In recent years, both the media and investors have questioned Bitcoin's efficacy. The reasons for its widespread interest include groundbreaking features, simplicity, transparency, and a developing reputation. Investors use Bitcoin as a currency or for investment purposes. Bitcoin values soared by nearly 5000% since it went online in July 2016, provoking its inquiry. The efficient market hypothesis was used to determine if the bitcoin market fully reflected the available information.
The term "poor form of efficiency" was used to describe a market that is deemed inefficient when past data cannot be used by investors to forecast future results. Initial Bitcoin's literature was subject to safety, as well as ethical aspects. However, current works have examined Bitcoin from an economic point of view. Analysts argue that if Bitcoin were a real value store, its volatility would vary to that of bubbles and crashes. Moreover, Bitcoin offers investors with substantial diversification benefits and has hedging capabilities compared to gold as well as the dollar.
Data and Methodology
The source of the data used is www.bitcoinaverage.com, the first aggregated price index of Bitcoin. Moreover, the site aggregates its rates from all Bitcoin exchanges available worldwide as well as providing a volume weighted price of Bitcoin; as a result, enabling a global price perspective, therefore its efficiency. The data comprised of Bitcoin daily closing prices between the beginnings of August 2010 also the end of July 2016. From the graph indicating Bitcoin prices as well as volume over the time, it noted that the costs of bitcoin's are comparatively stable before peaking intensely in late 2013. However, the rise in prices is considerable in the period's earliest years.
The sample period was divided into two parts including the beginning of August 2010 to the end of July 2010 as well as the beginning of August 2013 to the end of July 2016. The formula used to calculate the returns of the Bitcoin is; Rt = Ln [(Pt)/(Pt-1)] x 100. Where the bitcoin's return is Rt, Ln (Pt) also Ln (Pt-1) are the Bitcoin's prices natural logs at time t and t-1. To analyze the efficiency of Bitcoin, highly influential battery randomness tests were employed to avoid results that are spurious also capture all bitcoin's dynamics.
Initially, the Ljung-Box is used returns autocorrelation are first examined through Ljung-Box test which has the autocorrelation's null hypothesis. The independence of the returns is determined by the runs as well as Bartels test. The variance ratio test is employed. Automatic variance test determines parameters p and q automatically using a method that is data-dependent. The AVR's test small sample properties are improved by the wild-bootstrapped AVR. Lastly, the BDS test is used. The null assumption states that the procedures creating statistics are i.i.d, whereas a misspecification of the model is shown by the null assumption. The p-values are reported across different specifications. In conclusion, for long memories of stock returns, the rescaled Hurst exponent is employed. For values greater than 0.65, it indicates substantial persistence evidence, whereas values lower than 0.45 shows strong anti-persistence.
Empirical Results
The tests come up with a summary where the corresponding t-values, as well as the Hurst statistic, were reported. The bitcoin's weak form informational efficiency, for the full sample period, because of null hypothesis rejection by the p-values. The exponent of R/S Hurst indicates strong anti-persistence evidence, as a result, indicative of returns non-randomness. Hence, the results of the full sample period show significant Bitcoin inefficiency.
The entire sample period was split into two for study and in the first period of subsample, both tests rejected the randomness null hypothesis. However, there is an indication by the statistic of R/S Hurst of an anti-persistence that is strong. On the other hand, a study on the second subset shows the tests of Ljung-Box as well as automated variance test rejecting the null hypothesis, indicating no correlation, therefore the inefficiency of Bitcoin.
Conclusion
The analysis concluded indicates that, over the full period of the sample, the market of the Bitcoin is not weakly efficient. However, the study shows that, with some of the market efficiency tests, Bitcoin may become more efficient. The results suggest that, in the second subset, the returns of bitcoin's are random. However, the bitcoin's incompetence is quite high. The finding of inefficiency is not a surprise, because of its similarity to an emerging market and it is still in its infancy. As more investors do Bitcoin trade as well as analysis, the efficiency of Bitcoin will improve over time. Future studies may consist of additional empirical investigation of the shifting market degree efficiency as well as a comparison between Bitcoin and the emerging markets also other investments (Urquhart 2).
Work Cited
Urquhart, Andrew. "The inefficiency of Bitcoin." Economics Letters 148 (2016): 80-82.
