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Price run-ups and insider trading laws under different regulatory environments

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Abstract

We examine target firms’ price run-ups prior to takeovers in two different exchange regulatory environments within the same country. We show that target firms listed both in the secondary market of the UK, known as the Alternative Investment Market (AIM), and in the traditionally regulated Main Market, experience significant abnormal stock returns prior to takeover announcements. These results persist after controlling for market anticipation, indicating signs of information leakage. Contrary to the narrative that secondary markets may be more susceptible to market abusive behaviors, we find that the AIM targets experience significantly lower pre-announcement returns. In addition, we do not find support that the introduction of stricter laws reduces the price run-ups in any of the two markets. In sharp contrast, we find support that the enforcement of insider trading laws, through criminal convictions, reduces the pre-announcement abnormal stock returns but only in the market in which the enforcement focuses.

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Notes

  1. John Thain, New York Stock Exchange (NYSE) executive was quoted at the World Economic Forum in Davos Switzerland in January 2007 referring to the AIM as it "did not have any standards at all and anyone could list" (https://www.ft.com/content/beb09508-ad27-11db-8709-0000779e2340). Moreover, Roel Campos, a Securities and Exchange Commission member was quoted on a Dow Jones newswire in March 2007 saying “I am concerned that 30% of issuers that list in AIM are gone in a year. That feels like a casino to me and I believe investors will treat it as such” (https://www.ft.com/content/cd0530e2-cdab-11db-839d-000b5df10621). Finally, Kate Burgess, a journalist of the FT wrote “AIM’s numerous corporate collapses and scandals have earned the market its label as a wild west exchange where cowboys are allowed to roam free” (https://www.ft.com/content/2cb37958-af6a-11e7-beba-5521c713abf4).

  2. Interview of Marcus Stuttard to Proactive Investors in 2015 on the market’s 20th anniversary (https://www.proactiveinvestors.co.uk/companies/news/108159/if-aim-was-just-a-casino-it-wouldnt-have-lasted-20-years-108159.html).

  3. Apart from the academic literature, the UK regulators also tend to focus on M&As when it comes to information leakage. For example, the FCA has introduced the “market cleanliness statistic”, a statistic which is included in the FCA’s annual reports and focuses mostly on price run-ups prior to the announcement of M&As (Dubow and Monteiro 2006). This measure is an indicator of insider trading in the UK markets and a reduction signifies that the UK markets are clearer from informed trading. Moreover, 70% of the criminal sanctions related to insider trading in the UK are due to insider trading prior to takeovers showcasing the importance of M&As in this set up (an example of a UK criminal sanction and links to other cases can be found at https://www.fca.org.uk/news/press-releases/three-charged-insider-dealing).

  4. The Euronext Growth (formerly known as Alternext) was formed in 2005 and operates in Belgium, France and Portugal; the Mercado Alternativo was formed in 2008 and operates in Spain; Nasdaq’s First North was introduced in 2008 and operates in the Nordic countries; the Tokyo Pro market (formerly known as Tokyo AIM) was formed in Japan in 2009.

  5. See for example the white paper from the CFA Institute in May 2016 (https://www.cfainstitute.org/-/media/documents/article/position-paper/united-states-venture-market.ashx).

  6. Formerly known as Financial Service Authority or FSA.

  7. In 2009, the FCA achieved its first successful criminal sentence for insider trading which was followed by a series of other convictions with regards to insider trading (Goldman et al. 2014).

  8. We thank an anonymous reviewer for these valuable insights. See for example:

    (https://www.marketwatch.com/story/expert-networks-key-to-sec-insider-trading-cases-2012-11-21) and (https://www.bloomberg.com/news/articles/2017-01-27/hedge-funds-track-j-j-private-jet-for-an-edge-on-actelion-score).

  9. We thank the FCA for providing us with information regarding criminal convictions for insider trading in the UK.

  10. As stated by Margaret Cole, FSA's former managing director of enforcement and financial crime, insider trading cases are always difficult, time-consuming and expensive (https://www.bloomberg.com/features/2016-operation-tabernula/).

  11. Some examples of the FCA criticism are the following articles titled: “FSA failed to issue specific warnings to Dunfermline” (https://www.ft.com/content/68492f9e-7c60-11de-a7bf-00144feabdc0), “FSA failed spectacularly over banks” (https://www.ft.com/content/d42a2a5c-7d31-11de-b8ee-00144feabdc0) and “Regulator’s light touch led to failure” (https://www.ft.com/content/2bf14c52-24ce-11e1-bfb3-00144feabdc0).

  12. Sara George, a lawyer and partner at Allen & Overy who achieved a successful FCA criminal prosecution related to market abuse, shared her thoughts on the importance of prosecution penalties in the Financial Times “When the worst that can happen is that you might lose your job and be fined an amount, you can afford to lose. Prison—and you start off in a normal one, it’s not straight to Ford (open prison)—that really will make people think twice” (https://www.ft.com/content/7dc845ea-c9e6-11dc-b5dc-000077b07658).

  13. LBOs constitute approximately 2% of our sample. If we include LBOs, we obtain qualitatively similar results (unreported for brevity) on our empirical tests.

  14. Even though short-horizon abnormal returns are not sensitive to different event models (Armitage, 1995; Dionysiou, 2015), we have also estimated the abnormal returns using the market model and the Buy and Hold Abnormal Returns (BHARs) and find that the results are qualitatively similar.

  15. The statistical significance of CAARs is qualitatively similar when we test the significance levels using a) sign test, b) cross-sectional test, c) standardised cross-sectional test and, d) the method of moments estimation.

  16. To ensure that our results are not influenced by the announcement effect, we replicate our tests using the interval periods of (-40, -2 and -40, -3). The results are qualitatively similar.

  17. To split the sample into two groups, we compare the estimated takeover probability of each firm with the optimal cut-off probability (Palepu 1986). If a firm’s probability is higher (lower) than the cut-off probability, the firm is classified as a firm with high (low) probability of being taken over. For the calculation of the cut-off probability, we construct ten deciles sorted in descending order based on takeover probability following Powell (2004) and Brar et al. (2009). Each decile has the same number of firms. The optimal cut-off probability is then the first takeover probability in the portfolio with the highest concentration ratio (ratio of takeovers over the total number of firms in the portfolio). In untabulated results, we find that the highest concentration ratio is in the second to last decile for the AIM targets and the last decile for the MM targets. Specifically, the cut-off probability for the AIM targets is 0.30, and for the MM targets is 0.40. On average, the model predicts approximately 70% of target and non-target firms for both markets.

  18. It has been reported that market anticipation over acquisitions could stem from information provided in various press releases (Jensen and Ruback, 1983).

  19. Malatesta and Walkling (1988) and Comment and Schwert (1995) also report that firm with poison pill takeover defences tend to be less likely to become takeover targets. In our sample, there are no firms with poison pill defences in place and as such we do not include this variable.

  20. Once again, the results are qualitatively similar when we replicate the regressions using the interval periods of (-40, -2) and (-40, -3) to mitigate concerns of the announcement effect in our results.

  21. These are added interchangeably due to high correlation between them.

  22. The results are qualitatively similar when we use two alternative measurements for the calculation of Premium: 1) the ratio of the offer price to the target’s stock price four weeks before the acquisition announcement minus one (Levi et al., 2014) and 2) the difference between the offer price and the target’s total assets per share over the latter (Li et al., 2019). Furthermore, the results are qualitatively similar when we use one week premium (difference between offer price and the target firm's stock price, one week before the acquisition announcement divided by the latter).

  23. In particular, one concern could be that higher pre-announcement returns in one market may reflect higher deal quality (more valuable synergies, expectation of lower premium paid). With this measure, pre-announcement runups are normalized by deal quality, captured by (-40, 0) and hence these concerns are mitigated.

  24. The results are qualitatively similar when we estimate Eq. (3) for matched firms.

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Acknowledgements

We are grateful to Cheng-Few Lee (the editor) and two anonymous referees for their insightful comments and suggestions. We thank Panos Andrikopoulos, Nathan Lael Joseph, Thang Nguyen, Ronan Powell, Daniel Santamaria, Umut Turksen and Tina Yang for their comments in prior versions of this study. We also thank the participants at the British Accounting and Finance Association (BAFA) conference (Northern Area Group, September 2019), the Financial Management Association (FMA) 2020 and the Centre for Financial and Corporate Integrity (CFCI) 2020 seminar series for their helpful comments. In addition, we are grateful to the Financial Conduct Authority (FCA) for providing us with information regarding criminal convictions for insider trading in the UK. This study has been partly funded by the Committee of Departments of Accounting and Finance (CDAF).

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Authors and Affiliations

  1. Research Centre for Financial and Corporate Integrity, Coventry University, Coventry, UK

    Styliani Panetsidou & Angelos Synapis

  2. Adam Smith Business School, University of Glasgow, Glasgow, UK

    Ioannis Tsalavoutas

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  1. Styliani Panetsidou
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Appendices

Appendix A: Historical total listing and market capitalization in secondary markets

1.1 Total listings

figure a

1.2 Market capitalization ($mil)

figure b

This appendix presents the total number of firms listed and the market capitalization of the largest secondary markets from 1995 to 2018. These secondary markets include: the AIM in the UK, the Bratislava MTF in Slovenia, the Euronext growth in Belgium, France and Portugal, the Mercado Alternativo in Spain, the Nasdaq’s First North in Nordic countries, the NewConnect in Poland and the Tokyo Pro market in Japan. The data are hand collected from the exchanges’ websites. The market capitalization is shown in 2015 US dollars.

Appendix B: Variable definitions

Variable

Definition

AIM

An indicator variable that takes the value of one if the target firm was listed in the AIM and zero otherwise

CAAR

A variable that represents the cumulative average abnormal stock returns for the period (−40, −1) following an OLS market model as in Brown and Warner (1985)

CAAR residual

A variable that represents the residual from the regression in Eq. (3)

Cash offer

An indicator variable that takes the value of one if the offer is cash only and zero otherwise (Thomson One item “Consideration structure”)

Conviction

A variable that indicates the number of individuals imprisoned for insider trading. Data is provided by the FCA

Cross-border

An indicator variable that takes the value of one if the deal is cross-border and zero otherwise (Thomson One item “Cross-border deal”)

Dividend yield

Dividend per share as a percentage of the share price (DS item DY)

Enforcement

An indicator variable that takes the value of one if the deal was announced between March 2009 and December 2018

FCF

The ratio of free cash flow calculated as cash flow from operations (WS item WC04860) less cash flow from investing activities (WS item WC04870) scaled by the total assets (WS item WC02999)

FSMA

An indicator variable that takes the value of one if the deal was announced between November 2001 and February 2009

Growth resource mismatch

An indicator variable that takes the value of one if the target firm has a combination of (i) above average growth, below average liquidity and above average leverage; or (ii) below average growth, above average liquidity and below average leverage and zero otherwise

Historical stock return

Average abnormal stock returns compared to the FTSE AIM All share for the AIM targets or compared to the FTSE All share for the MM targets over the three years prior to the deal (−750, −40)

Hostile

An indicator variable that takes the value of one if the bid was hostile and zero otherwise (Thomson One item “Deal Started as Unsolicited Flag”)

Industry activity

An indicator variable that takes the value of one if there was another takeover in the target firm industry (using ICB industry classification) in the previous year and zero otherwise

Leverage

Average leverage ratio calculated as total debt (WS item WC032555) to total assets over the three years prior to the deal announcement. If there is no data for three consecutive years, we use the previous two years instead

Liquidity

Average liquidity ratio calculated as cash (WS item WC02003) to total assets over the three years prior to the deal announcement. If there is no data for three consecutive years, we use the previous two years instead

M/B

Market to book ratio of the target firm (DS item MVTB)

Number of bidders

A variable that indicates the number of bidders interested in the target firm (Thomson One item “Number of Bidders”)

Number of target advisors

A variable that indicates the number of advisors of the target firm involved in the deal (Thomson One item “Number of Target Advisors”)

Past acquisition

An indicator variable that takes the value of one if the target is pursued by another firm in the previous year and zero otherwise

Premium

The difference between the offer price and the target firm’s stock price, four weeks before the acquisition announcement divided by the latter (Thomson One item “Offer price to target stock price premium 4 weeks prior to announcement”)

Public bidder

An indicator variable that takes the value of one if the bidder is a public firm and zero otherwise (Thomson One item “Acq Public Status”)

R&D

The ratio of R&D expensed (WS item WC01201) over total assets (WS item WC02999)

Rumors

An indicator variable that takes the value of one if the acquisition was rumored prior to the deal announcement and zero otherwise (Thomson One item “Deal Began as Rumor”)

Sales growth

Average sales (WS item WC01001) percentage change over the three years prior to the takeover announcement. If there is no data for three consecutive years, we use the previous two years instead

Same industry

An indicator variable that takes the value of one if both the target and bidder are in the same industry and zero otherwise

Severity

A variable that indicates the severity of punishment calculated as the sum of imprisonment years over the number of individuals imprisoned. The years of imprisonment are hand-collected from FCA announcements and relevant newspapers such as the Financial Times

Size

The natural logarithm of the total assets (WS item WC02999) of the target firm in thousand US dollars

Stock illiquidity

Stock illiquidity is measured using the Amihud illiquidity ratio (Amihud 2002). This is calculated as the average absolute value of the daily stock return over the daily dollar volume (price multiplied by volume) over the period −250 to −101 days prior to the takeover announcement

Toehold

An indicator variable that takes the value of one when the acquirer holds a toehold and zero otherwise (Thomson One item “Percent of Shares Held at Announcement”)

This appendix presents the variables used in the empirical analysis. All accounting data are measured at the fiscal year end prior to the announcement of the deal, unless stated otherwise.

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Panetsidou, S., Synapis, A. & Tsalavoutas, I. Price run-ups and insider trading laws under different regulatory environments. Rev Quant Finan Acc 59, 601–639 (2022). https://doi.org/10.1007/s11156-022-01052-0

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