Financial econometrics, mathematics and statistics : theory, method and application
著者
書誌事項
Financial econometrics, mathematics and statistics : theory, method and application
Springer, c2019
大学図書館所蔵 全5件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
"This Springer imprint is published by the resistered company Springer Science+Business Media, LLC part of Springer Nature... New York"--T.p. verso
Includes bibliographical references and indexes
内容説明・目次
内容説明
This rigorous textbook introduces graduate students to the principles of econometrics and statistics with a focus on methods and applications in financial research. Financial Econometrics, Mathematics, and Statistics introduces tools and methods important for both finance and accounting that assist with asset pricing, corporate finance, options and futures, and conducting financial accounting research.
Divided into four parts, the text begins with topics related to regression and financial econometrics. Subsequent sections describe time-series analyses; the role of binomial, multi-nomial, and log normal distributions in option pricing models; and the application of statistics analyses to risk management. The real-world applications and problems offer students a unique insight into such topics as heteroskedasticity, regression, simultaneous equation models, panel data analysis, time series analysis, and generalized method of moments.
Written by leading academics in the quantitative finance field, allows readers to implement the principles behind financial econometrics and statistics through real-world applications and problem sets. This textbook will appeal to a less-served market of upper-undergraduate and graduate students in finance, economics, and statistics.
目次
Introduction to Financial Econometrics and Statistics.- Part A: Regression and Financial Econometrics.- Multiple Linear Regression.- Other Topics in Applied Regression Analysis.-Simultaneous Equation Models.-Econometric Approach to Financial Analysis, Planning, and Forecasting.- Fixed Effect vs Random Effect in Finance Research.- Alternative Methods to Deal with Measurement Error.-Three Alternative Errors-in-Variables Estimation Methods in Testing Capital Asset Pricing Model.- Spurious Regression and Data Mining in Conditional Asset Pricing Models.-Time-Series Analysis and Its Applications.-Time-Series: Analysis, Model, and Forecasting.-Hedge Ratio and Time-Series Analysis.- The Binomial, Multi-Nominal Distributions and Option Pricing Model.- Two Alternative Binomial Option Pricing Model Approaches to Derive Black-Scholes Option Pricing Model.-Normal, Lognormal Distribution, and Option Pricing Model.-Copula, Correlated Defaults, and Credit VaR.-Multivariate Analysis: Discriminant Analysis and Factor Analysis.-Stochastic Volatility Option Pricing Models.- Alternative Method to Estimate Implied Variance: Review and Comparison.- Numerical Valuation of Asian Options with Higher Moments in the Underlying Distribution.-Ito's Calculus: Derivation of the Black-Scholes Option Pricing Model.-Alternative Methods to Derive Option Pricing Models.-Constant Elasticity of Variance Option Pricing Model: Integration and Detailed Derivation.- Option Pricing and Hedging Performance under Stochastic Volatility and Stochastic Interest Rates.-Non-Parametric Method for European Option Bounds.
「Nielsen BookData」 より