Results 161 to 170 of about 278,010 (203)

Applied stochastic modelling in financial economics

2019
This Ph.D thesis focuses on two applied frameworks of stochastic con- trolling and optimisation in financial economics. The first focus (Chapter 1) is on the convergence trading with testing cross-listed stock arbitrage. The second (Chapter 2 to Chapter 4) is on the sequential studies of wealth inequality.
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Stochastic Processes in Economic Models

1986
Stochastic processes have found increasing applications in modern economic models. In earlier times they were mainly used as additive errors or noise in a deterministic model without contributing very much to our basic understanding of the model structure, except perhaps hleping in providing a satisfactory basis of econometric estimation, e.g., the use
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The Oil Energy Price Cycle in Economic Activities: A Stochastic Model

Energy Sources, Part B: Economics, Planning, and Policy, 2013
In the past, significant research has been conducted on the relationship between energy consumption and economic activities; a number of these articles have discussed the effects and shocks of energy prices in relation to economic growth. However, to date there has been little in the way of substantive research pertaining to the cycle of energy prices,
C.-C. Chang, T.-C. Lai
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Stochastic optimization in linear economic models

1985
Linear economic models containing variablesx,y and parametersθ, that may be subject to a stochastic generating mechanism pose two basic problems of optimization. One is the problem of estimation of parametersθ from observations onx andy. This is dealt with in econometrics. The second is the problem of optimal decision-making under uncertainty under the
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From Stochastics to Complexity in Models of Economic Instability

Nonlinear Dynamics, Psychology, and Life Sciences, 1997
Sixty years ago, the leading lights of the economics profession chose to model economic fluctuations as if they were caused by stochastic disturbances to an underlying stable, heavily damped system, in the mistaken belief that “a mathematically unstable system does not fluctuate; it just breaks down.” A perceptive minority instead concluded that the ...
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Stochastic differential games in economic modeling

1994
In this paper we present two continuous-time models of economic competition which are based on a stochastic differential game formalism. We focus our presentation on the modeling possibilities offered by the frameworks of piecewise deterministic and switching diffusion control systems respectively.
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Stochastic unit-root models in economics

2013
The dissertation at hand consists of three essays focussing on so-called stochastic unit-root (STUR) models in economics. A test of the null hypothesis of a unit root in an autoregressive model of order one (AR(1)) against alternatives nested in a STUR model is introduced. STUR models allow for changes between stationary and explosive regimes.
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THE TURNPIKE IN DYNAMIC STOCHASTIC ECONOMIC GROWTH MODELS FOR STATE-CONTINGENT CAPITAL STOCKS

Acta Mathematica Scientia, 1994
Turnpike theorems state conditions under which an optimal growth program converges to a stationary solution. This paper shows that a turnpike theorem holds in a stochastic environment for programs that satisfy a uniformly essentially dominant diagonal block condition.
Chiang, Chiaoning, Yu, Xiaopei, He, Sui, Jian, Ming   +3 more
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Measuring Economic Uncertainty in Syria: An Approach to the Stochastic Volatility Model

Indian Journal of Economics and Development, 2022
This research aimed to propose an index that measures the degree of economic uncertainty in Syria. As it is a difficult situation to predict, the economic future's uncertainty may be a latent variable that drives random fluctuations in the variables of the economy.
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Stochastic Control and Mathematical Modeling: Applications in Economics, by H. Morimoto

Contemporary Physics, 2012
Stochastic Control and Mathematical Modeling: Applications in Economics, by H. Morimoto, Cambridge, Cambridge University Press, 2010, 340 pp., £70.00 (hardback), ISBN 978-0-521-19503-4.
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