Tick Size and Informed Trading: Evidence from the Taiwanese Stock Market

We adopt the Sandås model for order-book equilibrium to examine informed trading on the Taiwanese stock market, a purely order-driven call-auction market. We find that adverse-selection cost is low for well-known stocks with high liquidity and low volatility, but cost is high for monitoring the order books of those stocks. Our empirical results show that the impact of adverse selection is greatest at the beginning of each trading day and that informed traders engage in stealth trading, supporting the stealth trading hypothesis. Finally, with the special tick size rules on the market, both adverse-selection cost and monitoring cost decline as tick size decreases.

Evolutionary Game Analysis on Behavioral Strategies of Multiple Stakeholders in Inclusive Green Growth

Inclusive green growth has been set as an important initiative to solve the severe problems of environmental degradation and severe income inequality. It requires the joint participation of local government, enterprise and public. However, these stakeholders are not enthusiasm enough as there are divergences among their interest goals. Hence, this paper analyses how to balance the stakeholders’ interest goals based on the central supervision and local regulation in environmental protection and income inequity alleviation. Therefore, an evolutionary game model between central and local government, and an evolutionary game model among local government and enterprise and public are conducted. The conclusions are drawn as follows: (1) The local government should play a leading role in promoting IGG, and the decrease of the economy proportion in the assessment on local government will significantly promote its enthusiasm; (2) When the penalty on enterprise increase, both enterprise and the public will choose positive participate behavior faster; (3) The high public monitoring cost will hinder both enterprise and public’s participation. Finally, some recommendations are put forward.

The Power of Renegotiation and Monitoring in Software Outsourcing: Substitutes or Complements?

Monitoring and contract renegotiation are two common solutions for addressing information asymmetry and uncertainty between a client and a vendor of software outsourcing services. Monitoring is mostly applied in time-and-materials contracts, as a basis for inspecting and reimbursing the vendor’s efforts in system development. Renegotiation, by contrast, is deployed in fixed-price and time-and-materials contracts to mitigate the loss of surplus from uncertainty after system development. We investigate the interaction between monitoring and renegotiation and examine the corresponding contract choice problem. We find that the client benefits from renegotiation based on two effects: an uncertainty-resolution effect and a post-development incentive effect, which incentivizes the vendor to exert additional effort in system development. Monitoring does not resolve uncertainty, although it does encourage the vendor to exert additional effort, a pre-development incentive effect. Our analysis shows that the choice of renegotiation or monitoring depends on the interactions of the above effects, which are moderated by the renegotiation cost, monitoring cost, and bargaining power in renegotiation. When renegotiation cost is low: if the client has high bargaining power and low monitoring cost, monitoring and renegotiation are complements and both are selected; otherwise, the two instruments are substitutes and contract renegotiation is preferred. When renegotiation cost is high: monitoring substitutes for renegotiation and the client only chooses monitoring if the cost to do it is low; or else neither is used. Overall, this research shows that four appropriate contract strategies should be used under somewhat different circumstances. We further analyze the impacts of some other key aspects of software outsourcing and extend the base model to address two alternative situations to show the robustness of our findings. The results apply to a range of software reliability growth models, including when machine learning or cloud computing are used.

Research on Monitoring Method of Remote Deformation and System Application Based on Image

The development of information technology and computer science has put forward higher requirements on the intelligence of deformation monitoring. We study a method based on image deformation analysis, which uses Scale-Invariant Feature Transform (SIFT) to extract image feature points after preprocessing the acquired images, applies All-Pixels Matching (APM) method to the sequence images to do further high-precision matching to achieve the accuracy of subpixels, and finally solves the deformation variables according to the relationship of the real size of the reference target and its pixel. Wavelet analysis and least squares are used to improve the image quality and matching accuracy. Based on this method, we design and develop a new remotely automated deformation monitoring system. In this paper, we introduce the algorithm principle of deformation analysis, the integration of the system, and the engineering application example of the monitoring system. The monitoring accuracy of the system satisfying 0.1 mm within 10 m and 0.8 mm within 60 m is verified in the simultaneous comparison observation according to the high-precision total station, which illustrates the effectiveness of the present deformation analysis method and monitoring system and also has the characteristics of low monitoring cost and high degree of automation.

Energy-saving MAC protocol design for body sensor networks

Remote and online patient monitoring can significantly reduce the cost for the health care system. Body Sensor Network (BSN) plays a key role in real-time remote health monitoring. Although the BSN can reduce the health monitoring cost, some technical challenges arise. One of the major challenges in BSN is the power consumption. The power recharge is very difficult and inconvenient in BSNs. Therefore, energy saving is one of the most appropriate approaches to prolong the network lifetime. In the thesis, we propose a context-aware Medium Access Control (MAC) design to extend the network lifetime of the BSN. The proposed MAC reduces data transmission by determining the more valuable fraction of data. The high-value portion of the data is transmitted, while the low-value fraction of the data is omitted, at the sensor node. The simulation results demonstrate that the proposed method can reduce the transmission energy by up to 30% compared to the existing method called burst communications.

Energy-saving MAC protocol design for body sensor networks

Remote and online patient monitoring can significantly reduce the cost for the health care system. Body Sensor Network (BSN) plays a key role in real-time remote health monitoring. Although the BSN can reduce the health monitoring cost, some technical challenges arise. One of the major challenges in BSN is the power consumption. The power recharge is very difficult and inconvenient in BSNs. Therefore, energy saving is one of the most appropriate approaches to prolong the network lifetime. In the thesis, we propose a context-aware Medium Access Control (MAC) design to extend the network lifetime of the BSN. The proposed MAC reduces data transmission by determining the more valuable fraction of data. The high-value portion of the data is transmitted, while the low-value fraction of the data is omitted, at the sensor node. The simulation results demonstrate that the proposed method can reduce the transmission energy by up to 30% compared to the existing method called burst communications.

A field evidence model: how to predict transport in heterogeneous aquifers at low investigation level

Aquifer heterogeneity in combination with data scarcity is a major challenge for reliable solute transport prediction. Velocity fluctuations cause non-regular plume shapes with potentially long-tailing and/or fast-travelling mass fractions. High monitoring cost and a shortage of simple concepts have limited the incorporation of heterogeneity into many field transport models up to now. We present an easily applicable hierarchical conceptualization strategy for hydraulic conductivity to integrate aquifer heterogeneity into quantitative flow and transport modelling. The modular approach combines large-scale deterministic structures with random substructures. Depending on the modelling aim, the required structural complexity can be adapted. The same holds for the amount of monitoring data. The conductivity model is constructed step-wise following field evidence from observations, seeking a balance between model complexity and available field data. The starting point is a structure of deterministic blocks, derived from head profiles and pumping tests. Then, subscale heterogeneity in the form of random binary inclusions is introduced to each block. Structural parameters can be determined, for example, from flowmeter measurements or hydraulic profiling. As proof of concept, we implemented a predictive transport model for the heterogeneous MADE site. The proposed hierarchical aquifer structure reproduces the plume development of the MADE-1 transport experiment without calibration. Thus, classical advection–dispersion equation (ADE) models are able to describe highly skewed tracer plumes by incorporating deterministic contrasts and effects of connectivity in a stochastic way without using uni-modal heterogeneity models with high variances. The reliance of the conceptual model on few observations makes it appealing for a goal-oriented site-specific transport analysis of less well investigated heterogeneous sites.

Evaluating Water Quality Variation in the Vietnamese Mekong Delta Area Using Cluster and Discriminant Analysis

The study aims to assess spatial and temporal water quality variations in the upper reaches of the Vietnamese Mekong Delta. Thirty-one water monitoring samples of the two main rivers (Tien and Hau Rivers) and six canals flowing through An Giang Province were collected in the dry season (March) and the rainy season (September) from 2009 to 2019. Seven physicochemical parameters were analyzed including temperature, pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), total suspended solids (TSS), orthophosphate (P-PO43-), and coliforms. Water quality index (WQI), cluster analysis (CA), and discriminant analysis (DA) were applied to evaluate water quality, spatial and temporal variations, and seasonal discriminant water variables. WQI values (15–71) indicated surface water quality was very bad to medium in which the water quality in larger and in smaller rivers in the dry season was less polluted than that in the rainy season due to erosion and runoff water containing waste materials in the wet season. CA grouped the water quality in the dry and rainy seasons into four clusters mainly due to BOD and coliforms in the dry season; TSS and coliforms in the rainy season. Discriminant analysis revealed that DO, TSS, coliforms, temperature and BOD significantly contributed to seasonal variations in water quality. Therefore, water quality monitoring in the surveyed area could only focus on DO, TSS, coliforms, temperature and BOD to reduce monitoring cost.

Allocation Of Residual Income Rights Under Internal Governance Empirical Results from the Hungarian Trucking Industry

The paper offers a property rights and monitoring cost explanation for the allocation of residual income rights between the carriers and truck drivers under internal governance. First, by applying property rights theory, we argue that the structure of residual income rights depends on the importance of noncontractible (intangible) assets of the truck driver to generate a residual surplus. The more important the truck driver’s intangible knowledgeassets, the more residual income rights should be transferred to him. In addition, we controlled for the monitoring costs as an additional explanatory variable of the allocation of residual income rights. According to agency theory, the higher the variable proportion of the driver’s income, the higher the monitoring costs.These hypotheses were tested by using data from the Hungarian trucking industry. The empirical results are supportive of the hypotheses. JEL- Index: G32, M2