The Dynamics of the Relationship Between Price and Volume of Cryptocurrencies: A Wavelet Coherence Analysis

Introduction

Cryptocurrency with its range depth has become popular in the past few years and the volume of its transactions are continuously increasing. Sanitary crisis COVID-19 with its different waves has accelerated the integration of the digital dimension in economies in general and in particular the financial sphere, now evolving in great uncertainty and favoring fintech development.

During COVID-19 time, Bitcoin price levels have not seemed to decline but rather, have increased in 2020 and 2021. The recent advent and increasing attention given to cryptocurrencies have given rise to a continuous demand for understanding the various aspects of cryptocurrencies from an empirical and theoretical financial point of view. Cryptocurrency is presented as a type of digital financial asset that uses blockchain technology and serves peer-to-peer financial transactions. The features that distinguish cryptocurrencies are: that they are traded in many independent markets and are circulating currency controlled by a software algorithm rather than any classic way of control (company, central administration, or government) (Ciaian et al., 2016). From a practical point of view, it’s believed that it necessitates a considerable volume exchange to move prices significantly (Najand and Yung, 1991). This relationship has been studied extensively for different asset classes, over different time intervals, and using different frequencies. In the financial literature, the price-volume relationship usually implies either relationship between volume and the magnitude of return, or a relationship between volume and return level. It has been established by previous studies that volume is positively related to the magnitude of return. However, it’s controversial in the context of cryptocurrency and the nature of its relationship between return and volume as it is still under study as most of it is undertaken in spot markets as there are restrictions on short selling in spot markets. The continuous fluctuations in volume and price attract attention to the nature of the relationship that drives several dimensions around cryptocurrencies such as price, volume, and volatility risk.

This chapter adds to the literature in several ways. Despite the significant amount of literature dedicated to the study role of traded volume in predicting movement in stock returns and volatility (Gebka and Wohar, 2013), the question remain unclearly answered when it comes to the Bitcoin market: to what extend the traded volume can have a predictability power for returns and volatility?

It contributes to the existing literature by using wavelet analysis to investigate the dynamic relationships between price and volume in cryptocurrency markets. We chose wavelet analysis because it is a powerful and robust methodology for studying the co-movements of non-stationary financial time series. In particular, this chapter employs wavelet coherence, which provides time-varying correlations between price and volume for various investment horizons, as opposed to co-integration and VAR, which are limited to one or two holding periods. Wavelet coherence has the advantage of exposing associations between cause and effect over time and frequency by providing regions that show the direction and degree of dependence of prices and trading volumes. Our research results provide investors and portfolio managers with additional information about the relationships between the prices and trading volumes of the most commonly traded cryptocurrencies. At the time of writing this chapter, we retained the market cap cryptocurrencies as choice criteria to determine the top three cryptocurrencies of our empirical study; Bitcoin (over 1 trillion Dollars), Ethereum (540 billion Dollars), and Binance (100 billion Dollars). Bitcoin (BTC), Ethereum (ETH,) and Binance (BNB) are considered a new asset class, with a not clear predicted evolution. Several undiscovered territories and unsolved financial issues to be investigated about cryptocurrency and in this chapter; we try to explore two of these characteristics: Price and volume.

The remainder of the chapter is organized as follows. Section 2 presents the literature review. Section 3 provides the research methodology used; Section 4 describes the data; Section 5 presents and discusses our empirical results. Our conclusions and research implications are revealed in section 6.