.pacfin.2018.08.004
  7. Bhowmik, R., & Wang, S. (2020). Stock market volatility and return analysis: A systematic literature review. Entropy, 22(5), 522.
  8. Cao, Z., Lv, D., & Sun, Z. (2021). Stock price manipulation, short-sale constraints, and breadth-return relationship. Pacific-Basin Finance Journal, 67, 101556.
  9. Varma, J. R. (2002). Mispricing of volatility in the Indian index options market.
  10. Badruzaman, J. (2019). Analysis relative strength index and earning per share on stock price. Hasil Reviewer, 12(4), 1-9. https://doi.org/10.9734/ajeba/2019/v12i430157
  11. Du, Q. (2020). Fear or Greed? How Retail Trades Move Markets?.
  12. Lina, L., Leeb, C. I., & Syuc, S. J. Fear vs. Greed: The Full Picture of the Autocorrelation in Market Volatility Index.
  13. Serur, J. A., Dapena, J. P., & Siri, J. R. (2021). Decomposing the VIX Index into Greed and Fear. Serie Documentos de Trabajo-Nro, 780.
  14. Liutvinavicius, M., Sakalauskas, V., & Kriksciuniene, D. (2020). Sentiment-Based Decision Making Model for Financial Markets. In Data Science: New Issues, Challenges and Applications (pp. 297-313). Springer, Cham.
  15. Elyasiani, E. (2018). The risk-asymmetry index as a new measure of risk. 34190693X.
  16. MathsIsFun.com (2022) retrieved from https://www.mathsisfun.com/data/correlation.html
  17. Li, C. A., & Chi, W. J. (2013). The influences of greed and fear on fund performance. The International Journal of Business and Finance Research, 7(5), 47-57.
  18. Serur, J. A., Dapena, J. P., & Siri, J. R. (2021). Decomposing the VIX Index into Greed and Fear. Serie Documentos de Trabajo-Nro, 780.
  19. SRIVASTAVA, V. (2020). IMPACT OF FEAR AND GREED IN FINANCIAL MARKET. Editorial Boards, 55.
  20. Frino, A., & Gallagher, D. R. (2001). Tracking S&P 500 index funds. The Journal of Portfolio Management, 28(1), 44-55.