Dynamical approach to complex regional economic growth based on Keynesian model for China

The paper addresses the problem of complex regional economic growth by using nonlinear Keynesian model with focusing on direct foreign investments effects. We investigate the dynamics of the model for the broad range of parameters which, in particular, contains the parameter values obtained recently by econometric analysis of the data for economic growth in China. For the single-region model we give conditions for which the dynamics of the model will be chaotic or regular. The parameters which prevent the economic stagnation are indicated. Further, we consider the model for two regions with a common trade as a coupling factor. The conditions are given for the two trading systems to exhibit chaotic synchronization, in-phase and out-of-phase behavior.     

Exponential wealth distribution in a random market. A rigorous explanation

In simulations of some economic gas-like models, the asymptotic regime shows an exponential wealth distribution, independently of the initial wealth distribution given to the system. The appearance of this statistical equilibrium for this type of gas-like models is explained in a rigorous analytical way.     

基于多分辨分析的沪深股市相关性分析

为了有效地揭示沪深股市不同交易周期股票交易的相关性,本文采用极大重叠离散小波变换,将上证指数和深圳成指高频收益率分解在不同的交易周期上,对各个周期的收益率采用semi-GPD模型作为其边缘分布分别进行拟合,在此基础上采用Copula函数方法建立同周期收益率的联合分布,度量了沪深两市同周期交易的相关性.实证表明,不同交易周期所表现出的相关性存在明显差异,并且随着交易期的增长,沪深两市非对称结构逐步明显。     

Complex nonlinear dynamics and controlling chaos in a Cournot duopoly economic model

Complex nonlinear economic dynamics in a Cournot duopoly model proposed by M. Kopel is studied in detail in this work. By utilizing the topological horseshoe theory proposed by Yang XS, the authors detect the topological horseshoe chaotic dynamics in the Cournot duopoly model for the first time, and also give the rigorous computer-assisted verification for the existence of horseshoe. In the process of the proof, the topological entropy of the Cournot duopoly model is estimated to be bigger than zero, which implies that this economic system definitely exhibits chaos. In particular, the authors observe two different types of economic intermittencies, including the Pomeau–Manneville Type-I intermittency arising near a saddle-node bifurcation, and the crisis-induced attractor widening intermittency caused by the interior crisis, which lead to the appearance of intermittency chaos. The authors also observe the transient chaos phenomenon which leads to the destruction of chaotic attractors. All these intermittency phenomena will help us to understand the similar dynamics observed in the practical stock market and the foreign exchange market. Besides, the Nash-equilibrium profits and the chaotic long-run average profits are analyzed. It is numerically demonstrated that both firms can have higher profits than the Nash-equilibrium profits, that is to say, both of the duopolists could be beneficial from a chaotic market. The controlled Cournot duopoly model can make one firm get more profit and reduce the profit of the other firm, and control the system to converge to an equilibrious state, where the two duopolists share the market equally.     

具有增益的概率网络金融计划模型

本文绘出一类具有增益的概率网络金融计划模型．许多多阶段金融计划问题可纳入这类模型．在这类模型中,随机变量的分布函数与Alexander过滤交易规则密切联系在一起,金融市场交易信号由神经网络产生,目标函数的最优值按其期望值计算．文中提出临界流和临界路的概念,给出目标函数下界等于其期望值的充分必要条件和期望最优解的求解方法．     

A novel chaotic particle swarm optimization approach using Hénon map and implicit filtering local search for economic load dispatch

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm driven by the simulation of a social psychological metaphor instead of the survival of the fittest individual. Based on the chaotic systems theory, this paper proposed a novel chaotic PSO combined with an implicit filtering (IF) local search method to solve economic dispatch problems. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed PSO introduces chaos mapping using Hénon map sequences which increases its convergence rate and resulting precision. The chaotic PSO approach is used to produce good potential solutions, and the IF is used to fine-tune of final solution of PSO. The hybrid methodology is validated for a test system consisting of 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. Simulation results are promising and show the effectiveness of the proposed approach.     

Complex economic dynamics: Chaotic saddle, crisis and intermittency

Complex economic dynamics is studied by a forced oscillator model of business cycles. The technique of numerical modeling is applied to characterize the fundamental properties of complex economic systems which exhibit multiscale and multistability behaviors, as well as coexistence of order and chaos. In particular, we focus on the dynamics and structure of unstable periodic orbits and chaotic saddles within a periodic window of the bifurcation diagram, at the onset of a saddle-node bifurcation and of an attractor merging crisis, and in the chaotic regions associated with type-I intermittency and crisis-induced intermittency, in non-linear economic cycles. Inside a periodic window, chaotic saddles are responsible for the transient motion preceding convergence to a periodic or a chaotic attractor. The links between chaotic saddles, crisis and intermittency in complex economic dynamics are discussed. We show that a chaotic attractor is composed of chaotic saddles and unstable periodic orbits located in the gap regions of chaotic saddles. Non-linear modeling of economic chaotic saddle, crisis and intermittency can improve our understanding of the dynamics of financial intermittency observed in stock market and foreign exchange market. Characterization of the complex dynamics of economic systems is a powerful tool for pattern recognition and forecasting of business and financial cycles, as well as for optimization of management strategy and decision technology.     

Chaos generation via a switching fractional multi-model system

This paper introduces a system with switching multi-model structure which can generate chaos. Sub-models in this structure are fractional-order linear systems with any desired commensurate order less than 1. It shows that this system is capable of demonstrating chaotic behavior if its parameters and switching rule are suitably chosen. The structure of the proposed system is defined in a general form; consequently various chaotic attractors can be created by this system with different choices of order, parameters and switching rule. Numerical simulations illustrate behavior of the introduced system in some different situations.     

CATCHMENT BEHAVIOR AND COUNTER‐CYCLICAL WATER TRADE: AN INTEGRATED MODEL

ABSTRACT. Murray Basin water resources are under increasing pressure to satisfy often conflicting environmental and economic objectives. Governments, as the “environmental steward,” have several management options including water trading and banking water until it can be used to greatest effect and occasionally selling water back to irrigators. This is sometimes known as counter‐cyclic trading. To examine the potential of the above options, a model of water trading and banking in a simple market is developed. The model combines a catchment hydrology model with economic information that drives land use practice and demand for water. Simulations are used to explore these options at a strategic level. The potential impacts of increased upland afforestation and climate change on catchment hydrology in the presence of a pro‐active environmental steward are considered. It is concluded that in a system where entitlements are capped it is likely that the most cost‐effective management system will involve counter‐cyclic trading.     

Optimal and coherent economic-capital structures: evidence from long and short-sales trading positions under illiquid market perspectives

This paper broadens research literature associated with the assessment of modern portfolio risk management techniques by presenting a thorough modeling of nonlinear dynamic asset allocation and management under the supposition of illiquid and adverse market settings. Specifically, the paper proposes a re-engineered and robust approach to optimal economic capital allocation, in a Liquidity-Adjusted Value at Risk (L-VaR) framework, and particularly from the perspective of trading portfolios that have both long and short-sales trading positions. This paper expands previous approaches by explicitly modeling the liquidation of trading portfolios, over the holding period, with the aid of an appropriate scaling of the multiple-assets’ L-VaR matrix along with GARCH-M technique to forecast conditional volatility and expected return. Moreover, in this paper, the authors develop a dynamic nonlinear portfolio selection model and an optimization algorithm which allocates both economic capital and trading assets subject to some selected financial and operational rational constraints. The empirical results strongly confirm the importance of enforcing financially and operationally meaningful nonlinear and dynamic constraints, when they are available, on economic capital optimization procedure. The empirical results are interesting in terms of theory as well as practical applications and can aid in developing robust portfolio management algorithms that financial entities could consider in light of the aftermath of the latest financial crisis.     

Measuring complexity in a business cycle model of the Kaldor type

The purpose of this paper is to study the dynamical behavior of a family of two-dimensional nonlinear maps associated to an economic model. Our objective is to measure the complexity of the system using techniques of symbolic dynamics in order to compute the topological entropy. The analysis of the variation of this important topological invariant with the parameters of the system, allows us to distinguish different chaotic scenarios. Finally, we use a another topological invariant to distinguish isentropic dynamics and we exhibit numerical results about maps with the same topological entropy. This work provides an illustration of how our understanding of higher dimensional economic models can be enhanced by the theory of dynamical systems.     

Optimal Execution in a Market with Small Investors

Abstract

The author considers the dynamic trading strategies that minimize the expected cost of trading a large block of securities over a fixed finite number of periods. In this model, the market impact function that yields the execution prices for individual trades is endogeneously determined. This analysis is novel in that it introduces small investors, who do not affect the price flow, and a noise trader as market participants other than the institutional investors into a general equilibrium model. It is found that the institutional investor takes a rather complicated strategy to make use of its private information. As a result, the price impact not only changes over time but also depends on the trade history. Although there are several studies that deal with this topic in the recent empirical literature, it has remained unnoticed in the context of the theoretical optimal execution model.     

Hierarchy of islands in conservative systems yields multimodal distributions of FTLEs

We investigate the motion in a chaotic layer of conservative systems using finite time Lyapunov exponents (FTLEs). For long finite time spans we find the distributions of FTLEs to be multimodal. Due to stickiness near islands of regular motion, the trajectory can spend a long time in their vicinity. The higher the order of an island in the hierarchy of islands, the smaller is the value of the largest FTLE. Using this connection, we explain the occurrence of multimodal distributions of FTLEs as a result of an overlap of individual distributions of FTLEs, each corresponding to the motion near islands of different orders.     

Complex dynamics in equilibrium asset pricing models with boundedly rational,heterogeneous agents

We study a simple model based upon the Lucas framework where heterogeneous agents behave rationally in a fully intertemporal setting but do not know other investors' personal preferences, wealth or investment portfolios. As a consequence, agents initially do not know the equilibrium asset pricing function and must make guesses, which they update via adaptive learning with constant gain. We demonstrate that even in this simple environment the economy can, depending on parameters, exhibit either stable convergence to equilibrium, or chaotic dynamical behavior of asset prices and trading volume without converging to the rational expectations equilibrium of the Lucas model. This contradicts the assertion that the Lucas model is stable in the face of modest deviations from the strong assumptions required to compute the equilibrium. © 2013 Wiley Periodicals, Inc. Complexity 19: 38–55, 2014     

基于实物期权定价方法的林业碳汇项目投资决策仿真研究

文章针对林业碳汇项目投资决策的复杂性、动态性和不确定性过程,利用林业—碳汇共同经营决策模型计算林业碳汇项目在投资期内的期望价值,采用实物期权定价方法对不同阶段不同策略下的林业碳汇项目价值进行评估,同时提出了多主体仿真建模方法,利用NetLogo仿真软件对林业碳汇项目投资决策过程进行动态模拟。仿真系统中涉及到的主体有林地、CO₂和投资者,投资者主要是作为观察者的身份,在不同阶段会做出不同的投资策略。模拟仿真三种不同状态下投资者的决策变化:一是传统林业投资动态模拟,不包含碳汇和期权因素动态模拟;二是引入碳汇市场后的林业投资动态模拟;三是引入碳汇市场和期权后林业投资动态模拟。NetLogo仿真分析结果表明引入碳汇市场可以提高投资者的收益并改变投资者的经营策略,同时引入期权,不仅增加了投资者的积极性而进行扩张投资,还可以更好地发挥林木碳汇功能,体现林业的生态价值及经济价值。     

期货合约的简单创新

本文通过观察代办收入最大化交换,提出期货合约创新的一个简单两阶段模型. 经济代理商具有均值-方差偏好,按代理买卖量的大小,在期货合约过程中收取交易费用.期货交易过程中存在价差.代办收入最大化交换促成期货合约的创新.     

Nonlinear electronic circuit,Part I: Multiple routes to chaos

A nonlinear electronic oscillator, suitable for synchronized chaotic communication, is studied. This circuit is capable of transmitting discrete chaotic signals, although the chaotic modes of operation are controlled in an analog way. In Part I of this review paper the three routes to chaotic operation that appear, namely the period doubling, intermittency and crisis induced intermittency, are thoroughly studied and discussed. In all three routes to chaos the appropriate experimental distributions were calculated. Moreover, the chaotic nature of the circuit operation was evaluated by using the Grassberger–Procaccia method. Calculation of the corresponding minimum embedding dimension, the Kolmogorov–Sinai entropy as well as the maximal Lyapunov exponent give useful information in order to fully characterize the circuit operation.     

Nonlinear electronic circuit, Part I: Multiple routes to chaos

A nonlinear electronic oscillator, suitable for synchronized chaotic communication, is studied. This circuit is capable of transmitting discrete chaotic signals, although the chaotic modes of operation are controlled in an analog way. In Part I of this review paper the three routes to chaotic operation that appear, namely the period doubling, intermittency and crisis induced intermittency, are thoroughly studied and discussed. In all three routes to chaos the appropriate experimental distributions were calculated. Moreover, the chaotic nature of the circuit operation was evaluated by using the Grassberger-Procaccia method. Calculation of the corresponding minimum embedding dimension, the Kolmogorov-Sinai entropy as well as the maximal Lyapunov exponent give useful information in order to fully characterize the circuit operation.     

LP models for pricing diffuse nitrate discharge permits

Nitrate discharges from diffuse agricultural sources significantly contribute to groundwater and surface water pollution. Tradable permit programs have been proposed as a means of controlling nitrate emissions efficiently, but trading is complicated by the dispersed and delayed effects of the diffuse pollution. Hence, markets in nitrate discharge permits should be carefully designed to account for the underlying spatial and temporal interactions. Nitrate permit markets can be designed similar to the modern electricity markets which use LPs to find the equilibrium prices because the two trading problems have close analogy. In this paper, we propose alternative LP models to find efficient permit prices for year-ahead markets. The model structure varies depending on the catchment hydro-geology and long-term goals of the community. We show how the market price structures are driven by the constraint structure under different environmental conditions. We discuss the physical and economic conditions required to assure consistent prices, the modeling of essential and optional constraints in an LP, and the problem of balancing resource allocation over time among delayed-response discharge units. We then extend the LP model to balance resource allocation over time and to improve the market performance.     

Application of seasonal SVR with chaotic gravitational search algorithm in electricity forecasting

Hybridization chaotic mapping functions with optimization algorithms into a support vector regression model has been shown its efficient potential to avoid converging prematurely. It is deserved to explore more possibility by hybridizing with other optimization algorithms. Electricity demand sometimes demonstrates a seasonal tendency due to complicate economic activities or climate cyclic nature. This investigation presents a SVR-based electricity forecasting model which applied a novel hybrid algorithm, namely chaotic gravitational search algorithm (CGSA), to improve the forecasting performance. The proposed CGSA employs the chaotic local search by logistic chaotic mapping function in the iteration of the original GSA to search and refine the current best solution. In addition, seasonal mechanism is also applied to deal with seasonal electricity tendency. A numerical example from an existed reference is used to illustrate the forecasting performance of the proposed SSVRCGSA model. The forecasting results indicate that the proposed model yields more accurate forecasting results than ARIMA and TF-ε-SVR-SA models.