Results 21 to 30 of about 229 (64)
Continuous invertibility and stable QML estimation of the EGARCH(1,1) model [PDF]
We introduce the notion of continuous invertibility on a compact set for volatility models driven by a Stochastic Recurrence Equation (SRE). We prove the strong consistency of the Quasi Maximum Likelihood Estimator (QMLE) when the optimization procedure ...
Wintenberger, Olivier
core +5 more sources
A Bayesian Networks Approach to Operational Risk
A system for Operational Risk management based on the computational paradigm of Bayesian Networks is presented. The algorithm allows the construction of a Bayesian Network targeted for each bank using only internal loss data, and takes into account in a ...
Aquaro, V. +5 more
core +1 more source
Price dynamics and trading volume: A semiparametric approach [PDF]
In this paper we investigate the relation between price impact and trading volume for a sample of stocks listed on the New York Stock Exchange. The parametric VAR-models that have been used in the literature impose strong proportionality and symmetry ...
Nijman, T.E. +2 more
core +3 more sources
Social Media Impact on the ‘Cosmos’ Blockchain Ecosystem: State and Prospect
The proliferation of blockchain technology heralds transformative impacts across various sectors, offering decentralization, transparency, and enhanced security.
Ivan Pavlyshyn +4 more
doaj +1 more source
Near-integrated GARCH sequences
Motivated by regularities observed in time series of returns on speculative assets, we develop an asymptotic theory of GARCH(1,1) processes {y_k} defined by the equations y_k=\sigma_k\epsilon_k, \sigma_k^2=\omega +\alpha y_{k-1}^2+\beta \sigma_{k-1}^2 ...
Berkes, Istvan +2 more
core +1 more source
Forecasting electronic money trends in Indonesia using neural network models: A comparative analysis
Forecasting electronic money transaction values is essential for effective financial planning and decision-making in various industries. This study evaluates the performance of three neural network models, which are Extreme Learning Machines (ELM ...
Umi Mahmudah +2 more
doaj +1 more source
Extremal behavior of stochastic volatility models [PDF]
Empirical volatility changes in time and exhibits tails, which are heavier than normal. Moreover, empirical volatility has - sometimes quite substantial - upwards jumps and clusters on high levels.
Fasen, V. +2 more
core +2 more sources
A Continuous Time GARCH Process of Higher Order [PDF]
A continuous time GARCH model of order (p,q) is introduced, which is driven by a single Lévy process. It extends many of the features of discrete time GARCH(p,q) processes to a continuous time setting.
Brockwell, Peter J. +2 more
core +2 more sources
Asymptotic equivalence for inference on the volatility from noisy observations
We consider discrete-time observations of a continuous martingale under measurement error. This serves as a fundamental model for high-frequency data in finance, where an efficient price process is observed under microstructure noise.
Reiß, Markus
core +1 more source
Modelling stock returns with AR-GARCH processes [PDF]
Financial returns are often modelled as autoregressive time series with random disturbances having conditional heteroscedastic variances, especially with GARCH type processes.
Ferenstein, Elzbieta, Gasowski, Miroslaw
core +2 more sources

