The income approach of asset valuation estimates the asset value according to the asset-discounted future earnings or the capitalizing process. As a result, a reasonable prediction of asset-expected future returns has...The income approach of asset valuation estimates the asset value according to the asset-discounted future earnings or the capitalizing process. As a result, a reasonable prediction of asset-expected future returns has become one of the core contents of the income approach. The forecast on expected future earnings is generally based on many uncertain factors, such as strict conditions of assumption and the complexity of environment. However, the current valuation practice in this aspect varies greatly and sometimes depends on personally experienced judgment of appraisers. Therefore, the obtained valuation results tend to be simplified and absolutized. This paper takes a listed company in China as an example to explore the way of inserting an uncertainty analysis into the prediction of the income approach, and then to obtain a series of valuation results within a certain probability fluctuation range. Finally, it puts forward some suggestions about the Monte Carlo simulation (MCS).展开更多
The effect of uncertainty about stochastic diffusion model on dynamic portfolio choice of an investor who maximizes utility of terminal portfolio wealth was studied.It applied stochastic control method to obtain the c...The effect of uncertainty about stochastic diffusion model on dynamic portfolio choice of an investor who maximizes utility of terminal portfolio wealth was studied.It applied stochastic control method to obtain the closed-form solution of optimal dynamic portfolio,and used the Bayesian rule to estimate the model parameters to do an empirical study on two different samples of Shanghai Exchange Composite Index.Results show,model uncertainty results in positive or negative hedging demand of portfolio,which depends on investor's attitude toward risk;the effect of model uncertainty is more significant with the increasing of investment horizon,the decreasing of investor's risk-aversion degree,and the decreasing of information;predictability of risky asset return increases its allocation in portfolio,at the same time,the effect of model uncertainty also strengthens.展开更多
As non-renewable natural resources, rare minerals' are extensively used as important raw materials in strategic emerging industries. As global consumption continues to increase over recent years, international compet...As non-renewable natural resources, rare minerals' are extensively used as important raw materials in strategic emerging industries. As global consumption continues to increase over recent years, international competition in the area of rare mineral minerals has been escalating. On the basis' of the identification of 22 rare mineral resources of six categories and analysis of their applications in strategic emerging industries, this paper has adopted a three-factor analytical framework and designed nine indicators from the three dimensions of supply risks, environmental impacts and economic impacts of restricted supply to conduct a quantitative evaluation of the strategic significance of rare mineral resources. The result indicates that the strategic significance of platinum-group metals is the highest and the strategic significance of cesium is the lowest. In order to further increase the reliability of evaluation results, this paper has employed the Monte Carlo simulation for uncertainty analysis'. Simulation result demonstrates that after the impacts" of individual indicators have been taken into account, the results' of this paper's evaluation of 22 rare mineral resources remain valid. Given the growing significance of rare mineral resources to strategic emerging industries, China should formulate a national strategy on rare mineral resources', strive to inerease the supply security of key raw materials for strategic emerging industries and achieve the sustainable development and utilization of rare mineral resources for national security of natural resources.展开更多
By introducing a stochastic element to the double-jump diffusion framework to measure the Knight uncertainty of asset return process, this paper builds the model of dynamic portfolio choice, which maximizes the expect...By introducing a stochastic element to the double-jump diffusion framework to measure the Knight uncertainty of asset return process, this paper builds the model of dynamic portfolio choice, which maximizes the expected utility of terminal portfolio wealth. Through specifying the state function of uncertainty-aversion, it utilizes the max-min method to derive the analytical solution of the model to study the effect of the time-varying, jumps, and Knight uncertainty of asset return process on dynamic portfolio choice and their interactions. Results of comparative analysis show: The time-varying results in positive or negative intertemporal hedging demand of portfolio, which depends on the coefficient of investor's risk aversion and the correlation coefficient between return shift and volatility shift; the jumps in asset return overall reduce investor's demand for the risky asset, which can be enhanced or weakened by the jumps in volatility; due to the existing of the Knight uncertainty, the investor avoids taking large position on risky asset, and the resulting is the improving of portfolio's steady and immunity. At last, an empirical study is done based on the samples of Shanghai Exchange Composite Index monthly return data from January 1997 to December 2009, which not only tests the theoretical analysis but also demonstrates that the proposed method in the paper is useful from the aspect of portfotio's equivalent utility.展开更多
文摘The income approach of asset valuation estimates the asset value according to the asset-discounted future earnings or the capitalizing process. As a result, a reasonable prediction of asset-expected future returns has become one of the core contents of the income approach. The forecast on expected future earnings is generally based on many uncertain factors, such as strict conditions of assumption and the complexity of environment. However, the current valuation practice in this aspect varies greatly and sometimes depends on personally experienced judgment of appraisers. Therefore, the obtained valuation results tend to be simplified and absolutized. This paper takes a listed company in China as an example to explore the way of inserting an uncertainty analysis into the prediction of the income approach, and then to obtain a series of valuation results within a certain probability fluctuation range. Finally, it puts forward some suggestions about the Monte Carlo simulation (MCS).
基金Key program of Natural Science Research of High Education of Anhui Province of China(No.KJ2009A157)
文摘The effect of uncertainty about stochastic diffusion model on dynamic portfolio choice of an investor who maximizes utility of terminal portfolio wealth was studied.It applied stochastic control method to obtain the closed-form solution of optimal dynamic portfolio,and used the Bayesian rule to estimate the model parameters to do an empirical study on two different samples of Shanghai Exchange Composite Index.Results show,model uncertainty results in positive or negative hedging demand of portfolio,which depends on investor's attitude toward risk;the effect of model uncertainty is more significant with the increasing of investment horizon,the decreasing of investor's risk-aversion degree,and the decreasing of information;predictability of risky asset return increases its allocation in portfolio,at the same time,the effect of model uncertainty also strengthens.
基金Innovation Project of Chinese Academy of Social Sciences(Grant No.SKGJCX2013-04)Key Program of National Social Sciences Foundation of China(Grant No.13&ZD169)Young Scientists Fund of National Natural Science Foundation of China(Grant No.71203232)
文摘As non-renewable natural resources, rare minerals' are extensively used as important raw materials in strategic emerging industries. As global consumption continues to increase over recent years, international competition in the area of rare mineral minerals has been escalating. On the basis' of the identification of 22 rare mineral resources of six categories and analysis of their applications in strategic emerging industries, this paper has adopted a three-factor analytical framework and designed nine indicators from the three dimensions of supply risks, environmental impacts and economic impacts of restricted supply to conduct a quantitative evaluation of the strategic significance of rare mineral resources. The result indicates that the strategic significance of platinum-group metals is the highest and the strategic significance of cesium is the lowest. In order to further increase the reliability of evaluation results, this paper has employed the Monte Carlo simulation for uncertainty analysis'. Simulation result demonstrates that after the impacts" of individual indicators have been taken into account, the results' of this paper's evaluation of 22 rare mineral resources remain valid. Given the growing significance of rare mineral resources to strategic emerging industries, China should formulate a national strategy on rare mineral resources', strive to inerease the supply security of key raw materials for strategic emerging industries and achieve the sustainable development and utilization of rare mineral resources for national security of natural resources.
基金supported by National Natural Science Foundation of China under Grant Nos.71271003 and 71171003Programming Fund Project of the Humanities and Social Sciences Research of the Ministry of Education of China under Grant No.12YJA790041+1 种基金Natural Science Foundation of Anhui Province under Grant No.1208085MG116Key Program of Natural Science Research of High Education of Anhui Province of China under Grant No.KJ2011A031
文摘By introducing a stochastic element to the double-jump diffusion framework to measure the Knight uncertainty of asset return process, this paper builds the model of dynamic portfolio choice, which maximizes the expected utility of terminal portfolio wealth. Through specifying the state function of uncertainty-aversion, it utilizes the max-min method to derive the analytical solution of the model to study the effect of the time-varying, jumps, and Knight uncertainty of asset return process on dynamic portfolio choice and their interactions. Results of comparative analysis show: The time-varying results in positive or negative intertemporal hedging demand of portfolio, which depends on the coefficient of investor's risk aversion and the correlation coefficient between return shift and volatility shift; the jumps in asset return overall reduce investor's demand for the risky asset, which can be enhanced or weakened by the jumps in volatility; due to the existing of the Knight uncertainty, the investor avoids taking large position on risky asset, and the resulting is the improving of portfolio's steady and immunity. At last, an empirical study is done based on the samples of Shanghai Exchange Composite Index monthly return data from January 1997 to December 2009, which not only tests the theoretical analysis but also demonstrates that the proposed method in the paper is useful from the aspect of portfotio's equivalent utility.