文件名称:
Mastering R for Quantitative Finance
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文件大小: 3mb
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上传时间: 2016-10-16
详细说明： Chapter 1, Time Series Analysis (Tamás Vadász) discusses some important concepts such as cointegration (structural), vector autoregressive models, impulse-response functions, volatility modeling with asymmetric GARCH models, and news impact curves. Chapter 2, Fa ctor Models (Barbara Dömötör, Kata Váradi, Ferenc Illés) presents how a multifactor model can be built and implemented. With the help of a principal component analysis, five independent factors that explain asset returns are identified. For illustration, the Fama and French model is also reproduced on a real market dataset. Chapter 3, Forecasting Volume (Balázs Árpád Szűcs, Ferenc Illés) covers an intraday volume forecasting model and its implementation in R using data from the DJIA index. The model uses turnover instead of volume, separates seasonal components (U shape) from dynamic components, and forecasts these two individually. Chapter 4, Big Data – Advanced Analytics (Júlia Molnár, Ferenc Illés) applies R to access data from open sources, and performs various analyses on a large dataset. For illustration, K-means clustering and linear regression models are applied to big data. ...展开收缩
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