This research is based on the phenomenon of new investment instrument called Cryptocurrency-Bitcoin which becomes popular in recent years. Based on that phenomenon, this research tries to search which is the best investment instrument from three instruments such as Bitcoin, stocks, and gold. The research method used is quantitative method with the type of research is comparative descriptive. In this study, the authors use Sharpe, Treynor and Jensen index approach to evaluate the performance. This study intends to do a comparison from the index using the data of the investment instrument in the period of January 2014 to August 2017. The study sample was taken from price result from every investment instrument during the period of study. The result shows that Bitcoin is the best instrument because based on Sharpe, Treynor, and Jensen value the return is better than the other two instruments.
The cryptocurrency market has witnessed significant growth in the past few months. The emergence of hundreds of new digital currencies and the huge increase in the prices of their leading representatives have attracted a lot of attention from investors. However, the financial characteristics of the cryptocurrency markets have not been systematically evaluated yet. As a consequence, there is currently no consensus on whether cryptocurrencies constitute an individual asset class or if they share substantial similarities to stocks, bonds, commodities or foreign exchange. Based on Markowitz et al. (2017) this paper aims to fill this lack of research by evaluating the cryptocurrency market based on seven requirements of an individual asset class. The authors find that the cryptocurrency market distinguishes itself remarkably from established asset classes in terms of risk and return. Additionally, the low correlation between the cryptocurrency markets and these established asset classes induces a diversification potential for investors, leading to more favorable risk/return profiles of their portfolios. But also the emergence of investment services and products provided by the financial industry and the increasingly cost-effective access to cryptocurrencies corroborate the conclusion that cryptocurrencies can be seen as an individual asset class.
Bitcoin is an exciting new financial product that may be useful for inclusion in investment portfolios. This paper investigates the implications of replacing gold in an investment portfolio with bitcoin (“digital gold”). Our approach is to use several different multivariate GARCH models (dynamic conditional correlation (DCC), asymmetric DCC (ADCC), generalized orthogonal GARCH (GO-GARCH)) to estimate minimum variance equity portfolios. Both long and short portfolios are considered. An analysis of the economic value shows that risk-averse investors will be willing to pay a high performance fee to switch from a portfolio with gold to a portfolio with bitcoin. These results are robust to the inclusion of trading costs.
Antônio Carlos da Silva Filho, Natália Diniz Maganini, Eduardo Fonseca de Almeida
The recent emergence and use growth of cryptocurrencies based on Blockchain technology increased interest in the study of its economic dynamics and financial characteristics. Bitcoin is up to now the more widely known and disseminated cryptocurrency, with greater volume of transactions, market value and acceptance in exchange services. In order to contribute to the comprehension of the price behavior of the Bitcoin market, this study analyzes whether the historical series of prices of this currency, quoted every 12 h from September 14, 2011 to November 20, 2017 has multifractal behavior. The results of the research identified multifractal characteristics in the series and that both long-range correlations and fat tails distribution contribute to Bitcoin’s multifractal behavior. We compared the non-Gaussian properties and the multifractality degrees of Bitcoin series with the non-Gaussian properties and multifractality degrees of several stock market indices scattered around the world. In addition, we investigated the power of multifractal analysis in the study of volatility and forecast for this series, pointing to a possible use of multifractal parameters in Technical Analysis.
We test the presence of regime changes in the GARCH volatility dynamics of Bitcoin log–returns using Markov–switching GARCH (MSGARCH) models. We also compare MSGARCH to traditional single–regime GARCH specifications in predicting one–day ahead Value–at–Risk (VaR). The Bayesian approach is used to estimate the model parameters and to compute the VaR forecasts. We find strong evidence of regime changes in the GARCH process and show that MSGARCH models outperform single–regime specifications when predicting the VaR.
Alexandra Piedad Cortez Ordoñez, Ana Belén Tulcanaza-Prieto
The new technological advances have brought a revolution on how economic agents interact with society and markets. Nowadays, the use of virtual currencies is more frequent in the financial transactions and bitcoin has been defined as the most important world cryptocurrency due to its high market capitalization and its technological infrastructure. Several studies have been conducted to discuss bitcoin advantages and disadvantages; however, few papers in literature have examined its connection and influence on the stock market. The objective of this paper is precisely cover this gap. Firstly, by providing tools and concepts to understand bitcoin’s dynamic, and then determining its relationship with stock market indexes. In that context, this manuscript examines the definition and function of bitcoin in the global world and its presence in Ecuador. Besides, exploratory and visual analyses are provided using the evolution of bitcoin and other market indexes. Finally, a linear correlation is computed between bitcoin, other cryptocurrencies, stock exchange indexes and commodities. The results in this study, employing visual and statistical analyses, demonstrated that bitcoin has: a strong relationship with other cryptocurrencies; a lineal correlation, not as strong as the previous one, with the main stock market indexes; and no linear correlation with commodities.
Kripto para birimleri teknolojinin gelişmesiyle birlikte son yıllarda önem kazanmış ve daha çok kullanılır hale gelmiştir. Merkezi bir otoriteye bağlı olmayan ve kriptografik sistemler ile güvenliği sağlanan bu para birimlerinden en bilineni Bitcoin’dir. Bu çalışmada, başlıca kripto para birimleri ve işleyiş süreçleri incelenmiştir. Buna ek olarak Bitcoin’in döviz, hisse senedi emtia piyasaları ve faiz ile olan ilişkisi ele alınmıştır. Çalışmada kullanılan veri setinin frekansı aylık olup Mart-2012 ile Mayıs-2018 dönemini kapsamaktadır. Zaman serisi yöntemlerinden Johansen Eşbütünleşme ve Granger Nedensellik analizleri uygulanmıştır. Çalışmanın sonuçlarına göre, Bitcoin fiyatlarının artan bir trende ve yüksek bir volatiliteye sahip olduğu görülmektedir. Faiz değişkeni ile Bitcoin fiyatları arasında diğer analizler ve Granger nedensellik testi sonuçlarına göre istatistiksel olarak anlamlı bir ilişki vardır.
Emmanouil Platanakis, Charles Sutcliffe, Andrew Urquhart
This paper contributes to the literature on cryptocurrencies by examining the performance of naïve (1/N) and optimal (Markowitz) diversification in a portfolio of four popular cryptocurrencies. We employ weekly data with weekly rebalancing and show there is very little to select between naïve diversification and optimal diversification. Our results hold for different levels of risk-aversion and an alternative estimation window.
This letter questions the true nature (true versus spurious) of the Long Range Dependence (LRD) behavior observed in the returns and volatility series of four Cryptocurrencies (CC). Using a robust approach, this letter shows that the LRD behavior exhibited by the returns and volatility series of Bitcoin, Litecoin, and Ripple is a true behavior, and not a statistical artifact. As for Ethereum, the results show that the true LRD is only supported for the volatility series. Our results confirm the inefficiency of all the considered markets, with the exception of Ethereum.
This study analyses the effect of adding bitcoin into the portfolio by exploiting the Long Only investment strategy. The Portfolio consists of five assets: bitcoin, crude oil price index, stock exchange of Thailand (SET) price index, the exchange rate between Thai and USD and Thai government bond compound with treasurer bill. The model used for modelling the return of all asset is Multivariate t-copula based on GARCH and also measure the risk of the portfolio using the Value-at-risk (VaR) under the condition of minimizing the variance of return. We find that when adding more bitcoin into the portfolio, the return and risk of asset increased. If we only invest in bitcoin, we will face the risk at 16.90% and gain 6.27%. When comparing the effectiveness of portfolio by using Return-risk ratio, it found that portfolio with bitcoin shows the higher return rate than portfolios without bitcoin. Therefore, it can conclude that bitcoin could indeed increase the effectiveness of portfolio.
Aurelio F. Bariviera, Luciano Zunino, Osvaldo A. Rosso
This paper discusses the dynamics of intraday prices of twelve cryptocurrencies during last months' boom and bust. The importance of this study lies on the extended coverage of the cryptoworld, accounting for more than 90\% of the total daily turnover. By using the complexity-entropy causality plane, we could discriminate three different dynamics in the data set. Whereas most of the cryptocurrencies follow a similar pattern, there are two currencies (ETC and ETH) that exhibit a more persistent stochastic dynamics, and two other currencies (DASH and XEM) whose behavior is closer to a random walk. Consequently, similar financial assets, using blockchain technology, are differentiated by market participants.
Kripto parateknolojisi, insanların herhangi bir aracıya ihtiyaç duymadan dünyanın dört biryanında ödeme yapmalarını sağlar ve internet üzerinden çalışır. Bu teknolojininortaya çıkışı ile dikkatler bu paralara çevrilmiş, fiyatları hızla artmayabaşlamış ve aynı zamanda oynak hale gelmişlerdir. Bu çalışmada GARCH (1,1)modeli kullanılarak Bitcoin ve Litecoin piyasalarında haftanın günü ve yılınayı etkilerinin varlığı incelenmiştir. Çalışma dönemi 1 Mayıs 2013-21 Aralık2016 arasını kapsamaktadır. Elde edilen sonuçlar Bitcoin ve Litecoingetirilerinde haftanın günü ve yılın ayı etkilerinin var olduğunugöstermektedir. Pazartesi, Salı ve Cuma günlerinin Bitcoin getirileri üzerindepozitif ve anlamlı, Cumartesi’nin ise Litecoin getirileri üzerinde negatif veanlamlı etkisi olduğu tespit edilmiştir. Ayrıca, yılın ayı etkisi açısındanŞubat, Ekim ve Kasım aylarının Bitcoin üzerinde pozitif ve anlamlı, Litecoingetirilerinde ise Ağustos ayının negatif ve anlamlı etkisiolduğubelirlenmiştir.
Çalışmada gün geçtikçe popülerliği ve buna bağlı olarak toplam piyasa değerleri ve işlem hacimleri artan, çok sayıda ve çok çeşitli piyasalarda işlem gören kripto paraların fiyatlarının birbiri üzerindeki etkisi araştırılmıştır. Çalışmada, Bitcoin, Ethereum, Ripple, Bitcoin Cash, Cardano, Litecoin, NEM, NEO, Stellar ve IOTA kripto paralarının seçiminde toplam piyasa değerleri dikkate alınmıştır ve en yüksek toplam piyasa değerine sahip 10 kripto para analize dahil edilmiştir. 15 Aralık 2017 ve 17 Ocak 2018 tarihleri arasında çalışmaya konu olan kripto paraların günlük fiyat hareketleri arasındaki ilişkiyi incelemek için serilere Johansen Eşbütünleşme Testi ve Granger Nedensellik Testi uygulanmıştır. Çalışmanın sonucunda, Cardano’nun NEO’nun Granger nedeni olduğu, Bitcoin’in Bitcoin Cash’in Granger nedeni olduğu, Litecoin’in Bitcoin Cash’in Granger nedeni olduğu, NEM’in Bitcoin Cash’in Granger nedeni olduğu, Ripple’ın Bitcoin’in Granger nedeni olduğu, NEO ve Ethereum’un birbirinin Granger nedeni olduğu, NEO ve Litecoin’in birbirinin Granger nedeni olduğu ve NEM’in Stellar’ın Granger nedeni olduğu tespit edilerek, bu değişkenlerin fiyat hareketlerinin kısa dönemde birbirini etkilediği ortaya konmuştur.
This paper explores the predictive qualities of Bitcoin Miners Revenue on Bitcoin Returns. Using data on Bitcoin in the cryptocurrency market from July 1, 2010 to February 20, 2018, we reflect intervariable correlations not previously examined. We analyze those relationships with a conditional regression analysis adjusting for calendar effects. We separate the sample, and use the last 17 trading days (month) to test a strategy based on the probability of Bitcoin Returns moving higher. After a slight modification to the logistic regression analysis, we find a profitable trading strategy exists based solely on Bitcoin Miners Revenue and the probability of Bitcoin Returns moving higher.
Bu çalışmada her geçen gün ilgiyle izlenmeye devam edilen sanal para birimi Bitcoin’de çoklu balonların varlığı Phillips, Shi ve Yu (2015) tarafından geliştirilen GSADF birim kök testi ve kritik değerlerin tespitinde her türlü değişen varyans problemini hesaba katarak işlem yapan Harvey, Leybourne, Sollis ve Taylor (2016) tarafından geliştirilen metot takip edilerek araştırılmıştır. Veri seti 16.07.2010 ve 31.12.2017 tarihleri arasında günlük bazdaki 24 saatlik ortalama Bitcoin fiyatlarından oluşmaktadır. Yapılan analizler sonucunda söz konusu veri aralığının büyük bir kısmında Bitcoin fiyatlarında çoklu balonların varlığı görülmüştür
The commodity industry, the transaction lifecycle of commodities, its value chain and supply chain are complex systems with many parties involved. Ownership of cargoes are determined by who is holding the physical paper, the Bill of Lading. The participants in the industry require constant verification between parties, and this resultsin cumbersome paper-heavy back-office operations which are exposed to human errors. \nThe entire commodity transaction life-cycle involves the value chain and supply chain, and it creates a complicated and long chain involving several intermediaries, each taking a piece of the pie and adds to transaction costs for producers. The roles of intermediaries in the commodity industry can be financing trades, facilitating trade, managing risk, on-site inspection and verification of cargoes, shipping, and logistics.\nBlockchain technology is the technology underlying bitcoins and most of the cryptocurrencies in existence. Bitcoin enabled people to transfer money, peer-to-peer without an intermediary to establish trust and facilitate transactions. Bitcoin has paved the way for further use-cases of the technology, which has a much broader use-case spectrum than just being the underlying technology of cryptocurrencies.\nBlockchain is a decentralized, distributed ledger, where transactions are stored in blocks and secured with cryptography. It allows anyone to execute trade without an intermediary to establish trust between parties. It allows for one single source of the truth between counterparties through enhancing transparency, visibility and availability of transactions data and information.\nBlockchains can be fully transparent, but a blockchain can also allow for privacy. There are different types of blockchain, public/private/hybrid, and each of these types serves its purpose a little bit differently. In a private or hybrid blockchain, information that is sensitive to a certain trade remains private by only allowing the counterparties of that trade transparency into the transactions of that certain trade.\nThe blockchain technology enhances cyber security through decentralization and cryptography. Digital tokens can replace the Bill of Lading to track ownership of cargoes. Smart contracts that self-execute triggered upon a set of predetermined conditions are among the features of blockchain technology. The convenience of blockchain technology, is that anyone at any time can build its own decentralized application on top of already existing blockchain platforms like Ethereum, Hyperledger and others. These factors create for a unique opportunity to digitalize the commodity industry, gaining security, efficiency and opening up possibilities for new trade models in trade finance.
In the world finance and technological development in finance, along with innovative financial instruments, have attracted investors. The most popular of these developments is undoubtedly Bitcoin, which is an output of the blockchain infrastructure .Bitcoin that is not connected to a central authority and contains cryptographic features, is one of the crypto moneys. The fact that Bitcoin does not depend on Central Authority and disclose the factors affecting its price by supply and demand have resulted in high volatility. In this study, firstly blockchain technology will be explained briefly and time-dependent price estimates for Bitcoin which is one of the important outputs of this technology, will be made. Artificial Neural Networks (YSA), which has become increasingly popular among estimation methods in recent years, has been used in the study and compared with ARIMA in traditional estimation methods. The sample of the study was created using daily closing prices between 02.02.2012 - 09.01.2018 dates. As a result of this study, both directions and values of estimated prices by artificial neural networks MPL (6-3-1) model between 10.01.2018 - 18.01.2018 have been more successful than ARIMA (1.1.6) model.
This study back-tests a marginal cost of production model proposed to value the digital currency Bitcoin. Results from both conventional regression and vector autoregression (VAR) models show that the marginal cost of production plays an important role in explaining Bitcoin prices, challenging recent allegations that Bitcoins are essentially worthless. Even with markets pricing Bitcoin in the thousands of dollars each, the valuation model seems robust. The data show that a price bubble that began in the Fall of 2017 resolved itself in early 2018, converging with the marginal cost model. This suggests that while bubbles may appear in the Bitcoin market, prices will tend to this bound and not collapse to zero.
This study back-tests a marginal cost of production model proposed to value\nthe digital currency bitcoin. Results from both conventional regression and\nvector autoregression (VAR) models show that the marginal cost of production\nplays an important role in explaining bitcoin prices, challenging recent\nallegations that bitcoins are essentially worthless. Even with markets pricing\nbitcoin in the thousands of dollars each, the valuation model seems robust. The\ndata show that a price bubble that began in the Fall of 2017 resolved itself in\nearly 2018, converging with the marginal cost model. This suggests that while\nbubbles may appear in the bitcoin market, prices will tend to this bound and\nnot collapse to zero.\n
Mutlu Başaran Öztürk, Halil Arslan, Temur Kayhan, Mustafa Uysal
2017 yılında Bitcoin’in piyasa değerinde önemli bir artış yaşanmış ve 200 milyar dolar seviyesi aşılarak Bitcoin kurumsal yatırımcıların gündemine gelmeye başlamıştır. CME ve CBOE gibi dünyanın en büyük vadeli işlem borsaları Bitcoin’i listelerken Microsoft, PWC ve Overstock gibi kurumlar Bitcoin’i tanımlamaya başlamışlardır. Bitcoin’in bir yatırım aracı olarak görülebilmesi için bazı şartlar gereklidir. Verimli bir piyasada işlem görmesi, fiyatlama formasyonunun belirginleşmesi ve portföyler için bir çeşitlendirme aracı olabilmesi bunlardan bazıları olarak görülebilir. Ana akım varlık grupları ile Bitcoin arasındaki uzun vadeli ilişkiyi Johansen Eşbütünleşme testi ile inceleyen çalışma sonuçlarına göre Bitcoin’in altın haricinde diğer geleneksel finansal ve emtia varlıklarından bağımsız bir hareket gösterdiği ortaya çıkmıştır. Bitcoin’in söz konusu bağımsız hareketi Bitconomi olarak tanımlanırken bu durum mikro seviyede riskli bir varlığın makro anlamda portföylerin riskini düşürebileceği anlamına gelmektedir. Finansal sistemde çok küçük bir alanı işgal etmesi ve Bitcoin üretimindeki zorluk derecesinin klasik ekonomi ile çelişmesi korelasyonun anlamsız olmasının nedenleri arasında gösterilebilir. Kuzey Kore ve Ukrayna gerilimlerinde Bitcoin fiyatındaki artışlar ve altın ile Bitcoin arasındaki uzun vadeli pozitif ilişki yüksek varyansı nedeniyle eleştirilen Bitcoin’in gelecekte güvenli liman olabileceği gibi ilginç bir ironiye işaret etmektedir. Literatürdeki çalışmalar her geçen yıl Bitcoin’in varyansının gerilediğini göstermektedir.