1,720,983 research outputs found
Modeling and analysis of financial time series beyond geometric Brownian motion
No full textIn this short review, the modeling and analysis of stock price financial series are presented in
two different flavors: the dynamical picture provided by stochastic volatility models, capturing
the non constant nature of price fluctuations, and a clustering Bayesian approach eliciting the
underlying partition structure of data. The main theoretical results, obtained for specific mod-
els, are presented and some examples of empirical analysis and financial application are then
considered, showing the effectiveness of these approaches in capturing the non Gaussian behav-
ior of empirical returns, their non trivial correlations, and, at a higher level, the effects of these features in determining the market risk exposure or the prices of stock option contracts
Minimal model of financial stylized facts
No full textIn this work we propose a statistical characterization of a linear stochastic volatility model featuring inverse-
gamma stationary distribution for the instantaneous volatility. We detail the derivation of the moments of the
return distribution, revealing the role of the inverse-gamma law in the emergence of fat tails and of the relevant
correlation functions. We also propose a systematic methodology for estimating the parameters and we describe
the empirical analysis of the Standard & Poor’s 500 index daily returns, confirming the ability of the model to
capture many of the established stylized facts as well as the scaling properties of empirical distributions over
different time horizons
Stochastic volatility with heterogeneous time scales
Full text linkIn this work, the model for the statistical description of financial stylized facts proposed in Delpini and Bormetti (2011) is amended from the unrealistically fast decay of the volatility autocorrelation. This is achieved by introducing an extra stochastic factor that drives the volatility. With respect to previous approaches and analyses of continuous-time stochastic volatility models, we believe that the estimation procedure proposed here represents a further improvement and fulfills the desirable requirements of statistical soundness. At the same time, it also allows us to focus on those facts which are established as relevant for the description of financial data. In particular, we pursue an heuristic approach to optimization that reduces the dimensionality of the parameter space and retains only the ingredients needed to capture the aforementioned empirical evidence
Exact moment scaling from multiplicative noise
No full textFor a general class of diffusion processes with multiplicative noise, describing a variety of physical as well
as financial phenomena, mostly typical of complex systems, we obtain the analytical solution for the moments
at all times. We allow for a nontrivial time dependence of the microscopic dynamics and we analytically
characterize the process evolution, possibly toward a stationary state, and the direct relationship existing
between the drift and diffusion coefficients and the time scaling of the moments
The ecology of animal species’ behaviors in a Solow-type model
No full textIn light of the rapidly expanding body of literature examining the adverse effects of human-induced changes in animal behavior on ecological dynamics, biodiversity conservation, and human well-being, this study investigates a bio-economic dynamic model characterized by a system of three ordinary differential equations. The model incorporates three state variables: K , x , and y . The variable K represents the stock of productive capital in the economy. The variable x denotes the size of the population of animals (from a representative species) exhibiting “typical” behavior; that is, the one that animals would adopt in the absence of human interference (e.g., hunting prey). The variable y denotes the size of the population displaying “non-typical” behavior, adopted either to mitigate the harmful impacts of human activities or to opportunistically exploit anthropogenic resources, such as food by-products. The dynamics of x and y are modelled starting from a system of Lotka-Volterra equations and augmenting it with a component depending on the difference in the payoffs (fitness) of the two behaviors. The stock of capital follows a Solow-type dynamics incorporating defensive expenditure aimed at protecting animals that adopt typical behavior. Our study reveals that the interaction between the dynamics of animal behavior adoption and economic growth can lead to a wide range of equilibrium outcomes. In some equilibria, the animal population fully specializes by adopting either the typical or the non-typical behavior, while in others, a coexistence is observed. We derive policy recommendations to minimize the adoption of non-typical behavior, finding that the optimal ecological outcome is not achieved by maximizing expenditure, but rather by striking a precise balance between ecological defense and economic viability
Dynamical analysis of a prey-predator-tourist model: Environmental preferences and optimal fee control
Full text linkExact moment scaling from multiplicative noise
No full textFor a general class of diffusion processes with multiplicative noise, describing a variety of physical as well as financial phenomena, mostly typical of complex systems, we obtain the analytical solution for the moments at all times. We allow for a nontrivial time dependence of the microscopic dynamics and we analytically characterize the process evolution, possibly toward a stationary state, and the direct relationship existing between the drift and diffusion coefficients and the time scaling of the moments. © 2010 The American Physical Society
The power to control
No full textUnderstanding something of the complexity of a financial network is one thing, influencing the behaviour of that system is another. But new tools from network science define a notion of 'controllability' that, coupled with 'centrality', could prove useful to economists and financial regulators
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