A new test on the conditional capital asset pricing model

Testing the validity of the conditional capital asset pricing model （CAPM） is a puzzle in the finance literature. Lewellen and Nagel[14] find that the variation in betas and in the equity premium would have to be implausibly large to explain important asset-pricing anomalies. Unfortunately, they do not provide a rigorous test statistic. Based on a simulation study, the method proposed in Lewellen and Nagel[14] tends to reject the null too frequently. We develop a new test procedure and derive its limiting distribution under the null hypothesis. Also, we provide a Bootstrap approach to the testing procedure to gain a good finite sample performance. Both simulations and empirical studies show that our test is necessary for making correct inferences with the conditional CAPM.

Using Binomial Tree Pricing Model in a Fuzzy Market

A model of using binomial tree pricing formulae in a fuzzy market is proposed. In the fuzzy market, a price interval can be got according to the belief degree. The rule for the reasonability of the price interval is proposed. The explicit expression of the interval is discussed in some special settings.

Pricing Model of Multiattribute Derivatives Based on Mixed Process

By Analyzing the behavior and character of derivative security, the authors established a pricing model of multiattribute derivative security whose underlying asset pricing process is a mixed process, and obtained a new model for option pricing of multiattribute derivatives based on mixed process, and improved some original results.

Application of Binomial Option Pricing Model to the Appraisal of Knowledge Management Investment

This paper views knowledge management （KM） investment from the angle of real options, and demonstrates the utility of the real options approach to KM investment analysis. First, KM project has characteristics of uncertainty, irreversibility and choice of timing, which suggests that we can appraise KM investment by real options theory. Second, the paper analyses corresponding states of real options in KM and finance options. Then, this paper sheds light on the way to the application of binomial pricing method to KM investment model, which includes modeling and conducting KM options. Finally, different results are shown of using DCF method and binomial model of option evaluation via a case.

Cost Management Strategy of Highway Engineering Construction Stage Using the List Pricing Model

Highway engineering requires higher investment and requires a long time of management compared to other construction projects.There are many factors that affect the project cost during the engineering construction stage of a highway.The effective development of cost management in the construction phase of highway engineering under the list pricing model can avoid unnecessary waste and help control the cost of highway engineering.However,there are still some problems in the development of cost management in the construction phase of highway engineering,which will affect the role of the list-based pricing mode in cost management.This paper explores and analyzes the advantages of the list pricing model and the problems existing in the cost management of the highway engineering construction stage under the list pricing model,and proposes effective management strategies to improve cost management of the highway engineering construction stage.

Research on Financial Lease Pricing Model

Financial leasing is a financial innovation product with leasing and financing functions.The research on the theory of financial leasing and risk pricing methods should be highly valued.Rent is set based on the total revenue of the lessor and the total cost of the lessee.The factors that affect pricing include project costs,security deposits,fees,lease terms,revenue,interest rates,etc.Using the principle of net present value to elaborate the components of financial leases and constructing a financial lease pricing model from the perspective of maximizing the profit and interests of the lessor,an empirical analysis of the model was carried out using an actual case,thus concluding that the model is effective.

A Pricing Model for Big Personal Data

Big Personal Data is growing explosively. Consequently, an increasing number of internet users are drowning in a sea of data. Big Personal Data has enormous commercial value; it is a new kind of data asset. An urgent problem has thus arisen in the data market： How to price Big Personal Data fairly and reasonably. This paper proposes a pricing model for Big Personal Data based on tuple granularity, with the help of comparative analysis of existing data pricing models and strategies. This model is put forward to implement positive rating and reverse pricing for Big Personal Data by investigating data attributes that affect data value, and analyzing how the value of data tuples varies with information entropy, weight value, data reference index, cost, and other factors. The model can be adjusted dynamically according to these parameters. With increases in data scale, reductions in its cost,and improvements in its quality, Big Personal Data users can thereby obtain greater benefits.

A Stock Pricing Model Based on Arithmetic Brown Motion

This paper presents a new stock pricing model based on arithmetic Brown motion. The model overcomes the shortcomings of Gordon model completely. With the model investors can estimate the stock value of surplus companies, deficit companies, zero increase companies and bankrupt companies in long term investment or in short term investment.

A Pricing Model for Optical Networks

Pricing of the optical networks will play a key role from network operator's point of view to achieve the maximum profit. This paper introduces pricing models for optical networks.

The Analyses of Risk Premium and the Model Revisions About Capital Asset Pricing Models

The pricing theories of capital assets are the principal part in the modern financial theories. Presently, the capital asset pricing model and the arbitrage pricing theory, including their evolutional forms, all don＇t embody the premium of non-system risks and non-factor risks. This paper analyses the risk reward of traditional capital assets pricing models, revises the traditional capital assets pricing models, and advances the revised models of capital assets pricing theories basing on full-risk reward.

Binomial Tree Pricing Model of Convertible Bond with Default Risk

In this paper we use a binomial tree to price convertible bond with default risk. A new way about pricing convertible bonds is proposed, which belongs to the deduced form approach. Firstly an inhomogeneous Possion process is used to describe default event and definition of default time. Secondly we combine the stock binomial tree with default intensity and obtain a new tree, then convertible bonds are priced according to the combined tree. It is worth pointing out that the model have following characters： simple, intuitive and having the strong ability to combine other items in convertible bonds＇ indenture.

Does the EVA valuation model explain the market value of equity better under changing required return than constant required return?

Through the Economic-Value-Added(EVA)valuation model,the expected market value of equity can be determined by adding the book value of equity with the present value of expected EVAs under the assumption of constant required return and constant return on equity.The equation of EVA valuation model has taken its shape under the assumption of constant required return and constant return on equity.However,a large body of empirical evidence indicates that required rate of return never remain constant.The EVA-valuation model formulated under constant required return cannot be implemented under the scenario of changing required return.In this study,we explored whether the EVA valuation model could be implemented under changing required return by making any changes in the model and found that it could be implemented under the scenario of changing required return by replacing the book value of the equity of the existing model with the present value of required earnings or normal market earnings.We further examined whether the explanatory ability of the EVA valuation model under the assumption of changing required return is better than that of the valuation model under the assumption of constant required return.Relative information content analyses were conducted by considering sample of the intrinsic value of equities determined by valuation models and the market value of equities of 69 large-cap,88 mid-cap,and 79 small-cap companies.The results showed that the EVA-based valuation model with changing normal market return outperformed the EVA-based valuation model with constant required return.

Water Resource Pricing Study Based on Water Quality Fuzzy Evaluation: A Case Study of Hefei City

Price plays an important role in water resources management. The price of water resources can also be considered as a “water resource tax” which reflects the value and opportunity cost of water, and people will pay for the right to use water. Currently, the water resource fees’ effect of regulating resource differential revenues is not manifest and it’s not enough to reflect the principle of paid use of resources as well as regulating resources differential revenues. Due to the ambiguity and complexity of water resources price, this paper uses methods relating to fuzzy mathematics for modeling and processing. The study had a comprehensive consideration of five factors including water quality, water resources per capita, household consumption level, per capita GNP, population or population density to evaluate the water resource price.

Dynamic Pricing of Tropical Fruits in Hainan Based on Internet of Things Technology

In recent years,the Internet of Things(IoT)technology has been widely used in the production and sales of tropical fruits,with strong practicability and wide application prospects.The tropical fruit dynamic pricing model based on the IoT technology can promote the healthy development of the tropical fruit industry in Hainan and ensure the income of fruit farmers.Based on IoT technology,the quality grade of tropical fruits in Hainan is obtained.According to the dynamic pricing strategy of revenue management,a dynamic pricing model based on the quality of tropical fruits and a dynamic pricing model based on consumer segmentation are established to study the dynamic pricing problem under the condition of maximum profit for tropical fruit sellers.The research results show that for different fruit quality and consumer groups,different pricing models are required for pricing,in order to get the maximum profit from tropical fruit sales.Sellers must flexibly adopt different dynamic pricing models to price tropical fruits to enhance the competitiveness of the tropical fruit industry.

International Financial Market＇s Integration and Modelling Returns of Risky Assets

The aim of this paper is to test the ability of conditional and unconditional capital asset pricing models （CAPMs） and to explain emerging markets returns in terms of their integration into the international market. The authors use data on five developed countries and five emerging countries as well as data on the Tunis Stock Exchange （TSE） after the reforms. The results show that the correlations between emerging markets returns and developed markets returns are very low and sometimes negative. Conditional arbitrage pricing theory （APT） as well as conditional CAPM has low predictive power for emerging markets than that for developed markets. Finally, following the financial reforms, Tunisian financial markets have became more and more integrated into the international market （excess returns and unconditional beta consistent with predictions）. However, conditional APT does not accurately explain Tunisian market returns. This study confirms the unavailability of an accurate modelling technique of the TSE structure.

Impact of Accessibility on Housing Prices in Dalian City of China Based on a Geographically Weighted Regression Model

This paper studies the relationship between accessibility and housing prices in Dalian by using an improved geographically weighted regression model and house prices, traffic, remote sensing images, etc. Multi-source data improves the accuracy of the spatial differentiation that reflects the impact of traffic accessibility on house prices. The results are as follows: first, the average house price is 12 436 yuan(RMB)/m^2, and reveals a declining trend from coastal areas to inland areas. The exception was Guilin Street, which demonstrates a local peak of house prices that decreases from the center of the street to its periphery. Second, the accessibility value is 33 minutes on average, excluding northern and eastern fringe areas, which was over 50 minutes. Third, the significant spatial correlation coefficient between accessibility and house prices is 0.423, and the coefficient increases in the southeastern direction. The strongest impact of accessibility on house prices is in the southeastern coast, and can be seen in the Lehua, Yingke, and Hushan communities, while the weakest impact is in the northwestern fringe, and can be seen in the Yingchengzi, Xixiaomo, and Daheishi community areas.

Development of land valuation approach based on hedonic model--A case study of Vientiane capital city Laos

The aim of this study is to identify the variables affecting land value. Examined land was selected from the village in Vientiane capital city Laos. Data was collected from 100 villages in center of Vientiane capital city by using survey methods. A hedonic price analysis was conducted to determine the marginal return to different land characteristics using an econometric model corrected for correlation. Parcel characteristics such as distance to public park, village income, distance of population, number of the school within 500 meters buffer, distance to the temple, distance to the major market and distance to the business center （CBD）. Arc GIS 9.2 was applied to calculate the distance of the factors, after that SPSS 15.0 was used to calculate the land price characteristic based on hedonic price model. The results showed that the distance to the center of population was the main factor influencing to the land price, and followed by school and village income. Map of the land price before and after hedonic price analysis were produced. The land price valuation approaches based on hedonic price model for Vientiane capital city were developed and land price map were predicted. Hedonic price model and GIS were very useful for this research, and finally the policy of the land valuation based on GIS was developed.

Investment in deepwater oil and gas exploration projects:a multi-factor analysis with a real options model

Deepwater oil and gas projects embody high risks from geology and engineering aspects, which exert substantial influence on project valuation. But the uncer- tainties may be converted to additional value to the projects in the case of flexible management. Given the flexibility of project management, this paper extends the classical real options model to a multi-factor model which contains oil price, geology, and engineering uncertainties. It then gives an application example of the new model to evaluate deepwater oil and gas projects with a numerical analytical method. Compared with other methods and models, this multi-factor real options model contains more project information. It reflects the potential value deriving not only from oil price variation but also from geology and engi- neering uncertainties, which provides more accurate and reliable valuation information for decision makers.

Estimation Methodology of Short-term Natural Rubber Price Forecasting Models

This study developed a short-term econometric model of world natural rubber price Standard Malaysia Rubber Grade 20 （SMR20）. Both single and simultaneous equations were utilized using monthly data from January 1990-December 2008 as estimation period and data from January 2009-June 2009 was used as an ex-ante forecast. The data were tested for unit root and Vector Error Correction and co-integration method was used to estimate the parameters of the model. The models specifications were developed in order to discover the inter-relationships between NR production, consumption and prices of SMR20 and to determine forecast price of SMR20. Comparative analysis between the single-equation specification and simultaneous supply-demand and price equation were made in terms of their estimation accuracy based on RMSE, MAE and （U-Thile） criteria. Ex-ante forecasts was carried out for the period of January 2009-June 2009. The results revealed that the values of the RMSE, MAE and U of simultaneous supply-demand and price equations model were comparatively smaller than the values generated by the single-equation model. These statistics suggest that the simultaneous equation of supply-demand and price model is more accurate and efficient measure in terms of its statistical criteria than the single-equation model in predicting the price of SMR20 in the next 6 months.

The Influence of Built Environment on the Spatial Distribution of Housing Price:Based on Multiple Big Data and Hedonic Model

In recent years,more and more researches focus on the self characteristics and spatial location of housing,and explore the influencing factors of urban housing price from the micro perspective.As representative of big cities,spatial distribution pattern of housing price in national central cities has attracted much attention.In order to return the spatial distribution pattern of housing price to the research on influencing factors of housing price,the reasons behind the spatial distribution pattern of housing price in three national central cities:Beijing,Wuhan and Chongqing are explored.The results show that①urban housing price is affected by many factors.Due to different social and economic conditions in each city,there are differences in the influence direction of the proximity to expressways,city squares,universities and living facilities,characteristics of companies and enterprises on Beijing,Wuhan and Chongqing.②Various factors have different value-added effects on housing price in different cities.The location of ring line in Beijing and Wuhan has the greatest increase effect on housing price,while metro station of Chongqing has the greatest increase effect on housing price.