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Showing posts with the label Classification

ETF Predictions

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Introduction An exchange traded fund ( ETF ) is a fund that owns multiple underlying securities. A popular example is the SPY ETF which tracks the S&P 500 index  which itself tracks the performance of the 500 largest companies in the United States. In the long term the stock market always goes up and investing in ETF's such as SPY is a lucrative passive investment that leverages this fact. Diversification is an important tool for an investor to minimize risks of owning individual stocks and ETFs accomplish this by owning multiple underlying securities. If fact in the 30 year period, ETF's such as SPY and VTSAX  outperform 99% of portfolio managers  . Thus predicting how ETF's will change over a given time horizon will improve our returns, possibly far more than the average 6%-10% annual return generated by the popular ETFs. However that's easier said than done. The efficient market hypothesis ( EMH ) says that it is impossible to consistently generate profits ( Fam...

Online Purchase Intent

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Online Purchase Intent In this blog we will explore a classification problem of judging whether an online buyer will end up buying an item based on his online activity. The dataset can be found here . There are 17 features of which 10 are continuous and 7 categorical. There is one target variable with binary classification of True or False depending on whether any revenue was generated. Exploring the Dataset Let us begin by exploring the data set. We have the following features and their description. # Administrative  Administrative Value # Administrative_Duration  Duration in Administrative Page # Informational  Informational Value #Informational_Duration  Duration in Informational Page #Product_related  Product Related Value #ProductRelated_Duration  Duration in Product Related Page #BounceRates  Bounce Rates of a web page #ExitRates  Exit rate of a web page #PageValues  Page values of each web page #SpecialDay...