Investtech Research: Stocks with the most upside fail to deliver – signal statistics Nordic markets 2008-2020

Published 16 August 2021

Basis and objectives

Our previous research with data from 1996 to 2018 showed that volatility matters for return from stocks in rising and falling trend channels, and for stocks with strong positive or negative RSI momentum. In particular, stocks with a combination of sell signals from falling trend or low RSI and high volatility saw much greater negative excess return than other stocks. Our article on "lottery stocks" is available in Norwegian here. Experience from 16 years of Investtech’s Stay Away Portfolio for the Norwegian market shows the same thing, i.e. that stocks with a combination of sell signal and high volatility have significantly underperformed.

We have summarized the data and research conducted in winter and spring of 2021, where we studied data from all listed stocks in Norway, Sweden, Denmark and Finland for the period 2008-2020. We studied the signal types Trend, Support and Resistance, Price Patterns, Volume Balance, Momentum and Insider Trades. Some of this research has not yet been translated into English, but is available in the Scandinavian languages, se links in the literature list below.

We chose to study the most important and largest sub-types of signals from each of the above categories, i.e. within rising/falling trend, break upwards through resistance/downwards through support, rectangle formations and head and shoulder type formations, high/low volume balance, high/low RSI momentum and insider buy/sell, respectively.

These gave a total of 254,409 signals, of which 150,311 buy signals and 104,098 sell signals. We studied the 20 and 10 per cent most volatile stocks separately. The group of the 20 per cent most volatile stocks gave 23,195 buy signals and 14,769 sell signals. The group of the 10 per cent most volatile gave 10,721 buy signals and 6,375 sell signals.

We wanted to look for any systematic deviation from the average for the groups of the most volatile stocks.

According to classical financial theory, highly volatile stocks should give statistical excess return due to investors in such high risk stocks having higher requirements for risk premiums.

Example buy signal: Within rising trend channel

The charts below show average price development following buy signal from stocks being within a rising trend channel. The signals are triggered on day 0. Only days when the exchange is open are included, so 66 days equal approximately three months. The thick blue line shows the development of buy signal stocks. The shaded areas are the standard deviation of the calculations. The thin blue line shows benchmark development in the same period as the buy signal stocks.

Three charts are shown; one for all volatility classes, one for the 20 per cent most volatile and one for the 10 per cent most volatile, respectively. Click the images for bigger version.

Figure 1a: All volatility classes.

Figure 1b: The 20 % most volatile.

Figure 1c: The 10 % most volatile.

Relative return after 66 days Norway Sweden Denmark Finland Weighted average
Excess return buy signal, all samples 1.6 %p 1.7 %p 1.1 %p 1.5 %p 1.6 %p
Excess return buy signal, 20 % most volatile -1.8 %p 0.7 %p 4.2 %p 1.3 %p 0.9 %p
Excess return buy signal, 10 % most volatile -9.6 %p -1.6 %p 3.1 %p -1.3 %p -2.2 %p

%p = percentage point

Example sell signal: Within falling trend channel

Figure 2a: All volatility classes.

Figure 2b: The 20 % most volatile.

Figure 2c: The 10 % most volatile.

Relative return after 66 days Norway Sweden Denmark Finland Weighted average
Excess return sell signal, all samples -3.7 %p -0.9 %p -1.6 %p 0.5 %p -1.5 %p
Excess return sell signal, 20 % most volatile -8.7 %p -5.2 %p -4.1 %p -0.3 %p -5.3 %p
Excess return sell signal, 10 % most volatile -12.3 %p -7.6 %p -9.2 %p 0.2 %p -7.7 %p

Results and recommendations

The examples above show results for rising and falling trends, which make up about a fourth of the total data. The 20 % most volatile group has underperformed compared to the average, especially in the case of sell signals. The 10 % most volatile group shows clear negative excess return both for buy signals and sell signals.

We converted into annualized figures and calculated a weighted average for all signals – and found that buy signals on average have given an annualized excess return of 4.6 percentage points vs benchmark, while buy signals in the 20 % group and the 10 % group have given an annualized excess return of -1.9 and -8.8, respectively.

These are clear indications that highly volatile stocks with buy signals are underperforming. The sell signal results are even more pronounced:

Sell signals have given an average annualized excess return of -4.1 vs benchmark, while sell signals in the 10 and 20 % groups have given an annualized excess return of -26,5 and -19,2 respectively. These are high figures! Historically this is a group of stocks that would have been better left by the wayside.

These results show that the market has completely contradicted classical financial theory. How can we explain this?

*The stock market is not a theoretical market. It is influenced by people, and to some degree by machines programmed by people, and people are not always rational. It is impossible for people, and also for machines, to have access to all information, and difficult to see consequences of available information.

*There are always also non-professional and inexperienced investors. They tend to not be so aware of the theory and how stocks should develop in the economic-logical sense, and are more influenced by news, stock forum chatter and in general by fear and greed. There is a larger share of non-professional investors in many of the smaller, recently listed high risk stocks than in average on the stock exchange.

*Many investors want to achieve extraordinarily high return, in a short time. In order to achieve this, they have to buy stocks with high upside potential. They forget or underestimate the risk and disregard the fall potential. This distortion in human assessment of upside and risk can cause short term wrongful pricing, with stock prices too high. When the realities become known, the companies’ problems remain unsolved and research results remain absent, prices will fall.

*Many inexperienced investors likely do not quite understand market mechanisms. For instance, it is common to think that a stock which has fallen, is cheaper than it used to be, even though the falling stock price often correlates with negative company news. Thus, stocks that have fallen, can be kept artificially afloat for a while, before falling further.

*There is also the idea of the stock exchange as a casino. As an alternative to lotteries, sports betting or casino gaming, some choose to invest on the stock exchange. For them, 10 or 20 per cent return can be boring, if they are in fact looking to make double, triple or more. Stocks that have been many times higher than their current price in the past, may easily look like potential candidates. This will again cause these stock prices to be kept artificially afloat for a while.

We studied a large data set covering 13 years in the four Nordic markets. The results have high statistical significance. We believe the data set is representative of market behaviour in the time period, and that the period is representative of general investor behaviour and human behaviour in the stock markets. There is never any guarantee that historical results will be valid in the future, but we have no reason to think that market mechanisms will notably change.

The results indicate that excess return can be achieved by consistently avoiding the 20 per cent most volatile stocks, including excess return compared to highly volatile stocks with similar buy signals. In particular, the group of extremely volatile stocks with sell signals should be avoided, as these have statistically underperformed vs the market by 25 percentage points.

Literature

 

Keywords: Buy signal,Helsingfors,Kjøpssignal,København,Momentum,Oslo,Salgssignal,Sell signal,statistics,statistikk,Stockholm.

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.

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