This paper considers the optimal consumption-investment strategy for a consumer receiving stochastic salary and having time-varying relative risk aversion. We assume that the consumer participates in the labor market, receives salary, consumes and invests her wealth in a risky stock and a risk-free bond, with the goal of maximizing the expected utility from both the future consumption and the terminal wealth at retirement. We define the stochastic salary process as a geometric Brownian motion, and assume her relative risk aversion to be time-varying. In our model, the financial market is complete and we provide an analytical characterization of the optimal consumption-investment strategy using the martingale approach. Furthermore, we present some sensitivity analysis of the optimal strategy. Our results show that when facing a time-varying relative risk aversion, the initial wealth plays a significant role in the consumer's optimal consumption. What is more, a new composition to hedge the salary risk exits in her optimal investment strategy, and when her liquid wealth level grows, the consumption-income ratio increases, but the change of her consumption is uncertain.
Order parameters indicate macro orderly degree of new system structure in the evolution of synergy system. For order parameter in the food quality chain coordination system, order parameter identification method is put forward based on attributes reduction and grey correlation degree. First of all, the role of order parameter principle in food quality chain coordination system is analyzed. Then, the food quality chain coordination elements are determined, and state parameters are established to describe the food quality chain system. Then the order parameter solving method is put forward. Parameter important degree of each state parameter is defined and solved based on grey correlation degree. Overlapping relation of state parameters is defined to make sure that state parameters with higher overlapping degree do not exist, and the specific steps to solve order parameter are put forward based on attribute reduction principle. Finally, the proposed order parameter identification method is applied to the concrete quality chain of dairy products and the effectiveness of the proposed method was verified.
Using the data of manufacturing private listed companies from 2008 to 2015 with the new perspective of banking connection structure, this paper studies the influence of financing debts on R&D investment. The empirical results show that the banking connection can promote companies' R&D investment and ease the predicament of enterprise's debt financing, which is more remarkable in long-term financing debt. Besides, enterprises with holdings relationship is more significant compared with that executives' relationship exists in our further research. And the impact is greater on companies that are small-sized, high-tech and in the worse financial ecological environment regional. In particular, we also find that the short-term financing debts also exist R&D governance role on small companies and high-tech companies with holdings relationship. This paper explains the important influence of banking connecting which made on private manufacturing companies' innovation.
A complete minimum attribute reduction algorithm based on fusion of rough equivalence class and tabu search is proposed. Firstly, three types of rough equivalence classes (RECs) are proposed based on the smallest computational granularity of global equivalences, 0-REC will be reduced to empty set in the incremental computation of reduction, through which an equal method to substitute positive region calculation is inferred. Also the two-directional diminishing strategies for reducing computation regions are designed, then basic algorithms are proposed such as the quick initial solution computation and limited solution certification. Then multiple tabu search strategies facing properties of attribute reduction are designed, including bidirectional neighbor search, aspiration criterion, limited random searching, limited validation. At last the complete minimum attribute reduction algorithm is proposed. 20 decision sets of UCI, KDDCup massive data sets are used to verify our algorithm using several performance measures, and the results prove that the theory of REC and tabu search can make the algorithm complete and efficient, in most conditions, the algorithm of this paper is able to acquire the minimum attribute reduction and superior to current algorithms in escaping from local optimum, rate of convergence and handling massive data.
In order to further improve the accuracy, a forecasting method with combined residual error correction is used in this paper. Based on the forecasting method, the residual error correction model and its combination ways are analyzed among some single forecasting methods, and the very high accuracy of the combination method with two minimum relative prediction errors is proven within a certain period. And then one forecasting method with dynamical combined residual error correction is proposed, based on choosing two minimum relative prediction errors to form the correction model during different periods. A study case indicates that the combination ways proposed in this paper can further improve the accuracy of combination forecast.
The topological importance or functional importance is only taken into consideration, when the existing measures are constructed. Based on functional properties of components, generalized importance measures, which improve topological measures in network theory, are proposed to combine with Choquet integral. In order to overcome the uncertainty and randomness, which exist if a single importance measure identifies critical components, aggregation operator (AO) is given through fusion multi-generalized importance measures and then used to identify critical components of complex electromechanical system. Finally, a case study which selects fuzzy integral to treat as AO is presented to identify critical components of bogie system. The results show that the method with Choquet integral regarding as AO and k fuzzy measure calculating weights, is effective.