The 52-week high as a signal

The 52W high column shows how close a price is to its highest level of the last 52 weeks. A plain number — and, according to the research, one of the most informative in this list.

That stocks near their 52-week high tend to keep rising sounds like market folklore. Thomas J. George and Chuan-Yang Hwang tested it in 2004: nearness to the 52-week high predicts future returns better than the past price change on which classic momentum is based.

This page explains the finding, the explanation for it, how the column is calculated here, and why the measure is once again a price ratio, like Levy's RSL. Where the finding sits in the history of momentum research is shown in Evolving the RSL Strategy.

52 weeks the highest price of a year as the reference point for the current price Thomas J. George 2004, Abstract
dominates nearness to the high predicts returns better than the past return of a stock and of its industry Thomas J. George 2004, Abstract
no reversal the returns predicted this way do not reverse in the long run Thomas J. George 2004, Abstract

The finding: nearness to the high beats the price change

What tells you most is not how far a price has risen — but how close it stands to its high.

George and Hwang put three measures in a direct comparison: classic momentum following Jegadeesh and Titman, which measures the past return; industry momentum following Moskowitz and Grinblatt, which asks the same question for whole industries; and the nearness of the price to its 52-week high. The third measure wins:

Nearness to the 52-week high dominates and improves upon the forecasting power of past returns (both individual and industry returns) for future returns.

Thomas J. George 2004, Abstract

“Dominates and improves upon”: in a direct comparison, nearness to the high is the stronger measure, and it improves the forecast over the past return — both over that of the individual stock and over that of its industry.

The second part of the finding concerns what happens afterwards, and it matters at least as much for the interpretation:

Future returns forecast using the 52-week high do not reverse in the long run.

Thomas J. George 2004, Abstract

The authors conclude that the short-term continuation of prices and their long-term reversal are largely separate phenomena — and not two phases of the same movement, as many models had described them until then.

Source: Thomas J. George 2004, Abstract, Narasimhan Jegadeesh 1993, Tobias J. Moskowitz 1999

The explanation: the high as an anchor

Investors hesitate to bid a price beyond a well-known high — even when the news would justify it.

The 52-week high is a number everyone knows. It appears in every price overview and on every brokerage statement. George and Hwang explain their finding by investors taking this number as a reference point, an anchor against which they measure new information.

When good news arrives while the price is already close to the high, they hesitate to push it beyond that mark. The price therefore absorbs the news only partly at first. The rest follows later, as the information prevails — and it is this later rise that nearness to the high predicts. The same applies in the opposite direction to bad news for prices far below the high.

This also explains why the returns do not reverse. If the price is merely catching up on delayed news, there is nothing to give back afterwards. An overreaction would correct itself; a delayed adjustment does not.

Source: Thomas J. George 2004, Introduction

How the column is calculated here

Today's closing price divided by the highest closing price of the last 260 trading days.

52 weeks of five trading days each give a window of 260 trading days. Today is part of it. The “annual high” here is therefore not the high of the calendar year but a rolling one: the window moves on by one day after every trading day, and an old high drops out as soon as it is more than 260 trading days old. Because public holidays are not trading days, the window usually reaches back a little further than 52 calendar weeks. If a stock does not yet have 260 trading days of price history, the field stays empty.

The calculation uses daily closing prices, not weekly ones: a window of Friday prices would miss a high that fell on a Tuesday. Highs reached only during a trading day are, on the other hand, unknown to the list; it only has closing prices.

What 1.00 and 0.80 mean

The value lies between 0 and 1, because no price in the window can be higher than its peak.

  • 1.00 means: today's closing price is itself the high of the window. The stock stands at its 52-week high or has just reached a new one.
  • 0.80 means: the price is 20% below its high.

A value above 1 cannot occur. The smaller the value, the further the stock is from its high.

A worked example to check

Two made-up prices are enough: the high and today's price.

Point in timePrice
highest closing price of the last 260 trading days125.00
today100.00

52W high = 100.00 ÷ 125.00 = 0.80. The price is −20.00% below its high.

A trap when reading it: the way back to the high is not 20% but more. From 100.00 to 125.00 it takes +25.00%, because the rise is measured from the lower price.

What the price did between the high and today does not matter. Whether it has moved sideways for months or dropped yesterday: the column shows the same. And whether the finding holds for a particular stock is not something the number tells you. The research results apply to broadly diversified portfolios over many years.

A price ratio again — like Levy's RSL

Both measures divide the current price by a reference point from the stock's own price history. They differ only in which one.

Levy had chosen exactly this form in 1967: price divided by a moving average. Later research largely took a different route and measured momentum as a return, as the price change between two points in time — like the Mom 12−2 column. George and Hwang's finding leads back to the form Levy started with: the strongest single measure in their comparison is once again a price ratio. Only the reference point is not the average but the high.

RSL following Levy52W high
Numerator current price current price
Denominator average of the current price and the 26 weekly closing prices before it highest closing price of the last 260 trading days
Period 26 weeks, about half a year 52 weeks, about a year
Range above 1 when the price is above its average at most 1

Source: Robert A. Levy 1967, Section II (“Price Ratios”), Thomas J. George 2004, Abstract

The difference in the denominator has consequences. An average follows the price with a delay: if a stock moves sideways for a long time, the average catches up and the RSL approaches 1. A high, by contrast, stays put until it drops out of the window. A stock that fell sharply half a year ago and has not recovered since can therefore have an RSL close to 1 — and still stand far below its 52-week high.

Conversely, a stock can stand at a new high, that is at 1.00, and still have only a moderate RSL if it has risen slowly and steadily. Both columns then show an upward trend, but with a different emphasis: the RSL the pace relative to the average, the 52W high the distance to the peak.

The list remains ranked by the RSL so that it stays comparable with other RSL lists, and shows the 52W high alongside because it was the strongest measure in George and Hwang's comparison. Where the RSL comes from is covered in RSL: Method & Origins.

Not investment advice and not a recommendation. Past performance is not a reliable indicator of future results, and investing in securities involves the risk of losing your entire investment.

Disclaimer and risk information in detail

References

Every figure on this page is shown with its exact location in the source — section, table or page. The links lead to the paper via its DOI; the full texts are mostly behind publishers' paywalls, but the bibliographic details are enough for any library.

  • Robert A. Levy (1967): Relative Strength as a Criterion for Investment Selection. The Journal of Finance 22(4), pp. 595–610. doi:10.1111/j.1540-6261.1967.tb00295.x
  • Narasimhan Jegadeesh, Sheridan Titman (1993): Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance 48(1), pp. 65–91. doi:10.1111/j.1540-6261.1993.tb04702.x
  • Tobias J. Moskowitz, Mark Grinblatt (1999): Do Industries Explain Momentum?. The Journal of Finance 54(4), pp. 1249–1290. doi:10.1111/0022-1082.00146
  • Thomas J. George, Chuan-Yang Hwang (2004): The 52-Week High and Momentum Investing. The Journal of Finance 59(5), pp. 2145–2176. doi:10.1111/j.1540-6261.2004.00695.x