Regulating Bitcoin and Block Chain Derivatives

Shadab, Houman B.

doi:10.2139/ssrn.2508707

Cited by 12 publications

(4 citation statements)

References 25 publications

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“…The establishment and bankruptcy of various Bitcoin exchange markets motivated the creation of the BPI [ 51 ]. The BPI combines a set of price indices from well-performing exchange marketplaces to provide a reference for BTC/USD exchange rates and is accepted as a standard measure of Bitcoin price in economics [ 18 , 52 , 53 ]. We use the daily closing prices of each day t at 23.59 GMT from , composing the time series of price P ( t ) from 1 February 2011 to 31 December 2014, shown in the top panel of figure 2 .…”

Section: Methodsmentioning

confidence: 99%

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Social signals and algorithmic trading of Bitcoin

2015

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The availability of data on digital traces is growing to unprecedented sizes, but inferring actionable knowledge from large-scale data is far from being trivial. This is especially important for computational finance, where digital traces of human behaviour offer a great potential to drive trading strategies. We contribute to this by providing a consistent approach that integrates various datasources in the design of algorithmic traders. This allows us to derive insights into the principles behind the profitability of our trading strategies. We illustrate our approach through the analysis of Bitcoin, a cryptocurrency known for its large price fluctuations. In our analysis, we include economic signals of volume and price of exchange for USD, adoption of the Bitcoin technology and transaction volume of Bitcoin. We add social signals related to information search, word of mouth volume, emotional valence and opinion polarization as expressed in tweets related to Bitcoin for more than 3 years. Our analysis reveals that increases in opinion polarization and exchange volume precede rising Bitcoin prices, and that emotional valence precedes opinion polarization and rising exchange volumes. We apply these insights to design algorithmic trading strategies for Bitcoin, reaching very high profits in less than a year. We verify this high profitability with robust statistical methods that take into account risk and trading costs, confirming the long-standing hypothesis that trading-based social media sentiment has the potential to yield positive returns on investment.

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Section: Methodsmentioning

confidence: 99%

“…Algorithm of trading simulation. rates, and is accepted as a standard measure of Bitcoin price in economics[52,53,18]. We use the daily closing prices of each day t at 23:59 GMT from coindesk.com, composing the time series of price P (t) from February 1st, 2011 to December 31th, 2014, shown in the top panel of Figure2.…”

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confidence: 99%

Social signals and algorithmic trading of Bitcoin

2015

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“…( 2019 ) worked on the pricing of cryptocurrency options and presents the case of Bitcoin and CRIX. The study by Shadab ( 2014 ) presented work on Bitcoin regulation and block chain derivatives.…”

Section: Literature Reviewmentioning

confidence: 99%

Implied volatility estimation of bitcoin options and the stylized facts of option pricing

Zulfiqar

Gulzar

2021

Financ Innov

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The recently developed Bitcoin futures and options contracts in cryptocurrency derivatives exchanges mark the beginning of a new era in Bitcoin price risk hedging. The need for these tools dates back to the market crash of 1987, when investors needed better ways to protect their portfolios through option insurance. These tools provide greater flexibility to trade and hedge volatile swings in Bitcoin prices effectively. The violation of constant volatility and the log-normality assumption of the Black–Scholes option pricing model led to the discovery of the volatility smile, smirk, or skew in options markets. These stylized facts; that is, the volatility smile and implied volatilities implied by the option prices, are well documented in the option literature for almost all financial markets. These are expected to be true for Bitcoin options as well. The data sets for the study are based on short-dated Bitcoin options (14-day maturity) of two time periods traded on Deribit Bitcoin Futures and Options Exchange, a Netherlands-based cryptocurrency derivative exchange. The estimated results are compared with benchmark Black–Scholes implied volatility values for accuracy and efficiency analysis. This study has two aims: (1) to provide insights into the volatility smile in Bitcoin options and (2) to estimate the implied volatility of Bitcoin options through numerical approximation techniques, specifically the Newton Raphson and Bisection methods. The experimental results show that Bitcoin options belong to the commodity class of assets based on the presence of a volatility forward skew in Bitcoin option data. Moreover, the Newton Raphson and Bisection methods are effective in estimating the implied volatility of Bitcoin options. However, the Newton Raphson forecasting technique converges faster than does the Bisection method.

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“…Although appearing to be steadily declining, 8 'extreme volatility' (Dallyn 2017: 465) reappeared in late 2017 as the exchange price of Bitcoin rose nearly twenty-fold. In response to such price volatility, large companies like Microsoft and smaller blockchain firms 9 have both drawn on blockchain technology to facilitate the execution and settlement of derivatives, the complex financial 'weapons of mass destruction' at the heart of the 2007/8 crisis (Shadab 2014;Taylor 2016). In their very short existence at the time of writing, these technical objects have extended rather than resolved market instabilities.…”

Section: Extending Trust In Objects Vulnerable To Market Instabilitiesmentioning

confidence: 99%

Blockchains, trust and action nets: extending the pathologies of financial globalization

Campbell‐Verduyn

Goguen

2018

Global Networks

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Blockchains combine digital encryption and time stamping technologies to enable digital exchange to occur in manners celebrated by proponents as ‘trust‐free’. Yet, an increasing range of scholars argue that actual applications of the peer‐to‐peer technology shifts, rather than eliminates, trust. In this article, we draw on organizational theory to argue that efforts to remove trust reorganize the action nets that underpin payment systems in manners that extend rather than eliminate longstanding pathologies afflicting financial globalization. Our analysis supports and extends the critiques that blockchain applications are far from ‘trust‐free’. By tracing how efforts to reconfigure the socio‐technical composition of the humans and objects that underpin payment systems, we illustrate how blockchain applications shift the location and character of the technical vulnerabilities that create market instabilities and concentration, as well as elite‐led governance.

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Regulating Bitcoin and Block Chain Derivatives

Cited by 12 publications

References 25 publications

Social signals and algorithmic trading of Bitcoin

Social signals and algorithmic trading of Bitcoin

Implied volatility estimation of bitcoin options and the stylized facts of option pricing

Blockchains, trust and action nets: extending the pathologies of financial globalization

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