paper-with-me

Papers

Are Bitcoin Bubbles Predictable? Combining a Generalized Metcalfe's Law and the LPPLS Model

2018-03-15 · Spencer Wheatley, Didier Sornette, Tobias Huber, Max Reppen, Robert N. Gantner

We develop a strong diagnostic for bubbles and crashes in bitcoin, by analyzing the coincidence (and its absence) of fundamental and technical indicators. Using a generalized Metcalfe's law based on network properties, a fundamental value is quantified and shown to be heavily exceeded, on at least four occasions, by bubbles that grow and burst. In these bubbles, we detect a universal super-exponential unsustainable growth. We model this universal pattern with the Log-Periodic Power Law Singularity (LPPLS) model, which parsimoniously captures diverse positive feedback phenomena, such as herding and imitation. The LPPLS model is shown to provide an ex-ante warning of market instabilities, quantifying a high crash hazard and probabilistic bracket of the crash time consistent with the actual corrections; although, as always, the precise time and trigger (which straw breaks the camel's back) being exogenous and unpredictable. Looking forward, our analysis identifies a substantial but not unprecedented overvaluation in the price of bitcoin, suggesting many months of volatile sideways bitcoin prices ahead (from the time of writing, March 2018).

📄 PDF Abstract BibTeX arXiv:1803.05663

Code (1)

HiddenOrder/extended-NVT-model

Tasks

Diagnostic

Similar Papers 제목 키워드 기반

Real-time Prediction of Bitcoin Bubble Crashes

2019-06-13

In the past decade, Bitcoin as an emerging asset class has gained widespread public attention because of their extraordinary returns in phases of extreme price growth and their unpredictable massive crashes. We apply the…

DiagnosticPredictionTime SeriesTime Series Analysis

Dissection of Bitcoin's Multiscale Bubble History from January 2012 to February 2018

2019-05-30

We present a detailed bubble analysis of the Bitcoin to US Dollar price dynamics from January 2012 to February 2018. We introduce a robust automatic peak detection method that classifies price time series into periods of…

Time Series Analysis

Are Bitcoins price predictable? Evidence from machine learning techniques using technical indicators

2019-09-03 · Samuel Asante Gyamerah

The uncertainties in future Bitcoin price make it difficult to accurately predict the price of Bitcoin. Accurately predicting the price for Bitcoin is therefore important for decision-making process of investors and mark…

BIG-bench Machine LearningDecision Makingregression

Bitcoin price and its marginal cost of production: support for a fundamental value

2018-05-19

This study back-tests a marginal cost of production model proposed to value the digital currency bitcoin. Results from both conventional regression and vector autoregression (VAR) models show that the marginal cost of pr…

regression

Why Topological Data Analysis Detects Financial Bubbles?

2023-04-14 · Samuel W. Akingbade, Marian Gidea, Matteo Manzi, Vahid Nateghi

We present a heuristic argument for the propensity of Topological Data Analysis (TDA) to detect early warning signals of critical transitions in financial time series. Our argument is based on the Log-Periodic Power Law …

Time SeriesTopological Data Analysis