中国科学院数学与系统科学研究院期刊网

25 October 2024, Volume 44 Issue 10
    

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  • Command Filtering Fuzzy Control for Stochastic System of Flexible Joint Manipulators with Dead-Zone Input
    DONG Yuanbao, LIU Jiapeng, YU Jinpeng, SU Junhao, LIN Chong
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 2881-2894. https://doi.org/10.12341/jssms23477
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    A fuzzy adaptive control method based on command filtering technology is proposed for a stochastic system of flexible joint manipulators with dead-zone input, which achieves tracking control of the system output on the expected trajectory. Firstly, command filtering technology is used to solve the problem of "explosion of complexity" inherent in the traditional backstepping method, and error compensation mechanism is introduced to eliminate the influence of filtering errors on the system control precision. Then, a fuzzy logic system is utilized to deal with uncertainties and stochastic disturbances in the system, which overcomes the influence of stochastic disturbances and improves the control effect of the system. Finally, considering the system with dead-zone input, the control signal is constructed by backstepping control method, which conquers the adverse impact of dead-zone input on system performance. In the stability analysis, the effectiveness of the control strategy studied in the stochastic system of flexible joint manipulators with dead-zone input is proved, and it is verified by Matlab simulation.
  • Longitudinal Control Strategy of Vehicular Platoon Based on a Finite-Time Disturbance Observer
    ZENG Ye, LEI Hongbo
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 2895-2906. https://doi.org/10.12341/jssms23620
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    This study investigates the longitudinal control problem of vehicle platoon. Considered the characteristic of vehicle platoons being easily affected by large-amplitude and discontinuous external disturbances, a new strategy based on a finite-time disturbance observer and non-singular terminal sliding-mode control (NSTSMC) is proposed. Firstly, disturbances are observed through the finite-time disturbance observer, allowing the observation error to converge to zero within a finite time. Then, by designing an NSTSMC controller, the spacing error of the platoon can move to the designed coupling sliding-mode surface within a finite time, and then the spacing error converges to zero in finite time. Furthermore, by designing the coupling sliding-mode surface coefficients and using the Laplace transform method, the string stability of the vehicle platoon is ensured. Finally, the effectiveness of the proposed algorithm is demonstrated through simulation results, and compared with the traditional sliding-mode control law (SMC), highlighting the superiority of the proposed control algorithm in suppressing disturbances. The results show that the algorithm designed solves the problem of disturbances easily causing instability in the vehicle platoon system, ensuring the safe and stable driving of the vehicle platoon.
  • Research on Feature Selection Method Based on Optimal Overall Default Identification Ability
    WANG Kui, CHENG Jingyi, LI Meiyuan, ZHU Xiaoqian, LI Gang
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 2907-2919. https://doi.org/10.12341/jssms23066
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    Feature selection is an important part of default discriminant modeling. A reasonable feature selection method can simplify the model structure and improve the accuracy of default discrimination. In view of the particularity of financial index data of small and medium-sized enterprises (SMEs) in Xinjiang Uygur Autonomous Region, this paper designs a novel feature selection method guided by the optimal overall default discrimination ability, so that it can comprehensively measure the financial lending risk of the SMEs in the region. In this paper, we collect the SMEs' financial index data of a bank in Xinjiang in 2021, carry out basic descriptive statistics of the data and filled in the missing values. Then, through index prediction ability analysis, multicollinearity diagnosis and a combination of multiple feature selection methods, we screen out the index set with the strongest default discrimination ability of a single index and the best overall default discrimination ability. It is helpful to distinguish the SMEs' default status further and evaluate the SMEs' credit risk. The effectiveness of the discriminant model is tested on the data, and the classification accuracy reaches 95.85%, which proves that the proposed model has great potential in the research and application of credit ratings in Xinjiang.
  • Dependence Between BRICS Stock Markets Based on Factor Hidden Markov Copula Model
    YE Wuyi, ZHANG Shan, JIAO Shoukun
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 2920-2936. https://doi.org/10.12341/jssms23369
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    In order to investigate the impact of significant economic or political events on the dependence of financial markets, we construct the factorial hidden Markov Copula model (FHM-Copula) that allows the coefficients of dependence to follow a regime-switching process in high-dimensional state space. The FHM-Copula model is able to capture external shocks of varying magnitude, direction, duration, and short or long-term from significant events to the dependence. In the empirical study, we analyze the dynamic dependence between the stock markets of China and other BRICS countries by adopting the FHM-Copula approach. Our findings indicate that the FHM-Copula model can effectively identify the external shocks caused by significant events such as the subprime crisis, the European debt crisis, the Chinese stock market crash, China's taking over the BRICS presidency and the COVID-19 epidemic on the dependence between the stock markets of China and other BRICS countries. Our works not only provide a theoretical analysis framework based on the information shock perspective for the study of dynamic dependence among financial variables, but also provide a reference for investors and government regulators in investment decisions and risk management.
  • Research on Supplier Financing Strategy Considering "Greenwashing" Risk
    HU Xueqin, LI Yafei, YANG Xiaoye
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 2937-2950. https://doi.org/10.12341/jssms23174
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    This paper considers the "greenwashing" risk of downstream retailers and constructs bank financing, hybrid financing, and supplier financing models based on game theory. It analyzes the financing preferences of suppliers and operational decisions of retailers under these scenarios. The findings are as follows: 1) Supplier perspective: Supplier financing is most advantageous when the retailer's greenwashing risk fluctuates within a certain range. In this model, suppliers can dynamically adjust interest rates based on the retailer's risk, reducing potential financing risks. 2) Retailer perspective: Retailers are inclined to choose supplier financing only when their greenwashing risk is high. In this model, retailers face dual competition in sales channels and financing costs, leading to reduced order quantities and profits. 3) Conflict of interest: From a self-interest maximization standpoint, supply chain participants cannot agree on a financing model. To achieve a win-win situation, suppliers can limit the order quantities of high-risk retailers based on the assessment of greenwashing risks, reducing competition among retailers.
  • An Analysis of Quality Information Disclosure Strategy of Agricultural Product Based on Blockchain Technology
    HU Sensen, LU Jingyi
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 2951-2972. https://doi.org/10.12341/jssms23532
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    The price mechanism failure caused by fake quality information disclosure restricts the development of the agricultural product market. The transparent and traceable feature of information in the blockchain provides a new solution to the problem of fake quality information disclosure in the agricultural product supply chain. However, the high cost of blockchain, consumer preferences in the market, and block traceability accuracy all affect the strategy of adopting blockchain. This paper uses the signaling game and sets price as the signal to explore blockchain adoption strategies and quality information disclosure strategies in the agricultural product supply chain. This paper finds that: 1) The agricultural supermarket will adopt blockchain technology only when the information increase is high; when farmers' planting cost is low, the agricultural supermarket will be more willing to adopt blockchain. 2) When blockchain technology is not adopted and the planting cost is low, low-quality farmers have the incentive to deliberately set high prices to confuse the market. 3) The adoption of blockchain technology by the agricultural supermarket may harm farmers' profits. Only when the consumers' preference is more information-sensitive, all participants in the agricultural product supply chain can benefit from blockchain.
  • Research on Pricing Strategy of Multi-Channel Supply Chain Based on the Introduction of the Live Streaming Channel
    ZHANG Lei, ZHAO Yu, DUAN Yulan
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 2973-2993. https://doi.org/10.12341/jssms23799
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    For the sales system composed of a manufacturer and a retailer, this paper constructs three decision models that the manufacturer does not introduce the live streaming channel, the manufacturer introduces the store live streaming channel and introduces the anchor live streaming channel, and uses the game theory method to explore the introduction strategy of the manufacturer's live streaming channel and the pricing strategy of multi-channel supply chain under the introduction of the live streaming channel. The results show that after the introduction of the live streaming channel, the manufacturer's revenue increase, the price and sales in the direct sales channel decrease, and the price decreases while the sales increase in the offline retail channel. When the cost of the store live streaming channel is low (high), the introduction of the store (anchor) live streaming channel is conducive to the “low price” strategy of the live streaming channel. When the cost of the store live streaming channel is low and the professional capability of the anchor is weak, the introduction of the store live streaming channel is conducive to the market “penetration” strategy of the live streaming channel, under other conditions, the introduction of the anchor live streaming channel is conducive to the market “penetration” strategy of the live streaming channel. Finally, the price is not necessarily cheap in the live streaming channel.
  • Model Analysis of Debt-to-Equity Ratio for Growth Firm from the Perspective of Supply Chain
    WANG Yu, HE Yutian, LI Xin
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 2994-3010. https://doi.org/10.12341/jssms23250
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    The debt-to-equity swap is an important way to reduce the leverage ratio of enterprises in the new economic situation. However, the market-oriented debt-to-equity swap falls into the dilemma of “more signing and less landing”, which greatly reduces its implementation effect. Present study constructs a debt-to-equity model for growth supplier in debt crisis under the perspective of supply chain, investigates the optimal swap ratio of AMC and operational decision of supplier, and analyses the swap conditions as well as the effect of multi-player game. The results are as follows: Firstly, the AMC chooses to convert all the debt to equity under high P/E ratio, but sets the swap ratio at the minimum value that the supplier is willing to adopt the debt-to-equity swap under low P/E ratio. Secondly, the reasonable matching of high growth and high P/E ratio is conducive to the implementation of the swap and the achievement of win-win situation, while the mismatch of high growth and low P/E ratio can only resolve the debt crisis but cannot improve supplier profitability. However, the low growth supplier should not be the target enterprise of debt-to-equity swap. Finally, the multi-player game behavior is detrimental to the benefits of the supplier and AMC, and even causes to the “prisoner's dilemma” for low-growth supplier, which increased the difficulty in implementing debt-to-equity swap.
  • Capital Market Liberalization and Knight Uncertainty—An Empirical Analysis Based on the Trading Behavior of Northbound Fund
    LI Yang, XIONG Xiong, MENG Yongqiang
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 3011-3024. https://doi.org/10.12341/jssms23609
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    Foreign investors are playing an increasingly important role in China's capital market, and the flow of northbound fund has always been the market indicator that investors focus on. This paper measures the trading behavior of northbound fund based on the data of northbound fund holdings, calculates the Knight uncertainty of stocks based on intraday high-frequency price data, and explores the impact of trading behavior of northbound fund on Knight uncertainty. The empirical results show that the higher the shareholding ratio of northbound funds, the lower the Knight uncertainty. The greater the change in shareholding ratio of northbound funds, the higher the Knight uncertainty. Further research shows that the mechanisms of northbound funds' reduction in Knight uncertainty include restraining the impact of noise trading, improving the speed of information integration, and enhancing investors' confidence. The research conclusion supports northbound fund holdings is conducive to reducing the Knight uncertainty of stocks, and plays a positive role in maintaining market stability, but the large inflow and outflow of northbound fund will also increase the risk of stock price uncertainty.
  • Agency VS. Wholesale: The Effect of Information Sharing on the E-Book Sales Model
    LIU Zheng, SHI Chunlai, DU Rong
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 3025-3039. https://doi.org/10.12341/jssms23618
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    Under the background of asymmetric demand information in a publisher and a retail platform, this paper establishes the Stackelberg game model to explore the impact of the retail platform's demand information sharing decision on the e-book sales model strategy. The main results show that: 1) The retail platform does not always share demand information with the publisher under the wholesale model. Under the agency model, if the commission rate from selling e-books is high, the retail platform will share demand information; Otherwise, the retail platform will not share demand information. 2) For the retail platform, in cases where the retail platform doesn't share demand information in both agency and wholesale models, the retail platform prefers the wholesale model. In cases where the retail platform shares demand information only in the agency model, if the accuracy of demand information is low, the retail platform prefers the agency model. 3) For the publisher, the retail platform's decision to share demand information, the substitution rate of e-books for paper books, and the accuracy of demand information will all affect the publisher's choice of sales model.
  • Research on Pricing and Promotion Strategy of Charging and Switching Mode of New Energy Vehicles
    WEI Lang, WANG Cuixia
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 3040-3053. https://doi.org/10.12341/jssms23836
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    Promoting new energy vehicles is an important measure to effectively reduce the carbon footprint of the transportation system. Based on the consumer utility theory, we construct a decision model for both charging and switching modes of new energy vehicles. This model enables a comparative analysis of pricing and promotion mechanisms for the two service modes. Additionally, we examine the impacts of battery production cost, switching model technology level, driving range, and energy prices on the promotion of both modes. Our main results are as follows: 1) Compared to the charging mode, the switching mode effectively alleviates consumer charging anxiety, albeit at the expense of a premium for switching services; 2) The production cost of power battery and the level of power change technology are important dimensions that affect the adoption of the two service modes; 3) There exists a divergence in the influence of battery production costs and driving range on the promotion of the two modes; 4) Decreasing battery production costs prove more beneficial for the promotion of the switching mode, while an extended driving range is more advantageous for the promotion of the charging mode. Changes in electricity or fuel prices exert similar effects on the promotion of both modes, accelerating their application by establishing operational cost advantages for new energy vehicles.
  • Financial Innovation and Informed Trading: Evidence from Chinese Industry ETFs
    LIU Xiaoqun, HOU Chenji, CHAO Youcong
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 3054-3075. https://doi.org/10.12341/jssms240170
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    Industry exchange-traded funds (IETFs) are designed to target as specific industries, providing investors with a low-cost, high-liquidity financial innovation tool. Combining the margin financing and refinancing systems in the Chinese financial market, this article uses (Huang, et al., 2020) method to construct industry ETFs to analyze the pricing of ETFs from the perspective of hedging. The study finds that: Firstly, under the hedging strategy of going long underlying stock/short industry ETF, when a listed company announces positive earnings surprise information, informed traders will significantly increase their long position in the underlying stock while simultaneously increasing their short position in the industry ETFs to which the stock belongs. This indicates that industry ETFs facilitate informed traders to use firm-specific information to hedge industry risks and realize the hedging function. Secondly, industry ETFs reduce the idiosyncratic volatility and illiquidity of their constituent stocks. This means that industry ETFs allow investors to benefit from firm-specific information. Consequently, stock prices will more fully reflect firm-level information, thus improving market efficiency. Finally, the introduction of refinancing facilitates informed traders into hedginge industry risks, indicating that Chinese refinancing system provides investors with diversified options to mitigate industry risks.
  • Research on Semiparametric Asymmetric Joint Elicitable Risk Model Based on the Laplace Distribution
    WU Zhimin, CAI Guanghui
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 3076-3094. https://doi.org/10.12341/jssms23738
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    In recent years, due to the superior performance of semiparametric joint elicitable risk models in joint statistical modeling and prediction of value at risk (VaR) and expected shortfall (ES), they have attracted widespread attention in the field of financial measurement. This paper first studies the statistical properties and risk prediction performance of the model under the framework of the asymmetric Laplace distribution. Unlike the existing semiparametric joint elicitable risk models, this model jointly models VaR and ES by assuming the conditional distribution of asset returns follows the asymmetric Laplace distribution based on VaR and ES, taking into account the typical asymmetric characteristic of financial markets, and regarding VaR and ES as dynamic structures composed of conditional standard deviation process of returns containing the asymmetric feature and a parameter to be estimated. Based on the structure of the model, we discuss the quasi-maximum likelihood estimation method and establish the consistency and asymptotic normality theorems for the estimator under certain regular conditions. Subsequently, numerical simulation results considering various conditions confirm the finite sample properties of the estimator and the effectiveness on predicting one-step ahead risks. Finally, empirical results show that the proposed model performs best in predicting multi-step ahead VaR and ES.
  • Confidence Intervals Construction for Relative Difference Under Binomial Sampling Based on MOVER Method
    GÜLISTAN Kurbanyaz, TIAN Maozai
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 3095-3114. https://doi.org/10.12341/jssms23481
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    Relative difference, also known as relative risk reduction, mainly measures the additional impact of risk factors or treatment factors on individuals, and has important clinical significance in epidemiological research. This paper presents nine interval estimation methods for relative differences using traditional interval estimation method and MOVER method under independent binomial sampling. The advantage of the MOVER method proposed in this paper is that by borrowing the MOVER method, the confidence interval of the relative difference can be constructed using the confidence intervals of two independent binomial distribution ratios. Compared with traditional interval estimation method, this method does not need to calculate the asymptotic variance of the relative difference in the process of constructing confidence intervals, and does not require the Fisher information matrix and its inverse matrix, which greatly simplifies the calculation. In addition, this paper investigates the performance of nine interval estimation methods under different parameter settings through Monte Carlo data simulation. The data simulation results show that the MOVER method can provide a more accurate confidence interval compared to traditional methods. Finally, this paper demonstrates the practical application of the proposed nine interval estimation methods through actual data cases.
  • Model Averaging of Multivariate Linear Regression Models with Heteroscedastic Covariance Matrix
    QU Tianyao, SONG Minghui
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 3115-3132. https://doi.org/10.12341/jssms23371
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    The average method of statistical model is a hot issue in the field of statistics research, which can effectively improve the accuracy of statistical prediction. In statistics, multivariate linear regression model is a kind of important and practical linear statistical model. This paper mainly studies the average method of this kind of model when the random error matrix is not completely equal. We find a matrix to “unify” the different covariance matrices of each line, and then obtain the corresponding Mahalanobis CV weight selection criteria based on Mahalanobis distance by cross-validation method, and prove the asymptotic optimality of the average estimation of the corresponding model. Simulation results show that the new method is better than S-AIC, S-BIC, MMA and JMA of linear regression model with single dependent variable and MMMA of multivariate linear regression model in general.
  • Time Series Models for Distributional Data in Bayes Space
    CHEN Meiling, YU Hanjun
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 3133-3154. https://doi.org/10.12341/jssms23695
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    To solve the problem of non-closed linear operations in distributional data, this paper proposes time series models for distributional data in Bayes space. Under the framework of symbolic data analysis, distributional data are known as numerical modal data whose realizations can be histograms, empirical distributions or empirical estimates of parametric distributions. Since the elements of the data table are probability density functions, cumulative distribution functions or quantile functions which carry information with constraints, standard methods are not appropriate for their statistical processing. In this paper, the specific features of density functions are accounted for in Bayes space whose linear operations are closed, and the space of density functions form a complete inner product space with good algebraic properties. To build up a concise methodology for distributional time series, numeric characteristics of distributional time series, the difference operator and the lag operator are first defined by linear operations and inner products of probability density functions in Bayes space. Furthermore, the methods for model specification and parameter estimation of the distributional AR model, MA model, ARMA model and the distributional ARIMA model are deduced with a complete modelling scheme. Finally, two series of simulation experiments and a real data analysis demonstrate the usefulness and effectiveness of the proposed methods for distributional time series.
  • Bayesian Analysis of Tweedie Compound Poisson Partial Linear Mixed Models for Longitudinal Semicontinuous Data
    DUAN Xingde, WU Zhenhuan, ZHANG Wenzhuan
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 3155-3169. https://doi.org/10.12341/jssms23521
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    Under the Bayesian framework, this paper develops a Tweedie compound Poisson partial linear mixed model on the basis of Bayesian P-spline approximation to nonparametric function for longitudinal semicontinuous data. It is quite difficult to directly implement Bayesian computation because the probability density function for Tweedie compound poisson distribution is not analytically tractable. Therefore, inspired by the data-augmentation strategy, we introduce a latent variable to obtain the joint probability density function of a semi-continuous random variable and the latent variable, and conduct the Bayesian statistical inference based on this joint probability density function. Furthermore, a hybrid algorithm combining the block Gibbs sampler and the Metropolis-Hastings algorithm is proposed for producing the joint Bayesian estimates of unknown parameters, random effects and nonparametric function, as well as the predicted value of latent variables. Finally, several simulation studies and a real example are presented to illustrate the proposed methodologies.
  • Block Bootstrap Tests for Persistence Change in Heavy-Tailed Dependent Sequence
    SU Menglin, JIN Hao, BAI Xue
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(10): 3170-3182. https://doi.org/10.12341/jssms23181
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    In this paper, we discuss the problem of persistence change test for heavy-tailed dependent sequences where the tail index $\kappa\in(0,2)$. The modified test statistics are constructed based on the Dickey-Fuller (DF) ratio type statistics, and its asymptotic distribution under the null hypothesis is proven to be a functional of a stable process. Under the alternative hypothesis, the test statistics are consistent and can correctly identify the persistence direction of change. At the same time, the consistency of the change point location estimation is also given. When the sequence is a stationary process, the constructed test statistics will not generate spurious rejection. Since the asymptotic distribution of the statistic under the null hypothesis contains the unknown parameter $\kappa$, the critical value of the statistic is determined by using the Block Bootstrap sampling method to avoid the estimation of the tail index $\kappa$. The Monte Carlo numerical simulation results fully demonstrate the robustness of the proposed test statistics. Finally, the feasibility and effectiveness of the proposed method are illustrated by a set of stock data.
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