scholarly journals On the Market Efficiency and Liquidity of High-Frequency Cryptocurrencies in a Bull and Bear Market

2020 ◽  
Vol 13 (1) ◽  
pp. 8 ◽  
Author(s):  
Yuanyuan Zhang ◽  
Stephen Chan ◽  
Jeffrey Chu ◽  
Hana Sulieman
Keyword(s):  
Market Efficiency ◽  
High Frequency ◽  
Trading Strategies ◽  
High Frequency Data ◽  
Fluctuation Analysis ◽  
Bear Market ◽  
The Past ◽  
Arbitrage Opportunities ◽  
Rolling Window ◽  
Detrended Fluctuation

The market for cryptocurrencies has experienced extremely turbulent conditions in recent times, and we can clearly identify strong bull and bear market phenomena over the past year. In this paper, we utilise algorithms for detecting turnings points to identify both bull and bear phases in high-frequency markets for the three largest cryptocurrencies of Bitcoin, Ethereum, and Litecoin. We also examine the market efficiency and liquidity of the selected cryptocurrencies during these periods using high-frequency data. Our findings show that the hourly returns of the three cryptocurrencies during a bull market indicate market efficiency when using the detrended-fluctuation-analysis (DFA) method to analyse the Hurst exponent with a rolling window. However, when conditions turn and there is a bear-market period, we see signs of a more inefficient market. Furthermore, our results indicated differences between the cryptocurrencies in terms of their liquidity during the two market states. Moving from a bull to a bear market, Ethereum and Litecoin appear to become more illiquid, as opposed to Bitcoin, which appears to become more liquid. The motivation to study the high-frequency cryptocurrency market came from the increasing availability of higher-frequency cryptocurrency-pricing data. However, it also comes from a movement towards higher-frequency trading of cryptocurrency. In addition, the efficiency of cryptocurrency markets relates not only to whether prices are predictable and arbitrage opportunities exist, but, more widely, to topics such as testing the profitability of trading strategies and determining the maturity of cryptocurrency markets.

Analysis of the Effects of Security Breaches on Firm Value

2018 ◽  
Vol 19 (2) ◽  
pp. 1-25
Author(s):  
Stoyu Ivanov
Keyword(s):  
Market Efficiency ◽  
Market Microstructure ◽  
Hedge Funds ◽  
High Frequency ◽  
Firm Value ◽  
Trading Strategies ◽  
Average Price ◽  
Scarce Resources ◽  
Corporate Security ◽  
Security Breaches

The purpose of this study is to examine, on intradaily market microstructure basis, fifteen recent occurrences of corporate security breaches to extend our understanding of market efficiency. We document minor average price responses to announcements of a security breach in the firms??target of an attack, contrary to many other corporate announcement studies, which document immediate price reaction to an announcement. Surprisingly, we find that the matching firms in our study have a stronger market microstructure response to the announcement of the attack instead. This study suggests to high-frequency investors, such as hedge funds, that they should focus their attention and scarce resources on developing trading strategies on other corporate events and announcements rather than on the announcement of security breaches.

scholarly journals A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets

2019 ◽  
Vol 12 (2) ◽  
pp. 67 ◽  
Author(s):  
Kyriazis
Keyword(s):  
Long Memory ◽  
Detrended Fluctuation Analysis ◽  
Efficient Market Hypothesis ◽  
Trading Strategies ◽  
Fluctuation Analysis ◽  
Efficient Market ◽  
Systematic Survey ◽  
Rescaled Range ◽  
Pricing Behavior ◽  
Detrended Fluctuation

This study conducts a systematic survey on whether the pricing behavior of cryptocurrencies is predictable. Thus, the Efficient Market Hypothesis is rejected and speculation is feasible via trading. We center interest on the Rescaled Range (R/S) and Detrended Fluctuation Analysis (DFA) as well as other relevant methodologies of testing long memory in returns and volatility. It is found that the majority of academic papers provides evidence for inefficiency of Bitcoin and other digital currencies of primary importance. Nevertheless, large steps towards efficiency in cryptocurrencies have been traced during the last years. This can lead to less profitable trading strategies for speculators.

scholarly journals HAS THE GLOBAL PANDEMIC OF 2020 LED TO PERSISTENCE IN THE SHARE PRICES OF LARGE GLOBAL COMPANIES?

2021 ◽  
Author(s):  
Hortense Santos ◽  
◽  
Rui Dias ◽  
Cristina Vasco ◽  
Paulo Alexandre ◽  
...  
Keyword(s):  
Stock Prices ◽  
Research Question ◽  
Correlation Coefficients ◽  
Trading Strategies ◽  
Fluctuation Analysis ◽  
Additional Risk ◽  
Share Prices ◽  
Global Pandemic ◽  
Global Companies ◽  
Detrended Fluctuation

This paper aims to analyze the predictability of the stocks of Apple, Microsoft Amazon.com, Tesla, Facebook, Samsung, Electronics, Johnson & Johnson, Walmart, in the period from October 1, 2019 to January 11, 2021. To carry out such an analysis, it is intended to answer two research questions, namely: (i) is there predictability in the stock prices of the companies under analysis? (ii) Can investors diversify risk by incorporating these companies’ shares into their portfolios? The results of the Exponents Detrended Fluctuation Analysis (DFA) show that Apple (0.51) Microsoft (0.49), Amazon.com (0.53), Samsung Electronics (0.53), Johnson & Johnson (0.53) do not have long memories in their time series, that is, investors cannot obtain abnormal profitability without incurring additional risk. Walmart (0.41) has anti-persistence, while Tesla (0.60), Facebook (0.55) indicate some predictability, meaning investors adjusting their trading strategies to the necessary missteps may have some above-average profitability, which partly rejects the first question of the research. To answer the second research question, we estimated the Detrended cross-correlation coefficient (pDCCA) model, which indicates 17 mean correlation coefficients (≈ 0.333 → ≈ 0.666), 7 strong cross-trend correlation coefficients (0.666 → ≈ 1,000), 4 weak correlation coefficients (≈ 0.000 → ≈ 0.333). These results show that investors should be careful to incorporate the shares of these companies into a single portfolio; the suggestion would be to group only the shares of companies that do not present predictability and have low rhoDCCA. The authors consider that this evidence will be important for institutional investors when carrying out trading strategies based on maximizing profitability, but also mitigating risk when diversifying.

Multifractal Analysis of African Stock Markets During the 2007–2008 US Crisis

2019 ◽  
Vol 22 (04) ◽  
pp. 1950022
Author(s):  
Oussama Tilfani ◽  
My Youssef El Boukfaoui
Keyword(s):  
Stock Markets ◽  
Global Financial Crisis ◽  
Fluctuation Analysis ◽  
Subprime Crisis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Multi Scale ◽  
Rolling Window ◽  
The Global Financial Crisis ◽  
Fractal Market Hypothesis ◽  
Detrended Fluctuation

In this paper, we examine the effects of subprime crisis on the largest African stock markets (South Africa, Nigeria, Egypt, and Morocco) by testing the fractal market hypothesis. We use a rolling window Multifractal Detrended Fluctuation Analysis, and find decline in local Hurst exponent and an increase in short-term trading activity for all considered stock markets during the global financial crisis. We furthermore investigate the interrelationships of African and the American stock markets using multi-scale contagion test. Findings suggest that the cross-correlation of African stock markets increases with American markets becoming higher during the crisis sub-period. However, the presence of contagion or interdependence effects are country and time horizon-dependent. Implications of the results are discussed.

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