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Found 11 papers, 4 papers with code
Scaling Laws And Statistical Properties of The Transaction Flows And Holding Times of Bitcoin
Defining age-dependent transaction flows as the fraction of bitcoins that are traded at a given time and that were born (last traded) at some specific earlier time, we document that the time-averaged transaction flow fraction has a power law dependence as a function of age, with an exponent close to $-1. 5$, a value compatible with priority queuing theory.
The inverse Cox-Ingersoll-Ross process for parsimonious financial price modeling
We propose a formulation to construct new classes of financial price processes based on the insight that the key variable driving prices $P$ is the earning-over-price ratio $\gamma \simeq 1/P$, which we refer to as the earning yield and is analogous to the yield-to-maturity of an equivalent perpetual bond.
Processes analogous to ecological interactions and dispersal shape the dynamics of economic activities
We find strong support for the models capturing positive interactions between economic activities and spatial dispersal of the activities across countries.
Comparing electricity generation technologies based on multiple criteria scores from an expert group
In many cases, R2>0. 8 suggests that the structured hierarchy of our approach has led to scores that may be used in a semi-quantitative way.
Physics and Society Applied Physics
Generalized logistic growth modeling of the COVID-19 outbreak in 29 provinces in China and in the rest of the world
Japan and Italy are in serious situations with no short-term end to the outbreak to be expected.
Populations and Evolution Biological Physics Applications
Prediction of ESG Compliance using a Heterogeneous Information Network
Negative screening is one method to avoid interactions with inappropriate entities.
Are Bitcoin Bubbles Predictable? Combining a Generalized Metcalfe's Law and the LPPLS Model
We develop a strong diagnostic for bubbles and crashes in bitcoin, by analyzing the coincidence (and its absence) of fundamental and technical indicators.
Learning like humans with Deep Symbolic Networks
The DSN model provides a simple, universal yet powerful structure, similar to DNN, to represent any knowledge of the world, which is transparent to humans.
Decision trees unearth return sign correlation in the S&P 500
However, these models are unsuited to find non-linearly separable patterns.
High quality topic extraction from business news explains abnormal financial market volatility
We show that the whole landscape of news that affect stock price movements can be automatically summarized via simple regularized regressions between trading activity and news information pieces decomposed, with the help of simple topic modeling techniques, into their "thematic" features.
Generalized q-Analysis of Log-Periodicity: Applications to Critical Ruptures
We use this generalized q-analysis to construct a signature called the (H, q)-derivative of discrete scale invariance, which we use to detect the log-periodicity in the energy release rate and its cumulative preceding the rupture of five pressure tanks made of composite carbon-matrix material.
Statistical Mechanics
