Statistical methods for decision support systems in finance: how Benford's law predicts financial risk

Cites Work

Title not available (Why is that?)
Two-stage financial risk tolerance assessment using data envelopment analysis
A data analytic approach to forecasting daily stock returns in an emerging market
Testing market efficiency on the Johannesburg Stock Exchange using the overlapping serial test
Logical analysis of data: classification with justification
Prediction of cryptocurrency returns using machine learning
Forecasting benchmarks of long-term stock returns via machine learning
ARCH modeling in finance. A review of the theory and empirical evidence
A comparison of linear regression and neural network methods for predicting excess returns on large stocks
Note on the frequency of use of the different digits in natural numbers.
A statistical derivation of the significant-digit law
Evolutionary-based return forecasting with nonlinear STAR models: evidence from the Eurozone peripheral stock markets
Equilibrium-based volatility models of the market portfolio rate of return (peacock tails or stotting gazelles)
Deep learning with long short-term memory networks for financial market predictions
Early warning on stock market bubbles via methods of optimization, clustering and inverse problems
Generalized autoregressive conditional heteroscedasticity
Long memory processes and fractional integration in econometrics
Modeling volatility persistence of speculative returns: a new approach
Forecasting financial failure using a Kohonen map: a comparative study to improve model stability over time
A differential evolution-based regression framework for forecasting Bitcoin price
Data validity and statistical conformity with Benford's law
A financial fraud detection indicator for investors: an \textit{IDeA}
Volatility in the stock market: ANN versus parametric models
Modelling and forecasting the kurtosis and returns distributions of financial markets: irrational fractional Brownian motion model approach
A further analysis of robust regression modeling and data mining corrections testing in global stocks
Cluster-based outlier detection
Estimating value-at-risk and expected shortfall using the intraday low and range data
Exploring the financial risk of a temperature index: a fractional integrated approach
Optimal and coherent economic-capital structures: evidence from long and short-sales trading positions under illiquid market perspectives
Support vector machine as an efficient framework for stock market volatility forecasting
Testing the accuracy of employee-reported data: an inexpensive alternative approach to traditional methods
Benford's law. Theory, the general law of relative quantities, and forensic fraud detection applications
Conditional Heteroskedasticity in Asset Returns: A New Approach
Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
Base-Invariance Implies Benford's Law
Volatility processes and volatility forecast with long memory
The Significant-Digit Phenomenon
Comparisons of various types of normality tests
Explaining the uneven distribution of numbers in nature: the laws of Benford and Zipf

This page was built for publication: Statistical methods for decision support systems in finance: how Benford's law predicts financial risk

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6666701)