Part of my job as a researcher and teacher is to periodically apply and grade exams in my classroom. Being constantly in the shoes of an examiner, you soon quickly realize that students are clever in finding ways to do well in an exam without effort. These days, photos and pdf versions of past exams and exercises are shared online in facebook, whatsapp groups, instagram and what not. As weird as it may sound, the distribution of information in the digital era creates a problem for examiners. If you use the same exam from past year, it is likely that students will simply memorize the answers from a digital record.
One of the first examples about using linear regression models in finance is the calculation of betas, the so called market model. Coefficient beta is a measure of systematic risk and it is calculated by estimating a linear model where the dependent variable is the return vector of a stock and the explanatory variable is the return vector of a diversified local market index, such as SP500 (US), FTSE (UK), Ibovespa (Brazil), or any other.
From the academic side, the calculation of beta is part of a famous asset pricing model, CAPM - Capital Asset Pricing Model, that relates expected return and systematic risk.
Recently, Bovespa, the Brazilian financial exchange company, allowed external access to its ftp site. In this address one can find several information regarding the Brazilian financial system, including datasets with high frequency (tick by tick) trading data for three different markets: equity, options and BMF.
Downloading and processing these files, however, can be exausting. The dataset is composed of zip files with the whole trading data, separated by day and market. These files are huge in size and processing or aggregating them in a usefull manner requires specific knowledge for the structure of the dataset.