论文标题:我国金融市场基准利率选择问题研究
论文作者
论文导师 史永东,论文学位 硕士,论文专业 金融工程
论文单位 东北财经大学,点击次数 134,论文页数 47页File Size2542K
论文网 http://www.lw23.com/lunwen_512112447/
Benchmark rates;; Hilbert spaces;; Nonparametric method
我国现在正处于利率市场化进程中，确定对市场具有基准性和依据性的基准利率有重要意义。由于基准利率可以作为其他市场利率制订的依据和标准，它应该能够充分反映市场上资金的供求状况，能够对其他风险资产的利率变动产生重要的影响，同时还需要具有系统稳定性并可以作为调控市场的有效工具。而只有确定了基准利率，才能够使得货币政策的制定和实施更加切合实际，资金更合理地使用及金融资产定价更具有现实意义和更加合理，尤其是对期货市场以及金融衍生品市场的发展更有着十分重要的促进和推动作用。 根据国际经验，利率市场化过程需要循序渐进地进行，而基准利率则是由货币市场中现存的起重要作用的各种利率中选出的，具体应该选择哪种利率作为基准利率对于利率市场化改革的成功与否起着关键作用。本文正是在这样的背景下，结合国内外学者的研究成果，对我国现有利率作了比较分析，试图找到现阶段我国的基准利率并为基准利率的确定找到一个有效而且可行的方法。 全文分七个部分：首先是引言，简要介绍了选题意义和主要结论。其次是文献回顾，重点介绍了国内外学者对于基准利率选择所作的研究；接着对我国市场目前利率体系进行了比较详尽的阐述。通过对我国现行市场中存在的利率的历史、形成过程和现状的研究，明了这些利率各自的特点及作为基准利率的优势和缺陷。第四部分是对国际市场基准利率的介绍和比较。希望通过对于国际市场基准利率选择的认识，可以为我国基准利率选择提供一定的指导。第五部分是基准利率选择思路和方法的介绍，介绍了最主要的定理和模型，并详细列出了实现步骤。紧接着给出了实证结果。最后是结论性的评价和政策性建议。通过本文的研究，给出一些关于基准利率选择、完善和应用的意见和建议。 本文最主要的创新点在于：以往学者对于基准利率的研究往往是从实践的角度出发，以定性分析为主，这难免就使得对于基准利率的研究缺乏坚实的理论基础。而本文从Beta定价的角度出发，认为如果是基准利率，必须能够满足处于前沿空间这一必要条件，由此我们构建了前沿空间，并测试现有利率是否处于前沿空间，以作为是否可以作为基准利率的判断标准。另外，本文选择非参数方法拟合概率，这主要是由于在总体分布未知的情况下，运用非参数方法可以得到更准确的估计，也克服了以往经典参数估计需要估计一些总体特有的变量的缺陷，使得估计的有效性更好。
Our country is developing the economy fast, and the financial market needs a benchmark rate to provide a reference to the other interest rates. As a pricing standard for other interest rates, the benchmark rate has to be capable to reflect the situation of the demand and the supply of the money in the market, and it could affect other interest rates effectively. Also, the benchmark rate needs system stability and can be used as an instrument to control the market. If monetary policies want to be made and operated reasonably, it becomes important to make it clear that which one is the benchmark. It is also helpful to judge whether the money is used suitably or the financial assets" prices proper. For now, we are obliged to develop the future market and the financial derivatives market, which both call for a benchmark interest rate. According to the international experience, the development process needs carrying out in steps. The benchmark rate is chosen from the existing interest rates, and which one can take on the responsibility is crucial to the success of the reform. In the background of this, the paper compares the existing rates, concludes the characteristics of each one, tries to find out the benchmark, and digs hard to find out the reasonable method to testing the benchmark rates. It includes seven chapters: Introduction tells you why we choose to study the benchmark rates and the point of it The second part is about other analysts" research on this field, and followed by the detailed description of existing interest rates system in our country. Here we introduce the history, the development and the state for now of the interest rates used in our money market. Meanwhile, the advantages and disadvantages of them are discussed. The fourth part is about benchmark rates in the international financial market. We hope to find something meaningful to the choice of the benchmark for our country. Then, we give the method used in this paper, including main theories and the model. Working steps and the results can be found in this chapter, too. We apply for nonparametric density to estimate the distribution function, and in Hilbert spaces to calculate the mean-variance frontier. After comparison, the result, which interest rate stands for the standard, comes out. At the end of the paper are conclusive discussion and political advices. The main contribution of us is the method, used to examining benchmark rates status, has a theory base. Most analysis before us generalized the characteristics of benchmark from the purely empirical matter, and it somehow makes the research lack of support from the theory. We begin with Beta pricing theory to find out prerequisites of the benchmark rates. If an interest rate is the benchmark, it should be in mean-variance frontier. So we calculate out the frontier spaces, and test if the interest rates are mean-variance frontier efficient. Another contribution is that we use nonparametric method to estimate the density function. It is a better estimation when the total distribution is unknown. Opposing to classical parametric estimation, nonparametric method dose not require the variances only belonging to the total distribution. As a result, the estimation is more efficient.
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