Loading...
Search
Search in this resource
sort by
Send to Friend
 Digital Object List
 Bookmark
 Review List
  1. بررسی قدرت پیش بینی کنندگی رفتار هیجانی سرمایه گذاران در بازده رمزارزها
بررسی قدرت پیش بینی کنندگی رفتار هیجانی سرمایه گذاران در بازده رمزارزها
169 viewed

بررسی قدرت پیش بینی کنندگی رفتار هیجانی سرمایه گذاران در بازده رمزارزها

هجران فر، محمد رضا Hejranfar, Mohammad Reza

The Predicting Power of Investors’ Sentiment for Cryptocurrency Returns

Hejranfar, Mohammad Reza | 2022

169 Viewed
  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55595 (44)
  4. University: Sharif University of Technology
  5. Department: Management and Economics
  6. Advisor(s): Arian, Hamid Reza; Hagh Panah, Farshad
  7. Abstract:
  8. Classical financial literature believes that people's decisions in financial markets are rational and that asset prices remain at their intrinsic value. On the other hand, behavioral finance literature believes that there are limitations in investors' decision-making and the impact of decisions on emotions, and states that investors' emotions directly affect asset prices. The aim of this research is to investigate which of the famous indicators introduced in the literature as a representative of the emotional behavior of investors has a better performance in predicting the returns of cryptocurrencies. For this purpose, in the first step, the information related to the calculation of three indicators that represent emotional behavior, including the analysis of the opinions of Twitter users, EMSI and ARMS, was collected and the effect of emotional behavior on the performance of the current period was investigated. The results of the research are in line with the behavioral finance literature and show that all three indicators have a significant effect on returns. Also, by adding the emotional index, the explanatory power of the model with the previous lag of return increased. In the second step, in order to examine the main question of the research, the previous interruptions of the emotional behavior of all three models were placed and it was observed that the first lag of all three indicators had a significant effect on the return of cryptocurrencies, which provides good evidence in against the strong inefficiency of the market. It provides evidence for the predictability of cryptocurrency market. In the following, numerically and using the recursive window, it is shown that on average, all three indicators outperform the holding strategy, and among the indices, on average, the EMSI index, which expresses the same correlation between returns and 30-day standard deviation of returns, outperforms other indices.
  9. Keywords:
  10. Asset Pricing Model ; Cryptocurrency ; Sentiment Analysis ; ARMS Index ; Return Prediction ; Bitcoin ; Investors’ Sentiment ; Twitter Posts Analysis

 Digital Object List

 Bookmark

No TOC