Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Why Do Markets Crash? Bitcoin Data Offers Unprecedented Insights.

ABSTRACT: Crashes have fascinated and baffled many canny observers of financial markets. In the strict orthodoxy of the efficient market theory, crashes must be due to sudden changes of the fundamental valuation of assets. However, detailed empirical studies suggest that large price jumps cannot be explained by news and are the result of endogenous feedback loops. Although plausible, a clear-cut empirical evidence for such a scenario is still lacking. Here we show how crashes are conditioned by the market liquidity, for which we propose a new measure inspired by recent theories of market impact and based on readily available, public information. Our results open the possibility of a dynamical evaluation of liquidity risk and early warning signs of market instabilities, and could lead to a quantitative description of the mechanisms leading to market crashes.

SUBMITTER: Donier J

PROVIDER: S-EPMC4598099 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Why Do Markets Crash? Bitcoin Data Offers Unprecedented Insights.

Donier Jonathan J Bouchaud Jean-Philippe JP

PloS one 20151008 10

Crashes have fascinated and baffled many canny observers of financial markets. In the strict orthodoxy of the efficient market theory, crashes must be due to sudden changes of the fundamental valuation of assets. However, detailed empirical studies suggest that large price jumps cannot be explained by news and are the result of endogenous feedback loops. Although plausible, a clear-cut empirical evidence for such a scenario is still lacking. Here we show how crashes are conditioned by the market ...[more]

PMID: 26448333

Similar Datasets

Trade informativeness and liquidity in Bitcoin markets.

Project description:Liquid markets are driven by information asymmetries and the injection of new information in trades into market prices. Where market matching uses an electronic limit order book (LOB), limit orders traders may make suboptimal price and trade decisions based on new but incomplete information arriving with market orders. This paper measures the information asymmetries in Bitcoin trading limit order books on the Kraken platform, and compares these to prior studies on equities LOB markets. In limit order book markets, traders have the option of waiting to supply liquidity through limit orders, or immediately demanding liquidity through market orders or aggressively priced limit orders. In my multivariate analysis, I control for volatility, trading volume, trading intensity and order imbalance to isolate the effect of trade informativeness on book liquidity. The current research offers the first empirical study of Glosten (1994) to yield a positive, and credibly large transaction cost parameter. Trade and LOB datasets in this study were several orders of magnitude larger than any of the prior studies. Given the poor small sample properties of GMM, it is likely that this substantial increase in size of datasets is essential for validating the model. The research strongly supports Glosten's seminal theoretical model of limit order book markets, showing that these are valid models of Bitcoin markets. This research empirically tested and confirmed trade informativeness as a prime driver of market liquidity in the Bitcoin market.

| S-EPMC8360696 | biostudies-literature

Deciphering Bitcoin Blockchain Data by Cohort Analysis.

Project description:Bitcoin is a peer-to-peer electronic payment system that has rapidly grown in popularity in recent years. Usually, the complete history of Bitcoin blockchain data must be queried to acquire variables with economic meaning. This task has recently become increasingly difficult, as there are over 1.6 billion historical transactions on the Bitcoin blockchain. It is thus important to query Bitcoin transaction data in a way that is more efficient and provides economic insights. We apply cohort analysis that interprets Bitcoin blockchain data using methods developed for population data in the social sciences. Specifically, we query and process the Bitcoin transaction input and output data within each daily cohort. This enables us to create datasets and visualizations for some key Bitcoin transaction indicators, including the daily lifespan distributions of spent transaction output (STXO) and the daily age distributions of the cumulative unspent transaction output (UTXO). We provide a computationally feasible approach for characterizing Bitcoin transactions that paves the way for future economic studies of Bitcoin.

| S-EPMC8989952 | biostudies-literature

Dynamic sentiment spillovers among crude oil, gold, and Bitcoin markets: Evidence from time and frequency domain analyses.

Project description:This paper examines the sentiment spillovers among oil, gold, and Bitcoin markets by employing spillovers index methods in a time-frequency framework. We find that the total sentiment spillover among crude oil, gold and Bitcoin markets is time-varying and is greatly affected by major market events. The directional sentiment spillovers are also time-varying. On average, the Bitcoin market is the major transmitter of directional sentiment spillovers, whereas the crude oil and gold markets are the major receivers. In particular, the sentiment spillover effects are major created at high-frequency components, implying that the markets rapidly process the sentiment spillover effects and the shock is transmitted over the short-term. Moreover, we also find that the sentiment spillover effects differ significantly in term of intensity and direction when compared with return and volatility spillover effects. The present study has certain applications for investors and policymakers.

| S-EPMC7714240 | biostudies-literature

Towards open data blockchain analytics: a Bitcoin perspective.

Project description:Bitcoin is the first implementation of a technology that has become known as a 'public permissionless' blockchain. Such systems allow public read/write access to an append-only blockchain database without the need for any mediating central authority. Instead, they guarantee access, security and protocol conformity through an elegant combination of cryptographic assurances and game theoretic economic incentives. Not until the advent of the Bitcoin blockchain has such a trusted, transparent, comprehensive and granular dataset of digital economic behaviours been available for public network analysis. In this article, by translating the cumbersome binary data structure of the Bitcoin blockchain into a high fidelity graph model, we demonstrate through various analyses the often overlooked social and econometric benefits of employing such a novel open data architecture. Specifically, we show: (i) how repeated patterns of transaction behaviours can be revealed to link user activity across the blockchain; (ii) how newly mined bitcoin can be associated to demonstrate individual accumulations of wealth; (iii) through application of the naïve quantity theory of money that Bitcoin's disinflationary properties can be revealed and measured; and (iv) how the user community can develop coordinated defences against repeated denial of service attacks on the network. Such public analyses of this open data are exemplary benefits unavailable to the closed data models of the 'private permissioned' distributed ledger architectures currently dominating enterprise-level blockchain development owing to existing issues of scalability, confidentiality and governance.

| S-EPMC6124103 | biostudies-literature

Vehicular crash data used to rank intersections by injury crash frequency and severity.

Project description:This article contains data on research conducted in "A double standard model for allocating limited emergency medical service vehicle resources ensuring service reliability" (Liu et al., 2016) [1]. The crash counts were sorted out from comprehensive crash records of over one thousand major signalized intersections in the city of Chicago from 2004 to 2010. For each intersection, vehicular crashes were counted by crash severity levels, including fatal, injury Types A, B, and C for major, moderate, and minor injury levels, property damage only (PDO), and unknown. The crash data was further used to rank intersections by equivalent injury crash frequency. The top 200 intersections with the highest number of crash occurrences identified based on crash frequency- and severity-based scenarios are shared in this brief. The provided data would be a valuable source for research in urban traffic safety analysis and could also be utilized to examine the effectiveness of traffic safety improvement planning and programming, intersection design enhancement, incident and emergency management, and law enforcement strategies.

| S-EPMC4961217 | biostudies-literature

Implications of using administrative healthcare data to identify risk of motor vehicle crash-related injury: the importance of distinguishing crash from crash-related injury.

Project description:BackgroundAdministrative healthcare databases, such as Medicare, are increasingly used to identify groups at risk of a crash. However, they only contain information on crash-related injuries, not all crashes. If the driver characteristics associated with crash and crash-related injury differ, conflating the two may result in ineffective or imprecise policy interventions.MethodsWe linked 10 years (2008-2017) of Medicare claims to New Jersey police crash reports to compare the demographics, clinical diagnoses, and prescription drug dispensings for crash-involved drivers ≥ 68 years with a police-reported crash to those with a claim for a crash-related injury. We calculated standardized mean differences to compare characteristics between groups.ResultsCrash-involved drivers with a Medicare claim for an injury were more likely than those with a police-reported crash to be female (62.4% vs. 51.8%, standardized mean difference [SMD] = 0.30), had more clinical diagnoses including Alzheimer's disease and related dementias (13.0% vs. 9.2%, SMD = 0.20) and rheumatoid arthritis/osteoarthritis (69.5% vs 61.4%, SMD = 0.20), and a higher rate of dispensing for opioids (33.8% vs 27.6%, SMD = 0.18) and antiepileptics (12.9% vs 9.6%, SMD = 0.14) prior to the crash. Despite documented inconsistencies in coding practices, findings were robust when restricted to claims indicating the injured party was the driver or was left unspecified.ConclusionsTo identify effective mechanisms for reducing morbidity and mortality from crashes, researchers should consider augmenting administrative datasets with information from police crash reports, and vice versa. When those data are not available, we caution researchers and policymakers against the tendency to conflate crash and crash-related injury when interpreting their findings.

| S-EPMC11318118 | biostudies-literature

3D Screen Printing Offers Unprecedented Anticounterfeiting Strategies for Oral Solid Dosage Forms Feasible for Large Scale Production.

Project description:A threat to human health in developed and, in particular, in developing countries, counterfeit medicines represent the largest identified fraud market worldwide. 3D screen printing (3DSP), an additive manufacturing technology that enables large-scale production, offers unique opportunities to combat counterfeit drugs. One such possibility is the generation of oral dosage forms with a distinct colored inner structure that becomes visible upon breakage and cannot be copied with conventional manufacturing methods. To illustrate this, we designed tablets containing a blue cross. Owing to paste properties and the limited dimensions of the cross, the production process was chosen to be continuous, involving two screen and paste changes. The two pastes (tablet body, cross) were identical except for the blue color of the latter. This ensured the build-up and mechanical stability of the resulting tablets in a mass production environment. The ensuing tablets were found to be uniform in weight and size and to comply with regulatory requirements for hardness, friability, and disintegration time (immediate release). Moreover, all tablets exhibited the covert anticounterfeit feature. The study delivers a proof-of-concept for incorporating complex structures into tablets using 3DSP and showcases the power of the technology offering new avenues for combating counterfeit drugs.

| S-EPMC10974705 | biostudies-literature

Stabilization of Aliphatic Phosphines by Auxiliary Phosphine Sulfides Offers Zeptomolar Affinity and Unprecedented Selectivity for Probing Biological CuI.

Project description:Full elucidation of the functions and homeostatic pathways of biological copper requires tools that can selectively recognize and manipulate this trace nutrient within living cells and tissues, where it exists primarily as CuI . Buffered at attomolar concentrations, intracellular CuI is, however, not readily accessible to commonly employed amine and thioether-based chelators. Herein, we reveal a chelator design strategy in which phosphine sulfides aid in CuI coordination while simultaneously stabilizing aliphatic phosphine donors, producing a charge-neutral ligand with low-zeptomolar dissociation constant and 1017 -fold selectivity for CuI over ZnII , FeII , and MnII . As illustrated by reversing ATP7A trafficking in cells and blocking long-term potentiation of neurons in mouse hippocampal brain tissue, the ligand is capable of intercepting copper-dependent processes. The phosphine sulfide-stabilized phosphine (PSP) design approach, which confers resistance towards protonation, dioxygen, and disulfides, could be readily expanded towards ligands and probes with tailored properties for exploring CuI in a broad range of biological systems.

| S-EPMC6105516 | biostudies-literature

Driver crash risk factors and prevalence evaluation using naturalistic driving data.

Project description:The accurate evaluation of crash causal factors can provide fundamental information for effective transportation policy, vehicle design, and driver education. Naturalistic driving (ND) data collected with multiple onboard video cameras and sensors provide a unique opportunity to evaluate risk factors during the seconds leading up to a crash. This paper uses a National Academy of Sciences-sponsored ND dataset comprising 905 injurious and property damage crash events, the magnitude of which allows the first direct analysis (to our knowledge) of causal factors using crashes only. The results show that crash causation has shifted dramatically in recent years, with driver-related factors (i.e., error, impairment, fatigue, and distraction) present in almost 90% of crashes. The results also definitively show that distraction is detrimental to driver safety, with handheld electronic devices having high use rates and risk.

| S-EPMC4790996 | biostudies-literature

Radar interferometry offers new insights into threats to the Angkor site.

Project description:The conservation of World Heritage is critical to the cultural and social sustainability of regions and nations. Risk monitoring and preventive diagnosis of threats to heritage sites in any given ecosystem are a complex and challenging task. Taking advantage of the performance of Earth Observation technologies, we measured the impacts of hitherto imperceptible and poorly understood factors of groundwater and temperature variations on the monuments in the Angkor World Heritage site (400 km2). We developed a two-scale synthetic aperture radar interferometry (InSAR) approach. We describe spatial-temporal displacements (at millimeter-level accuracy), as measured by high-resolution TerraSAR/TanDEM-X satellite images, to provide a new solution to resolve the current controversy surrounding the potential structural collapse of monuments in Angkor. Multidisciplinary analysis in conjunction with a deterioration kinetics model offers new insights into the causes that trigger the potential decline of Angkor monuments. Our results show that pumping groundwater for residential and touristic establishments did not threaten the sustainability of monuments during 2011 to 2013; however, seasonal variations of the groundwater table and the thermodynamics of stone materials are factors that could trigger and/or aggravate the deterioration of monuments. These factors amplify known impacts of chemical weathering and biological alteration of temple materials. The InSAR solution reported in this study could have implications for monitoring and sustainable conservation of monuments in World Heritage sites elsewhere.

| S-EPMC5332155 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data