Unknown Indicator

Simple Regression model is a single variable regression model that attempts to put a straight line through equity instruments price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.
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In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as price historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Simple Regression In A Nutshell

Using regression can allow you to implement a trading and investing style that is based on reversion of the mean. If you are unfamiliar with standard deviation, head over to that informational section of the site and become familiar, as this will make more sense after. Simple regression will allow you to identify when an equity is far from the mean, standard deviation wise, giving you an idea of when the stock may revert back to the mean.

There are many different ways to come up with data points, and simple regression is another one of those. This type of tool would fall under both, quantitative and technical analysis. Simple regression looks to eliminate the human element and give you a statistical regression data point you help you identify trading situations.

Closer Look at Simple Regression

Some of the perks of using this particular data set is that it will eliminate the human element, giving you statistical data that is concrete and certain. Keeping emotion out of trading is one way to potentially give yourself an edge. Another perk is that this type of investing and trading will hopefully give you an edge in trend trading, allowing you to spot when the market is slightly over bought or over sold.

However, with any trading tool there are negatives to keep in mind. First, you have to understand that there will always be a human element to trading and investing, and by eliminating all of it, it could hurt your data outcomes. Find the happy medium and tweak it to what will fit your trading style best. Secondly, mean reversion does not always work, just with an trading style, so using a simple regression mind set could prove to be unprofitable.

With any trading idea, you should throw it on a demo account and find out if it is exactly what you are a looking for. Tweak time frames and other limitations to have it fit your current needs. If you get stuck, reach out to an investing community and they can certainly help you fine tune your charts. Once you feel comfortable, take it step further and integrate it with other tools to see if you can find a edge to increase your returns. Again, this is a great data set to use with mean reversion and is worth your time if you believe in that market philosophy.

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Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Positions Ratings module to determine portfolio positions ratings based on digital equity recommendations. Macroaxis instant position ratings are based on combination of fundamental analysis and risk-adjusted market performance.

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