The Efficient Market Hypothesis for Bitcoin in the context of neural networks
@article{Kraehenbuehl2022TheEM, title={The Efficient Market Hypothesis for Bitcoin in the context of neural networks}, author={Mike Kraehenbuehl and Joerg Osterrieder}, journal={ArXiv}, year={2022}, volume={abs/2208.07254} }
This study examines the weak form of the efficient market hypothesis for Bitcoin using a feedforward neural network. Due to the increasing popularity of cryptocurrencies in recent years, the question has arisen, as to whether market inefficiencies could be exploited in Bitcoin. Several studies we refer to here discuss this topic in the context of Bitcoin using either statistical tests or machine learning methods, mostly relying exclusively on data from Bitcoin itself. Results regarding market ef…
Figures and Tables from this paper
table 1 figure 1 table 2 figure 2 table 3 figure 3 figure 4 figure 5 figure 6 table 6 figure 8 figure 9 figure 10 figure 12 figure 14 figure 16 figure 17 figure 18 figure 19 figure 21 figure 22 figure 23 figure 25 figure 27 figure 28 figure 29 figure 31 figure 33 figure 34 figure 35 figure 37 figure 39 figure 40 figure 41 figure 43 figure 45 figure 46 figure 47 figure 49 figure 51 figure 52 figure 53 figure 55 figure 57 figure 58 figure 59 figure 61 figure 63 figure 64 figure 65
References
SHOWING 1-10 OF 56 REFERENCES
Bitcoin and market-(in)efficiency: a systematic time series approach
- EconomicsDigital Finance
- 2019
Recently, cryptocurrencies have received substantial attention by investors given their innovative features, simplicity and transparency. We here analyze the increasingly popular Bitcoin and verify…
Short-Term Bitcoin Market Prediction via Machine Learning
- Computer Science
- 2021
Bitcoin price prediction using machine learning: An approach to sample dimension engineering
- Computer ScienceJ. Comput. Appl. Math.
- 2020
What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis
- EconomicsPloS one
- 2015
It is found that the Bitcoin forms a unique asset possessing properties of both a standard financial asset and a speculative one.
Time-series forecasting of Bitcoin prices using high-dimensional features: a machine learning approach
- Computer ScienceNeural Computing and Applications
- 2020
This paper demonstrates high-performance machine learning-based classification and regression models for predicting Bitcoin price movements and prices in short and medium terms, and indicates that the presented models outperform the existing models in the literature.
Predicting bitcoin returns using high-dimensional technical indicators
- Computer Science, EconomicsThe Journal of Finance and Data Science
- 2019
The Inefficiency of Bitcoin
- Economics, Mathematics
- 2016
Bitcoin has received much attention in the media and by investors in recent years, although there remains scepticism and a lack of understanding of this cryptocurrency. We add to the literature on…
Efficiency, multifractality, and the long-memory property of the Bitcoin market: A comparative analysis with stock, currency, and gold markets
- Economics, BusinessFinance Research Letters
- 2018
On the Relationship of Cryptocurrency Price with US Stock and Gold Price Using Copula Models
- Computer ScienceMathematics
- 2020
The empirical findings show that S&P 500 and Gold price are statistically significant to Bitcoin in terms of log-return and volatility.