Return following signals from medium long term double bottom/top formations on the Oslo Stock Exchange 1996 - 2014

Research results from Investtech, 13 February 2017
Published in English on 24 March 2017. Norwegian original here >>

About the author
Geir Linløkken is the Head of Analysis and Research at Investtech, and is responsible for portfolios and money management. He founded Investtech in 1997, to provide independent technical analyses based on science and investor psychology. Mr. Linløkken has an MSc. in Computer Science, specializing in Mathematical Modeling, at the University of Oslo. He is the author of the book “Technical Stock Analysis”. His daily work includes analysing stocks and developing quantitative methods for stock market investments.

Keywords: double top formation, double bottom formation, buy signal, sell signal, Oslo stock exchange, technical analysis, statistics

Abstract:

Geometric price patterns, like double bottom and double top formations, are used in technical analysis to predict future price development. Many investors use this as an important part of their decision making process when buying or selling stocks. We have studied at the price movements that followed signals from these formations on the Oslo Stock Exchange in a period of 19 years, from 1996 to 2014. The statistics indicate that the formations have low predictive power in the medium long term.

Research into technical price formations

This research report is part of a bigger research project conducted by Investtech into price development following technical formations in stock prices. This report is on medium long term double bottom and double top formations on the Oslo Stock Exchange in Norway.

Short term Medium term Long term
Rectangle Report Report Report
Inverse/ head and shoulders Report Report Report
Double top, double bottom Report Present Report

Double bottom and double top formations

Identification of geometric price patterns in stock prices is an important area of technical analysis. The idea is that these patterns describe the investors’ mental state, i.e. whether they will want to sell or buy stocks in the time ahead, and they thereby indicate the future direction of the stock price. Double top and double bottom formations are two kinds of such patterns.

A double top formation is a top formation which marks the end of a rising period. The formation consists of two tops of approximately the same width and height, see figure 1. The formation of a double top mirrors increasing pessimism among investors and signals the beginning of a falling trend. Double top formations are especially useful in predicting long term market trend reversals, but are also used in the shorter term.

There is an opposite version of this formation; the double bottom formation, see figure 2. This is a bottom formation which marks the end of a falling period. A double bottom formation signals increasing optimism among investors and the start of a rising trend.

Double top formation - sell

Figure 1: Sell signal from double top formation.

Double bottom formation - buy

Figure 2: Buy signal from double bottom formation.

In technical analysis terminology, a break down from a double top formation triggers a sell signal. Similarly a break upwards from a double bottom formation triggers a buy signal. We have studied the price movements following buy and sell signals from such formations on the Oslo Stock Exchange in Norway.

Identification

It is no easy task to identify double top formations in stock prices. The illustrations above show that the price forms two even tops of approximately the same size, before it breaks downwards and triggers a signal. However, stock prices are rarely as regular as these illustrations. The price will often be quite uneven and the tops will be of differing width or height.

Many investors identify price patterns by looking at price charts and drawing lines by hand. This method has many weaknesses, most of all that it is subjective, allowing you to see the formations you want to see, and it is very time consuming. Therefore we need an automatic algorithm whereby computers identify the formations and the signals they trigger.

Investtech has studied technical and quantitative analysis since 1997. We have developed mathematical algorithms for automatic identification of double top and double bottom formations in stock prices. The formations are entered into the technical analysis charts, shows in signal lists and presented updated daily to Investtech’s subscribers.

In this report we have looked at the price movements that follow buy and sell signals from double bottom and double top formations on the Oslo Stock Exchange. The statistics are based on formations automatically recognized by Investtech’s computer programs. No parameter optimization or changes to algorithms have been made during this study. This is an analysis based on the existing historical material.

The Base Data

We have used stock prices from 1 January 1996 to 10 October 2014 as the basis for the statistics. In this period, the main index on the Oslo Exchange rose from 106.9 to 573.6 points, which is 437 % or approximately 9.3 % a year. Compared to the risk free interest rate in this period, this is approximately what can be expected for similar periods of time.

In eight of these 19 years, the exchange rose by over 30 %, while it fell by more than 10 % in five of the years, and varied between minus 10 % to plus 30 % in five of the years. We have had both good and bad periods, and several sideways periods as well, and consider this representative for a normal period of time on the exchange.

All stocks that have been listed in the period are included. Stocks that have been delisted due to for instance mergers, takeovers and bankruptcy are included. However, we only have data for these companies for as long as they were listed. A company which went bankrupt will then have a final trading price which is not zero, which is a weakness in this study. However, this is only the case for a small number of companies. Most companies also fall a lot before they are delisted, so the difference between the price fall from when they were listed and a price fall down to zero will be small.
It is also very rare that new buy signals are generated from double bottom formations when a company’s stock price is falling. Therefore it matters very little to the statistics for buy signals. Return from sell signals would however have been a little weaker had we corrected for bankruptcies. Combined it is our opinion that these conditions have minimal impact on the results of this study.

All prices are adjusted for splits, dividend payments, reverse splits, and other corporate capital changes, in order to reflect the actual value development of the stocks.

715 time series are included, of which 597 are stocks with at least 66 days of trading. At the end of the period, approximately 220 stocks were listed on the exchange.

The stock’s daily closing price is used. We have only used prices and turnover figures from the stock’s primary market place. Alternative markets like Chi-X, Bats and Burgundy are excluded.

The Data Set

We have used Investtech’s algorithms for automatic identification of price formations. The algorithms were run on medium term charts made up of 395 price days, approximately 18 calendar months. We consider the algorithms good at identifying actual double top and double bottom formations, and they do not classify indistinct patterns as actual formations.

At identification of signals, only data up to the date the signal was triggered were used. The later data were hidden from the algorithm.

All signals identified from double top and double bottom formations are used. Normally each formation only triggers one signal. However, in rare cases they may trigger several signals. This happens if the price following the break reacts back into the formation, creates a modified formation and then breaks out again.
Sometimes one stock can also trigger several signals on the same day. This happens if the algorithms have recognized several formations of different length and height which are broken out from at the same time.

In order to have the data set as representative for the Oslo Stock Exchange as possible, we remove certain signals from the data set:

  • Duplicate signals are removed. This will be the case when there have been mergers and ticker changes, where Investtech has two editions of the same historical time series. For instance, we remove a buy signal from DNB if we already have it for DNBNOR.
  • Signals that are very close in time to a previous signal are removed. It is a requirement that there have been at least seven calendar days since the previous signal from the same stock in order for a new signal to be counted.
  • Formations that are less than 2 % in height are discarded. These are small and considered to have low signal value.
  • Signals from stocks with poor liquidity are discarded. This is because it is difficult for investors to make actual trades in such stocks, and also because the price is often uneven and with big leaps, making pricing uncertain and subject to noise.
    We discard signals where daily average turnover on the Oslo Exchange in the past ten days including the signal day was lower than half a million Norwegian krone (NOK) or where the stock was traded on less than half the days. This also removed all signals from the exchange indices, leaving us with signals from stocks and equity certificates only, and a few traded funds. The actual turnover of stocks that gave signals may have been above this limit, as trade in other markets than the Oslo Exchange, like Chi-X, Bats and Burgundy, are not included.
  • Signals with less than 66 days' price history following the signals are removed. This gives complete price history for the first 66 days following the signals.

Our data set now consists of 653 identified buy signals from medium long term double bottom formations and 744 sell signals from medium long term double top formations in stocks and equity certificates on the Oslo Stock Exchange in the period 1996 to 2014.

Results


Figure 3: Price development after buy and sell signals from double bottom and double top formations on the Oslo Stock Exchange identified by Investtech’s automatic algorithms in medium long term price charts. Click the image for bigger version.

The chart shows average price development following buy and sell signals from double top and double bottom formations. The signals are triggered on day 0. Only days when the exchange is open are included, so 66 days equal approximately three months. Buy signals are the blue line and sell signals are the red one. The shaded areas are the standard deviation of the calculations. Benchmark index is the black line.

Buy signal Day 1 10 22 66
Absolute 0.43 % 0.69 % 1.23 % 4.78 %
Benchmark 0.05 % 0.48 % 1.06 % 3.31 %
Relative, percentage points 0.39 0.21 0.16 1.47
Statistical T-value 2.08 0.46 0.23 1.11
Sell signals Day 1 10 22 66
Absolute 0.46 % 1.07 % 1.51 % 4.00 %
Benchmark 0.05 % 0.48 % 1.06 % 3.31 %
Relative, percentage points 0.42 0.60 1.45 0.69
Statistical T-value 3.52 1.96 0.98 0.78

We have studied the statistical price development following buy signals from double bottom formations and sell signals from double top formations identified in Investtech's medium long term technical charts.

Figure 3 shows that both buy and sell signals have been followed by price development in line with average benchmark development. There are some differences, but the buy and sell signals differ in the same direction and based on statistical t-values they are not statistically significant.

The importance of liquidity

In the calculations above we have included signals from stocks with an average daily turnover of at least half a million Norwegian krone on the Oslo Stock Exchange at the time the signal was triggered. Varying the liquidity parameters allows us to investigate if there is a difference in signal strength for smaller and bigger companies.

Drawing the line at five million krone splits the companies into two roughly similar groups. Signals from stocks with turnover below five million come to 727 signals, and those with turnover above five million come to 670 signals.

Figure 4: Signals from companies with daily turnover between one half and five million krone.

Figure 5: Signals from companies with daily turnover above five million krone.

Figures 4 and 5 show non-significant predictive power for double top and double bottom formations for both sub-groups of less and more liquid companies.

The Stockhom Stock Exchange in Sweden

Figure 9. Price development following medium long term buy and sell signals from double bottom and double top formations on the Stockholm Stock Exchange.

We have conducted the same study on the Stockholm Stock Exchange in Sweden, for the period 1 April 2003 to 10 October 2014. Investtech’s computers identified 876 buy signals and 1215 sell signals in this period.

The Stockholm results show no significant difference between price development after signals from double top/bottom formations and average benchmark development.

This strengthens the indication that double top and double bottom formations have low predictive power in the medium long term.

Read more about the Stockholm Stock Exchange study here.

Summary

We have studied return from stocks on the Oslo Stock Exchange with breaks through double top and double bottom formations in Investtech's medium long term technical charts over a period of 19 years, from 1996 to 2014. Investtech’s automatic algorithms identified a total of 653 buy signals and 744 sell signals from such formations.

The buy signals gave an average return of 4.8 per cent in the following three months, and the sell signals gave a return of 4.0 per cent. Relative to average benchmark development in a three-month period, the buy signals gave an excess return of 1.5 percentage points and the sell signals an excess return of 0.7 percentage points.

The study covers a relatively long time period, the quality of the base data is high and the algorithms used are entirely automatic and only identify genuine formations.

However, the return from the signals is not significantly different from average benchmark development. Neither did we find statistically significant price development following such signals on the Stockholm Stock Exchange in Sweden. Thus the results indicate that signals from medium long term double top and double bottom formations have low predictive power.

Previous studies indicate that double top and double bottom formations have good predictive power in the longer term. The results above indicate that such formations are better suited for long term charts than shorter term ones. A possible explanation may be that the formations are relatively small and can be easily triggered by a day or two of especially noisy price development in medium long term and short term charts.

Even with 11 years of data from the Stockholm Stock Exchange and 19 years from Oslo, we do not have a large data set. The results have low significance. Consequently we cannot decisively conclude that double top and double bottom formations do not have any predictive power in medium long term charts, and we would like to conduct more studies on data from several Stock Exchanges and for longer periods of time.

For now, we assume that it is statistically risky to follow signals from double top and double bottom formations in medium long term charts. These results imply that in the presence of such formations it will be useful to look at other indicators as well, for example volume balance, momentum and trend, which have all shown more significant results.

Litteratur

  • Investtech, Insight & Skills. Price formations. Link
  • Investtech, Insight & Skills. Buy signal from double bottom formation. Link
  • Investtech, Insight & Skills. Sell signal from double top formation. Link
  • Geir Linløkken. Return following signals from double bottom and double top formations - the Stockholm Stock Exchange 2003-2014 . Investtech.com, 2014. Link (in Swedish)
  • Geir Linløkken. Return following signals from rectangle formations - the Oslo Stock Exchange 1996-2014. Investtech.com, 2014. Link
  • Geir Linløkken. Return following signals from rectangle formations - the Stockholm Stock Exchange 2003-2014. Investtech.com, 2014. Link
  • Geir Linløkken. Return following signals from head and shoulders formations - the Oslo Stock Exchange 1996-2014. Investtech.com, 2014. Link
  • Geir Linløkken. Return following signals from head and shoulders formations - the Stockholm Stock Exchange 2003-2014. Investtech.com, 2014. Link (in Swedish)
  • Geir Linløkken og Steffen Frölich. Technical Stock Analysis - for reduced risk and increased returns. Investtech.com, 2001.
  • John J. Murphy. Technical Analysis of the Financial Markets. New York Institute of Finance, 1999.

 

Kirjoittaja

Geir Linløkken
Perustaja ja tutkimustyön johtaja
Investtech

"Investtech analysoi markkinoiden psykologiaa ja antaa konkreettisia kaupankäyntisuosituksia päivittäin."

Espen Grønstad
Partner & Senior Advisor - Investtech
 


Investtech ei takaa analyysien tarkkuutta tai kattavuutta. Kaikkien analyysien tuottamien neuvojen ja signaalien käyttäminen on täysin käyttäjän vastuulla. Investtech ei vastaa mistään tappioista, jotka saattavat syntyä Investtechin analyysien käytön seurauksena. Mahdollisten eturistiriitojen yksityiskohdat mainitaan aina sijoitusneuvon yhteydessä. Lisätietoja Investtechin analyyseistä löytyy täältä disclaimer.


Investtech ei takaa analyysien tarkkuutta tai kattavuutta. Kaikkien analyysien tuottamien neuvojen ja signaalien käyttäminen on täysin käyttäjän vastuulla. Investtech ei vastaa mistään tappioista, jotka saattavat syntyä Investtechin analyysien käytön seurauksena. Mahdollisten eturistiriitojen yksityiskohdat mainitaan aina sijoitusneuvon yhteydessä. Lisätietoja Investtechin analyyseistä löytyy täältä disclaimer.

Titlex

OK
+

Informasjonskapsler

Vi benytter informasjonskapsler (cookies) for å gi deg en bedre brukeropplevelse. Hvis du fortsetter å bruke nettstedet, aksepterer du dette. Du kan lese mer om vår bruk av informasjonskapsler her.

Investtechs bruk av informasjonskapsler

Når du bruker nettstedet vårt, lagrer vi en informasjonskapsler på enheten din. En slik informasjonskapsel brukes til å gjenkjenne enheten din slik at innstillingene dine fungerer når du bruker nettsidene våre. Informasjonen som lagres er fullstendig anonymisert. Informasjonskapslene slettes automatisk etter en viss tid.

Nødvendige informasjonskapsler

Investtech bruker informasjonskapsler for å sikre grunnleggende funksjoner som sidenavigasjon og språkvalg. Uten slike informasjonskapsler fungerer ikke nettstedet som det skal. Du kan derfor ikke reservere deg mot disse. Hvis du fortsatt ønsker å deaktivere slike informasjonskapsler, kan du gjøre det i din nettlesers innstillinger. Legg til denne nettsiden i listen over nettsteder som ikke har tillatelse til å lagre informasjonskapsler på enheten din.

Informasjonskapsler fra Google

Vi bruker tjenester fra Google Analytics og Google AdWords. Disse registrerer informasjonskapsler på enheten din når du besøker nettstedet vårt. Google registrerer din IP-adresse for å føre statistikk over brukeraktivitet på nettstedet. IP-adressen er anonymisert, slik at vi ikke har noen mulighet til å knytte aktivitetene til en bestemt person. Vi bruker denne statistikken for å hele tiden kunne forbedre oss. Google AdWords samler inn data slik at vår annonsering på andre nettsteder gir bedre resultater. Vi kan ikke spore data til enkeltpersoner.

Tillat informasjonskapsler fra Google