24 research outputs found
Analysis of Return and Risk of Cryptocurrency Bitcoin Asset as Investment Instrument
This study aims to explore the potential use of the cryptocurrency bitcoin as an investment instrument in Indonesia. The return obtained from bitcoin cryptocurrency is compared to other investment instruments, namely stock returns, gold and the rupiah exchange rate. The research period was carried out based on research data from 2011 to 2020. This study employee compares means test (t test) and analysis of variance (F test) on rate of return of bitcoin investment. The bitcoin return compare to the rate of return form the others investments instruments namely exchange rate, gold and stock. The study collected 120 data of each investments instruments: bitcoin, exchange rate, gold and stock from various of sources during 2011–2020. Then, we calculate the return and risk of individual investment instruments. The results showed that the bitcoin currency had the highest rate of return 18% with a standard deviation of 61% compared to exchange rate, gold and stock returns. While the rate of return for the others investment instruments showed less than 0.5% with standard deviation less than 5%. The rate of return bitcoin has significance difference compare to the rate of return of exchange rate, gold and stock. The study contribute for the investors who would like to invest on bitcoin. The investors should understand the characteristic of bitcoin in term of rate of returns and also the risk. This study also contributes to government of Indonesia on crypto currency development. The Indonesia government should adopt and regulate on crypto currency in the future to secure the investor and economic growth
Complexity in economic and social systems: cryptocurrency market at around COVID-19
Social systems are characterized by an enormous network of connections and
factors that can influence the structure and dynamics of these systems. All
financial markets, including the cryptocurrency market, belong to the
economical sphere of human activity that seems to be the most interrelated and
complex. The cryptocurrency market complexity can be studied from different
perspectives. First, the dynamics of the cryptocurrency exchange rates to other
cryptocurrencies and fiat currencies can be studied and quantified by means of
multifractal formalism. Second, coupling and decoupling of the cryptocurrencies
and the conventional assets can be investigated with the advanced
cross-correlation analyses based on fractal analysis. Third, an internal
structure of the cryptocurrency market can also be a subject of analysis that
exploits, for example, a network representation of the market. We approach this
subject from all three perspectives based on data recorded between January 2019
and June 2020. This period includes the Covid-19 pandemic and we pay particular
attention to this event and investigate how strong its impact on the structure
and dynamics of the market was. Besides, the studied data covers a few other
significant events like double bull and bear phases in 2019. We show that,
throughout the considered interval, the exchange rate returns were multifractal
with intermittent signatures of bifractality that can be associated with the
most volatile periods of the market dynamics like a bull market onset in April
2019 and the Covid-19 outburst in March 2020. The topology of a minimal
spanning tree representation of the market also used to alter during these
events from a distributed type without any dominant node to a highly
centralized type with a dominating hub of USDT. However, the MST topology
during the pandemic differs in some details from other volatile periods
Collective dynamics, diversification and optimal portfolio construction for cryptocurrencies
Since its conception, the cryptocurrency market has been frequently described
as an immature market, characterized by significant swings in volatility and
occasionally described as lacking rhyme or reason. There has been great
speculation as to what role it plays in a diversified portfolio. For instance,
is cryptocurrency exposure an inflationary hedge or a speculative investment
that follows broad market sentiment with amplified beta? This paper aims to
investigate whether the cryptocurrency market has recently exhibited similarly
nuanced mathematical properties as the much more mature equity market. Our
focus is on collective dynamics and portfolio diversification in the
cryptocurrency market, and examining whether previously established results in
the equity market hold in the cryptocurrency market, and to what extent.Comment: Equal contributio
Multifractal cross-correlations of bitcoin and ether trading characteristics in the post-COVID-19 time
Unlike price fluctuations, the temporal structure of cryptocurrency trading
has seldom been a subject of systematic study. In order to fill this gap, we
analyse detrended correlations of the price returns, the average number of
trades in time unit, and the traded volume based on high-frequency data
representing two major cryptocurrencies: bitcoin and ether. We apply the
multifractal detrended cross-correlation analysis, which is considered the most
reliable method for identifying nonlinear correlations in time series. We find
that all the quantities considered in our study show an unambiguous
multifractal structure from both the univariate (auto-correlation) and
bivariate (cross-correlation) perspectives. We looked at the bitcoin--ether
cross-correlations in simultaneously recorded signals, as well as in
time-lagged signals, in which a time series for one of the cryptocurrencies is
shifted with respect to the other. Such a shift suppresses the
cross-correlations partially for short time scales, but does not remove them
completely. We did not observe any qualitative asymmetry in the results for the
two choices of a leading asset. The cross-correlations for the simultaneous and
lagged time series became the same in magnitude for the sufficiently long
scales
Time-varying properties of asymmetric volatility and multifractality in Bitcoin
This study investigates the volatility of daily Bitcoin returns and
multifractal properties of the Bitcoin market by employing the rolling window
method and examines relationships between the volatility asymmetry and market
efficiency. Whilst we find an inverted asymmetry in the volatility of Bitcoin,
its magnitude changes over time, and recently, it has become small. This
asymmetric pattern of volatility also exists in higher frequency returns. Other
measurements, such as kurtosis, skewness, average, serial correlation, and
multifractal degree, also change over time. Thus, we argue that properties of
the Bitcoin market are mostly time dependent. We examine efficiency-related
measures: the Hurst exponent, multifractal degree, and kurtosis. We find that
when these measures represent that the market is more efficient, the volatility
asymmetry weakens. For the recent Bitcoin market, both efficiency-related
measures and the volatility asymmetry prove that the market becomes more
efficient.Comment: 27 pages, 11 figure