Insider Trading and Market Efficiency: 
Evidence from the Swedish Stock Market  
  
  
Authors:   
Adam Astudillo  
Endi Mulic 
 
Supervisor: 
Sadia Awan 
 
 
  
 
 
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Abstract: 
This thesis investigates whether insider trading announcements influence stock prices in the 
Swedish stock market and examines the market’s efficiency in processing such information. 
Or more specifically, challenges the semi-strong form of market efficiency. A sample of 30 
insider transactions are analyzed, divided equally into 15 buy-side and sell-side events. Using 
an event study methodology, average abnormal return (AAR) and cumulative average 
abnormal return (CAAR) are computed to measure market reactions surrounding the 
announcement dates. While the AAR results are statistically insignificant for both groups, the 
CAAR analysis reveals statistically significant and directional price movements: insider sales 
are followed by sustained negative performance, whereas insider purchases lead to a delayed 
but consistent upward trend. These findings indicate that the Swedish market does not 
incorporate insider information immediately, but rather adjusts gradually over time. The 
results challenge the assumptions of semi-strong form of market efficiency and suggest the 
existence of exploitable trading opportunities based on public insider disclosures. Our 
conclusions contribute to the literature on market efficiency, while also offering practical 
implications for investors seeking to interpret insider behavior. 
 
 
 
 
 
 
 
Acknowledgements: 
We would like to express our deepest gratitude to our supervisor, Sadia, for her invaluable 
guidance and insightful feedback throughout the course of our thesis work. Her consistent 
availability and willingness to listen to our ideas and concerns have greatly contributed to the 
progress and quality of this project. 
We also extend our sincere thanks to our fellow students who participated in this semester's 
seminars. Your thoughtful feedback and inspiring theses have played an important role in 
shaping and improving our work. 
 
 
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Table of contents 
 
1. Introduction 4 
1.1 Background description: 4 
1.2 Problem description and problem analysis 5 
1.3 Aim of the study 7 
1.4 Research Questions 7 
2. Theoretical framework 8 
2.1 Efficient market hypothesis (EMH) 8 
2.2 Informational asymmetry 9 
2.3 Signaling theory 9 
2.4 Regulatory framework for swedish insiders 11 
3. Previous research 13 
3.1 Hypothesis development 15 
4. Methodology 17 
4.1 Method in general 17 
4.2 The model: Risk-adjusted event study 17 
5. Data 21 
5.1 Data collection 21 
5.2 Cleaning the data 24 
5.3 Descriptive statistics 25 
6. Empirical results 27 
6.1 The sale announcement firms 27 
6.2 The purchase announcement firms 32 
6.3 Robustness checks 37 
7. Discussion 38 
7.1 The results 38 
7.1.1 Significance of AAR and CAAR 38 
7.1.2 The CAAR graphs 39 
7.1.3 Opportunities for outside investors 41 
7.2 Limitations 42 
8. Conclusion 44 
9. References 45 
 
 
 
 
 
 
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1. Introduction 
 
1.1 Background description: 
In financial markets, information efficiency is a fundamental concept for understanding price 
movements and investor behavior. The Efficient Market Hypothesis (EMH) requires that all 
publicly available information is incorporated into stock prices, and hence it should be 
impossible to consistently earn abnormal profits using public information. The semi-strong 
form of the EMH, in particular, is that publicly disclosed information on corporations, 
including insider trading news, is rapidly reflected in security prices with no room for 
systematic outperformance (Fama, 1970). 
 
Insider trading, when disclosed in accordance with financial regulations, offers a means of 
testing this hypothesis. Corporate insiders such as executives and board members are required 
to report their trades in the shares of their companies (Finansinspektionen, n.d). If markets are 
efficient, the stock price would immediately respond at the release of such insider 
information on trading, and no systematic pattern of return should be observed after the 
announcement (Fama, 1970). But it has been established in the existing literature that in 
specific, insider buying could be followed by abnormal positive returns, suggesting that the 
market is not always efficient enough to digest the information at the time of disclosure 
(Roddenberry & Bacon, 2011; Seyhun, 1986). 
 
Moreover, the interpretation of insider transactions varies based on the direction and size of 
the trade. Insider purchases are generally viewed as a signal of undervaluation or insider 
optimism, while sales may be prompted by other non-informative factors, such as 
diversification etc (Lakonishok & Lee, 2001). The asymmetry suggests whether or not 
markets efficiently process buys and sells in terms of information. In addition, characteristics 
of the insiders themselves, such as risk tolerance or wealth, can influence the informativeness 
of the trades. For example, less wealthy insiders are discovered to time sales more effectively 
before price declines, suggesting a better informational motive than more wealthy insiders 
(Kallunki et al., 2018). At the same time, short-term market prices may be distorted by noise 
 
 
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trader activity, as irrational but correlated trading can move prices away from fundamentals 
and delay the full incorporation of information (De Long, Shleifer, Summers, & Waldmann, 
1990). 
 
In Sweden, disclosure to the public is mandatory for insider dealings through the official 
insider register of Finansinspektionen. The notice must be submitted to both the company and 
Finansinspektionen within three business days of the transaction (Finansinspektionen, n.d). 
The availability and quality of this information create a rich empirical context, but the 
Swedish market remains relatively under-researched in this respect compared to the US and 
UK stock markets. Some studies have indicated that even publicly disclosed insider trades are 
able to produce abnormal short-term returns, although the effect is varying depending on 
trade size and market liquidity (Oenschläger and Möllenhoff, 2025). 
 
This study aims to shed new light on insider trading by applying an event study methodology 
to the Swedish market. Specifically, it investigates whether disclosures of insider purchases 
and sales are followed by statistically significant abnormal stock returns. By separating the 
effects of purchases and sales and examining stock price reactions within a defined event 
window [-30, +30], the thesis contributes to a deeper understanding of market efficiency and 
the role of insider trading disclosures in a Scandinavian context 
 
 
1.2 Problem description and problem analysis 
Despite regulatory demands for disclosure of insider transactions and the availability of such 
information in general, it remains questionable whether markets react efficiently to 
disclosures of such information. According to the semi-strong form of the Efficient Market 
Hypothesis (EMH), all public information available, including insider transaction disclosures, 
should be immediately reflected in stock prices. In fact, however, several empirical 
researches have found that this is not necessarily the case, particularly in the instance of 
insider buying, which tends to be followed by positive abnormal returns (Roddenberry & 
Bacon, 2011; Seyhun, 1986; Lakonishok & Lee, 2001). This evidence contradicts 
fundamental assumptions regarding whether or not markets actually capture all extant public 
information immediately and exactly as EMH theory predicts. 
 
 
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One of the most important questions is whether insider purchases are an informational signal 
to the market. Insider purchases are generally viewed as a signal of undervaluation or insider 
optimism about the firm's future performance, but insider sales are more ambiguous 
(Lakonishok & Lee, 2001). This interpretation asymmetry implies that informativeness of 
insider trades would be context-dependent, and therefore it is uncertain if both types of trades 
are to be expected to impact stock prices in the same way. To what extent the market 
differentiates between these signals, and if it responds efficiently, is uncertain, especially in 
the Swedish case. 
 
Another issue is that of the practical tradability of insider tips. While some studies suggest 
that unusual profits are possible through copying insider trades (Seyhun, 1986), others have 
shown that even rapid responses to such announcements may not yield economically viable 
profits due to liquidity constraints and limited trade scalability (Oenschläger & Möllenhoff, 
2025). If there are abnormal returns in the Swedish market, it is not yet known if these can be 
converted into successful trading strategies, or if they are merely short-run inefficiencies that 
are hard to take advantage of. 
From a methodology perspective, the problem also entails separating the impact of a single 
insider disclosure from general market movement. Insider trades are informatively of unequal 
value, and price movement around the event window may be susceptible to the impact of 
confounding events such as earnings announcements or macroeconomic news. This 
complicates empirical analysis and requires careful event window design and testing of 
statistics. 
 
This thesis addresses these concerns by investigating whether Swedish insider trading 
disclosures, particularly buys and sales uncovered by Finansinspektionen's public registry, 
provoke abnormal stock returns. It applies a risk-adjusted event study approach to 
differentiate the market reaction to these events on a −30 to +30 trading days window.  
 
By examining the difference in stock price reactions to insider purchases and sales, and 
whether these reactions are statistically significant and economically significant, the study 
contributes new evidence to the controversy surrounding market efficiency, information 
asymmetry, and the utilization of insider signals. In doing so, it provides insights not only for 
 
 
6 
 
scholars but also for investors, regulators, and financial analysts who utilize insider 
information as part of their decision-making process. 
1.3 Aim of the study 
The aim of this study is to examine whether insider trading announcements in the Swedish 
stock market are followed by abnormal stock returns, thereby assessing the informational 
efficiency of the market (strong-,semi-, weak efficiency or something between). In particular, 
the study investigates whether public disclosures of insider purchases and sales contain 
predictive value for future stock price movements, and whether these effects differ depending 
on the type of trade (purchase/sell). By applying an event study methodology, the thesis 
measures abnormal returns in the period surrounding the disclosure of insider trades. The 
analysis focuses on two separate groups: insider purchases and insider sales across a sample 
of 15 Swedish listed firms each, and considers both short-term and medium term market 
reactions. This separation allows for a more precise interpretation of market behavior and 
potential asymmetries in how different types of trades are perceived and priced by investors. 
The contribution of this study lies in its application of established empirical methods to a 
relatively underexplored market. While prior research has largely focused on the United 
States and other markets, there is limited evidence on whether similar patterns hold in 
Sweden. By bridging this gap, the study adds to the growing literature on market efficiency 
and insider behavior in different institutional settings. In doing so, the thesis also tests the 
semi-strong form of the Efficient Market Hypothesis in a Scandinavian context, contributing 
empirical evidence on whether publicly available insider trading information is immediately 
and fully reflected in stock prices. 
1.4 Research Questions 
1. Are insider purchases followed by statistically significant positive abnormal returns? 
2. Are insider sales followed by statistically significant negative abnormal returns? 
3. Do abnormal returns following insider trade disclosures indicate exploitable 
opportunities for outside investors? 
4. What do the results suggest about market efficiency within the framework of the 
Efficient Market Hypothesis (EMH)? 
 
 
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2. Theoretical framework 
 
2.1 Efficient market hypothesis (EMH) 
Efficient Market Hypothesis (EMH) is a fundamental finance theory first introduced by Fama 
(1970) that states that stock prices reflect all available information. According to this view, it 
is impossible for investors to be in a position to earn abnormal returns on a regular basis by 
using information-based trading strategies that are already available. The EMH is usually 
classified into three forms, weak, semi-strong and strong, each relating to the type of 
information hypothesized to be contained in stock prices. 
The weak form of EMH states that all past trading information available, such as historic 
prices and volumes of trading, are already reflected incurrent stock prices. It suggests that 
technical analysis or even the utilization of the past price trends is impossible to assist the 
investor in beating the market at all times. The semi-strong form states that all publicly 
available information is already reflected in the stock prices. This includes not only historical 
data but all available public information, earnings reports, macroeconomic data and 
regulatory filings such as insider trades. In this formulation, investors cannot earn abnormal 
returns by trading on public information, since the market immediately and fully adjusts to it. 
Finally, establishing the strong-form variant of the EMH, all information, whether public or 
private, is assumed to be priced into stock prices. And even if the insider or confidential 
information is available, they could not consistently get abnormal returns as the market itself 
would have priced in this information too (Fama, 1970).  
However, if abnormal returns are consistently observed after certain disclosures, this may 
suggest the presence of information asymmetry in the market, meaning that some investors 
have access to relevant information before it is fully reflected in stock prices. Such a 
condition challenges the assumptions of the EMH, particularly its semi-strong and strong 
forms. 
 
 
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2.2 Informational asymmetry 
Informational asymmetry refers to a situation where one party in a transaction possesses more 
or superior information than the other. This imbalance can lead to inefficient outcomes, as 
decisions are made based on unequal access to relevant facts. The concept was first formally 
introduced by Akerlof (1970) in his paper “The Market for Lemons”, where he demonstrated 
how quality uncertainty in the used car market could cause market breakdowns. In his model, 
sellers typically have more information about the true condition of a car than buyers do, 
leading to adverse selection, where higher quality goods are driven out of the market by 
lower quality ones.  
In an insider trader sense, this underlying principle can be applicable in the form that 
corporate insiders inherently possess private knowledge about a firm’s performance and 
prospects. This gives them a potential advantage over public investors who become price 
chasers while insiders can earn abnormal returns on their private information (Sarwar, 2024). 
This can lead to price distortions and trading behavior that challenge the assumptions of 
market efficiency, particularly in its semi-strong and strong forms. 
If information asymmetry exists, insider purchases become particularly relevant from a 
signaling perspective, as they may serve as credible signals to the market based on private 
information. 
 
2.3 Signaling theory 
Signaling theory, which was developed by Spence (1973) in the labor economics context, 
addresses the problem of information asymmetry between two parties, typically one informed 
and one uninformed. Education is a signal of ability in Spence's model: it is more costly for 
low ability people to attain, and therefore it is a good signal of high ability. This early idea 
has been extended to a wide range of economic and financial conditions, including capital 
markets and corporate finance.  
 
In finance, signaling theory is used to explain how information in the possession of firm 
insiders is communicated to outside investors by observable action. One of the earliest and 
 
 
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most significant applications of this is in Ross (1977), where he argued that capital structure 
decisions can be used as a signal to the market. According to his model, firms with higher 
future prospects are more likely to issue debt, signaling optimistically to outside investors. 
Most notably, for a signal to be effective, it must be costly to imitate. Otherwise, low-quality 
firms would imitate high-quality ones, and the signal would no longer be effective (Ross, 
1977). 
 
In the context of insider trading, it is possible to apply this model to study how insiders' 
transactions,  e.g., those made by executives or directors, are able to provide information 
regarding the firm's value. Although insider transactions are disclosed, the motivation behind 
the transactions is not always clear to external investors. Based on signaling theory, when an 
insider purchases their own firm's stock, the market can interpret the insider purchase as a 
credible signal of undervaluation or good inside information. Further support for the idea that 
insider trading acts as a signal comes from recent research. Chen & Li (2023) show that 
insider purchases can work as a form of voluntary disclosure, where managers use their own 
capital to send a message to the market about the firm's value. These signals are especially 
effective in situations with information asymmetry, where outside investors do not have the 
same access to information as insiders. The study supports the idea that investors often react 
positively to insider purchases because they view them as credible signs of strong future 
performance. 
 
This argument is further empirically confirmed by Lakonishok and Lee (2001), who examine 
a large sample of U.S. insider trades and find that insider buying is followed by positive 
abnormal returns, especially in small-cap firms where information asymmetry is most likely 
to be greater. They argue that insider buying is most likely to occur when firms are 
undervalued and is particularly revealing when by top executives. Conversely, insider selling 
is discovered to be significantly less informative since it is typically motivated by 
non-informative considerations. Research clearly says that while purchases can be good 
leading indicators of performance, sales "appear to have no predictive ability" (Lakonishok & 
Lee, 2001). 
 
 
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2.4 Regulatory framework for swedish insiders 
Under the European Union's Market Abuse Regulation (MAR), persons under managerial 
responsibilities (PDMRs) such as board members, managing directors, and other executives 
are required to report their own transactions in the company's financial instruments. 
Reporting must also be made for transactions conducted by persons closely associated with 
the insider, such as spouses, registered partners, dependent children, or legal entities 
controlled by the insider. 
Transactions must be reported no later than three business days after the transaction date. The 
information must include the identity of the person, the name of the issuer, the nature of the 
transaction, the date, the place of the transaction, the volume, the price, and the trading 
venue. The issuer's Legal Entity Identifier (LEI code) must also be included. Reporting must 
be done electronically through Finansinspektionen's official portal and the company is 
responsible for ensuring public disclosure through the insider register. From December 2024, 
reporting is only required once the insider or the closely associated person's total transactions 
in a calendar year reach 20,000 euros. This threshold is based on cumulative transactions 
without netting purchases against sales. 
In addition to disclosure obligations, PDMRs and their closely associated persons are 
prohibited from conducting any transactions during closed periods. A closed period is 
typically 30 calendar days before the publication of interim financial reports or year-end 
financial statements. Exceptions may apply in exceptional circumstances such as severe 
financial difficulties (Finansinspektionen, n.d). 
Insider trading with private information is strictly forbidden under the Market Abuse 
Regulation (MAR). It refers to buying or selling financial instruments while in possession of 
material non-public information. Engaging in such trading constitutes a criminal offense and 
may result in fines or imprisonment under Swedish law. To convict someone of insider 
trading, authorities must prove that the person had access to the information and acted upon 
it. Evidence such as internal emails, messages, meeting notes, or access to confidential 
material is often necessary to establish liability (Ekobrottsmyndigheten, n.d). 
 
 
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However, because the legal threshold for prosecution is high, insider trading may still occur 
without detection or punishment. In practice, insiders could exploit information asymmetries 
and make informed trades with a relatively low risk of legal consequences, as long as no 
direct evidence exists to link them to the non-public information. If abnormal returns are 
observed following insider transactions in this study, it may therefore be partially explained 
by undetected insider trading based on privileged information. The presence of such 
information asymmetries challenges the assumptions of semi-strong form market efficiency, 
which posits that all publicly available information is already reflected in market prices. 
Even if a transaction is fully compliant and based on public information, a highly profitable 
trade, for example buying just before a major positive announcement, can trigger an 
investigation. The Swedish Economic Crime Authority (Ekobrottsmyndigheten) may 
summon the insider for questioning to ensure that no illegal insider trading took place. 
All these regulations fall under Regulation (EU) No 596/2014, the Market Abuse Regulation, 
which harmonizes rules across the European Union to ensure fair, efficient, and transparent 
financial markets. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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3. Previous research 
 
Research on insider trading and its implications for market efficiency has been extensive, 
particularly in the context of the semi-strong form of the Efficient Market Hypothesis (EMH). 
A central theme in this literature is whether public announcements of insider trades convey 
information that is not immediately reflected in stock prices, thus allowing for the possibility 
of abnormal returns. This section reviews studies that have examined this question from 
different theoretical and empirical perspectives. 
Roddenberry and Bacon (2011) conduct a comprehensive event study to investigate whether 
publicly disclosed insider trading activity in the U.S. market leads to abnormal stock returns. 
Their study centers on testing the semi-strong form of the EMH by analyzing the stock price 
behavior around insider purchase and sale announcements. By calculating risk-adjusted 
returns using the market model, they find that insider purchases are followed by statistically 
significant positive abnormal returns, while insider sales do not exhibit similar effects. This 
suggests that markets may not fully incorporate the information conveyed by insider 
purchases, leaving room for potential outperformance by those who act on such signals. The 
authors interpret this as partial evidence against market efficiency particularly in the 
semi-strong form, and raise the question of whether insiders are able to “buy low and sell 
high” based on superior information. 
In addition to these core findings, Roddenberry and Bacon emphasize the importance of 
distinguishing between different types of trades. They argue that insider purchases are more 
likely to reflect genuine information about undervaluation, while sales may be motivated by 
other factors such as diversification or personal liquidity needs. Their methodology, including 
the use of an event window (−30 to +30 days) and estimation window (−180 to −31 days), as 
well as the application of the market model serves as the basis for our thesis, which seeks to 
replicate and extend their study in a Swedish context. 
Complementing this work, Seyhun (1986) analyzes over 60,000 insider transactions in U.S. 
firms between 1975 and 1981 to assess whether insiders can earn abnormal returns. He uses 
the market-adjusted return model, where abnormal returns are measured as the difference 
 
 
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between the firm’s return and the market index return on the same day. The results show that 
insiders consistently earn positive abnormal returns, particularly following purchases, where 
prices increase by approximately 3% within 100 trading days. Insider sales are also followed 
by modest negative abnormal returns (-1,7%). The study finds that outsiders mimicking 
insider trades using public data can also earn abnormal profits, suggesting that the market 
does not immediately incorporate the information contained in insider trading. Additionally, 
the effect is more pronounced in small firms, and insiders in executive roles tend to make the 
most informative trades. These findings challenge the semi-strong form of the Efficient 
Market Hypothesis and support the idea that insider trading reflects informational advantages. 
Like Roddenberry and Bacon, Seyhun's findings challenge the semi-strong form of EMH and 
suggest that public disclosures may not eliminate insiders’ informational advantage. 
Lakonishok and Lee (2001) conduct a comprehensive study on the informativeness of insider 
trading by examining transactions from all firms listed on the NYSE, AMEX, and Nasdaq 
from 1975 to 1995. Using a portfolio based methodology, they construct value weighted 
portfolios of stocks with significant insider activity and assess post trade performance over 
long horizons. Their findings indicate that insider purchases are associated with positive 
abnormal returns, particularly in small firms, suggesting that insiders may exploit mispricing 
or undervaluation. In contrast, insider sales provide little to no predictive power, which the 
authors attribute to motivations unrelated to information (such as diversification). The study 
emphasizes that only insider buying appears to be genuinely informative, and this effect is 
strongest in firms with higher information asymmetry, typically smaller, less efficiently 
priced firms. 
Aktas, de Bodt, and Van Oppens (2008) focus on whether legal insider trading contributes to 
price efficiency. Using a sample from the US stock market from 1995-1999, they find that 
while insider trades do not trigger large short-term price movements, they are followed by 
faster price discovery. Their findings suggest that insider trading can improve informational 
efficiency, not by generating abnormal profits per se, but by helping markets incorporate 
relevant information more quickly. This provides a more nuanced view of insider trading one 
that aligns with market efficiency, even if the trading appears informative. Their emphasis on 
market microstructure and price adjustment mechanisms adds an important dimension to this 
thesis, which similarly evaluates how markets respond to disclosed insider activity. 
 
 
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The study by Kallunki et al. (2018) is directly relevant for Sweden, providing evidence on 
how insider characteristics affect trading behavior and its informativeness in Sweden. The 
authors show that less wealthy insiders are more likely to time their trades before adverse 
price movements, while wealthier insiders tend to act more conservatively. Their findings 
suggest that personal financial incentives can influence how and when insiders trade, which 
in turn affects how informative their actions may be to the market. This highlights that insider 
trades are not homogeneous and that the market’s interpretation may vary depending on 
context.  
Finally, Oenschläger and Möllenhoff (2025) examine the tradability of insider information by 
analyzing whether outside investors can profit by reacting quickly to insider filings. Their 
results show that while abnormal returns are sometimes observed in the short term, these 
gains rarely translate into economically meaningful or scalable profits due to liquidity 
constraints and limited tradable volume.. This raises important questions about the practical 
limitations of trading strategies based on public insider data, even when the data appears to be 
informative. 
Together, these studies highlight several consistent findings: insider trades, particularly 
purchases, can signal future stock performance. The market does not always react 
immediately or fully to these disclosures and various factors, such as insider characteristics, 
trade type, and market structure, influence the informativeness of insider trades. These 
insights lay the groundwork for the current thesis, which builds on Roddenberry and Bacon’s 
(2011) methodology to investigate whether insider trading disclosures lead to abnormal stock 
returns in the Swedish market. 
 
3.1 Hypothesis development 
The formulation of the hypotheses in this study is based on some of the aforementioned 
theories and literature on insider trading and its relation to market efficiency. Following the 
discussion of signaling theory and prior studies such as Seyhun (1986) and Lakonishok and 
Lee (2001), insider purchases are generally associated with undervaluation and subsequent 
positive abnormal returns, while insider sales are often perceived as less informative. At the 
 
 
15 
 
same time, the semi-strong form of the Efficient Market Hypothesis (Fama, 1970) argues that 
if markets are informationally efficient, publicly disclosed insider trades should be fully and 
immediately reflected in prices, eliminating the opportunity for abnormal returns. Thus the 
first hypothesis is defined as follows: 
 
- H11: The risk-adjusted return of the stock price on the announcement day is positively 
affected by the insider sale or purchase announcement. 
- H12: The risk-adjusted return of the stock price on the announcement day is 
negatively affected by the insider sale or purchase announcement. 
- H10: The risk-adjusted return of the stock price on the announcement day is not 
affected by the insider sale or purchase announcement. 
 
Previous literature, including Roddenberry and Bacon (2011) and, also in this case,  
Lakonishok and Lee (2001), suggests that insider trades may influence prices beyond the 
announcement day. The results from these studies indicate that while price reactions may 
occur on the announcement date, they can also be gradual, reflecting a market that processes 
insider information over time. Therefore, in order to capture both immediate and delayed 
reactions, this study analyzes a broader event window. Thus the second hypothesis is defined 
as follows: 
 
- H21: The risk-adjusted return of the stock price during the event window [-30, +30] is 
positively affected by the insider sale or purchase announcement. 
- H22: The risk-adjusted return of the stock price during the event window [-30, +30] is 
negatively affected by the insider sale or purchase announcement. 
- H20: The risk-adjusted return of the stock price during the event window [-30, +30] is 
not affected by the insider sale or purchase announcement. 
 
 
 
 
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4. Methodology 
 
4.1 Method in general 
To reiterate, the purpose of this study is to challenge the semi-strong form of the Efficient 
Market Hypothesis (EMH), which states that public information, such as insider trading 
disclosures, should be immediately and accurately reflected in stock prices. If significant 
abnormal returns are observed around or particularly after the announcement, this would 
suggest a deviation from market efficiency. To explore this relationship a replication of 
Roddenberry and Bacon’s event study methodology using the market model is applied, in a 
Swedish context, which allows us to isolate and examine abnormal price reactions around the 
dates of public disclosures. 
 
Two key metrics are employed to assess these effects: Average Abnormal Return (AAR) 
and Cumulative Average Abnormal Return (CAAR). AAR is calculated to measure the 
immediate or short-term price reaction on a specific day within the event window, most 
notably on the announcement date. This variable is therefore used to answer the H1 
hypothesis. In contrast, CAAR is computed to assess the aggregate impact on stock price 
performance across the entire event window, which makes it relevant to use to answer the H2 
hypothesis. The analysis and all computation is carried out in Microsoft Excel, where 
statistical significance of these metrics is evaluated through t-tests. While more sophisticated 
software like R or Python could be used, Excel is sufficient for the scope of this study given 
the sample size and relatively straightforward calculations. To support the interpretation of 
the results, the development of AAR and CAAR over time is also visualized using line 
graphs. These visualizations, created in Excel, help highlight trends and provide intuitive 
insights into the market’s reaction. 
 
4.2 The model: Risk-adjusted event study  
The event study methodology is widely used in empirical finance to evaluate how specific 
events impact firm value by analyzing abnormal stock returns around an event date. 
 
 
17 
 
According to MacKinlay (1997), the main strength of this approach lies in its ability to isolate 
the effect of an event (such as an insider trade announcement) on security prices under the 
assumption of market rationality, meaning that any relevant new information will be reflected 
quickly in prices. This makes it a justifiable tool for assessing whether insider transactions 
convey information to the market.  
Additionally, the event study methodology enables researchers to measure economic 
significance of such events over short windows, reducing the risk of confounding factors that 
could bias longer-term performance measures. MacKinlay emphasizes that, when executed 
properly with appropriate modeling of normal returns (e.g using the market model), this 
method provides robust insights into market reactions. The method’s established usage in 
insider trading literature also supports its relevance in the context of this study. Therefore, 
given the research objective, which is to assess market reactions to insider public disclosures, 
the event study methodology is particularly fitting. It allows the determination of whether the 
announcements of insider trades are followed by statistically and economically significant 
abnormal returns, thereby testing aspects of market efficiency and the informativeness of 
such trades. 
This study employs an event window spanning from 30 days before to 30 days after the event 
date [-30, +30], and an estimation window covering 180 days prior to 31 days before the 
event [-180, -31]. The timeframes were chosen to align with the methodology used by 
Roddenberry and Bacon (2011), ensuring consistency with established research. 
The analysis is based on two groups: insider purchases and insider sales, with each group 
including trades from 15 different Swedish-listed firms. To ensure economic relevance, only 
trades with a minimum value of SEK 200,000 are included. For the purpose of this study, it is  
assumed that all insider trades are equally informative. This simplifying assumption is 
commonly used in similar event study designs and is necessary to standardize the treatment 
of events across firms and insiders, especially when detailed information on insider 
characteristics (such as rank, tenure, or wealth) is not available. Although this may not fully 
reflect the heterogeneity in signal strength among different insiders, it allows for a consistent 
and unbiased comparison of average market responses to insider activity. Data on insider 
trades was collected from Finansinspektionen’s insider register, and stock price data was 
 
 
18 
 
collected from 180 trading days before to 30 trading days after each event. The OMX 
Stockholm 30 (OMXS30) index serves as the market benchmark. 
Daily returns for individual firms and the market index are calculated in the following way: 
𝑃 −𝑃
𝑅 = 𝑖,𝑡 𝑖,𝑡−1
𝑖𝑡 𝑃
 
𝑖,𝑡−1
where 𝑅  is the return of stock i on day t, and 𝑃  is the closing price of stock i on day t.  
𝑖𝑡 𝑖,𝑡
For each sample, 15 OLS regression analysis was performed (one for each firm) in excel with 
the return of each company as the dependent variable and the return of the OMXS30 as the 
independent variable over the estimation window [−180, -31]. This will give us the intercept 
alpha and coefficient beta for each company. Using these variables, the expected return 
during the event window (−30 to +30 days) can be calculated using the following formula: 
𝐸(𝑅 ) = α + β 𝑅  
𝑖𝑡 𝑖 𝑖 𝑚𝑘𝑡
where: 
●  𝑅  = return of stock i on day t 
𝑖𝑡
● 𝑅  = return of the market index on day t 
𝑚𝑘𝑡
● α  = intercept 
𝑖
●  β  = stock’s sensitivity to the market (beta) 
𝑖
The standard errors of the estimated alpha and beta coefficients were calculated automatically 
through Excel’s regression tool. This tool calculates conventional (OLS) standard errors 
under classical OLS assumptions, meaning it assumes homoscedasticity. As excel does not 
provide robust standard errors, no adjustments were made for heteroscedastic or 
autocorrelation. This is a limitation of the method, as standard errors may be biased if the 
underlying assumptions of constant error variance are violated.  
The abnormal return (AR) for firm i on day t is then: 
𝐴𝑅 = 𝑅 −𝐸(𝑅 ) 
𝑖𝑡 𝑖𝑡
 
 
19 
 
The AAR across all firms in a sample on each day t in the event window is: 
𝑛
𝐴𝐴𝑅 = 1
𝑡 𝑛
∑ 𝐴𝑅  
𝑡
𝑖=1
where: 
● n = the total amount of firms in the sample 
The CAAR over a given interval [−30, +30]) is calculated as: 
𝑡
2
𝐶𝐴𝐴𝑅 = ∑ 𝐴𝐴𝑅  
𝑡 ,𝑡 𝑡
1 2 𝑡=𝑡
1
Where: 
● 𝑡 = the starting day of the event window 
1
● 𝑡 = any specific day within the event window (e.g., day –10, 0, or +15), up to which 
2
the cumulative return is calculated 
E.g 𝐶𝐴𝐴𝑅 = 𝐶𝐴𝐴𝑅 + 𝐶𝐴𝐴𝑅  ...  + 𝐶𝐴𝐴𝑅 + 𝐶𝐴𝐴𝑅  
30 30 29 2 1
To assess statistical significance, one sample t-tests are used to test whether the AAR and 
CAAR differ significantly from zero.  
 
 
 
 
 
 
 
 
20 
 
5. Data 
 
5.1 Data collection 
To conduct this study, two key datasets were collected:  insider trading disclosures and daily 
stock price data.  In the process of collecting and refining the dataset for this study, several 
variables from Finansinspektionens’s insider trading register were considered, each serving a 
specific purpose on the selection and filtering of observations. These categories were 
carefully evaluated to ensure the quality, consistency and relevance of the data included in the 
final analysis. The table below outlines each category, provides definitions, and explains the 
rationale behind their selection and prioritization in the data collection process: 
Table 1: Categories, definitions and inclusion criteria 
Category Category definition Inclusion criteria 
Publication date The date the insider A transaction was chosen for 
transaction was made public each company if the specific 
date had:  
 
- No other major 
transactions that 
occurred within the 
event window (-30 to 
+30) 
-  Existing data for the 
majority of the daily 
stock prices for the 
estimation window 
(-180 to +30) 
Issuer The company whose None (randomly chosen) 
financial instrument was 
traded 
Person in a leading position The name of the insider who None 
 
 
21 
 
is subject to reporting 
requirements 
Position The insider’s role or title Persons holding 
within the company (e.g high-ranking positions 
CEO, board member, CFO within the company (e.g 
etc.) CEOs, board members etc.) 
Related party Indicates if the transaction No trades conducted by 
was made by someone related parties were included 
closely associated with the in the two selected samples 
insider (e.g spouse, child 
etc.). Is registered as “yes” if 
this is the case. 
Character Describes the nature or type Acquisition and disposal 
of transaction (e.g 
acquisition, disposal, etc.) 
Instrument name (Ticker) The name of the traded None 
instrument  
Instrument type The type of financial Share 
instrument (e.g share, bond, 
warrant etc.) 
ISIN A 12-character identifier None 
that uniquely identifies the 
traded instrument. 
Transaction date The date when the actual Benchmark for checking 
transaction took place. Not consistency between Nasdaq 
to be mistaken with the prices and reported 
publication date.  transaction prices 
Volume The number of units (e.g Verified that each 
shares) traded transaction value (volume × 
price) met the 200,000 SEK 
threshold 
Price The price per unit at which Verified that each 
the transaction occurred. transaction value (volume × 
price) met the 200,000 SEK 
threshold 
 
 
22 
 
Currency The currency in which the SEK 
transaction price is 
denominated (e.g SEK, EUR 
etc.) 
Table 1 outlines the variables extracted from Finansinspektionen’s insider register and their corresponding inclusion criteria. The table 
defines how each category was selected, with specific requirements applied only to the publication date to ensure data quality and avoid 
confounding events. 
 
The publication date was used as the reference point when it came to identifying when insider 
transactions were publicly disclosed. Each transaction for each company was selected only if 
their publication date met the earlier specified criterias in the table above: no other significant 
transactions occurred within the event window (-30 to +30 days) and that there was available 
and consistent daily stock price data covering the whole estimation period (-180 to +30 days) 
for that specific firm. To clarify the term 'no significant trade', this refers either to the absence 
of any transaction within the event window or to trades of such small value that they did not 
come close to meeting the 200,000 SEK threshold. This was necessary to ensure that the 
event window (-30 days to +30 days) accurately captured the impact of a single disclosure.  
The issuer for each sample was randomly selected to minimize selection bias and ensure that 
the analysis reflects the broader stock market rather than focusing on specific sectors. The 
person in a leading position and their title were noted to confirm that the majority of trades 
made by individuals in top executive positions, in line with the study’s focus on potentially 
informative transactions. In addition, all transactions conducted by related parties were 
excluded. This was based on the assumption that such trades may not reflect the same level of 
informational value as those conducted directly by primary insiders. The character of the 
transaction was also noted, with the study focusing exclusively on acquisitions (purchases) 
and disposals (sales), in line with the methodology of the Roddenberry and Bacon (2011) 
study. 
No specific selection criteria were applied to the instrument name, as it primarily served to 
confirm that the transaction involved a financial instrument covered by insider trading 
regulations. The same applies to the ISIN code, which was used solely to accurately identify 
the corresponding stock in the Nasdaq database. Since this study focuses on stock price 
 
 
23 
 
movements in connection with public insider disclosures, the instrument type was restricted 
exclusively to shares. 
To verify the financial significance of each transaction, the volume (number of shares) and 
price (per share) were used to calculate the total transaction value. Only trades with a value of 
at least 200 000 sek were included in the dataset, ensuring that the analyzed transactions were 
sufficiently large to be considered potentially impactful on the market. The transaction date 
was also used as a reference for cross-checking prices against Nasdaq data, ensuring 
consistency and accuracy between disclosed and market prices. Finally, all transactions were 
required to be denominated in SEK, to align with the domestic market scope of the study. 
Through this selection process, the data collection was refined to a sample that ensured 
comparability and reduced noise from unrelated factors. As previously mentioned, the 
collected ISIN codes were used to identify the corresponding stocks in Nasdaq’s database, 
from which relevant price data was retrieved. This process is described in more detail in the 
following section. 
 
5.2 Cleaning the data 
As mentioned in the previous section, the data on insider trades was collected from 
Finansinspektionen’s public insider trading register (Insynshandel). To minimize bias and 
overlapping events, trades were selected at different months introducing an element of 
randomization into the sample selection. 
To obtain the corresponding stock price data, ISIN codes were used to retrieve historical price 
series from Nasdaq’s database. For each transaction, up to five years of historical price data 
were collected. However, in line with the event study design, this dataset was later narrowed 
to include only the trading days within the defined event window, from day –180 to +30 
relative to the publication date. The raw price files included several variables such as bid 
price, ask price, opening price, high price, low price, average price, total volume, and 
turnover. For the purpose of this study, only the closing prices were retained, as closing prices 
reflect the final valuation agreed upon after a full trading day. 
 
 
24 
 
Additionally, historical price data for the OMXS30 index was retrieved from Nasdaq, 
applying the same cleaning process to match the data with each firm. All irrelevant columns 
were removed, and only the daily closing prices were kept. For the market index, ten years of 
price data were collected to ensure sufficient coverage for benchmarking stock returns both 
before and after the insider transactions. Care was taken to align the benchmark data with the 
corresponding trading dates for each firm, and in cases where data were missing for the 
market index on a given day the previous day’s closing price was carried forward to maintain 
continuity. 
 
5.3 Descriptive statistics 
The sample size and number of observations were selected to align with the approach used by 
Roddenberry and Bacon (2011), ensuring consistency with established research practice. Our 
dataset consists of 30 insider transactions, evenly split between 15 buy transactions and 15 
sell transactions. For each company associated with a transaction, 211 daily return 
observations surrounding the event date were collected, forming an event window to capture 
potential abnormal returns. All companies in the sample are Swedish firms listed either on 
Nasdaq Stockholm or Nasdaq First North Growth Market. In terms of insider roles, 12 
transactions were made by Chief Executive Officers (CEOs), 14 by Board Members, 2 by a 
Chief Financial Officer (CFO) and 2 by a Chairman of the Board). 
In terms of sector classification, the companies in the sample span a variety of industries. On 
the sell side, the most common sectors are Health Care and Industrials, each represented by 
four transactions. This is followed by Information Technology and Real Estate with two 
transactions each, while Energy, Consumer Staples, and Casinos & Gaming are represented 
by one transaction each. 
On the buy side, the most frequently represented sector is Industrials with five transactions, 
followed by Information Technology and Financials, each with three transactions. Additional 
buy transactions are found in Food Retail, Automobiles, Health Care, and Consumer Staples, 
each with one transaction. The sectoral diversity of the sample allows the study to capture 
insider trading behavior across a broad spectrum of industries. This breadth increases the 
 
 
25 
 
external validity of the results and reduces the risk that findings are driven by sector-specific 
dynamics. 
 
The table below presents summary statistics for both AAR and CAAR on the purchase and 
sale sides: 
Table 2: Summary statistics for AAR & CAAR 
Statistic Purchase side Sale side 
Mean (AAR)  -0,0007453  -0,0020881 
Observations (AAR) 61 61 
T-score (AAR)  -0,8208377  -1,9309588 
Two-sided p-value (AAR)  0,41498814  0,05821687 
Mean (CAAR)  -0,036404  -0,0587636 
Observations (CAAR) 61 61 
T-score (CAAR)  -15,637084  -12,060351 
Two-sided p-value (CAAR)  7,8187 *10-23 1,1128 * 10-17 
Table 2 presents key descriptive statistics from the empirical analysis, including AAR and CAAR for both the purchase and sale samples. It 
reports the mean values, number of observations, t-scores, and two-sided p-values, providing insight into the statistical significance of 
abnormal returns over the event window. 
 
 
 
 
 
 
 
 
 
 
 
26 
 
6. Empirical results 
 
To shortly reiterate, to assess the impact of insider trading announcements on stock price 
movements, this study uses two key dependent variables: AAR and CAAR. These variables 
are used to capture two different time aspects regarding the price movements connected to 
insider public disclosures. The AAR is used to investigate more short-term market reactions, 
such as daily reactions, to provide an answer to the H1 hypotheses. The CAAR is instead 
used to investigate the overall market reaction around the event window which can then be 
used to answer the H2 hypotheses. 
 
The expected relationship, based on previous research, is that insider purchases would result 
in significant positive abnormal returns, while insider sales would result in significant 
negative abnormal returns. The following subsections present regression outcomes, graphs 
and t-tests that evaluate whether the observed stock price movements significantly deviate 
from their risk-adjusted expected returns. This serves to test the hypotheses and assess the 
validity of the semi-strong form of market efficiency in the Swedish stock market. 
 
6.1 The sale announcement firms 
As stated before, on the sell side 15 firms were chosen according to the mentioned criterias in 
the Data collection chapter. The tables below presents the selected firms, along with other 
relevant firm-specific information: 
 
 
 
 
 
 
 
 
 
 
 
 
27 
 
Table 3: Description of selected firms - sale announcements. 
 
Table 3 presents the 15 selected insider sale transactions included in the analysis. Each row provides the announcement date, company 
name, ticker symbol, beta significance (* = p < 5%, ** = p < 1%, and no star means no significance), transaction date, trade volume, and 
corresponding stock price at the time of transaction. The selection was based on public disclosures that met the study's criteria for inclusion 
and span various sectors and firm sizes. 
 
Table 4: Alphas and betas for firms - sale announcements 
 
Table 4 displays the firm-specific alpha and beta coefficients derived from the market model regression for each of the 15 companies 
included in the sale-side sample. Alpha represents the firm’s abnormal return independent of market movement, while beta measures the 
firm’s sensitivity to market returns. These parameters were used to estimate expected returns and calculate abnormal returns in the event 
study. 
 
 
28 
 
The regression outputs show that the beta coefficient, a measure of the firm’s sensitivity to 
the market movements, was statistically significant at the 5% level in 10 out of the 15 
regressions. This suggests that market returns were a reasonably good predictor of 10 
individual firm returns during the estimation period. However, for the other five firms, this 
was not the case as the betas were statistically insignificant. This implies that the relationship 
between these firms’ returns and the market index was weak or not reliably estimated. This 
variability highlights a potential limitation of applying the market model to individual firms.  
 
To test whether statistically significant abnormal returns were present on a daily basis within 
the event window, a paired two-sample t-test was conducted within the timeframe of -30 to 
+30 between Actual daily average returns and Expected daily average returns. Additionally,  
a one-sample t-test was performed on the series of AAR during the same window to 
determine whether their mean significantly differed from zero. Since these tests are 
mathematically equivalent, and were used to cross-validate the significance, both yielded the 
same results: a t-statistic of approximately -1.93 and a two-sided p-value of 5,8%. As this 
p-value exceeds the 5% threshold, the result is not statistically significant. Therefore, the H1 
null hypothesis cannot be rejected, as the AAR observed on a day-to-day basis throughout the 
event window did not deviate sufficiently from expected returns to reach statistical 
significance.  
 
However, on the cumulative side (CAAR), this wasn’t the case. A one-sample t-test 
conducted on the CAAR values yielded a t-statistic of approximately -12,06 and a p-value 
well below 1% (1,113*10-17), indicating strong statistical significance even under the 1% 
threshold. This result suggests that the cumulative abnormal returns significantly differ from 
zero, allowing the CAAR variable to be used for further analysis and to support one of the H2 
hypotheses. Below, graphs are presented to visualize the development of AAR and CAAR 
across the event window, highlighting their respective trends over time: 
 
 
 
 
 
 
29 
 
Graph 1: Average abnormal return - sale announcements 
 
Graph 1 presents the Average Abnormal Return (AAR) for firms involved in insider sale announcements. The x-axis represents the event 
window in trading days, ranging from day -30 to day +30 relative to the transaction date (day 0), while the y-axis displays the average 
abnormal return values. 
 
Graph 2: Cumulative average abnormal return - sale announcements 
 
 
Graph 2  presents the Cumulative Average Abnormal Return (CAAR) for firms involved in insider sale announcements. The x-axis represents 
the event window in trading days, ranging from day -30 to day +30 relative to the transaction date (day 0), while the y-axis displays the 
cumulative average abnormal return values. 
 
 
 
30 
 
Although the AAR variable was just slightly above the 5% threshold in statistical 
significance , it remains relevant to examine the graphical trajectory to assess how the market 
responded to the announcements and whether the visual trend diverges from or is in accord 
with what would be expected under the H1 hypothesis.  
 
As graph 1 shows, the trajectory of abnormal returns show no discernible or patterned 
movement around the announcement date (day 0). Although there are occasional spikes and 
drops, particularly in the pre-event period (e.g., around day -6), these fluctuations appear to 
be random and do not coincide with the timing of the announcements. On the announcement 
day itself, the AAR does not exhibit any significant deviation, and in the post-event period, 
movements are relatively minor around zero. This absence of a consistent abnormal price 
reaction around the disclosure of insider sales suggests that the market did not interpret the 
information as particularly impactful on a day-to-day basis. Therefore, the observed pattern is 
consistent with the H1 null hypothesis and would lead to the same conclusion, even if the 
results would have been of statistical significance. 
 
When it comes to graph 2 (CAAR), a clear and continuous downward trend is shown over the 
entire event window indicating that, cumulatively, firms that disclosed insider sale 
transactions experienced a consistent loss in value relative to expected returns. The decline 
begins gradually in the pre-announcement period, with a minor upward spike observable 
around day -3 to 0 (which is around the transaction date) indicating a good sale, but gets more 
aggressive after the announcement date with the CAAR curve dropping more sharply 
between day 0 and day +25. This trend suggests that the market reacts negatively to insider 
sales not only on the announcement date, but also in the days following.  
 
Given that a one-sample t-test on these CAAR values produced a highly significant result, 
this pattern provides strong statistical evidence to reject the H20 hypothesis and support the 
H22 hypothesis: The risk-adjusted return of the stock price during the event window is 
significantly negatively affected by the insider sale or purchase announcement.  
 
 
 
 
31 
 
6.2 The purchase announcement firms  
As with the sell-side analysis, a total of 15 insider transactions were examined, each from a 
different firm and selected based on the criteria outlined in the data collection chapter. The 
tables below present the companies included in the buy-side analysis, including transaction 
dates, volumes, and prices. These insider purchases serve as the basis for evaluating whether 
such announcements lead to abnormal returns, and whether markets incorporate this 
information efficiently over the short-term event window. 
 
Table 5: Description of selected firms - Purchase announcements 
 
Table 5 presents the 15 selected insider purchase transactions included in the analysis. Each row provides the announcement date, company 
name, ticker symbol, beta significance (* = p < 5%, ** = p < 1%, and no star means no significance), transaction date, trade volume, and 
corresponding stock price at the time of transaction. The selection was based on public disclosures that met the study's criteria for inclusion 
and span various sectors and firm sizes. 
 
 
 
 
 
 
 
 
 
 
 
 
 
32 
 
Table 6: Alphas and betas for firms - Purchase announcements 
 
Table 6 displays the firm-specific alpha and beta coefficients derived from the market model regression for each of the 15 companies 
included in the purchase-side sample. Alpha represents the firm’s abnormal return independent of market movement, while beta measures 
the firm’s sensitivity to market returns. These parameters were used to estimate expected returns and calculate abnormal returns in the event 
study. 
 
The regression outputs for the purchase-side sample showed that the beta coefficient, a 
measure of each firm’s sensitivity to market movements, was statistically significant at the 
5% level in 12 out of the 15 regressions (slightly better than on the sale-side). This suggests 
that, for the majority of the firms, market returns served as a reasonably strong predictor of 
stock returns during the estimation period. However, in three of the cases, the beta 
coefficients were not statistically significant, indicating that the relationship between those 
firms’ returns and the market index was either weak or not reliably captured by the model.  
This variation in model fit highlights an important limitation of applying the market market 
models to individual firms. While the model appears valid for most stocks, it may fail to 
capture the return generating process for firms with more idiosyncratic behavior or low 
correlation with the market. Consequently, the reliability of expected return estimates and by 
extension, abnormal return calculations may be compromised for these firms.  
 
 
33 
 
The analysis of AAR around insider purchase announcements reveals no evidence of 
statistically significant price reactions on a daily basis. Across the [-30, +30] event window, 
AAR fluctuates moderately, but without any consistent upward or downward trend that would 
suggest a meaningful market response. To formally assess this, both a paired two-sample 
t-test comparing actual and expected daily returns and a one-sample t-test on AAR were 
performed. These tests, which are mathematically equivalent, yielded consistent results: a 
t-statistic of -0.82 and a two-tailed p-value of 41.5%. Given that this value is far above the 
standard 5% threshold, no statistical support is found to reject the null hypothesis (H20). 
In practical terms, as mentioned in the sales-side, this implies that insider purchase 
disclosures were not perceived by the market as significant informational events, at least not 
on a daily basis. Any short-term fluctuations in stock price appear to fall within the bounds of 
normal market volatility. 
However, on the cumulative side (CAAR), this was not the case. A one-sample t-test 
conducted on the CAAR values produced a t-statistic of approximately –15.64 and a p-value 
well below 1% (7.82 × 10⁻²³), indicating strong statistical significance even under the strictest 
threshold. This result suggests that the cumulative abnormal returns significantly differ from 
zero, allowing the CAAR variable to be used for further analysis and to support one of the H2 
hypotheses.  
 
 
 
 
 
 
 
 
 
34 
 
Graph 3: Average abnormal return - Purchase announcements 
 
Graph 3 presents the Average Abnormal Return (AAR) for firms involved in insider purchase announcements. The x-axis represents the event 
window in trading days, ranging from day -30 to day +30 relative to the transaction date (day 0), while the y-axis displays the average 
abnormal return values. 
 
Graph 4: Cumulative average abnormal return - purchase announcements 
 
Graph 4  presents the Cumulative Average Abnormal Return (CAAR) for firms involved in insider purchase announcements. The x-axis 
represents the event window in trading days, ranging from day -30 to day +30 relative to the transaction date (day 0), while the y-axis 
displays the cumulative average abnormal return values. 
 
 
35 
 
Although the AAR variable did not reach statistical significance, it remains relevant to 
examine the visual development of abnormal returns across the event window to assess 
whether any patterns are observable in connection with the insider purchase announcements. 
As seen in Graph 3, the trajectory of AAR fluctuates throughout the window without 
displaying a consistent pattern. Spikes and dips appear on several days, most notably around 
day –6 and +22, but these do not align with the announcement date (day 0) and instead 
suggest random variation. On the day of the announcement itself, the AAR remains close to 
zero. However, two consecutive days of slightly positive abnormal returns are observed 
immediately following the publication date, suggesting a minor short-term market response. 
Still, this effect is not strong or systematic enough to reach statistical significance. Taken 
together, the lack of a clear and consistent reaction indicates that the market did not perceive 
the insider purchases as materially informative. This pattern aligns with the null hypothesis 
H10, which states that the risk adjusted return of the stock price on the announcement day is 
not significantly affected by the insider purchase announcement. 
Graph 4 illustrates the development of CAAR following insider purchase announcements. 
The curve shows a clear downward trend leading up to the announcement date, indicating 
that the sampled firms were underperforming relative to expectations before disclosure. 
Immediately after day 0, a small upward movement is visible, followed by a downward trend 
up to day +20, then a more sustained recovery is visible between day +20 and +26, where 
CAAR increases by approximately three percentage points. This suggests that the market 
partially corrected earlier losses, potentially responding to the insider purchases in a delayed 
and moderate manner.  
Given that a one-sample t-test on the CAAR values yielded a highly significant result, this 
provides statistical evidence to reject the null hypothesis H20. This supports the alternative 
hypothesis H22, which states that the risk-adjusted return during the event window is 
significantly negatively affected by the insider purchase announcement. However, the CAAR 
curve also shows a clear upward movement from day –1 to day +2, and a more sustained 
recovery from day +20 to approximately day +26. These intervals reflect a temporary 
reversal in performance that may suggest a partial alignment with H21, which posits a 
positive effect. While H22 is supported over the full window, these subperiods imply that 
 
 
36 
 
market reactions are not uniformly negative, and may vary in intensity and direction 
depending on timing. 
 
6.3 Robustness checks 
To ensure validity and reliability of our findings, several robustness checks were conducted. 
These were implemented with the aim of improving the statistical significance of the key 
variables under investigation, namely AAR and CAAR.  
For both the buy-side and sell-side samples, the event window was reduced from [-30, +30] 
to a narrower window of [-11, +11] to assess whether a shorter timeframe would yield 
stronger statistical significance. Contrary to expectations, this adjustment resulted in a 
noticeable increase in the two-sided p-values for the AAR in both samples, indicating even 
lower statistical significance in the shorter window. 
Additionally, for the purchase-side sample, a portfolio substitution test was performed in 
which 14 of the 15 firms were replaced with new companies that met the same selection 
criteria. This was done in response to the initial findings, which indicated an overall negative 
price reaction within the event window, an outcome inconsistent with prior literature 
employing similar methodologies. Interestingly, the new sample produced results that were 
strikingly similar to the original, both in magnitude and in graphical trajectory, thus 
reinforcing the robustness of our initial findings. While the AAR results for the new portfolio 
showed marginal improvement in significance levels. they remained far from reaching 
statistical significance. However, ultimately it was chosen to use the new portfolio as the 
purchase-side sample to ensure the highest possible accuracy and reliability of our results. 
 
 
 
 
 
 
 
37 
 
7. Discussion 
 
7.1 The results 
7.1.1 Significance of AAR and CAAR 
The discrepancy between the insignificance of the AAR and the strong significance of the 
CAAR is both methodologically and economically meaningful. The AAR captures the 
average abnormal return on a day-to-day basis within the event window, while the CAAR 
aggregates these daily abnormal returns over time to identify broader trends. In this study, the 
AAR for both the purchase- and sales samples failed to show statistical significance, 
indicating that abnormal returns did nor deviate strongly from expected returns on any 
individual day. This finding aligns with Aktas, de Bodt, and Van Oppens’ (2008) results, who 
argue that insider trades do not typically trigger immediate or large short-term price reactions. 
However, the CAAR was statistically significant for both samples, revealing a sustained 
pattern of abnormal returns when viewed cumulatively. 
 
The divergence may be explained by the fact that, as De Long et al (1990) states in their 
article, noise trader activity can delay information processing which moves prices away from 
fundamentals in the short-term market. These short-term fluctuations on a daily-basis may 
obscure any clear signal in the AAR, making it difficult to detect significance at the daily 
level. In contrast, CAAR smooths out this noise by capturing the broader price movement 
across the entire event window. A consistently small but directional shift in returns 
(undetectable in AAR) can accumulate into a statistically significant trend in the CAAR.  
 
Economically, this suggests that while investors may not react sharply on the announcement 
day itself, there is a gradual assimilation of the information into stock prices. This pattern 
suggests that the market is not fully semi-strong efficient. While public disclosures such as 
insider trades do influence stock prices, the delayed and gradual price adjustments indicate 
that the market does not immediately incorporate all publicly available information. 
Therefore the results support that the efficiency of the Swedish stock market is that of a 
weaker form of semi-strong efficiency. 
 
 
38 
 
7.1.2 The CAAR graphs 
The analysis of the CAAR graphs for both the purchase-side and sale-side transactions 
reveals several important insights about market behaviour surrounding insider trades. Starting 
with a brief summary of the results, the CAAR for the purchase-side portfolio shows an 
overall upward trend following the announcement of insider purchases, while the sell-side 
CAAR demonstrates a consistent downward trajectory. These opposing directions are not 
only statistically significant, as confirmed by the one-sample t-test, but also indicative of how 
the market interprets insider trading activities over the event window. 
 
Looking more closely at the trajectories, it becomes evident that both CAAR-graphs display 
subtle but meaningful fluctuations around the announcement date. Notably, in the days 
leading up to the insider transactions, the purchase-side CAAR dips slightly, whereas the 
sale-side CAAR shows a modest increase. The asymmetric behavior suggests that insiders 
might possess material non-public information that enables them to optimally time their 
trades. For example, according to the results, insiders appear to buy when the stock is 
undervalued,  i.e just before an upward price movement, and sell when the stock is 
overvalued, i.e just before a decline. This supports the theory of informational asymmetry, 
which posits that insiders have superior knowledge about firm-specific developments and use 
this to their advantage when entering the market.  
 
Following the announcement date, the divergence between the two groups becomes clearer. 
The buy-side CAAR overall increases throughout the event window, while the sell-side 
CAAR consistently continues to decline. Although, it is important to note that the upward 
trend observed post-announcement on the buy side is relatively volatile, as the CAAR 
initially rises around day 0, followed by a downward movement lasting until approximately 
day 20, after which it resumes an upward trajectory. This delayed rise may reflect a gradual 
reassessment by investors, suggesting that the market does not fully absorb the insider signal 
immediately, but instead responds over time as confidence in the trade builds. 
Since insider trading on non-public information is prohibited under the EU Market Abuse 
Regulation (MAR), this timing advantage is unlikely to result from illegal behavior. Rather, 
as Chen and Li (2023) states in their study, it likely reflects insiders’ deep and broad 
understanding of the company’s operations, financial position, and industry context. Their 
 
 
39 
 
ability to interpret various factors affecting the firm enables them to recognize when the stock 
is undervalued, even without knowledge of a specific event. This informed timing helps 
explain the upward price movement seen after day 20 and reinforces the view that insider 
purchases can act as credible signals to the market. 
Throughout the event window, these cumulative effects indicate that, post-announcement, the 
market tends to react positively to insider purchases and negatively to insider sales. This 
observation is consistent with previous research, including Roddenberry and Bacon (2011), 
Lakonishok and Lee (2001) and Seyhun (1986), who found that insider purchases are 
typically associated with positive abnormal returns, while insider sales are associated with 
negative abnormal returns.  
 
From a signaling theory perspective, these findings suggest that the market interprets insider 
activity in a meaningful way. Insider purchases may signal confidence in the firm’s future 
prospects, thus encouraging outside investors to follow suit. In contrast, insider sales may be 
interpreted as a lack of confidence or an indication that the stock is overvalued, prompting a 
negative reaction. This implies the presence of information asymmetry (as stated before), as 
the observed price movements suggest that the market interprets insider trades as potentially 
informative, reflecting a belief in their access to value-relevant information.. 
 
A common misconception when interpreting CAAR values is to equate a negative level with 
a lack of market outperformance. However, this interpretation overlooks the importance of 
the trajectory of the CAAR rather than its absolute level. In this study, and studies before 
(such as Roddenberry and Bacon), although the CAAR for the buy-side sample remains 
negative across the full or majority of the event window, the positive slope following the 
announcement date indicates a shift in the market sentiment in response to insider purchases. 
This upward movement implies that had the event window been narrower or realigned to 
begin at the time of the announcement, the CAAR could have reached positive values, 
signaling a short-term abnormal return exceeding expectations. Therefore, while the 
full-window CAAR does not cross zero, the post-announcement trend may still reflect a form 
of market outperformance, especially when interpreted in the context of short-term investor 
reactions. This aspect highlights the importance of analyzing both the level and direction of 
 
 
40 
 
cumulative returns in event studies, particularly when assessing market efficiency and insider 
trading implications.  
7.1.3 Opportunities for outside investors 
An analysis of the CAAR graph for the sale side reveals a consistent downward trend 
throughout the entire event window. However, around the transaction date, there is a 
short-lived upward movement in returns, suggesting that insiders tend to sell at relatively 
favorable price levels. At the time of the transaction, the insider holdings had only decreased 
by approximately 2%, indicating well-timed execution. Following the public announcement, 
the cumulative abnormal return declines by roughly 10%, highlighting the effectiveness of 
the trade from the insider’s perspective. 
The CAAR graph for the sale side shows a gradual and consistent decline across the entire 
event window, with a short-lived upward movement around the transaction date. This pattern 
suggests that insiders tend to sell at relatively favorable valuations, shortly before a broader 
negative price trend sets in. Such timing indicates that insider sales may be based on private 
information not yet reflected in market prices.  
Given the statistical significance of our results and the clear post-announcement decline, this 
pattern provides a basis for a potential trading strategy. The announcement appears to 
function as a negative signal to the market, implying that the stock may be overvalued. Based 
on the companies included in our study, investors could consider selling their positions or 
initiating short trades shortly after the announcement. A holding period of up to day 26–27, 
where the CAAR curve reaches its lowest point, may be appropriate. Since the cumulative 
decline is approximately 10%, the potential return from such a strategy appears plausible. 
Moreover, because the decline unfolds gradually, short positions initiated on nearly any day 
after the announcement would likely remain profitable. Even if the insider sale is identified 
several days later, particularly if disclosed by a high-ranking executive, our data suggest that 
further price declines are still likely, making the trade actionable even with a slight delay. 
On the purchase side, while daily returns (AAR) lack statistical significance, the CAAR 
exhibits a statistically significant upward trend following the announcement, suggesting that a 
trading strategy based on cumulative price movement, rather than immediate reaction, may be 
more viable. Prior to the announcement date, a steady decline is observed, with insider 
 
 
41 
 
transactions occurring close to the lowest point in the window. This suggests that insiders are 
buying at relatively low valuations, possibly indicating undervaluation. 
Following the announcement, the CAAR graph shows a short-term increase of approximately 
1.5% day 0 to day  2, suggesting that the market responds positively to the insider signal. A 
short-term strategy could involve entering a long position on the announcement date and 
exiting one to two trading days later to capture this immediate reaction. 
In the longer term, the price continues to rise, and a strategy of holding the position from the 
announcement date until approximately day 24–27 would yield a return of around 2.5%. This 
upward movement reinforces the idea that insider purchases are perceived as credible signals 
of firm value, and that the market gradually incorporates this information into the stock price. 
It is important to emphasize that these strategies are derived from the firms in our sample and 
should be interpreted as an indicative pattern rather than a general investment 
recommendation. While our findings suggest that insider sales may function as negative 
signals in these specific cases, further research on a broader and more diversified dataset 
would be necessary to evaluate the generalizability and robustness of such a strategy across 
different market contexts. 
7.2 Limitations 
One limitation of our approach relates to the estimation of expected returns using the Market 
Model. Beta and alpha for each firm are calculated using a regression based on a 150-day 
estimation window (day −180 to −31), with OMXS30 as the market benchmark. However, 
given the high market volatility during the study period, such a short estimation window may 
result in unstable or biased coefficients. If the estimated beta fails to accurately reflect the 
firm’s true exposure to systematic risk, the expected return will also be misestimated. This 
directly affects the accuracy of the abnormal return (AAR), which is calculated as the 
difference between actual and expected returns. 
This issue may partly explain why our AAR results are not statistically significant, despite 
observable movements in return trajectories. If the expected return is inaccurate due to a 
poorly estimated beta, the residuals will not correctly capture the market’s reaction to insider 
trades. This reinforces the need for caution when interpreting daily abnormal returns in 
 
 
42 
 
short-term event studies with limited estimation periods, especially during volatile market 
conditions. 
Additionally, the market model does not account for firm-specific volatility or other risk 
factors beyond market movements. Insider trades often occur in connection with firm-specific 
news or events that may not correlate with the market index. By using a single-factor model, 
our approach may have oversimplified the complexity of return dynamics around insider 
transactions. Future research could benefit from using multi-factor models, such as 
Fama-French three-factor or Carhart four-factor models, which may offer more precision in 
estimating expected returns. 
Another limitation concerns the assumption that all insider trades are equally informative. In 
reality, insiders differ in role, access to information, and financial incentives. Prior research 
by Kallunki et al. (2018) shows that less wealthy insiders tend to time their trades more 
effectively before adverse price movements, while wealthier insiders act more cautiously. 
This implies that some insider trades carry stronger signals than others, depending on who is 
trading and why. 
Although the study does not directly control for insider characteristics such as personal 
wealth or executive position, a minimum trade value of 200,000 SEK was set to filter out 
minor transactions that are less likely to be information-driven. This threshold was chosen to 
help capture trades with greater market relevance. However, without explicitly accounting for 
the profile of each insider, it is not possible to fully isolate which trades carry the most 
informational weight. This may reduce the clarity of the observed market reactions in our 
aggregated analysis. 
Finally, it is acknowledged that the sample size and firm selection may limit the 
generalizability of the findings. Although our data set includes 30 firms, it is possible that 
sector-specific effects, firm size, or liquidity conditions could have influenced the observed 
outcomes. A broader or stratified sample could offer more representative insights and enable 
comparative analysis between sectors or firm types. 
 
 
43 
 
8. Conclusion 
This thesis has investigated whether insider trading disclosures by Swedish executives lead to 
abnormal returns in the stock market, and whether these price reactions differ between 
purchases and sales. Using event study methodology and data from Finansinspektionen, 
abnormal returns were evaluated through both AAR and CAAR for two samples of insider 
purchase and sale transactions. 
The study contributes to the growing literature on insider trading by showing that while daily 
abnormal returns (AAR) are not statistically significant, the cumulative patterns (CAAR) 
reveal strong, directional price reactions. Specifically, insider sales are followed by a steady 
and significant price decline, whereas insider purchases produce a delayed but significant 
upward trend. This suggests that while the Swedish market does not react immediately to 
insider trades, it does gradually incorporate the information over time, which possibly leaves 
profitable opportunities for outside investors to capitalize on before the information is fully 
reflected in prices. This challenges the fundamental definition of a semi-strong form of 
market efficiency and instead indicates a partially semi-strong form. Our findings also 
support the theory that insider trades convey asymmetric information and that market 
participants interpret insider activity as meaningful signals. 
These insights are particularly relevant to financial analysts, policy makers and private 
investors, who seek to understand the informational role of insider transactions. 
In conclusion, this thesis demonstrates that insider sales provide clearer and more immediate 
signals to the market than purchases, at least in the Swedish context. Future research could 
build on these findings by analyzing cross-country comparisons, sector-specific behaviors or 
regulatory impacts on insider trading informativeness. 
 
 
 
 
 
 
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