Efficient Market Hypothesis

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Theoretical framework

In this section I present the necessary aspects for abnormal profit to outsiders mimick-ing insiders. After that, a presentation of the Efficient Market Hypothesis (EMH) which claims that it is unlikely that outsiders will benefit from insiders will be described. Fi-nally the Behavioural Finance (BF) is introduced in order to try to explain the pattern found in previous research where EMH fails to explain.

Exploiting insider trading

According to Seyhun (2000) there are three factors to be considered in order for outsid-ers to be able to earn abnormal return from insider trading. The first assumption regards the reporting delay when insiders reporting their transactions. If for example it would take up to two months for an outsider to know that an insider has made a transaction, then that special information the insider traded on has already become public, leaving the information useless now. However, internet and the stricter governmental laws to-ward insider trading, has contributed so that most countries demand that insiders must report their transactions within 5 days. Knowing that the banks insider must hold their stocks for at least 30 days, the outsider know if the insider is trading on special knowl-edge then he or she will also be able to benefit from it.
The second assumption is that the abnormal profit must exceed transaction costs. Since an active investment strategy is more costly than a simple buy-and-hold strategy with the index portfolio, the awareness of transaction cost becomes even more important. This goes hand in hand with Copeland et al (2005) remarks about economic signifi-cance.
The last factor in order to be able to earn from insiders is that the risk to outsider must be minimized in order for them to see it beneficial. This is because Seyhun (2000) claims most people are risk averse, meaning that they are not only concerned with the ability to make profit, but also the probability to make losses. Seyhun continue saying that as long as the transactions are not cross-correlated with each other the portfolio re-mains diversified which minimizes the risk further.
In order for an outsider to have the opportunity of abnormal return, the outsider must be able to act before the rest of the market does. This could be difficult since the market re-ceive the news simultaneously. According to the Efficient Market Hypothesis this is in-deed very unlikely to occur.

Efficient Market Hypothesis

“If you find a $100 bill on the street walk, don’t pick it up. If it were real somebody would have picked it up already” – Unknown
The quote above is a common joke among economists in order to describe the Efficient Market Hypothesis (EMH). The theory behind the EMH comes from Fama (1970). To describe the theory in short it would be that prices fully reflect all available information. In his article he states that there are some conditions that should be fulfilled if the theory should hold. In a summary they are;
• There are no transaction costs
• All available information is available at no costs to all of the market participants
• All investors analyses the available information and make the same conclusions. Hence they are being rational.
Fama (1970) continues stating that even though these conditions are sufficient for the capital market efficiency, they are not necessary. As long as a satisfactory amount of in-vestors have access to available information and that there are not some investors who constantly make better evaluations of available information than others, the market effi-ciency holds. He later divides up the market condition into three groups;
• Weak form;
For the weak form (also called tests of return predictability) to hold, all past stock prices must be reflected into current stock price (Fama, 1991). This means that as an individ-ual you cannot analyse recent stock prices in order to predict future stock prices. The market should follow what is called a Random Walk. A Random Walk explain that the likelihood that the price tomorrow will go up, down or stay the same, have the same probability to occur (Fama, 1965).
The random walk theory claims that the usage of both technical analysis and fundamen-tal analyses of stock prices are inefficient. Technical analysis is based upon examine past returns in order to find trends or other abnormalities to be able to predict future stock prices. Fundamental analysis focuses more on today’s data (for example annual reports) in order to make future forecasts. In the weak form however the usage of fun-damental analysis could still be useful in order to predict future returns.
• Semi-strong form;
The semi-strong form (also called studies of announcements) states that all public avail-able information is reflected in the stock price (Fama, 1991). The assumption of this is that it is impossible to make abnormal returns by analysing publicly available data, for example annual reports. This means that the usage of fundamental analysis no longer is effective. Fama (1970) finds that much empirical results support the market conditions up to this level.
• Strong form;
The strong form represent a market were both public and non-public information are re-flected in the stock price. This proposes a scenario where not even insiders can trade on information which is not known to the public, and make excessive profit. Fama (1970) argues that even if this market state is most likely unreachable, there are so few who can take advantage of it, leaving the EMH still in a good description of the real world.
In conclusion for this study the weak form will not be tested since the purpose of this study does not concern it. The strong form seems to have little real life proof of existing and even Fama (1970) states that it is unlikely to hold. Even this state is not in direct concern of this study; the bank sector must however not be in this form, in order for outsider to be able to profit from insiders abnormal returns investments. The state that is interesting to examine is the semi-strong form, and according to EMH my result would look similar to Figure 3-1, if the market assumes that the insider contain special infor-mation. This leaves no possibility for abnormal return after the announcement of insider trading.
could state that the market researched simply does not meet the requirements for semi-strong form and conclude that the market is, at highest, in a weak form state. This how-ever does not explain what is happening when people earn abnormal return on public available information. In order to try to explain why that would be possible in the first place, the concept of Behavioural Finance (BF) is introduced.

Behavioural Finance

The definition of Behavioural Finance (BF) is “The study of the role played by psycho-logical factors in financial decision making and hence their effect on overall market outcomes” (Law, 2008). BF is according to Shleifer (2000) based upon two founda-tions, which are Limits to Arbitrage and Investor Sentiment. Limits to Arbitrage states that a lot of securities do not have good substitutes, which is very risky for the arbitra-geur, since the prices do not go back to the equilibrium state directly. This gives indica-tion that prices do not always shift in the right amount, leaving the market inefficient. Investor sentiment tries to explain how investors own biases and belief creating the demand for securities, which contradicts the assumptions of rational behaviour. Therefore BF is based upon the idea of irrational investors’ makes disturbances in the market which arbitrageurs cannot eliminate (Shleifer, 2000).

Limits to Arbitrage

According to the EMH theory, even if there are irrational investors in the market, there will always be so called arbitrageurs who exploit this irrationality and therefore brings back the price back to its fundamental value. In order for them to be able to do that, they must be able to short sell stocks. Short selling is illegal or at least regulated in many markets. In those markets where it is not, it can still be very hard to find any brokers who are willing to lend their stocks (Shleifer, 2000).
Shleifer and Vishny (1997) found that arbitrageurs do make the price return towards its fundamental value, when the mispricing is small. When the mispricing is larger the ef-fect is not as powerful. The reason being the higher the mispricing the higher the vola-tility of the arbitrage position will be. Even though the position would have attractive expected returns, the volatility would also bring greater risk of losses and the ability to liquidate the portfolio under pressure from the outside investors.
Ritter (2003) divides the opportunity of arbitrage into high frequency events and low frequency events. He claims that high frequency events are in line with the EMH be-cause it is hard to locate an investment strategy that is continuously profitable. The low frequency events do not support the EMH because if it did then for example the 1987 stock market crash or the 1999-2000 IT-bubble would not have occurred. For low fre-quency events the arbitrageurs gets wiped out, even though their assumptions of the long run are correct but they cannot afford to stay in their position until the market real-ises the mispricing.
When researching for opportunities in insider trading, the theory of limited arbitrage claims that this indeed would be possible, since the professionals fail to close the gap that may occur from market movements. However the most interestingly factor when regarding opportunity for abnormal return, is the possibility to do this if you understand peoples motives and be able to exploit this. This brings us to the concept of Investor Sentiment.

Investor Sentiment

The idea of people being rational has been questioned by many researchers. Ricciardi and Simon (2000) found evidence that there is a correlation between decision and irra-tionality, where the EMH claims that the irrational investors’ behaviour is random and that the effects will cancel them out. Ritter (2003) lists some patterns describing irra-tional behaviour;
• Heuristics
• Overconfidence
• Mental accounting
• Framing
• Representivness
• Conservatism
• Disposition effect
The points which are the most relevant to this study are the overconfidence, represen-tivness and conservatism factors14. According to Shefrin (2008) investors seem to be overconfident in their investing abilities and ignoring or at least underestimate the risk that is involved. The conservatism factor states according to Ritter (2003) that investors seem to adjust slowly to news announcements, especially when the news contradicts their own beliefs for the future. However if the same news keeps on coming for a long time then people will react to it, but they will probably by then overreact due to the rep-resentivness bias. This bias describes the pattern when investors ignore the long term averages and instead only analyse recent events. This is according to Shiller (2002) one of main the reasons why economic bubbles like the stock market crash in 1987 and the IT bubble bursting in 2000 were realised.
These points help the understanding of why there is a possibility to earn abnormal re-turn. This is because they explain the phenomena of over- and underreactions in the stock price of news announcements. In Figure 3-2 we can see that if people overreact to news, then it will take awhile before the price returns to its fundamental value. This is because arbitrageurs are unable to correct this directly. If an investor is able to foresee this, then he or she would be able to benefit from this before the stock price adjusts back to its fundamental value. This phenomenon could very well explain why recent studies have shown that earning abnormal return by mimicking insiders is possible.
In criticism towards BF, Fama (1998) argued that BF theories can only explain one spe-cific event at the time and are unable to explain the whole market. He therefore argues that BF is not a good replacement for EMH. Further he claims that the techniques in or-der to find anomalities are predetermined and when using other methods, the anomali-ties disappear. He therefore questions the results of BF research.
To summarize, Seyhun (2000) brings up three factors in order to be able to mimic insid-ers as an outsider. The EMH claims that this is not possible in the semi-strong form, and if it is possible then the market could be described as at most to be in weak form effi-ciency. The EMH fails to describe why some researchers found events that could dis-prove the semi-strong form. BF however claims that it is not likely for markets to be ef-ficient in the first place, indicating that opportunities for abnormal return do exist, due to Limits to Arbitrage and Investor Sentiment.

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Empirical Findings

In this chapter the results of the findings will be presented, together with the tests of significance. First the overall market movements on the event day will be tested. Later in the chapter the results of the findings on the days after the event of each of the banks will be accessible. There will also be a short statement whether or not the results are significant.
Before presenting the result I will present the different critical values15 each statistical test must be larger, in absolute values, in order for the results to be considered signifi-cant. For the buy transactions, all of the companies have more than 30 observations which lead them to have the same critical values. When it comes to sell transactions, three of the banks do not overcome 30 observations. This means that they have different critical values and will therefore first be compared towards the Wilcoxon test. The criti-cal values for the t-test are presented in Table 4-1.

Market movements

When observing the market adjustments on the event day for the bank sector, Table 4-2 shows that there in fact are no adjustments. This pattern seems to hold until 60 days has passed, when the negative CAAR result of 1,6% is 99% significant on both the t-test and the Wilcoxon test. Between the 60th day and the 120th day the market shows indica-tion to adjust back to its fundamental value. Interestingly, the result on the 60th day is negative, indicating that the market is acting opposite of what the insiders predicted. Further the Chi-square test shows strong indication that the distributions does not re-main normal when the number of observations exceeds 30, since the Chi square results are significant on all periods with 99% significance.
The market movements of insiders sell transactions are presented in Table 4-3. From the table we can conclude that there are no movements in the market at, or after, the an-nouncement. The result on the 60th day show however a weak significance (90%) on the Wilcoxon test. As the same as for the buy transactions, the Chi-square test tells us that also that the distribution for sell transactions tends to be non-normal. Since the signifi-cance in the Wilcoxon test is only 90% and not 95% significant, the result will not be viewed as significant.
In order to see if the results are the same as within each of the banks we move to the next section.

The event day in each bank

The first test in each bank was to observe how the market responded on the day of the announcement of insider trading. Over viewing the results from Table 4-4 there seems to be a very small difference from zero for the CAAR value, the result of 0,008 for SEB, being the highest observable. Notably the market seems to respond negatively when an insider makes a purchase within SHB and Swedbank. However when compar-ing all the t-tests to their critical value of 1.96, none of the results remain significant. This results in a non-rejection of the null hypothesis. Therefore based on the t-test the market does not seem to adjust to the new information.
When observing the chi-square test, we note that the Swedbank data tends to move to-wards a non-normal distribution, however the Wilcoxon Z-test is not significant differ-ent from zero. The SEBs distribution is also non-normal on a 90% significant, but the Wilcoxon test also turns out to be non significant. One of the Wilcoxon test is however significant, which is Nordea’s result. The result is undermined by the fact that the chi-square test is not significant, indicating a normal distribution hence the t-test should be used. Therefore the CAAR of the Nordea stock will be viewed as insignificant.
Still keeping focus on the event day, but instead observing the result of the sell transac-tion (Table 4-5), we tend to see that the results are similar to the buy transactions.
Since the numbers of observations are very few we know that we should emphasize the non-parametric result. This is the case for each bank with the exception of SEB which have n>30. Notably the changes in CAAR are larger in sell transactions than for the buy transactions, but nevertheless the results fail to be significant in both the t-test and the Wilcoxon test.
So there seems that the market do not adjust the prices when the news is announced, in order to see if the market is reacting correctly or not, the CAAR from the days after the event must be tested.

CAAR 30 days after

For the buy transactions in Table 4-6 there are some of the CAAR results that are in-deed significant. The Nordea CAAR of 0,79% is significant on the 95% level with the Wilcoxon test. However the t-test is not significant resulting in contradictory conclusion of the two tests. The chi-square gives an argument for the Wilcoxon test being more re-liable, even though it is only showing the distribution not being normal with a 90% sig-nificance, the result will be regarded as significant. The CAAR result for Swedbank is at least significant on the 95% level on both the t-test and the Wilcoxon test (99% on the t-test). Interestingly the CAAR of Swedbank is negative, which again gives indication that the market acts opposite of the insiders’ forecasts.
Two of the banks showed significant result for buy transactions, resulting in that the market did not act correct on the event day. Whether there is the same result for sell transactions after 30 days we take a look at Table 4-7.
From the table there is one of the results that are significant. It is the result of the Swed-bank CAAR showing a positive reaction of 2,78%, with a t-test showing a significance of 99%. Again one must be very careful in interpreting the t-test, since the number of observation with sell transaction in Swedbank were only nine. Observing that the Wil-coxon tests value being only 0,296 there seems to be doubt about the assumption that the result should be absolute and not have appeared by chance. Since the Wilcoxon test is so low the Swedbank CAAR will be regarded as insignificant.

Table of Contents
1 Introduction
1.1 Background
1.2 Insider Trading Law
1.3 Earlier studies
1.4 Problem discussion
1.5 Purpose
1.6 Method
2 Methodology
2.1 Method approach
2.2 Research approach
2.3 Event study
2.4 Abnormal return
2.5 Cumulative Average Abnormal Return
2.6 Hypotheses
2.7 T-test
2.8 Wilcoxon signed rank test
2.9 Chi-square test for normal distribution
2.10 Validity
3 Theoretical framework
3.1 Exploiting insider trading
3.2 Efficient Market Hypothesis
3.3 Behavioural Finance
4 Empirical Findings
4.1 Market movements
4.2 The event day in each bank
4.3 CAAR 30 days after
4.4 CAAR 60 days after
4.5 CAAR 120 days after
4.6 Event studies overview
4.7 Economic significance
5 Analysis
5.1 Explaining the scenario
5.2 Economic significance
6 Conclusion
6.1 Further research
List of References

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