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Title: Real-time analysis of the intraday financial volatility: Big data, simulations and stochastic volatility using R Authors:  Antonio Santos - University of Coimbra (Portugal) [presenting]
Abstract: The financial volatility is a key element for economic agents that make decisions in financial markets. To define the measures of volatility through the financial models, data need to be collected, models need to be estimated, and the relevant results need to be presented in an integrated way. Using the capabilities of R these tasks can be performed in an integrated form, allowing a more efficient use of the data, models and measures to characterize the volatility evolution in the financial markets. A package in R that integrates the three tasks of collecting and treating big financial datasets, estimation of the models and definition relevant measures of volatility, and also the presentation the results in an intuitive and iterative form is certainly useful. The capabilities of R to retrieve public available data from different sites and to organize the data conveniently are used to deal with big data sets. Estimation of the parameters within the stochastic volatility model, and the forecasting of the volatility are usually made through the Bayesian statistics and Markov chain Monte Carlo methods. A mix of code in R and C is used to accomplish these tasks. The presentation of the measures of volatility forecasts can take advantage of the resources available in R. This will be done by an R Shiny web application. A package in R was developed to perform the three aforementioned tasks, and some of the main functions will be described.