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.

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.

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.

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.

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.

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.

Short-Term and Long-Term Price Forecasting Models for the Future Exchange of Mongolian Natural Sea Buckthorn Market

Sea buckthorn market floated uncertainly within a narrow range. The market situation provided upward pressure on prices, and producer and consumer interest were poor, coupled with weak prices in the regional markets. The objectives of the study are: 1) to estimate the relationship between wild Sea buckthorn (SB) price and Supply, Demand, while some other factors of crude oil price and exchange rate by using simultaneous Supply-Demand and Price system equation and Vector Error Correction Method (VECM);2) to forecast the short-term and long-term SB price;3) to compare and evaluate the price forecasting models. Firstly, the data was analyzed by Ferris and Engle-Granger’s procedure;secondly, both price forecasting methodologies were tested by Pindyck-Rubinfeld and Makridakis’s procedure. The result shows that the VECM model is more efficient using yearly data;a short-term price forecast decreases, and a long-term price forecast is predicted to increase the Mongolian Sea buckthorn market.

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.

Financial Rogue Waves

We analytically give the financial rogue waves in the nonlinear option pricing model due to Ivancevic,which is nonlinear wave alternative of the Black-Scholes model.These rogue wave solutions may be used to describe thepossible physical mechanisms for rogue wave phenomenon in financial markets and related fields.

Hedonic price analysis of urban housing:An empirical research on Hangzhou,China

The hedonic price model is widely applied to study the urban housing market because of the heterogeneity of housing products. Literature indicated that the hedonic price theory mainly includes two parts: Lancaster’s partiality theory and Rosen’s characteristic market equilibrium analysis. This paper chose 18 characteristics as independent variables and set up a linear hedonic price model for Hangzhou City. The model was tested with 2473 housing samples and field survey data of 290 housing commu-nities. This research found that 14 out of 18 characteristics had significant influence on housing price. They were classified into 5 groups according to their impact degree.

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.

A review of refinery complexity applications

Refinery complexity quantifies the sophistication and capital intensity of a refinery and has found widespread application in facility classification, cost estimation, sales price models, and other uses. Despite the ubiquity and widespread use of refining complexity, however, surprisingly little material has been written on its applications. The pur- pose of this review is to describe the primary applications of refinery complexity and some recent extensions. A secondary purpose of this review is to provide a framework that unifies complexity applications and suggests avenues for future research. Examples illustrate the applications considered.

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.

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.

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.

Empirical analysis on risk of security investment

The paper analyzes the theory and application of Markowitz Mean-Variance Model and CAPM model. Firstly, it explains the development process and standpoints of two models and deduces the whole process in detail. Then 30 stocks are choosen from Shangzheng 50 stocks and are testified whether the prices of Shanghai stocks conform to the two models. With the technique of time series and panel data analysis, the research on the stock risk and effective portfolio by ORIGIN and MATLAB software is conducted. The result shows that Shanghai stock market conforms to Markowitz Mean-Variance Model to a certain extent and can give investors reliable suggestion to gain higher return, but there is no positive relation between system risk and profit ratio and CAPM doesn＇t function well in China＇s security market.

Discount Rate of China’s New Energy Power Industry

Under the dual pressures of energy crisis and environmental pollution,China’s new energy power industry has become a focal point for environmental management and requires greater investment.In this context,as a significant input of investment projects,discount rate requires a well-calibrated evaluation because new energy power investment projects are highly capital intensive.The main objective of this paper is to evaluate the discount rate of China’s new energy power industry.First,we use Moving Average to correct the parameters of capital asset pricing model(CAPM)and weighted average cost of capital,which extends the literature on the avoidance of CAPM noise information problem.Second,we study the industry-level annual discount rates of mainly China’s new energy power industries,including hydropower,nuclear power,wind power,and photovoltaic power industries for the period of 2014-2019.The results show that discount rates in China’s new energy power industries evolved differently between the years of 2014-2019 with average annual discount rates being 7.56%,5.83%,5.60%,and 8.64%,for the hydropower,nuclear power,wind power,and photovoltaic power industries,respectively.In 2019,the four annual discount rates were highest for the photovoltaic power industry(8.66%),followed by hydropower(7.17%),wind power(5.72%),and nuclear power industry(5.26%).Forecasting to 2020 from the 2019 evaluation base period,the discount rates are 6.37%,5.00%,6.57%,and 9.05%for the photovoltaic power,hydropower,wind power,and nuclear power industries,respectively.Under the different capital structures,their forecasts for the photovoltaic power,hydropower,wind power,and nuclear power industries in 2020 are,respectively,within[4.35%,9.24%],[3.92%,7.10%],[4.58%,10.40%],[5.46%,14.81%].We also discussed more details on capital structure and forecast period of discount rates for China’s new energy power industries.Our analysis shows that it is necessary to establish a new energy power industry database and steadily promote the implementation of policies.