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RESEARCHES ON NEW MEASUREMENT METHODS FOR MARKET RISK, CREDIT RISK AND LIQUIDITY RISK IN FINANCIAL MARKETS.

金融市场市场风险、信用风险、流动性风险新计量方法研究。

基本信息

批准号：
10308014
负责人：
TAKAHASHI Masafumi
金额：
$ 25.92万
依托单位：
University of Tsukuba
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (A)
财政年份：
1998
资助国家：
日本
起止时间：
1998 至 2000
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-10308014/
关键词：
Non-Normal Distribution Fat-Tail Distribution Value at Risk Credit Risk Hyperbolic Sine Transform Option Valuation Feymnan-Kac Theorem Structual Credit Model Samuelson Model Margrabe Exchange Option 市場リスク流動性リスク金融リスク管理信用リスクの計測

项目摘要

The big financial topics like the US Black Monday in 1987, and the Japanese stock market crash, the bad-loan problem involving financial institutions, and increasing of big corporate default events in 1990's have strongly come under our notice for new methods to measure the various kind of financial risks such as Market Risk, Credit Risk, Liquidity Risk, and so on. This research is one of the realistic and concrete answers, and we propose the new methods to evaluate and measure those risks except liquidity risk.We first introduce a Hyperbolic Sine (HS) stochastic process, a very new and original concept in financial study. Checking the Normal Hypothesis (distribution and/or process) of returns in the real markets, it seems doubtful to accept the Hypothesis, particularly it cannot explain the fat-tail structure in return distribution. If we deny the normal Hypothesis, it affects a lot to the traditional financial studies that strongly depend on the Hypothesis. In our researches, after taking a HS Transform to return data, we are soon aware that this process makes the distribution approximately normal. Using this simple property, we show the fact that it can measure the market and credit Value at Risk (VaR) and it is also applicable to the fat-tail problem and the extreme value theory.Next we take into account various methods like PDE, the Fynman-Kac theorem, and risk neutral method, and we directly apply our HS concept to price European and American derivatives whose underlying security returns in stock/bond market depend on HS process.Lastly we apply it to the structural credit model and derive our new models to value and measure the credit risks.

1987年美国黑色星期一、日本股灾、金融机构不良贷款问题、90年代S重大企业违约事件增多等重大金融话题，引起了我们对市场风险、信用风险、流动性风险等各种金融风险新方法的强烈关注。这项研究是现实而具体的答案之一，我们提出了评估和度量除流动性风险以外的其他风险的新方法。我们首先引入了双曲正弦(HS)随机过程，这是金融研究中一个非常新颖的概念。检验现实市场中收益率的正态假设(分布和/或过程)，似乎很难接受这个假设，特别是它不能解释收益率分布中的厚尾结构。如果否定正态假设，将对依赖正态假设的传统金融研究产生很大影响。在我们的研究中，在对数据进行HS变换后，我们很快意识到这个过程使分布近似正态。利用这一简单的性质，我们证明了它可以度量市场和信用风险价值(VaR)，它也适用于厚尾问题和极值理论；其次，我们考虑了偏微分方程、Fynman-Kac定理和风险中性方法等多种方法，直接将我们的HS概念应用于股票/债券市场基础安全收益依赖于HS过程的欧美衍生品的定价；最后，将其应用于结构性信用模型，得到了我们的新模型来评估和度量信用风险。