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Dynamic Structural Change of Financial Intermediation and Restructuring of Business Models in Japanese Banking

日本银行业金融中介的动态结构变化与业务模式重组

基本信息

批准号：
15530227
负责人：
MUNECHIKA Midori
金额：
$ 1.41万
依托单位：
Toyo University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2003
资助国家：
日本
起止时间：
2003 至 2005
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-15530227/
关键词：
Mean-Variance Optimization Stylized facts Monte Carlo Simulation Anomaly Correlation Covariance matrix Value at Risk Stochastic finance 共分散行列バリュー・アット・リスク Stylized facts ダウンサイド・リスク資産価格の過剰変動性 time deformation 分布混合仮説 Stochasti

项目摘要

In this study, my overall research objective was to analyze the relationship between risk-reward optimization and risk-taking decisions in Japanese banking. Since the emergence of modern portfolio theory originated with Markowitz, risk analysis in quantitative finance has extensively addressed market risk in the capital markets. In the context of integrated risk management, the extension to the various risks in banking has advanced in the United States and Europe, but it still remains a challenge in the Japanese banking industry. However, in order to enhance the risk-return profile, it is necessary for Japanese banks to implement risk-based policies and practices, and thus, to adequately model and measure banking risk utilizing a quantitative approach.I concentrated on the issue of modeling and measuring market risk. The term ‘risk' is used in finance in two different but related ways : as the magnitude of the standard deviation of the potential return of investment portfolio, or the p … More otential loss over some period of time. Risk models in quantitative finance analyze risk using stochastic approaches.First, I studied mean-variance analysis, in which portfolio risk is statistically calculated by using a covariance matrix, in which volatilities and correlations are the two key determinants of risk. Theoretically, mean-variance analysis postulates normally distributed stock returns and rational behavior of investors. In fact, histograms of stock returns, however, exhibit excess peakness and fat-tailed distributions rather than normal distributions, which are referred to as stylized facts. These features need to be accounted for in the process of implementing optimization.In the process of implementing stochastic mean-variance optimization, I used Monte Carlo simulation as an optimizer. By examining forecasting results of Monte Carlo simulation, I extended to the second view of risk : the magnitude of the potential loss, in which risk is evaluated in the tail of the distribution, such as the concept of value at risk. Now the VaR framework is used as the methodology of risk measurement of the Basel Accord in the context of integrated risk management in banking. Less

在本研究中，我的总体研究目标是分析日本银行业的风险回报优化和风险决策之间的关系。自马科维茨提出现代投资组合理论以来，定量金融中的风险分析已经广泛地研究了资本市场中的市场风险。在综合风险管理的背景下，银行业的各种风险的扩展在美国和欧洲取得了进展，但在日本银行业仍然是一个挑战。但是，为了提高风险收益率，日本银行必须实施基于风险的政策和实践，因此，必须充分利用定量方法对银行风险进行建模和测量。风险一词在金融学中有两种不同但相关的用法：一是投资组合潜在收益的标准差的大小， ...更多信息在一段时间内的潜在损失。风险模型在定量金融学中使用随机方法分析风险。首先，我研究了均值-方差分析，其中投资组合风险是通过使用协方差矩阵统计计算的，其中波动率和相关性是风险的两个关键决定因素。从理论上讲，均值-方差分析假设股票收益率服从正态分布，投资者行为是理性的。事实上，股票收益率的直方图，然而，表现出过剩的峰值和厚尾分布，而不是正常的分布，这被称为程式化的事实。在实现随机均值-方差优化的过程中，我使用蒙特卡罗模拟作为优化器。通过检验蒙特卡洛模拟的预测结果，我扩展到风险的第二种观点：潜在损失的大小，其中风险是在分布的尾部进行评估的，例如风险价值的概念。在银行业综合风险管理的背景下，VaR框架被作为巴塞尔雅阁协议的风险度量方法。少