Chaoticity versus stochasticity in financial markets: are daily S\&P 500 return dynamics chaotic?
From MaRDI portal
Publication:2076249
DOI10.1016/j.cnsns.2021.106218OpenAlexW4226424557MaRDI QIDQ2076249
Peter Gordon Rötzel, Markus Vogl
Publication date: 16 February 2022
Published in: Communications in Nonlinear Science and Numerical Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cnsns.2021.106218
Mathematical economics (91Bxx) Inference from stochastic processes (62Mxx) Dynamical systems with hyperbolic behavior (37Dxx)
Related Items (2)
Chaos measure dynamics in a multifactor model for financial market predictions ⋮ Recurrence-based reconstruction of dynamic pricing attractors
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Hopf bifurcation and topological horseshoe of a novel finance chaotic system
- Combining a feedback linearization controller with a disturbance observer to control a chaotic system under external excitation
- Dynamic bifurcations on financial markets
- Random walk or chaos: a formal test on the Lyapunov exponent
- Forecasting business cycle with chaotic time series based on neural network with weighted fuzzy membership functions
- Neural network method for determining embedding dimension of a time series
- A new method to control chaos in an economic system
- Testing the null hypothesis of stationarity against the alternative of a unit root. How sure are we that economic time series have a unit root?
- An equation for hyperchaos
- Stochastic analysis of recurrence plots with applications to the detection of deterministic signals
- An observer-based tracker for hybrid interval chaotic systems with saturating inputs: the chaos-evolutionary-programming approach
- Testing for nonlinearity in time series: the method of surrogate data
- Nonlinear evolution operators and wavelets
- Determining Lyapunov exponents from a time series
- Measuring the strangeness of strange attractors
- Extracting qualitative dynamics from experimental data
- Statistical description of chaotic attractors: the dimension function
- State space reconstruction in the presence of noise
- Chaotic behaviour in exchange-rate series. First results for the Peseta- U.S. Dollar case
- Practical method for determining the minimum embedding dimension of a scalar time series
- The analysis of chaotic time-series data
- Critical phenomena in natural sciences. Chaos, fractals, selforganization and disorder: concepts and tools.
- On complex behavior and exchange rate dynamics
- Is a hyperchaotic attractor superposition of two multifractals?
- A two-dimensional Haar wavelets method for solving systems of PDEs
- Nonlinear manifold learning for early warnings in financial markets
- A generalized BDS statistic
- The chaotic attractor analysis of DJIA based on manifold embedding and Laplacian eigenmaps
- The bootstrap and Lyapunov exponents in deterministic chaos
- Entropy and predictability of stock market returns.
- Predicting chaotic time series with wavelet networks
- Identification of models for chaotic systems from noisy data: implications for performance and nonlinear filtering
- Robust estimation of tangent maps and Liapunov spectra
- The topological invariance of Lyapunov exponents in embedded dynamics
- The influence of noise on the correlation dimension of chaotic attractors
- Testing chaotic dynamics via Lyapunov exponents.
- Exploring the topology of dynamical reconstructions
- Chaotic signals inside some tick-by-tick financial time series
- Nonlinearities and regimes in conditional correlations with different dynamics
- Cryptocurrency forecasting with deep learning chaotic neural networks
- Multiscale transfer entropy: measuring information transfer on multiple time scales
- A financial hyperchaotic system with coexisting attractors: dynamic investigation, entropy analysis, control and synchronization
- Wavelet shrinkage of a noisy dynamical system with non-linear noise impact
- Analysis of neural networks with chaotic dynamics
- A practical method for calculating largest Lyapunov exponents from small data sets
- Algorithms for generating surrogate data for sparsely quantized time series
- Chaos and Hopf bifurcation of a finance system
- Nonparametric neural network estimation of Lyapunov exponents and a direct test for chaos
- Line structures in recurrence plots
- A wavelet filtering based analysis of macroeconomic indicators: the Indian evidence
- Financial modeling and quantum mathematics
- High level chaos in the exchange and index markets
- Adaptive wavelet thresholding for image denoising and compression
- Adapting to Unknown Smoothness via Wavelet Shrinkage
- Statistical properties of demand fluctuation in the financial market
- Independent coordinates for strange attractors from mutual information
- On Endogenous Competitive Business Cycles
- Increasing seasonal variation; unit roots versus shifts in mean and trend
- A test for independence based on the correlation dimension
- Deterministic Nonperiodic Flow
- Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
- WHY THE RETURN NOTION MATTERS
- The Kolmogorov-Smirnov Test for Goodness of Fit
- Controlling chaotic dynamical systems
This page was built for publication: Chaoticity versus stochasticity in financial markets: are daily S\&P 500 return dynamics chaotic?