does analyst target price on stocks hold any importance
Many brokerage houses provide research reports and in those reports, they provide the target prices. Many investors blindly follow these reports and invest based on them. So, in this blog, we will see if analyst target on stocks can help you pick winners. The purpose will be to backtest a strategy that picks stocks where there is a high potential upside to the median target price by analysts.
But before that, some definitions.
An analyst target price on a stock is an estimated value that analysts assign to a specific stock based on their assessment of its future performance. This target price (also called fair value) represents the price at which the analysts believe the stock should trade in the future, usually over the next 12 months.
Essentially, the target price is nothing but an analyst’s estimate of a stock’s fair value after 12 months. Target price is primarily determined by some valuation methodology (like DCF, P/E, P/B, etc).
On sharpely, we capture analyst target price through a metric called Upside to Target Price (%).
This is the percentage upside to the consensus target price from the current market price. If the consensus target price is below the current market price, this number will be negative. For example, if the CMP of Reliance is 2430 and the consensus target price is 2830, the upside will be 16.5%. We use the median target price as a proxy for consensus instead of the average.
Target price is an exciting measure because people love to see a quantification of the upside. It also creates an anchoring effect and provides a sense of comfort.
But is it helpful? Should an investor be swayed by a high upside and buy stocks where the analyst community is projecting a huge upside?
Let’s run our standard metric performance backtest on the Upside to Target Price (%).
Under the hood, here is what happens (more details on backtesting of metric can be found here):
1. We first select a universe - Nifty 500 in this case.
2. Stocks in the universe are sorted in ascending order and then portfolios are created based on percentiles. So, Quintile 1 will have stocks in 0 – 20 percentiles while Quintile 5 will have stocks in 80 – 100 percentiles. For each portfolio, stocks are assigned an equal weight in the portfolio.
3. Using our standard walk-forward framework, 5 such portfolios are constructed every quarter (based on quintile splitting) and portfolios are rebalanced to new stocks.
Note that in our case, Quintile 5 portfolio is the one that contains stocks with the highest upside to the target price. Quintile 1 portfolio, on the other hand, contains stocks with the lowest upside to the target price.
If the upside to target price was a useful metric for stock selection, we would expect Quintile 5 portfolio to outperform Quintile 1 portfolio.
Let’s see the result (it will surprise you!).
In the last 10 years, Quintile 5 portfolio has underperformed Quintile 1 portfolio by 143 bps. So as an investor, you were better off pricking stocks that had the lowest upside to the target price.
As a matter of fact, there is absolutely no pattern here and we can conclusively say that upside to target price is not a metric that should be used for stock selection decisions.
Note that this is in contrast to another analyst metric called Strong BUY Rating (%), which looked at the percentage of analysts with a buy rating on the stock. We found that this metric can be somewhat useful in picking stocks.
Why this dichotomy?
Our guess is that while analysts are generally successful in making a positive or negative opinion on the stock. But when it comes to putting a number to a stock’s fair value, they fail miserably.
This is expected. Sell-side analysts are a smart bunch of people with Ivy League MBAs. One could expect them to get the direction right (more than 50% of the time). But predicting a price is a different ball game altogether. In fact, historically, target prices have been so wrong that a lot of brokerages have stopped publishing target prices and just publish recommendations.
Note that different stocks have different numbers of analysts covering them and therefore using an aggregated upside measure has its own pitfalls. We have tried to circumvent this problem by including only those stocks that were covered by at least 5 analysts.