The Relationship Between Bitcoin and Stock Market

The Relationship Between Bitcoin and Stock Market

Xin Wang (Saint Peter's University, USA), Xi Chen (Beijing University of Civil Engineering and Architecture, China) and Peng Zhao (Intelligentrabbit, LLC., USA)
DOI: 10.4018/IJORIS.2020040102


This article analyzes the relationship between Bitcoin and the stock market by using a vector autoregressive model. To enhance the impulse response signal, the Sliding Window technique is applied. Study results show the relationship between Bitcoin and the stock market. First, the S&P 500 has a relatively significant effect on Bitcoin, while the influence caused by the S&P 500 is weak. In addition, after involving the Sliding Window technique, the effects caused by the standard deviation of the S&P 500 and the mean of the Dow Jones are remarkably strong on the mean of Bitcoin and the standard deviation of the S&P 500 has a comparatively significant effect on the standard deviation of Bitcoin as well. Generally, the S&P 500 and the Dow Jones indexes have an advantageous effect on Bitcoin. Financial investment can be made based on this model and conclusion.
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Bitcoin, regarded as a new type of new digital currency that could be used on transaction among different parties, has attracted increasing attention from scholars and financial experts. Satoshi Nakamoto (2008) first invented Bitcoin, the appearance of which realized decentralized transaction. Bitcoin allows online payment to be transacted directly from one party to another without getting through an intermediate financial institution, while traditional finance resists the trust-in-third-party mechanism centralized on the financial institution. Even though the public believe Bitcoin finance has the potential to replace the antiquated finance paradigm, Bitcoin and traditional finance are currently coexisting. In Bitcoin finance, more reliable trust is established not by authority intermediaries, but by network consensus, cryptography, digital signature, which reduces high transaction costs. However, the possibility of system failures and attacks or fraud behavior is always unavoidable in online transactions. In this case, traditional finance stands in a more advantageous position.

Gandal et al. (2018) provided analyses for the Bitcoin Price in recent years and argued that Bitcoin experienced both rising and falling tendency in the past years. Price of Bitcoin gets a falling shock, following large investments in Bitcoin. The volatility of Bitcoin has graphical similarity with that of the stock market. Many related predictive analysis methods, proposed by economists to predict the stock market, have also been used to forecast Bitcoin price volatility. With the development of the Bitcoin economy and more and more attentions from the industry of financial investment, whether the relationship between Bitcoin and the stock market has become a valuable research subject, although this subject has not been mentioned by experts and scholars widely. The relationship between the stock market and Bitcoin will help investors to make their investment strategy and find out possible influencing factors on the Bitcoin market.

The study of this paper has made significant contributions to the academic field and financial market analysis as follows:

  • We present a groundbreaking study of the relationship between Bitcoin and the stock market over time based on Vector Autoregressive model of Time Series. The impulse response is involved as signal to observe the reaction of this dynamic system of Bitcoin and stock market in response to some change caused by relative parameters.

  • Sliding Window technique is utilized to enhance impulse response signals. With the size changes of sliding window, the loudness of the impulse response signal varies as well.

  • Big Data technology is applied in data processing. The study applied Yahoo API for batch data collection of three stock indexes.

In this paper, we firstly introduce the development background of Bitcoin as one type of cryptocurrency based on blockchain protocol, recall the existing economic modeling strategies, including Random Walk hypothesis, SVR, RF, ANN, etc., used for stock market forecasting and further explore the solutions of VAR, impulse response and sliding window to figure out non-stationary time series with the feature of seasonal volatility, corresponding to the data of stock market and Bitcoin, in Section 2. In Section 3, data collection of the three main stock indexes is performed through Yahoo Finance API on Python and then we study the time series tendency over time for each series and their respective price return series. We describe in detail about the basic modeling framework of VAR model on four variables in Section 4. In Section 5, the results of impulse response and variance decomposition are shown, and further efforts are made to obtain impulse response among variables through setting up sliding windows. Discussion for further study is elaborated in Section 6. Finally, we conclude a dynamic relationship between Bitcoin and the stock market.

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