A New Mean Reversion Model of Close-End Fund

On the basis of fractal theory, one of the nonlinear theories, this paper studies the validity of Chinese fund market fractal time sequence through Hurst exponent, calculates the H value and proposes a new close-end fund mean reversion model. Meanwhile, this paper validates the mean reversion time sequence for consecutive 54 week data of fund market. The result indicates that this model can effectively prove that Chinese close-end fund market follows the biased random walk. The research also proves that the fund discount does have mean reversion tendency and averagely the fund with high discount has a higher excess yield than that of the fund with low discount. The mean excess yield and the ratio between discount rate deviation and standard deviation demonstrate a descending relationship. The optimum investment period based on ＂mean reversion＂ is one month. Consequently this model provides a new arbitrage method through the discount of close-end fund.

Valuation of the flexibility in decision-making for revamping installations―A case from fertilizer plants

This paper puts forward a valuation model for the flexibility of revamping urea plants based on the substitutability of switching between the internationally accepted fertilizer feedstock fuel oil and natural gas. The paper first builds a stochastic mean-reversion model for fuel oil prices and natural gas prices respectively, then estimates and tests the parameters using the fuel oil and natural gas prices data from the U.S. market. This paper also conducts a sensitivity analysis with important parameters. The results show that the real option method can be applied successfully to evaluate the flexibility in decision- making for revamping installations in fertilizer plants or other similar plants.

A stochastic approach for integrating market and technical uncertainties in economic evaluations of petroleum development

The paper presents a stochastic and economic analysis for petroleum development under uncertain market and technical environments. Mean-reversion with jumps for price forecasting is used to consider market uncertainty, while various scenarios for the reservoir properties and cost are employed to consider technical uncertainty. Monte Carlo simulation is carried out to obtain the feasible range of net present values and internal rates of return. The influence of stochastic parameters is examined through correlation coefficients. The stochastic approach yields more reliable evaluation and effectively investigates the characteristics of development. The integration of uncertainties and contractual terms results in an irregular tendency in the future cash flow and reveals that a larger reserve does not guarantee a greater profit. The reserve and the well rate affect the economic values whereas the parameters for price prediction don＇t. The research confirms the necessity of qualifying uncertainties for realistic decision-making at the initial stage of development.