Summary

This chapter presents advanced techniques which are implemented for capital markets. I have presented various supervised and unsupervised learning in detail along with examples. This chapter particularly used Dow Jones Index closing price as dataset, which was divided into in-sample and out-sample data. The in-sample data was used for model building and the out-sample data for validation of the model. Overfitting and underfitting generally questions the generalization capacity of the model which can be understand using confusion matrix. The accuracy of the model was defined using confusionMatrix() or table().

There are various types of risks that exists in the market and in the next chapter, I will explain how to calculate risk associated with various investments, in particular market risk, portfolio risk, and so on. I will also explain Monte Carlo simulation for risk, hedging techniques, and credit risk, along with Basel regulations.