We show a simple way to let the data speak for itself. Specifically, we show how a large mixed bag of data, potentially embedded with missing data points and collinearities, and therefore unsuitable for traditional econometric analysis, can be useful in building fast and meaningful big data and...

Cover -- Title Page -- Copyright -- Contents -- Preface -- 1 Why Big Data? -- Introduction -- Appendix 1.A Coding Big Data in Python -- Reference -- 2 Neural Networks in Finance -- Introduction -- Neural Network Construction Methodology -- The Architecture of Neural Networks -- Choosing the...

Why big data? -- Neural networks in finance -- Supervised models -- Semi-supervised learning -- Letting the data speak with unsupervised learning -- Big data factor models -- Data as a signal versus noise -- Applications : big data in options pricing and stochastic modeling -- Data clustering.

We show a simple way to let the data speak for themselves. Specifically, we show how a large mixed bag of data, potentially embedded with missing data points and collinearities, and therefore unsuitable for traditional econometric analysis, can be useful in building fast and meaningful big data...