Estimation Of Value Research Articles

The Impact of the Tone of a Prospectus on IPO Underpricing: Evidence from China

AbstractA prospectus is an essential disclosure document requested by stock market regulators and used by potential investors to acquire necessary information about the fair value estimate of an initial public offering (IPO) and subsequent investment decisions. Using IPO firms in China during the period 2007 to 2017, this study provides novel evidence for the impact of the tone of a prospectus on IPO underpricing. The results show that the tone of a prospectus is positively associated with underpricing. Supplementary analyses show that the positive effect of prospectus tone on IPO underpricing is more pronounced for IPO firms having CEO duality and large board size, lower managerial shareholding and institutional shareholding, and big audit firms and prestigious underwriters. Finally, the results indicate that the positive tone of a prospectus is able to predict negative operating performance in future.

Better value estimation in Q-learning-based multi-agent reinforcement learning

Better value estimation in Q-learning-based multi-agent reinforcement learning

Approximation of van Genuchten Parameter Ranges from Hydraulic Conductivity Data.

The use of retention function and relative conductivity function is essential for the calculation of flow in a variably saturated media using the Richards equation. A widely used mathematical model for this is the Mualem-van Genuchten model which requires the shape parameters and . These, however, are difficult to obtain. When data is scarce, and are often taken from literature and may deviate largely from actual values. The current study presents a novel mathematical model for the approximation of and and for the further estimation of realistic value ranges, which may be used as parameter space, for example, for the calibration of a numerical model. The model was developed for cases where data is scarce and only values of saturated hydraulic conductivity are available. It is based on a large data set from literature and it is demonstrated that the model estimates mean values from that data set with a good accuracy. In order to show the applicability of the model, a second data set has been compiled anew (provided as Supporting Information). The model is incorporated into the current version of the freeware computer program HYPAGS, which enables easy usage.

Comparative assessment of the effective population size and linkage disequilibrium of Karan Fries cattle revealed viable population dynamics.

Karan Fries (KF), a high-producing composite cattle was developed through crossing indicine Tharparkar cows with taurine bulls (Holstein Friesian, Brown Swiss, and Jersey), to increase the milk yield across India. This composite cattle population must maintain sufficient genetic diversity for long-term development and breed improvement in the coming years. The level of linkage disequilibrium (LD) measures the influence of population genetic forces on the genomic structure and provides insights into the evolutionary history of populations, while the decay of LD is important in understanding the limits of genome-wide association studies for a population. Effective population size (Ne) which is genomically based on LD accumulated over the course of previous generations, is a valuable tool for e valuation of the genetic diversity and level of inbreeding. The present study was undertaken to understand KF population dynamics through the estimation of Ne and LD for the longterm sustainability of these breeds. The present study included 96 KF samples genotyped using Illumina HDBovine array to estimate the effective population and examine the LD pattern. The genotype data were also obtained for other crossbreds (Santa Gertrudis, Brangus, and Beefmaster) and Holstein Friesian cattle for comparison purposes. The average LD between single nucleotide polymorphisms (SNPs) was r2 = 0.13 in the present study. LD decay (r2 = 0.2) was observed at 40 kb inter-marker distance, indicating a panel with 62,765 SNPs was sufficient for genomic breeding value estimation in KF cattle. The pedigree-based Ne of KF was determined to be 78, while the Ne estimates obtained using LD-based methods were 52 (SNeP) and 219 (genetic optimization for Ne estimation), respectively. KF cattle have an Ne exceeding the FAO's minimum recommended level of 50, which was desirable. The study also revealed significant population dynamics of KF cattle and increased our understanding of devising suitable breeding strategies for longterm sustainable development.

The value of natural capital in Canada’s national parks and national marine conservation areas

Growing attention is being given to protected areas and the ability of their natural capital assets to provide a varied and long-term stream of benefits to individuals and society in general. These areas are often heralded for ensuring natural capital assets persist, but value is often limited to the economic impact of visitor expenditures and the associated effects on regional and national economies. Few studies have attempted to quantify the economic value of natural capital assets in protected areas, especially in Canada. This study uses a benefit transfer approach to produce an initial estimate of the potential economic value of ecosystem services and natural capital associated with the terrestrial and marine environments in Canada’s federal system of national parks and national marine conservation areas. The results suggest that the economic value of these assets ranges between CA$ 156 billion and CA$ 588 billion annually.

Adaptive Output Regulation of a Class of 1-D Hyperbolic PDEs With Unknown Boundary Scaled Parameters

This paper considers the problem of adaptive output regulation of a class of 1-D anti-collocated hyperbolic PDEs. The model is subject to unknown scaled parameters in both the boundary condition and boundary measurement. An adaptive boundary observer, providing online estimates of the system state and parameters, is designed. Particularly, to realize that the pure boundary state at left side tracks a reference signal, a challenging problem with the estimate of the true value of unknown scaled parameter appearing in measurement (at the left side) is tackled in this paper. It is shown that the proposed observer is exponentially convergent and furthermore the exponential output regulation and stabilization are achieved.

Positron annihilation lifetime measurement with TOF-PET detectors: feasibility of Iodine-124 use

Positronium (Ps) imaging is getting attention for nuclear medicine applications, but appropriate radionuclides have not been evaluated systematically. This paper investigated the use of 124I, which is a positron emitter with 603 keV prompt gamma ray emission with a fraction of 11.7%. The accuracy of positron annihilation lifetime measurement with 124I was compared with 22Na, which is often used in positron annihilation lifetime measurement, for certified reference materials. Results obtained with TOF-PET detectors suggested that the accuracy of the lifetime value estimation was slightly worse than that for 22Na, while the positron annihilation lifetime measurement using 124I was a feasible choice.

Construction of a model of steganographic embedding of the UAV identifier into ADS-B data

Secure data exchange in the control system of unmanned aerial vehicles (UAVs) is an important aspect for preventing unauthorized access and safety of aerial vehicles. Given the problems of automatic dependent surveillance-broadcast (ADS-B) data protection, the safety level of UAV flight tasks and air traffic in general is significantly reduced. Therefore, the protection of ADS-B data is an urgent task. The object of the study is the process of steganographic protection of ADS-B format data. A relevant problem of estimating the probabilistic time characteristics of the steganographic protection process is solved, taking into account the features of data embedding in the ADS-B format container. To solve it, a mathematical formalization of the methods of finding probabilistic-temporal characteristics of steganographic systems was carried out. A model of steganographic data transformation operations based on the Chinese remainder theorem has been built. The main difference of the model is taking into account the features of the ADS-B format data. This made it possible to formalize and evaluate the time functions of steganographic encoding and decoding of UAV identifiers with an integrated ADS-B system. A model of steganographic data transformation operations based on the finite integral ring theorem has been constructed. A list of operations performed in the developed algorithm has been compiled. This made it possible to carry out mathematical formalization of operations for complex use in the model of steganographic protection of UAV identifiers with a built-in ADS-B system. The mathematical model was studied and the estimation of the random value of the time of steganographic transformation of data, as well as the confidence interval, was performed. With the help of the reported set of models, it is possible to estimate the probability of the algorithm’s execution time falling within the given interval. The results of the calculation of probabilistic-time characteristics could be used in models of a higher level of the hierarchy

SemNav-HRO: A target-driven semantic navigation strategy with human–robot–object ternary fusion

Target-Driven Semantic Navigation (TDSN) shows great potential to be applied in intelligent domestic assistants supporting humans with daily activities. Although numerous methods have been explored to achieve efficient static TDSN, socially aware TDSN in dynamic and crowded scenarios remains challenging and has not been adequately investigated. The main challenges come from the complex human–robot interaction mechanisms and the semantic relation exploitation, which requires the robot to understand the surroundings and perform foresighted behaviors. In this paper, a TDSN strategy named SemNav-HRO is proposed by considering Human–Robot–Object (HRO) ternary feature fusion. Specifically, a Deep Reinforcement Learning (DRL) based Dual-Channel Value Estimation Network (DCVEN) is first proposed by integrating multi-granularity map features and social awareness to learn crowded TDSN strategies. Meanwhile, the tricky and socially aware TDSN problem is slackened by eliminating the dependence on costly features (e.g., pedestrian speed) and introducing a pedestrian trajectory predictor. For the learning and evaluation of crowded TDSN strategies, a novel and semantic-rich simulator with complex layouts is constructed based on realistic domestic scenes, instead of employing the previous naive simulation settings. Experimental results show that our method relatively improves the navigation success rates by 12.8%∼25.5% and 14.6%∼19.2% compared to the baselines on the MP3D and Gibson datasets, respectively. Furthermore, we experimentally verify the promising generalization and interpretability of our method.

Fair Value of Earnouts: Valuation Uncertainty or Managerial Opportunism?

ABSTRACT This study investigates the economic consequences of the IFRS 3 (2008) requirement for fair valuing earnouts. Using a hand-collected sample of earnout fair value estimates in acquisitions completed by Australian firms, we find that a significant portion of acquirers overstate initial earnout liabilities and strategically reverse them as operating gains to boost post-M&A earnings. These overstatements are more pronounced when acquirers face investment- and performance-related pressure but attenuated in the presence of high-quality auditors and debt-financed deals. Acquirers also obfuscate earnout-related disclosures, inhibiting investors’ assessment of earnout values. By doing so, managers extend their tenure. Further analysis reveals that IFRS 3 (2008) leads to a significant increase in both the frequency and magnitude of earnouts in public acquirers’ transactions. Overall, we highlight the accounting benefit of earnouts for acquirers under IFRS 3 (2008), with implications for investors, analysts, auditors, and standard setters. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: G34; M41.

Potential Impacts of Mining to Resources along Carac-an Watershed, Eastern Mindanao, Philippines: Total Economic Value Estimate Runnint Title: Total Economic Value of Mining Impacts

Mining extracts minerals are important in the technological advancements of humanity. This leads to a progressive society, address relevant medical issues, food-security problems, and even creates various jobs. However, the externalities of mining activities like land-use changes are inevitable that could affect the resources and various users. Hence, this study was conducted to obtain an estimate of the total economic value of resources that are adversely impacted by mining activities, particularly the basic goods and services used by the people. Estimating the total economic value, includes computing the use and non-use values and the existence and bequest values. The study sites covered were within the Carac-an Watershed along the Municipalities of Cantilan, Madrid, and Carrascal. Primary and secondary data were obtained and used as basis in estimating the total economic value. Results showed that the total economic value of use and non-use goods and services along the Carac-an Watershed had amounted to PhP 4,569,224,709.00 per year. This can be considered as an environmental asset that would be lost as a consequence of mining operations. However, this economic value is too huge to be compromised by the externalities (e.g. pollution, deforestation, land use change and siltation) out of mining activities thereby putting the community and the environment at risk. While this finding was only based on estimated values, it is still imperative to revisit the implementation of mining operation. Further, relevant comprehensive study is recommended to fully capture the values of other resources not considered in this study.

Capacity Value Assessment for a Combined Power Plant System of New Energy and Energy Storage Based on Robust Scheduling Rules

With the rapid increase in new energy penetration, the uncertainty of the power system increases sharply. We can smooth out fluctuations and promote the more grid-friendly integration of new energy by combining it with energy storage. This paper proposes an evaluation method for assessing the value of a combined power plant system of new energy and energy storage using robust scheduling rules. Firstly, the k-means clustering algorithm is improved by using the elbow method in order to generate typical scenarios that can be used for the operation optimization of the combined power plant system of new energy and energy storage. Then, a two-stage robust optimization model of the combined power plant system of new energy and energy storage with a min–max–min structure is constructed according to the uncertainty of new energy. In this model, the operation constraints and coordinated control of wind–solar–thermal–storage units are considered. By constructing the uncertainty set of the new energy output, the overall operating cost of the system is minimized and uncertainty adjustment parameters are introduced to flexibly adjust the conservatism of the scheduling rules. Furthermore, based on the column and constraint generation algorithm and strong duality theory, the original problem can be decomposed into a master problem and subproblems with mixed integer linear characteristics for an alternating solution, so as to obtain the optimal solution of the original problem, and finally obtain the robust scheduling rule with the lowest operating cost under the worst scenario. Finally, based on the wind and solar power output curves and the output of each unit under the robust scheduling rules, combined with the value estimation method of the combined power plant system of new energy and energy storage, the value of the combined power plant system of new energy and energy storage is evaluated. Through the establishment of models and example analysis, it is proven that raising the quantity of the grid-connected power generated with new energy will cause an increase in the volatility of the power system; it will also bring considerable benefits to new energy plants, and the energy storage can improve the stability of the system. The above can provide references for the subsequent energy storage configuration in the planning of a combined power plant system of new energy and energy storage.

Predicting, Validation of Frequency of Transgressive Recombinant Inbred Lines and Minimum Population Size Required to Recover them in Groundnut (Arachis hypogaea L.)

Background: Identification of transgressive recombinant inbred lines (RILs) that can be use as pure-line cultivars is the prime objective of a breeder in self-pollinated crops including groundnut.
 Aim: Thus, identification of such promising segregating generations assumes importance. This can be achieved by predicting the transgressive RILs that could be derived from advanced generations of segregating population.
 Materials and Methods: In our study we predicted and validated transgressive RILs derived from cross TMV 2 × GPBD 4 for five quantitative traits based on estimates of mid parental value [m], additive genetic effects [a] and additive genetic variance [σ2A].
 Results: the frequency of transgressive RILs was higher for all the five traits. Primary branches per plant had highest frequency of predicted transgressive RILs with minimum population size of 6.95. Narrow difference between the predicted and realised frequency of RILs was seen.
 Conclusion: Our results indicate that this approach could be the efficient in selecting the best breeding population out of many number of crosses made.

Influence of the inbreeding level on the genomic assessment of Holstein bulls of different genealogical complexes

The studied 338 bulls of the new generation of US selection belong to the previously identified genealogical complexes (branches) of H.H.С. Manfred (Mf), B.M.T. Cleitus (Cl), Prelude (Pr)in the W. Ideal line and Blackstar Emori (BE), Magic (Mg), Adam (Ad) and G. Arlinda Chief (AC) in the R. Sovereign line. The influence of genetic factors: father, line, branch and level of inbreeding on the Genomic Estimation of Breeding Value (GEBV) for the productive qualities of young bulls was studied. On average, the inbreeding coefficient of the studied livestock is 13.14±0.15 from 12.72±0.54 to 15.98±1.26%, the genomic estimate for milk yield varied from 1204±101 to 1571±198 kg with an average value 1308±27 kg of milk.A significant weak positive correlation between the genomic assessment of bulls for milk yield and the inbreeding coefficient was revealed (r = +0.118, p?0.95).Differences in the GEBV of milk productivity traits between groups of bulls of different genealogical complexes are not significant. Significant differences in inbreeding coefficients only between Cl and AC (–3.08%, p?0.95), Ad and AC (–3.06%, p?0.95), BE and AC (–3.26%, p?0.95). Using one-way analysis of variance (ANOVA), a large influence on the genomic breeding value was established by the factor inbreeding coefficient - 42.4% for milk yield, 53.6% for fat content and 58.9% for protein content, which is comparable to the influence of the father on the GEBV for milk yield 42.6%, fat and protein content 50.8 and 46.0%, respectively.

Methodology of load effect analysis and ultimate limit state design of semi-submersible hulls of floating wind turbines: With a focus on floater column design

A main challenge in the design of hull structures of floating wind turbines (FWTs) is to properly estimate the load effects and resistance to perform the safety design check. While great efforts have been devoted to the load effects in terms of global motions, there is a lack of effective methods to calculate internal loads and lateral pressures of hulls in a fully coupled aero-hydro-servo-elastic environment, which should serve as the basis for the assessment of load effects in hulls. Moreover, very limited knowledge and experience exist in the current guidelines and research publications to deal with the detailed design of hull structures of FWTs. This study outlines an effective methodology and procedure to determine load effects for structural design of semi-submersible hulls, and demonstrates their application in a case study of column design based on the ultimate limit state (ULS) criteria. First, a novel multi-body floater model is established in a fully coupled FWT numerical system, which is capable of calculating floater internal loads. Second, the environmental contour approach is employed to initially choose load cases for ULS design, based on important wind speed conditions and criterial wave periods. Next, a screening of the critical load cases is made based on Von Mises stress analysis of columns considering global loads. Then, lateral pressure on columns is calculated, and a detailed design check is made based on combined global loads and lateral pressure as well as relevant safety factors for loads and resistance. Furthermore, the relative influence of global loads and lateral pressure on ULS performance of columns is investigated, which serves as the basis to reset the critical load cases for ULS design check. Subsequently, sensitivity analysis of ULS performance with respect to column design parameters, extreme value estimation, and shell buckling design checks, are performed to determine the plate thickness and ring stiffener distances of central and outer columns. Finally, optimized ring stiffener dimensions are estimated for different design cases based on panel buckling design criteria, and detailed design parameters for the central and outer columns are obtained. The methodology and procedure established and applied in a case study in this work, contribute to improving engineering practice and establishing improved design standards.

Real estate assessment of agricultural lands outside the zoning plan with artificial neural networks and multiple regression analysis methods: The case of Aksaray, Bahçesaray and Kırımlı rural districts

This study aims to determine the market value of the agricultural lands in the rural Bahçesaray and Kirimli districts, which are outside the zoning plan, where agricultural production continues in Aksaray Province, Central District, in Turkey, by mass valuation methods. It is also aims to provide value estimation and value map production with the help of geographic information systems (GIS). Using the sales data from 125 parcels in the study area, the market value of the real estates for which the value is unknown in the region, was estimated. The most frequently used criteria in the assessment of agricultural lands were determined, and the valuation was carried out with Multiple Regression Analysis (MRA) and Artificial Neural Networks (ANN). By means of the assessment and the valuation study, the performance of the valuation methods was compared, and it was determined that the best result according to the test data was the valuation with ANN. In the performance analysis conducted with ANN, the Coefficient of Determination (R²)=0.87, Mean Absolute Percentage Error (MAPE)=0.192, Mean Absolute Error (MAE)=0.047 and Root Mean Square Error (RMSE)=0.059 was found. Moreover, according to the proportional standards guide determined by the International Association of Assessing Officers (IAAO), the performance measurement, the values derived for the Coefficient of Dispersion as (COD)=19.58 and Price-Related Differential as (PRD)=1.02 were also found to be within acceptable limits. Since the valuation of agricultural lands is a less studied subject, there are few articles in the literature. For this reason, it will be useful to increase such as article and evaluate the results applying it region by region. In this study, estimates were found with MRA and ANN methods and value maps were created.

Third-Party Source Switches: Objective Valuation or Fair Value Opinion Shopping?

ABSTRACT Fair value estimates from external third-party sources are generally considered more reliable than internal estimates based on managerial inputs. However, even externally sourced estimates are subject to managerial opportunism, because firms can switch from one external source to another. In the context of life insurance companies that mostly rely on external sources, we posit that such source switches could be driven by managerial incentive either to faithfully report fair values (objective valuation) or to inflate estimates to avoid OTTI (opinion shopping). Our results support both motives. In instances in which the two incentives yield conflicting predictions for source switching, we find the opinion-shopping motive dominates. We also find that switches that increase fair value estimates are associated with a reduced OTTI likelihood and magnitude, especially for high-impairment-risk securities. On balance, our evidence suggests that opportunism with respect to source switching can compromise the reliability of externally sourced fair value estimates. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: G22; M41.

Hierarchical Episodic Control

Deep reinforcement learning is one of the research hotspots in artificial intelligence and has been successfully applied in many research areas; however, the low training efficiency and high demand for samples are problems that limit the application. Inspired by the rapid learning mechanisms of the hippocampus, to address these problems, a hierarchical episodic control model extending episodic memory to the domain of hierarchical reinforcement learning is proposed in this paper. The model is theoretically justified and employs a hierarchical implicit memory planning approach for counterfactual trajectory value estimation. Starting from the final step and recursively moving back along the trajectory, a hidden plan is formed within the episodic memory. Experience is aggregated both along trajectories and across trajectories, and the model is updated using a multi-headed backpropagation similar to bootstrapped neural networks. This model extends the parameterized episodic memory framework to the realm of hierarchical reinforcement learning and is theoretically analyzed to demonstrate its convergence and effectiveness. Experiments conducted in four-room games, Mujoco, and UE4-based active tracking highlight that the hierarchical episodic control model effectively enhances training efficiency. It demonstrates notable improvements in both low-dimensional and high-dimensional environments, even in cases of sparse rewards. This model can enhance the training efficiency of reinforcement learning and is suitable for application scenarios that do not rely heavily on exploration, such as unmanned aerial vehicles, robot control, computer vision applications, and so on.

Main stages of calibration of measuring instruments

The main stages of calibration of measuring instruments are described. The stage of preparation for calibration and its main steps are considered: setting a measurement task, choosing a method and equipment, choosing (developing) calibration methods and their verification (validation). The content of the measurement experiment is presented together with the main measurement methods that can be used to calibrate the indications of measuring instruments and material measures. The main steps of experimental data processing, which lead to the estimation of the numerical value and uncertainty evaluation of the measurand being calibrated, are considered. The preparation of calibration results, including the uncertainty budget and calibration certificate, is described. Procedures for assessing the probability of compliance of a calibrated measuring instrument and material measure with the specified metrological characteristics, as well as for validating their calibration methods, are considered.

Covenant violation concern and investors’ pricing of Level 3 fair value adjustments

We examine the influence of concerns relating to violation of the borrowing covenant on the investors’ valuation of Level 3 fair value adjustments. We reason that managerial bias in Level 3 fair value estimation is greater for firms approaching violation of the borrowing covenant. Based on a sample of Australian real estate firms, we find that managers report upward adjustments to Level 3 investment property values when they approach the threshold where the borrowing covenant is violated; and further find that this deliberate use of discretion is significant for firms closer to the interest coverage thresholds, but not for those approaching the gearing thresholds. We then find that, while fair value adjustments are priced positively, investors apply incremental discounts for firms closer to the violation threshold, or firms which are in technical default of borrowing covenants relative to those that are far from violation. Additionally, we show that the pricing discount on fair value adjustments attributable to the concern over covenant violation is significant only for the weaker governance sub-sample, indicating that effective monitoring mitigates faithful representation concerns about Level 3 fair value estimations.