I saw an interaction on social media today that prompted me to write about the terms “Overbought” and “Oversold”, words that while used very frequently by financial bloggers and traders in discussions of the bullish or bearish qualities of the equity market and individual stocks, can have very different meanings and uses from one investor to the next. I’m going to focus on the term Oversold so please keep in mind that the meanings for the term Overbought are the same, just opposite.
In a general way, when someone says that XYZ stock is oversold they either mean A: the price of the stock is well below the true value of the company based on fundamental valuation metrics such as price/earnings, price/growth, etc or B: a drop in the price has pushed some technical indicator to an extreme and unsustainable level. For all intents and purposes, particularly outside a value investing setting, it will be definition B that you’ll be hearing. But that still leaves a lot of room for interpretation and application so let’s look at a couple of examples, including how I define and use it as an indicator in my own portfolio management process.
Firstly, and very important to remember when hearing traders or investors mention a stock being “oversold” is that many of them are not referring to a specific and trackable statistical condition but are relying visually on an oscillator like the Relative Strength Index or a Moving Average Convergence Divergence reading that appears “stretched” and now must snap back. I consider these to add fine anecdotal evidence on the surface, and could actually be tracked effectively in tabular form but the fact is that’s not how most traders use them. Here’s an example using Google. I’ve circled the extreme position of both RSI and MACD.
Another method, and the one that I employ, is to use past volatility to calculate a statistical bell curve for the asset in question, plotting where in the curve the stock is currently priced and express it as a percentage of the mid-point of the curve ie: 10% overbought, 35% oversold etc on a curve like this.
The concept behind this approach is that 3 standard deviations from the mean, (normal) is considered 100% overbought or oversold. This does NOT mean the stock will magically snap back to normal or that it’s somehow fundamentally cheap. In fact stocks can and do go much further than 100% overbought or sold, in reality the tails on a bell curve go to infinity so that’s a reason I would only use this as a secondary indicator after trend and pattern to help guide buy/sell decisions. Also, a stock can go from oversold to normal without even changing price, but through time as the back data refreshes to create a new normal.
Going back to our Google example, here’s data in tabular form showing overbought, normal and oversold levels by week and as a percentage of normal based on that weeks closing price.
By using this information I believe you can add another strong data point to the weight of evidence guiding your investment decision making. Remember, when someone says that a stock is overbought or oversold, be aware of how they’re using the term and what that can mean for a buy sell or hold decision you may be considering.