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Article
Publication date: 10 May 2018

Shoudong Chen, Yan-lin Sun and Yang Liu

In the process of discussing the relationship between volume and price in the stock market, the purpose of this paper is to consider how to take the flow of foreign…

Abstract

Purpose

In the process of discussing the relationship between volume and price in the stock market, the purpose of this paper is to consider how to take the flow of foreign capital into consideration, to determine whether the inclusion of volume information really contributes to the prediction of the volatility of the stock price.

Design/methodology/approach

By comparing the relative advantages and disadvantages of the two main non-parametric methods mainstream, and taking the characteristics of the time series of the volume into consideration, the stochastic volatility with Volume (SV-VOL) model based on the APF-LW simulation method is used in the end, to explore and implement a more efficient estimation algorithm. And the volume is incorporated into the model for submersible quantization, by which the problem of insufficient use of volume information in previous research has been solved, which means that the development of the SV model is realized.

Findings

Through the Sequential Monte Carlo (SMC) algorithm, the effective estimation of the SV-VOL model is realized by programming. It is found that the stock market volume information is helpful to the prediction of the volatility of the stock price. The exchange market volume information affects the stock returns and the price-volume relationship, which is achieved indirectly through the net capital into stock market. The current exchange devaluation and fluctuation are not conducive to the restoration and recovery of the stock market.

Research limitations/implications

It is still in the exploratory stage that whether the inclusion of volume information really contributes to the prediction of the volatility of the stock price, and how to incorporate the exchange market volume information. This paper tries to determine the information weight of the exchange market volume according to the direct and indirect channels from the perspective of causality. The relevant practices and conclusions need to be tested and perfected.

Practical implications

Previous studies have neglected the influence of the information contained in the exchange market volume on the volatility of stock prices. To a certain extent, this research makes a useful supplement to the existing research, especially in the aspects of research problems, research paradigms, research methods and research conclusion.

Originality/value

SV model with volume information can not only effectively solve the inefficiency of information use problem contained in volume in traditional practice, but also further improve the estimation accuracy of the model by introducing the exchange market volume information into the model through weighted processing, which is a useful supplement to the existing literature. The SMC algorithm realized by programming is helpful to the further advancement and development of non-parametric algorithms. And this paper has made a useful attempt to determine the weight of the exchange market volume information, and some useful conclusions are drawn.

Details

China Finance Review International, vol. 8 no. 3
Type: Research Article
ISSN: 2044-1398

Keywords

Article
Publication date: 6 June 2022

Yanlin Sun, Siyu Liu and Shoudong Chen

This paper aims to identify the direct impact of fund style drift on the risk of stock price collapse and the intermediary mechanism of financial risk, so as to better…

Abstract

Purpose

This paper aims to identify the direct impact of fund style drift on the risk of stock price collapse and the intermediary mechanism of financial risk, so as to better protect the interests of minority investors.

Design/methodology/approach

This paper takes all the non-financial companies on the Chinese Growth Enterprise Market from 2011 to 2020 as study object and selects securities investment funds of their top ten circulation stocks to study the relationship between fund style drift and stock price crash risk.

Findings

Fund style drift is likely to add stock price crash risk. Financial risk is positively correlated with stock price crash risk. Fund style drift affects stock price crash risk via the mediating effect of financial risk, and fund style drift and financial risk have a marked impact on the stock price crash risk of non-state enterprises, yet a non-significant impact on that of state-owned enterprises.

Originality/value

This paper links fund style drift with stock price crash risk in an exploratory manner and enriches the study perspectives of relationship between institutional investors’ behaviors and stock price crash risk, thus enjoying certain academic value. On the one hand, it furnishes a new approach to the academic frontier issue concerning financial risk and stock price crash risk, and proves that financial risk is positively correlated with stock price crash risk. On the other hand, it regards financial risk as a mediating variable of fund style drift for stock price crash risk and further explores different influencing mechanism of institutional investors’ behaviors.

Details

China Finance Review International, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-1398

Keywords

Article
Publication date: 11 November 2014

Yan Wang, Shoudong Chen and Xiu Zhang

The purpose of this paper is to measure a single financial institution's contribution to systemic risk by using extremal quantile regression and analyzing the influential…

Abstract

Purpose

The purpose of this paper is to measure a single financial institution's contribution to systemic risk by using extremal quantile regression and analyzing the influential factors of systemic risk.

Design/methodology/approach

Extreme value theory is applied when measuring the systemic risk of financial institutions. Extremal quantile regression, where extreme value distribution is assumed for the tail, is used to measure the extreme risk and analyze the changes in and dependencies of risk. Furthermore, influential factors of systemic risk are analyzed using panel regression.

Findings

The key findings of the paper are that value at risk and contribution to systemic risk are very different when measuring the risk of a financial institution; banks’ contributions to systemic risk are much higher; and size and leverage ratio are two significant and important factors influencing an institution's systemic risk.

Practical implications

Characterizing variables of financial institutions such as size, leverage ratio and market beta should be considered together when regulating and constraining financial institutions.

Originality/value

To take extreme risk into account, this paper measures systemic financial risk using extremal quantile regression for the first time.

Details

China Finance Review International, vol. 4 no. 4
Type: Research Article
ISSN: 2044-1398

Keywords

Article
Publication date: 16 May 2016

Xiu Zhang, Shoudong Chen and Yang Liu

The purpose of this paper is to empirically analyze the transmission mechanism between benchmark interest rate of financial market, money market interest rate and capital…

1168

Abstract

Purpose

The purpose of this paper is to empirically analyze the transmission mechanism between benchmark interest rate of financial market, money market interest rate and capital market yields in order to reveal the dynamic evolution characters and core influential structure between different market interest rates.

Design/methodology/approach

Using Dirichlet-VAR (DVAR) model, this study analyze the relationship between markets rates according to the equilibrium model in money market and capital market.

Findings

Empirical results show that the interest rate transmission mechanism functions smoothly between interest rates of different levels. Interest rate of bills issued by the central bank can effectively reflect changes in monetary policy and guide the fluidity of market, playing the anchor role in interest rate pricing. There exists a closed loop feedback between interest rate of bills issued by the central bank, and money market interest rate, as well as between money market interest rate and bond market interest rate. The former is a loop by administrative means while the latter is the one mainly affected by market-oriented means. The response by money market and bond market toward the change of benchmark interest rate is unsymmetrical as money market is more sensitive to a loose monetary policy while bond market is more sensitive to a tight monetary policy. Stock market is strongly affected by uncertainty of benchmark interest rate.

Originality/value

DVAR model is the extension of research on instable data and multiple variable causality test, which expands the causality analysis between two variables to multiple variables causality impact analysis which contains non-stable and structurally instable economic data.

Details

China Finance Review International, vol. 6 no. 2
Type: Research Article
ISSN: 2044-1398

Keywords

Article
Publication date: 21 December 2021

Shanling Han, Shoudong Zhang, Yong Li and Long Chen

Intelligent diagnosis of equipment faults can effectively avoid the shutdown caused by equipment faults and improve the safety of the equipment. At present, the diagnosis…

Abstract

Purpose

Intelligent diagnosis of equipment faults can effectively avoid the shutdown caused by equipment faults and improve the safety of the equipment. At present, the diagnosis of various kinds of bearing fault information, such as the occurrence, location and degree of fault, can be carried out by machine learning and deep learning and realized through the multiclassification method. However, the multiclassification method is not perfect in distinguishing similar fault categories and visual representation of fault information. To improve the above shortcomings, an end-to-end fault multilabel classification model is proposed for bearing fault diagnosis.

Design/methodology/approach

In this model, the labels of each bearing are binarized by using the binary relevance method. Then, the integrated convolutional neural network and gated recurrent unit (CNN-GRU) is employed to classify faults. Different from the general CNN networks, the CNN-GRU network adds multiple GRU layers after the convolutional layers and the pool layers.

Findings

The Paderborn University bearing dataset is utilized to demonstrate the practicability of the model. The experimental results show that the average accuracy in test set is 99.7%, and the proposed network is better than multilayer perceptron and CNN in fault diagnosis of bearing, and the multilabel classification method is superior to the multiclassification method. Consequently, the model can intuitively classify faults with higher accuracy.

Originality/value

The fault labels of each bearing are labeled according to the failure or not, the fault location, the damage mode and the damage degree, and then the binary value is obtained. The multilabel problem is transformed into a binary classification problem of each fault label by the binary relevance method, and the predicted probability value of each fault label is directly output in the output layer, which visually distinguishes different fault conditions.

Details

International Journal of Intelligent Computing and Cybernetics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 13 September 2018

Jian Zhan, Xin Janet Ge, Shoudong Huang, Liang Zhao, Johnny Kwok Wai Wong and Sean XiangJian He

Automated technologies have been applied to facility management (FM) practices to address labour demands of, and time consumed by, inputting and processing manual data…

Abstract

Purpose

Automated technologies have been applied to facility management (FM) practices to address labour demands of, and time consumed by, inputting and processing manual data. Less attention has been focussed on automation of visual information, such as images, when improving timely maintenance decisions. This study aims to develop image classification algorithms to improve information flow in the inspection-repair process through building information modelling (BIM).

Design/methodology/approach

To improve and automate the inspection-repair process, image classification algorithms were used to connect images with a corresponding image database in a BIM knowledge repository. Quick response (QR) code decoding and Bag of Words were chosen to classify images in the system. Graphical user interfaces (GUIs) were developed to facilitate activity collaboration and communication. A pilot case study in an inspection-repair process was applied to demonstrate the applications of this system.

Findings

The system developed in this study associates the inspection-repair process with a digital three-dimensional (3D) model, GUIs, a BIM knowledge repository and image classification algorithms. By implementing the proposed application in a case study, the authors found that improvement of the inspection-repair process and automated image classification with a BIM knowledge repository (such as the one developed in this study) can enhance FM practices by increasing productivity and reducing time and costs associated with ecision-making.

Originality/value

This study introduces an innovative approach that applies image classification and leverages a BIM knowledge repository to enhance the inspection-repair process in FM practice. The system designed provides automated image-classifying data from a smart phone, eliminates time required to input image data manually and improves communication and collaboration between FM personnel for maintenance in the decision-making process.

Details

Facilities, vol. 37 no. 7/8
Type: Research Article
ISSN: 0263-2772

Keywords

Article
Publication date: 15 June 2010

Wu Li, Chaoyuan Yue, Shoudong Han and Mingfu Zhu

The purpose of this paper is to derive the optimal procurement policy of an item for a buyer and reduce the total cost to the buyer.

919

Abstract

Purpose

The purpose of this paper is to derive the optimal procurement policy of an item for a buyer and reduce the total cost to the buyer.

Design/methodology/approach

In a multi‐supplier setting and from the perspective of the buyer, the paper addresses long‐term supply contracts for a single item with total minimum commitments and order constraints each period. Under the conditions, the buyer agrees to procure at least a certain quantity of an item from every selected supplier over the predetermined plan horizon and the order constraints specify the minimum and maximum of the quantity purchased each period. An optimization model is developed minimizing the total cost to the buyer, including purchase, transportation, and storage cost of all periods. To derive the optimal procurement policy for the buyer, a two‐phase solution is proposed integrating multidimensional dynamic programming with heuristic method.

Findings

The optimal procurement policies can be computed easily and result in a certain decrease on the total cost to the buyer. There may be multiple optimal procurement strategies resulting in the same total cost to the buyer. The commitments to the suppliers result in an increase on the total cost to the buyer.

Research limitations/implications

Sensitivity analysis should be provided and uncertain demands should be considered.

Practical implications

This paper presents a very useful approach to derive optimal procurement strategy for such buyers as project owners.

Originality/value

The paper extends the total minimum commitment to a multi‐supplier setting.

Details

Kybernetes, vol. 39 no. 6
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 9 September 2014

Wen-Yang Chang and Chih-Ping Tsai

This study aims to investigate the spectral illumination characteristics and geometric features of bicycle parts and proposes an image stitching method for their automatic…

Abstract

Purpose

This study aims to investigate the spectral illumination characteristics and geometric features of bicycle parts and proposes an image stitching method for their automatic visual inspection.

Design/methodology/approach

The unrealistic color casts of feature inspection is removed using white balance for global adjustment. The scale-invariant feature transforms (SIFT) is used to extract and detect the image features of image stitching. The Hough transform is used to detect the parameters of a circle for roundness of bicycle parts.

Findings

Results showed that maximum errors of 0°, 10°, 20°, 30°, 40° and 50° for the spectral illumination of white light light-emitting diode arrays with differential shift displacements are 4.4, 4.2, 7.8, 6.8, 8.1 and 3.5 per cent, respectively. The deviation error of image stitching for the stem accessory in x and y coordinates are 2 pixels. The SIFT and RANSAC enable to transform the stem image into local feature coordinates that are invariant to the illumination change.

Originality/value

This study can be applied to many fields of modern industrial manufacturing and provide useful information for automatic inspection and image stitching.

Details

Assembly Automation, vol. 34 no. 4
Type: Research Article
ISSN: 0144-5154

Keywords

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