In the Decentralized Finance (DeFi) setting, we present a new parametrized family of Constant Function Market Makers (CFMMs) which we call the Generalized Mean Market Makers (G3Ms), based on the generalized means. The G3Ms are intermediate between the Arithmetic Mean and Geometric Mean CFMM models, which G3Ms incorporate as special cases. We also present an extension of the G3Ms, based on the so-called Generalized f-Means, called Generalized f-Mean Market Makers (Gf3Ms). We show in addition that the G3Ms possess certain properties preferable to those exhibited by either the Arithmetic Mean CFMM or the Geometric Mean CFMM alone.
Optimal simple rules for the monetary policy of the first stochastically dominant crypto-currency are derived in a Dynamic Stochastic General Equilibrium (DSGE) model, in order to provide optimal responses to changes in inflation, output, and other sources of uncertainty. The optimal monetary policy stochastically dominates all the previous crypto-currencies, thus the efficient portfolio is to go long on the stochastically dominant crypto-currency: a strategy-proof arbitrage featuring a higher Omega ratio with higher expected returns, inducing an investment-efficient Nash equilibrium over the crypto-market. Zero-knowledge proofs of the monetary policy are committed on the blockchain: an implementation is provided.
The aim of this study is to investigate the volatility spillover connectedness between NFTs attention and financial markets. This paper firstly proposes a new direct proxy for the public’s attention in the NFT market: the non-fungible tokens attention index (NFTsAI), based on 590m news stories from the LexisNexis News & Business database and applies the historical decomposition to assess the historical variations of the NFTsAI. Then the empirical analysis is performed via a TVP-VAR volatility spillover connectedness model. The empirical results show that NFTsAI indicates NFT markets are dominated by cryptocurrency, DeFi, equity, bond, commodity, F.X. and gold markets. And NFT markets are volatility spillover receivers. In addition, NFT assets could impede financial contagion and have significant diversification benefits. Employing a panel pooled OLS regression model as a supplementary analysis and a GARCH-MIDAS model as a robustness test. This study reveals that NFTsAI has sufficient power to explain the return of NFT assets from a fixed effect perspective, and NFTsAI contains useful forecasting information for both short and long-term volatility of NFT markets, separately. The new NFTsAI and the empirical findings contain useful insights for risk-averse investors, portfolio managers, institutional investors, academics and financial policy regulators.
Bitcoin has grown in popularity and has now attracted the attention of individual and institutional investors. Accurate Bitcoin price direction forecasts are important for determining the trend in Bitcoin prices and asset allocation. This paper addresses several unanswered questions. How important are business cycle variables like interest rates, inflation, and market volatility for forecasting Bitcoin prices? Does the importance of these variables change across time? Are the most important macroeconomic variables for forecasting Bitcoin prices the same as those for gold prices? To answer these questions, we utilize tree-based machine learning classifiers, along with traditional logit econometric models. The analysis reveals several important findings. First, random forests predict Bitcoin and gold price directions with a higher degree of accuracy than logit models. Prediction accuracy for bagging and random forests is between 75% and 80% for a five-day prediction. For 10-day to 20-day forecasts bagging and random forests record accuracies greater than 85%. Second, technical indicators are the most important features for predicting Bitcoin and gold price direction, suggesting some degree of market inefficiency. Third, oil price volatility is important for predicting Bitcoin and gold prices indicating that Bitcoin is a substitute for gold in diversifying this type of volatility. By comparison, gold prices are more influenced by inflation than Bitcoin prices, indicating that gold can be used as a hedge or diversification asset against inflation.
Bu çalışmanın amacı, en fazla ilgi gören kripto para birimleri arasında yer alan Bitcoin ile gelişmekte olan piyasalar arasında önde gelen Borsa İstanbul (BİST) endekslerinden BİST 100 (XU100), BİST Mali (XUMAL) ve BİST Teknoloji (XUTEK) endeksleri arasındaki ilişkilerin incelenmesi olarak belirlenmiştir. Bu amaçla çalışma kapsamında Borsa İstanbul 100 fiyat endeksi, Borsa İstanbul Mali fiyat endeksi ve Borsa İstanbul Teknoloji fiyat endeks ile Bitcoin arasındaki kısa ve uzun dönemli ilişki ARDL sınır testi yaklaşımı ile incelenmiştir. Elde edilen bulgular, Bitcoin fiyatı ile Borsa İstanbul Mali Endeksi arasında uzun dönem bir ilişkinin var olduğunu göstermiştir. Ancak, Bitcoin fiyatı ile diğer endeks fiyatları arasında uzun dönemli bir ilişkinin varlığına yönelik herhangi bir bulguya ulaşılamamıştır. Elde edilen kısa dönem bulgular ise Bitcoin fiyatı ile Borsa İstanbul Mali fiyat endeksi arasında herhangi anlamlı bir ilişkinin bulunmadığını göstermektedir.
The paper is devoted to studying the bitcoin blockchain as a new global phenomenon in monetary economics, which requires comprehending from the economic theory view - a self-regulating system of decentralized emission without participation of a central monetary authority. Mathematical modelling is the instrument of this studying. The author has analyzed the Bitcoin system parameters that determine dynamics of a self-regulating emission mechanism. This mechanism operates in a peer-to-peer computer network and provides a smooth increasing of the "money supply" with a gradually decreasing rate of growth. The limit of this growth is determined by maximal volume 21 million BTC. Self-regulation is implemented through negative feedback between changes of control parameters (the target interval for the hash function values and the Bitcoin Difficulty level) and the speed of mining process. Control parameters depend on the real speed deviations from the target value. This mechanism provides a stable mining speed and determines annual rate of emission. The author suggests a spline-function for describing the annual rate of the cryptocurrency emission in accordance with the Proof-of-Work protocol in the Bitcoin blockchain algorithm. This spline-function gives possibility to find a monetary rule for annual rate of emission. The author in the paper proposes to call this monetary rule by the name of the Bitcoin system inventor - Nakamoto Monetary Rule. The Nakamoto Monetary Rule could be seen as the first example of a programmable monetary rule of the decentralized emission algorithm on the basis of blockchain technology. Central banks could use a similar approach, with the necessary modifications, to develop their programmable monetary rules for Central Bank Digital Currencies (CBDCs) emission based on DLT or blockchain technology
The purpose of this article has been the Bitcoin rates modeling, as the most important digital currency, by depending on 1932 daily observations. As a result , the Bitcoin rates follow the ARIMA(1,1,2) model while the residuals pursue GARCH(1.1) model . In the second semester of 2017, a structural change was noticed, at that moment, the Bitcoin has reached the highest level, and overcame the rate of 16560 Euro. The Bitcoin leap is due to several factors, the most important ones are that it has been accredited as a legal currency by many great world governments , benefits of the tax exemption for its users , has been considered as an entertainment tool , and a short term hedging tool as many researchers have declared .
French title: Modelisation de pieces Bitcoin utilisant le modele autoregressif heteroscedasticite conditionnelle
Cet article vise a modeliser les valeurs de bitcoin comme la monnaie numerique la plus importante a travers les vues quotidiennes de 1932. Il a ete constate que les valeurs de bitcoin suivent le modele ARIMA (1,1,2) tandis que les autres suivent le modele GARCH(1,1), en plus de surveiller les changements structurels dans la serie au deuxieme semestre 2017, au cours de cette periode, le bitcoin a atteint un record, depassant 16590 euros. Le boom du bitcoin est du a plusieurs facteurs, dont le plus important est son acceptation dans de nombreux grands pays comme monnaie legale, l'exoneration fiscale de son detenteur, en plus d'etre consideree comme une methode de luxe, en particulier avec ses avantages, car de nombreux chercheurs ont souligne qu'il s'agissait d'un outil de couverture a court terme.
This paper conducts a review on theoretical and empirical findings on the increasingly popular measure of trade policy uncertainty (TPU) in economics and finance. Moreover, an empirical investigation takes place in order to find the impact that TPU exerts on Bitcoin market values by employing a spectrum of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) specifications. Existing studies support that trade policy uncertainty leads to lower-quality and more expensive products and weak participation in international trade. Moreover, it contributes to lower democratic sentiment, hesitant internal migration and lesser socio-economic mobility and higher fluctuations in profitable assets. Moreover, our econometric findings reveal that TPU positively affects Bitcoin prices while crude oil values negatively influence this major cryptocurrency. Thereby, higher trade policy uncertainty is found to increase demand and favorite investments into risky assets in order to ameliorate the risk-return trade-off in investors’ portfolios. This study provides a compass for investing during turmoil due to trade wars and tariffs.
This literature review covers hyperinflation in Venezuela, from the 1980s to the present. Particular emphasis is placed on the role of cryptocurrency in the country and how the Venezuelan government has been using crypto, specifically the Petro, as a means to avoid further blunders with hyperinflation. From Hugo Chávez and “Socialism of the 21st Century” to the current regime of Nicolás Maduro, Chávez’ successor, the printing of money in Venezuela has sky-rocketed to the point of the government needing cryptocurrency, such as Bitcoin, as a means of circumventing inflation to fund the government’s ambitious social projects. A key element in its success, however, will be whether the Venezuelan people will opt to use the government-backed Petro, or whether they will opt to use a different, decentralized alternative digital currency to avoid the perils of hyperinflation. The paper will examine this issue from several diverse points of view: specifically, the Austrian School (Echarte Fernández, Hernández, & Zambrano, 2018), the neo-Keynesian school (Pagliacci & Barráez, 2010), and public policy and institutional perspective (Corrales, 1999). The use of cryptocurrencies by governments, in particular socialist governments, is a new occurrence and merits much attention for the future of public and monetary policy in those countries.
We rationalize cryptocurrency adoption in a small open economy model. We show that digital dollarization, where stablecoins pegged to the USD are used for transactions, can improve social welfare. In contrast, the adoption of volatile cryptocurrencies, such as El Salvador’s 2021 decision to make Bitcoin legal tender, results in welfare losses. This outcome aligns with the observed low take-up of Bitcoin as legal tender. The welfare benefits of digital dollarization increase with the magnitude of macroeconomic shocks, providing motivation for the growing use of stablecoins in emerging markets as a safeguard against high inflation and macroeconomic instability .
Abdelkader Derbali, Lamia Jamel, Monia Ben Ltaifa, Ahmed K. Elnagar · 5 authors
Purpose This paper provides an important perspective to the predictive capacity of Fed and European Central Bank (ECB) meeting dates and production announcements for the dynamic conditional correlation (DCC) between Bitcoin and energy commodities returns and volatilities during the period from August 11, 2015 to March 31, 2018. Design/methodology/approach To assess empirically the unanticipated component of the US and ECB monetary policy, the authors pursue the Kuttner's approach and use the federal funds futures and the ECB funds futures to assess the surprise component. The authors use the approach of DCC as introduced by Engle (2002) during the period from August 11, 2015 to March 31, 2018. Findings The authors’ results suggest strong significant DCCs between Bitcoin and energy commodity markets if monetary policy surprises are incorporated in variance. These results confirmed the financialization of Bitcoin and commodity energy markets. Finally, the DCC between Bitcoin and energy commodity markets appears to respond considerably more in the case of Fed surprises than ECB surprises. Originality/value This study is a crucial topic for policymakers and portfolio risk managers.
Abstract Crypto currencies have sparked great interest lately not only among regular people, billionaires and Wall Street, but it also caught the attention of national and global financial regulators across the world. In this article, we try to answer the following questions: what is bitcoin? It is money, a mean of payment, a huge bubble or just a way to evade taxes, launder money and fund illegal trade? We will answer these questions by testing whether bitcoin is a bubble with the help of right-tailed ADF tests and analyzing if the price of bitcoin has experienced shocks. We identify bitcoin price shock when the price of bitcoin is above its Hodrick-Prescott trend plus one standard deviation. Also, we will analyze if bitcoin fulfils the roles of money and if itself or a stablecoin like Libra can attain an important place within the international monetary system. We will also research the potential risks associated with the adoption of Libra, especially in poorer countries. Despite Bitcoin and Libra’s weaknesses, an advantage is that they insist on the necessity of faster and cheaper cross-border funds transfers 24/7, 365 days a year.
Finansal piyasaların ilgi noktasını oluşturan kripto para birimlerinden bitcoin’in para birimi olarak yayılması ve kullanılmasından sonra herkesin aklında, bitcoin’in bir yatırım aracı olarak ya da hedge enstrümanı olarak değerlendirilip değerlendirilemeyeceği sorusu yer almaya başlamıştır. Çalışmada kripto para birimlerinden en çok işlem hacmine sahip olan bitcoin’in alternatif yatırım araçları arasında uzun dönemli ilişkilerini ortaya koymak için istatistiki analiz yapılmış ve bununla ilgili bulgular tartışılmıştır. Birçok kripto para olmasına karşın Bitcoin’in her açısından önde gelmesi nedeniyle, bitcoin ile alternatif yatırım araçları arasında bir eş bütünleşmenin olup olmadığı ARDL testi ile ortaya koyulmaya çalışılmıştır. Çalışmada Bitcoin ile alternatif yatırım araçları arasında geniş kapsamda ele alan salt bir çalışma görülmediğinden dolayı bu çalışmanın yapılmasına karar verilmiştir.
The paper highlights why, contrary to frequent claims, cryptocurrencies will not replace the existing monetary system. The reason is that despite its shortcomings the current monetary system is a product of a long evolution which had adjusted it to the needs of the economy. Cryptocurrencies will probably remain what they have been during the last decade, i.e. the popular speculative assets and the means of payment used – due to their anonymity – for illicit operations. The recent monetary system, based on deposit money issued by commercial banks, will not be replaced also by deposit money issued by central banks (Central Bank Digital Currency) as the CBDC would lack a rational mechanism of its allocation and would pose risks to financial stability
The Holy Grail of a decentralised stablecoin is achieved on rigorous\nmathematical frameworks, obtaining multiple advantageous proofs: stability,\nconvergence, truthfulness, faithfulness, and malicious-security. These\nproperties could only be attained by the novel and interdisciplinary\ncombination of previously unrelated fields: model predictive control, deep\nlearning, alternating direction method of multipliers (consensus-ADMM),\nmechanism design, secure multi-party computation, and zero-knowledge proofs.\nFor the first time, this paper proves:\n - the feasibility of decentralising the central bank while securely\npreserving its independence in a decentralised computation setting\n - the benefits for price stability of combining mechanism design, provable\nsecurity, and control theory, unlike the heuristics of previous stablecoins\n - the implementation of complex monetary policies on a stablecoin, equivalent\nto the ones used by central banks and beyond the current fixed rules of\ncryptocurrencies that hinder their price stability\n - methods to circumvent the impossibilities of Guaranteed Output Delivery\n(G.O.D.) and fairness: standing on truthfulness and faithfulness, we reach\nG.O.D. and fairness under the assumption of rational parties\n As a corollary, a decentralised artificial intelligence is able to conduct\nthe monetary policy of a stablecoin, minimising human intervention.\n
A digital currency in which encryption techniques are used to regulate the generation of units of currency and verify the transfer of funds, operating independently of a central bank. Therefore, Bitcoin is a form of digital currency that was designed by Satoshi Nakamoto (an unknown author of Bitcoin white paper 2008) and since then it has able to generate a considerable attention from investors due to its decentralized characteristics and the technology (block-chain) behind it. Bitcoin is a form of digital peer-to-peer currency system where transactions take place without a central bank. The transactions are verified by the nodes of the network and recorded in the Blockchain. Since the popularization of Bitcoin, this technology has caught attention of several technology companies who started to do research on the applications and opportunities of this technology. In this paper, an attempt has been made to capture the time varying variance of most prominent Cryptocurrency Bitcoin with world’s top traded currencies such as USD, GBP, Euro, Yen and CHF. In order to realise the stated objectives the researchers have collected the data from Prowess and Yahoo finance database from September 2013 till March 2018. In the first phase the collected data has been for normality and stationarity. Bitcoin was modelled for GARCH and EGARCH tests to capture the time varying volatility and leverage effect. Later the Johansen cointegration test has been conducted to find out the existence of cointegration between the top global currencies with Bitcoin. In the last phase the VECM has been run to capture the both long run and short relationship between Bitcoin and top five traded currencies. In the last phase Variance Decomposition has been run to capture the variance explained by the prominent global currencies on Bitcoin. Both USD and GBP share long run relationship with Bitcoin. Finally, the results have been compared with the possible evidence.
The paper investigates whether Bitcoin is a good predictor of the Standard & Poor’s 500 Index. To answer this question we compare alternative models using a point and density forecast relying on Dynamic Model Averaging (DMA) and Dynamic Model Selection (DMS). According to our results, Bitcoin does not show any direct impact on the predictability of Standard & Poor’s 500 for the considered sample.
This article considers the problem of testing for an explosive bubble in financial data in the presence of time-varying volatility. We propose a sign-based variant of the Phillips, Shi, and Yu (2015, International Economic Review 56, 1043–1077) test. Unlike the original test, the sign-based test does not require bootstrap-type methods to control size in the presence of time-varying volatility. Under a locally explosive alternative, the sign-based test delivers higher power than the original test for many time-varying volatility and bubble specifications. However, since the original test can still outperform the sign-based one for some specifications, we also propose a union of rejections procedure that combines the original and sign-based tests, employing a wild bootstrap to control size. This is shown to capture most of the power available from the better performing of the two tests. We also show how a sign-based statistic can be used to date the bubble start and end points. An empirical illustration using Bitcoin price data is provided.
İbrahim Korkmaz Kahraman, Habib Küçükşahin, Emin ÇAĞLAK
Getirilerin normal dağıldığı varsayımını temel alan öngörü modelleri sığ piyasalarda yeterince başarılı performans sergileyememektedir. Bu modeller, özellikle yüksek oynaklık gösteren piyasalarda ulaşılabilecek uç noktaların öngörüsünde daha fazla başarısızlık göstermekte ve bu durum da yatırımcıları volatilite tahminlemesine yöneltmektedir. Bahsedilen durumlar çerçevesinde, çalışmada finansal yatırımcılar için alternatif yatırım aracı olarak görülen ve piyasalarında yüksek oynaklıkların görüldüğü kripto paraların volatilite tahmininde Tekil Oynaklık Modelleri (ARCH, GARCH, T-GARCH, GARCH-M, E-GARCH, I-GARCH) ile uzun hafıza modelleri (AP-GARCH ve C-GARCH) kullanılmıştır. Ayrıca oynaklık tahmini için yararlanılan modeller arasından en uygun model test edilmeye çalışılmıştır. Bu bağlamda, kripto para piyasası içerisinde en yüksek piyasa değerine sahip, Bitcoin, Ethereum ve Ripple para birimlerinin 24/08/2016-07/05/2018 tarihleri arası fiyat verilerinden yararlanılmıştır. Araştırma sonuçlarına göre, Bitcoin ve Ethereum için şokların volatilite etkisi kalıcı ve pozitif şokların etkisi negatif şokların etkisinden daha fazla iken Ripple için şokların volatiliteye etkisi geçici karakterde ve oynaklığın geçişkenliği kısa dönemli olmaktadır.
Bitcoin and other cryptocurrencies have been frequently on media lately. As these cryptocurrencies are relatively new, there are not much economic theory explaining their behavior and price developments. Due to these reasons, the goal of this thesis is to find an economic theory to study the demand for Bitcoin. \n \nIn this thesis, I will write about Bitcoin applying it to Walsh’s Money in Utility function (MIU function). I will modify Walsh’s original model by incorporating Bitcoin to it. In this model, Bitcoin is used as payment method and as a store of value. Both Bitcoin and money can be used to buy any goods, but there are certain goods that are easier to buy using bitcoin. Hence, Bitcoin has transaction benefit and the households will always need some bitcoin holdings in their portfolio. Using Walsh’s MIU function, I will derive a demand function for Bitcoin. \n \nIn addition to this, I will go through the working paper “Bitcoin Pricing, Adoption, and Usage: Theory and Evidence” written by Athey et Al. (August 2016). In this paper, Bitcoin is used both as a payment method and a store of value. From the findings by Athey et Al., Bitcoin seems to be mainly used as a store of value. I will present an overview of the paper including the results and then concentrate on their aggregate analysis on Bitcoin exchange rate. \n \nBased on the Bitcoin exchange rate equation presented by Athey et Al., I will study whether Bitcoin demand function derived from MIU model is able to explain the changes in Bitcoin’s aggregate demand in real market. As expected, due to the assumptions and restrictions of the model, Bitcoin demand function derived in this thesis is not able to fully explain the changes in demand for Bitcoin in real world. Nonetheless, subject to the assumptions and restrictions of the model, Bitcoin demand function can be used to study the relationship between bitcoin demand, domestic nominal interest rate and consumption. Finally, I will present an alternative approach to further study Bitcoin’s demand.