Blockchain Papers

Shi Chen, Cathy Chen, TM Lee, Bobby Ong

No abstract is available for this record.

Joerg Osterrieder

Cryptocurrencies became popular with the emergence of Bitcoin and have shown an unprecedented growth over the last few years. As of November 2016, more than 720 cryptocurrencies exist, with Bitcoin still being the most popular one. We show the statistical properties of the most important cryptocurrencies. We characterize their exchange rates versus the US Dollar by fitting parametric distributions to them, including the Student t distribution, the generalized hyperbolic distribution as well as the asymmetric normal inverse Gaussian and the asymmetric variance gamma distribution. Our findings show that cryptocurrencies exhibit strong non-normal characteristics, with standard heavy-tailed distributions such as the Student t distribution giving good descriptions of the data. This is the first study that looks at the parametric distribution of cryptocurreny returns. The results are important for investment and risk management purposes.

Anne Haubo Dyhrberg

This paper sets out to explore the hedging capabilities of bitcoin by applying the asymmetric GARCH methodology used in investigation of gold. The results show that bitcoin can clearly be used as a hedge against stocks in the Financial Times Stock Exchange Index. Additionally bitcoin can be used as a hedge against the American dollar in the short-term. Bitcoin thereby possess some of the same hedging abilities as gold and can be included in the variety of tools available to market analysts to hedge market specific risk.

Anne Haubo Dyhrberg

This paper explores the financial asset capabilities of bitcoin using GARCH models. The initial model showed several similarities to gold and the dollar indicating hedging capabilities and advantages as a medium of exchange. The asymmetric GARCH showed that bitcoin may be useful in risk management and ideal for risk averse investors in anticipation of negative shocks to the market. Overall bitcoin has a place on the financial markets and in portfolio management as it can be classified as something in between gold and the American dollar on a scale from pure medium of exchange advantages to pure store of value advantages.

Yogesh Malhotra

No abstract is available for this record.

Soumya Easwaran, Manu Dixit, Sitabhra Sinha

No abstract is available for this record.

Andrew Hencic, Christian Gouriéroux

No abstract is available for this record.

Ole Christian Andreas Valstad, Kristian Vagstad

Alloreactivity after transplantation is associated with profound immune suppression, and consequent opportunistic infection results in high morbidity and mortality. This immune suppression is most profound during GVHD after bone marrow transplantation where an inflammatory cytokine storm dominates. Contrary to current dogma, which avers that this is a T-cell defect, we demonstrate that the impairment lies within conventional dendritic cells (cDCs). Significantly, exogenous antigens can only be presented by the CD8(-) cDC subset after bone marrow transplantation, and inflammation during GVHD specifically renders the MHC class II presentation pathway in this population incompetent. In contrast, both classic and cross-presentation within MHC class I remain largely intact. Importantly, this defect in antigen processing can be partially reversed by TNF inhibition or the adoptive transfer of donor cDCs generated in the absence of inflammation.

Rafael Delfin-Vidal, Guillermo Romero-Meléndez

No abstract is available for this record.

René García, Éric Renault, Georges Tsafack

Value at risk (VaR) is a central concept in risk management. As stressed by Artzner et al. (1999, Coherent measures of risk, Math. Finance 9(3) 203–228), VaR may not possess the subadditivity property required to be a coherent measure of risk. The key idea of this paper is that, when tail thickness is responsible for violation of subadditivity, eliciting proper conditioning information may restore VaR rationale for decentralized risk management. The argument is threefold. First, since individual traders are hired because they possess a richer information on their specific market segment than senior management, they just have to follow consistently the prudential targets set by senior management to ensure that decentralized VaR control will work in a coherent way. The intuition is that if one could build a fictitious conditioning information set merging all individual pieces of information, it would be rich enough to restore VaR subadditivity. Second, in this decentralization context, we show that if senior management has access ex post to the portfolio shares of the individual traders, it amounts to recovering some of their private information. These shares can be used to improve backtesting to check that the prudential targets have been enforced by the traders. Finally, we stress that tail thickness required to violate subadditivity, even for small probabilities, remains an extreme situation because it corresponds to such poor conditioning information that expected loss appears to be infinite. We then conclude that lack of coherence of decentralized VaR management, that is VaR nonsubadditivity at the richest level of information, should be an exception rather than a rule.

Benoît B. Mandelbrot, John W. Van Ness

Previous article Next article Fractional Brownian Motions, Fractional Noises and ApplicationsBenoit B. Mandelbrot and John W. Van NessBenoit B. Mandelbrot and John W. Van Nesshttps://doi.org/10.1137/1010093PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] I. Adelman, Long cycles—fact or artifact?, Amer. Economic Rev., 60 (1965), 444–463 Google Scholar[2] William Feller, The asymptotic distribution of the range of sums of independent random variables, Ann. Math. Statistics, 22 (1951), 427–432 MR0042626 0043.34201 CrossrefISIGoogle Scholar[3] I. M. Gel'fand and , N. Ya. Vilenkin, Generalized functions. Vol. 4, Academic Press [Harcourt Brace Jovanovich Publishers], New York, 1964 [1977]xiv+384 MR0435834 Google Scholar[4] C. W. J. Granger, The typical spectral shape of an economic variable, Econometrica, 34 (1966), 150–161 CrossrefISIGoogle Scholar[5] G. A. Hunt, Random Fourier transforms, Trans. Amer. Math. 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