1-12. Regression

So, how is regression used in stock trading? In practice, using regression to predict a stock’s return is difficult because the signal and financial data is low compared to the noise. Moreover, the models are sensitive to some choices you make about the model. For instance, you’ll have to decide how much of your previous … Read more

Earlier, we touched on using multiple independent variables to predict a single dependent variable. We call this multiple regression. In this example, we are using a house’s area, number of rooms and number of years since the house was built. All three are variables that we use to predict the house price. We can go … Read more

Now, we’ll look at how to use one random variable to predict another random variable. We’ll cover the basics of regression as this forms the basis for several models that are used to analyze stock returns over time. If we want to estimate the price of a house, we may assume that home buyers are … Read more

So, now the question is, what do we do when our data is not normally distributed? Similarly, what do we do when our data is heteroscedastic? To reshape our data and make it more normal, we can feed our data into the log function. To get data that is homoscedastic, we can take the time … Read more

Recall that we also need to check if our data is stationary over time. By stationary, we mean that the mean, variance, and covariance are the same over time. In particular, we want to check that the variance of our data is stable over time. This is important because if the variance changes over time, … Read more

We’ve just seen how to model our data if we assume that it is normally distributed. But how do we decide if our data can be described by a normal distribution in the first place? A quick way to visually check, is to plot a histogram of our data. We can then compare the histogram … Read more

A probability distribution is defined in math by an equation. We call this equation a probability density function or PDF. For every number from negative infinity to infinity, the probability density function gives a probability that this number will be generated. Using math notation, X tilde D means the random variable X follows a probability … Read more

Many statistical models assume that the data follows a normal distribution, also referred to as a Gaussian or a bell curve. This is important when checking whether our models are valid. There are various tests that we use to check that our models describe a meaningful relationship. These tests assume that the data are normally … Read more

You’ve been busy learning here, building up your knowledge and skills through your nanodegree work. But, what’s actually happening inside your head to enable this growth? Well, each time you think about something, you activate particular neural pathways in your brain, and that activation strengthens the pathways themselves. As a simple example, if I just … Read more

Congratulations on making it through this lesson. You’ve built a foundation that will help you with the next few lessons. Coming up, we’ll discuss time series analysis in more depth. Time series analysis includes statistical techniques such as auto-regression and moving averages. Time series analysis also includes machine learning techniques such as Kalman Filters and … Read more

This lesson focuses on two main concepts. 1. Checking if your data fits a normal distribution. 2. Checking if your data is stationary over time and what to do in both cases when they’re not. To understand regression which we will build upon later in time series analysis when using regression, we choose one or … Read more