{"title":"The Information Content of ICO White Papers","authors":"David Florysiak, Alexander Schandlbauer","doi":"10.2139/ssrn.3265007","DOIUrl":"https://doi.org/10.2139/ssrn.3265007","url":null,"abstract":"White papers are likely the most important source of information provided to potential Initial Coin Offering (ICO) investors in platform-based ventures that may reduce information asymmetry between ICO issuers and investors. We use textual analysis to measure the information content of white paper documents. Testing predictions of adverse selection and signaling during the pre-ICO, ICO, and post-ICO phases, observed empirical associations between ratings, ICO success, funding volume, token exchange-listing probability, underpricing, cumulative returns, and trading volume are jointly consistent with high-quality ICO issuers signaling their type by providing more informative content, i.e. excess or new textual information not contained in recent and peer white papers. Moreover, signaling is likely impaired during the ICO process as investors include potentially biased expert ratings in their investment decision-making. As a result, low-quality ICO issuers successfully raise funds and exchange-list their tokens, leading to inefficient funding allocation, generating potentially large adverse selection costs, and increased risk of market failure.","PeriodicalId":151990,"journal":{"name":"ERN: Foreign Exchange Models (Topic)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117315544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Is Bitcoin Really Un-Tethered?","authors":"J. Griffin, Amin Shams","doi":"10.2139/SSRN.3195066","DOIUrl":"https://doi.org/10.2139/SSRN.3195066","url":null,"abstract":"This paper investigates whether Tether, a digital currency pegged to the U.S. dollar, influenced Bitcoin and other cryptocurrency prices during the 2017 boom. Using algorithms to analyze blockchain data, we find that purchases with Tether are timed following market downturns and result in sizable increases in Bitcoin prices. The flow is attributable to one entity, clusters below round prices, induces asymmetric autocorrelations in Bitcoin, and suggests insufficient Tether reserves before month-ends. Rather than demand from cash investors, these patterns are most consistent with the supply-based hypothesis of unbacked digital money inflating cryptocurrency prices.","PeriodicalId":151990,"journal":{"name":"ERN: Foreign Exchange Models (Topic)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128851051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Estimation of Tail Index and Value-at-Risk for the TA25 and the USD-ILS Exchange Rate Under Assumption of Pareto Distribution","authors":"Sharon Peleg Lazar","doi":"10.2139/ssrn.3300828","DOIUrl":"https://doi.org/10.2139/ssrn.3300828","url":null,"abstract":"While it is clear that returns of financial assets are not well described by the normal distribution, it is unclear how best to describe them. One distribution suggested is the Pareto distribution. I apply an extreme value theory framework to estimate the tails of the distributions of returns of the TA25, the Tel-Aviv Stock Exchange's leading stock index and the USD-ILS exchange rate, under the assumption returns follow the Pareto distribution. I find that the left tail of the TA25 is lighter than that of the S&P500, suggesting less extreme events in the TA25 and the right tail of the USD-ILS exchange rate is heavier than the left tail, indicating that there are more extreme events when the ILS weakens against the USD than vice versa. This may be due to central bank intervention. I use the estimated tail indexes to assess the value-at-risk of the TA25 and USD-ILS and find the estimations fit historical values well for relatively high percentiles, which are most problematic to estimate.","PeriodicalId":151990,"journal":{"name":"ERN: Foreign Exchange Models (Topic)","volume":"625 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123955137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Extreme Correlation in Cryptocurrency Markets","authors":"Konstantinos Gkillas, S. Bekiros, C. Siriopoulos","doi":"10.2139/ssrn.3180934","DOIUrl":"https://doi.org/10.2139/ssrn.3180934","url":null,"abstract":"In this paper, we study the contemporaneous tail dependence structure in a pairwise comparison of the ten largest cryptocurrencies, namely Bitcoin, Dash, Dogecoin, Ethereum, Litecoin, Monero, Namecoin, Novacoin, Peercoin, and Ripple. We apply multivariate extreme value theory and we estimate a bias-corrected extreme correlation coefficient. Our findings reveal clear patterns of significantly high bivariate dependency in the distribution tails of some of the most basic and widespread cryptocurrencies, primarily over various downside constraints. This means that extreme correlation is not related to cryptocurrency market volatility per se, but to the trend of the cryptocurrency market. Therefore, extreme correlation increases in bear markets, but not in bull markets for these pairs. Interestingly, there is also a significant number of pairs which exhibit a weak level of dependency in distribution tails.","PeriodicalId":151990,"journal":{"name":"ERN: Foreign Exchange Models (Topic)","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123078602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rudan Wang, Bruce Morley, Michalis P. Stamatogiannis
{"title":"Forecasting the Exchange Rate Using Non-Linear Taylor Rule Based Models","authors":"Rudan Wang, Bruce Morley, Michalis P. Stamatogiannis","doi":"10.2139/ssrn.3354751","DOIUrl":"https://doi.org/10.2139/ssrn.3354751","url":null,"abstract":"This research utilises a non-linear Smooth Transition Regression (STR) approach to modelling and forecasting the exchange rate, based on the Taylor rule model of exchange rate determination. The separate literatures on exchange rate models and the Taylor rule have already shown that the non-linear specification can outperform the equivalent linear one. In addition the Taylor rule based exchange rate model used here has been augmented with a wealth effect to reflect the increasing importance of the asset markets in monetary policy. Using STR models, the results offer evidence of non-linearity in the variables used and that the interest rate differential is the most appropriate transition variable. We conduct the conventional out-of-sample forecasting performance test, which indicates that the non-linear models outperform their linear equivalents as well as the non-linear UIP model and random walk.","PeriodicalId":151990,"journal":{"name":"ERN: Foreign Exchange Models (Topic)","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115521930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the Economics of Digital Currencies","authors":"Jesús Fernández-Villaverde, Daniel Sanches","doi":"10.21799/frbp.wp.2018.07","DOIUrl":"https://doi.org/10.21799/frbp.wp.2018.07","url":null,"abstract":"Can a monetary system in which privately issued cryptocurrencies circulate as media of exchange work? Is such a system stable? How should governments react to digital currencies? Can these currencies and government-issued money coexist? Are cryptocurrencies consistent with an efficient allocation? These are some of the important questions that the sudden rise of cryptocurrencies has brought to contemporary policy discussions. To answer these questions, we construct a model of competition among privately issued .at currencies. We .nd that a purely private arrangement fails to implement an efficient allocation, even though it candeliver price stability under certain technological conditions. Currency comptition creates problems for monetary policy implementation under conventional methods. However, it is possible to design a policy rule that uniquely implements an efficient allocation by driving private currencies out of the market. We also show that unique implementation of an efficient allocation can be achieved without government intervention if productive capital is introduced.","PeriodicalId":151990,"journal":{"name":"ERN: Foreign Exchange Models (Topic)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123475754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Metcalfe's Law as a Model for Bitcoin's Value","authors":"Timothy Peterson","doi":"10.2139/ssrn.3078248","DOIUrl":"https://doi.org/10.2139/ssrn.3078248","url":null,"abstract":"This paper demonstrates that bitcoin’s medium- to long-term price follows Metcalfe’s law. Bitcoin is modeled as a token digital currency, a medium of exchange with no intrinsic value that is transacted within a defined electronic network. Per Metcalfe’s law, the value of a network is a function of the number of pairs transactions possible, and is proportional to n-squared. A Gompertz curve is used to model the inflationary effects associated with the creation of new bitcoin. The result is a parsimonious model of supply (number of bitcoins) and demand (number of bitcoin wallets), with the conclusion bitcoin’s price fits Metcalfe’s law exceptionally well. Metcalfe’s law is used to investigate Gandal’s et.al. [2018] assertion of price manipulation in the Bitcoin ecosystem during 2013-2014.","PeriodicalId":151990,"journal":{"name":"ERN: Foreign Exchange Models (Topic)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124967961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exchange Rate Exposure and Firm Dynamics","authors":"Juliana Salomao, Liliana Varela","doi":"10.2139/ssrn.2846134","DOIUrl":"https://doi.org/10.2139/ssrn.2846134","url":null,"abstract":"\u0000 This article develops a heterogeneous firm-dynamics model to jointly study firms’ currency debt composition and investment choices. In our model, foreign currency borrowing arises from a dynamic trade-off between exposure to currency risk and growth. The model endogenously generates selection of productive firms into foreign currency borrowing. Among them, firms with high marginal product of capital use foreign loans more intensively. We assess econometrically the model’s predicted pattern of foreign currency borrowing using firm-level census data from the deregulation of these loans in Hungary, calibrate the model, and quantify the aggregate impact of this financing. Our counterfactual exercises show that understanding the characteristics of firms borrowing in foreign currency is critical to assess the aggregate consequences of this financing.","PeriodicalId":151990,"journal":{"name":"ERN: Foreign Exchange Models (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129446305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Applicability of Random Forests Forecating on International Currency Trade: An Investigation Through R Language","authors":"K. Musunuru, S. Rao","doi":"10.2139/ssrn.3261755","DOIUrl":"https://doi.org/10.2139/ssrn.3261755","url":null,"abstract":"The goal of this research is to study the performance of foreign exchange trade in both India and China. India and China raised rapidly in recent times and there is abundant of speculation that these countries might reach to the level of few other developed nations as far as international trade is concerned. Whereas there isn’t any doubt that these countries emerging as economic powers in the Asia-Pacific region, a lot of effort is required at international platform with respect to trade and commerce. One of such areas of competition is international currency trade. The aim of this study is to understand trends of currency trade in order to predict how likely these countries are going to emerge as best in the region. The study used certain secondary datasets from very reliable and authenticated sources. As far as statistical techniques are concerned, random walk forecasting methods were employed to test the study hypothesis. The study gathered certain evidence that though there are similarities in present and past performance, it is not likely to be the same in the future. However, the study concludes that random forests forecasting as a methodology is highly useful in studying trends in the data.","PeriodicalId":151990,"journal":{"name":"ERN: Foreign Exchange Models (Topic)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117103519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Beneath the Gold Points: European Financial Market Integration, 1844-1870","authors":"V. Bignon, Jinzhao Chen, Stefano Ugolini","doi":"10.2139/ssrn.3057367","DOIUrl":"https://doi.org/10.2139/ssrn.3057367","url":null,"abstract":"We measure the degree of financial integration among the top five financial centers of mid-19th-century Europe by applying threshold-regression analysis to a new database of exchange rates and bullion prices. We find that, instead of London, Hamburg, Frankfurt or Amsterdam, it was Paris that played the role of hub of European foreign exchange markets. We also document a high level of financial integration before the gold standard period, with estimated transaction costs far lower than historically-observed “gold” and “silver points” (i.e., the costs to bullion arbitrage). We review the assumptions of the classical gold-point arbitrage model and conclude that TAR-computed thresholds cannot be interpreted as transaction costs in the bullion trade. High integration may be explained not by low transaction costs in bilateral bullion arbitrage, but by the availability of multilateral financial arbitrage techniques.","PeriodicalId":151990,"journal":{"name":"ERN: Foreign Exchange Models (Topic)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127312267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}