The determinants of leveraged buyout activity

Not taking into account taxes, weighted average coat of equity:

R_D - cost of debt, W_D - leverage ratio Leverage ratio = Equity/(Debt+Equity)

R_e - cost of equity, W_e - equity ratio

According to the formula presented above, cost of equity could be calculated as:

Component “r” represents a business risk, whereas, component “” stays for company's financial risk. Business risk depends entirely on the nature of company's operations, while financial risk is determined by the capital structure.

Picture 1. “The effect of financial leverage on the cost of capital and the value, M&M model without taxes”

In other words, the cost of equity, being a linear function of company's capital structure, depends on three variables: the cost of debt (), the required rate of return on company's assets (r) and debt-to-equity ratio (D/E). That means that gradual growth in the debt capacity (as less expensive source of founding) will certainly be accompanied by a simultaneous increase in cost of equity, thus turning weighted average cost of equity into a constant value. In worth mentioning, that M&M theory is a rather academic one, being highly assumption intensive, it does not give full answers to the question about how to manage financial structure in a real company. The main assumptions of basic M&M theory are follows:

- Shares and bonds are traded on efficient capital markets: no taxes (corporate as well as personal), no transaction and agency costs, absence of bankruptcy costs. Moreover, investors can borrow at the same rate and in the same amount as corporations. Besides, all participants in the market as well as potential investors have homogeneous expectations regarding future levels and risk of EBIT as well as investment opportunity of each company (no information asymmetric)

- Risk-free nature of the debt as well as cost of debt level does not depend on the size of the debt financing.

- Going concern cash flows: EBIT assumed to be constant due to zero growth, bonds are issued for an indefinite period (annuity)

In 1963, Franco Modigliani and Merton H. Miller published the second article devoted to the capital structure, in which authors relaxed the assumption of «no income tax». Given that the interest paid on debt is partially deducted from the amount of taxable income, the basic formulations of M&M theory have changed:

- Value of the company, that has a financial leverage is equal to the company's value with no use of leverage, increased by the present value of tax shields (resulted from tax deductibility of interest).

-present value of tax shields

The higher the rates of business taxation, the more profitable the use of debt financing is. Following this logic, the optimal capital structure is the one that consist 100% of debt. Cost of equity calculation takes the following form:

Picture 2. “The effect of financial leverage on the cost of capital and the value, M&M model with taxes”

In other words, the cost of equity increases as the company more heavy relies on debt financing. However, cost of equity growth rate become insufficient to compensate the influence of increased taxed benefits. As a result, the higher the debt level, the lower the WACC is.

The fundamental basis of trade-off theory was laid on the base of M&M's constructive criticism. Firstly, Robinchek and Mayers (1966), later Kraus and Litzenberger (1973) hypothesized that an excessive increase in the debt burden leads to a sharp rise in bankruptcy costs, as a result, the cost of equity increases along with cost of debt.

Picture 3. “The influence of bankruptcy costs on the cost of capital and the value, Trade-off Theory”

Value of a company obtained by adding three components (APV approach)

Value of the firm (base case) + Present Value of side effects + Present value of bankruptcy costs

According to trade off theory, the optimal capital structure is achieved at the point when the marginal benefit of a new debt tranche equals the marginal costs of bankruptcy.

Further, the basic trade-off theory was refined with dynamic assumption, offering much flexibility in the process of optimal capital structure estimation. According to dynamic trade-off theory, managers could deviate company's capital structure from a target one within a range in which the cost of maintaining a non-optimal capital structure does not exceed the cost of recapitalization.

In a tradition leveraged buyout transaction, private equity managers try to conduct the deal in the way to reach optimal capital structure. Typically, debt burden accounts for 60-70% in financial structure, while 30-40% goes to equity contribution. Private equity managers contrive to reach such disproportionally high level of debt owning to: their sound reputation as well as stable expected free cash flow of a target firm. The rule of «tax deductibility of interest expense» guarantees the additional benefits (in terms of tax savings) to financial sponsors. It worth mentioning, that post-buyout financial structure of a target company is flexible enough. Target's cash flows are mainly used to repay debt obligation, thereby equity share gradually increases to industry's average values. Withal, financial sponsors are unlikely to be satisfied by benefits merely generated by tax shields. On the contrary, investors expect private equity managers to realize full potential of a target company, to improve the financial and operational performance, thereby increase target's exit value and enhance returns.

II. Determinants of leveraged buyout activity: literature review

2.1 Hypothesis of leveraged buyout activity

Firstly, in order to answer a question about core drivers of leveraged buyout activity, we have underlined main hypothesis that exist in corporate finance research. Summarized data presented in table 1.

Table 1. “Hypothesis of LBO drivers”

2.2 Phases in the public-to-private process

The following part of current work is devoted to a precise analysis of literature on company's public-to-private activity conducted in form of LBO. To begin with, in order to provide structured collective literature review, all researches on leveraged buyout transactions are grouped in response to a certain phase in the public-to-private process. It worth mentioning, that each group differs from one another not only by corresponding stage of LBO process but also by research method employed. L. Renneboog, T. Simons (2005) defines next steps in buyout cycle and related areas of econometric research: intent, impact, process, duration. Let's go point by point.

The literature devoted to intent stage of going private decision has an aim to figure out main features of “ideal” LBO candidate, in other words, researches do their best in order to define set of common firm's characteristics before the decision to move from public to private position. Than target's determinants are compared with corresponding proxies of companies that still remain publicly traded. In a result of econometric modeling on different samples, main motives of successful LBO transactions might be revealed empirically. It worth mentioning, that when it comes for «intent» stage analysis, Cox's proportional hazard model and probit regression models are core instruments available to researches. Than the determinants of LBO activity with high level of significance can be fruitfully used by professional investors in their routine process of assessing potential targets on the ability for LBO style transformation.

The roots of literature dedicated to LBO's intent phase goes to Jensen's Free Cash Flow theory and from that time annually has being updated by different scientists all over the globe. Precise review on literature on the intent stage of LBO will be provided in the next chapter.

The second block of literature is called impact estimation. In other words, this group of studies focuses on the immediate target's stock price reaction in response to the leveraged buyout announcement. Moreover, `impact' group literature identifies the link between pre-transaction characteristics of target and the size of premium paid by new investors. Calculating abnormal returns (CAARs) is one of the most effective ways in conducting impact phase research. Despite the fact, that determinants related to impact stage are not in the focus of current study, some examples will be provided in table 2.

Table 2. “Impact phase estimation”

The third group of LBO studies (Process) investigates the post buyout financial and operating “health” of target company and compare these characteristics with corresponding features of comparable companies that didn't have the experience of public-to-private transformation.

The last group of studies devoted to leverage buyout process (Duration) investigates the longevity of private state in LBO cycle before the decision to go public again. In order to define determinants of private ownership duration Cox's hazard model is commonly used by researches on this field.

After fast overview of general literature on public-to-private activity it worth focusing on definite area of researches - Intent phase of LBO. In order to provide precise analysis on determinants of leveraged buyout decision, four hypothesis are examined through academic literature.

2.3 Determinants of LBO activity: operating, financial and market-wide factors

buyout transaction leverage

Operating Characteristics

Hypothesis 1. Likelihood for a firm to be a LBO target relates to pre-transaction Operating characteristics of this company.

Table 3 presents summarized findings of researches devoted to estimation the link between pre-transaction operating characteristics of companies and the probability of making leveraged buyout decision. In other words, Table ¹4 presents the core features of “ideal” LBO candidate revealed by different researchers using various samples and econometric techniques. The figure recorded in brackets relates to the number of LBO hypothesis supported.

Table 3. “Operating characteristics of LBO targets”

On the base of findings provided in Table ¹4 we can conclude that academic literature does not provide a common view on the set of characteristics for “ideal” LBO candidate in terms of operating performance. Different theories (often mutually exclusive) are confirmed on various samples by different researches. For example, studies conducted during 1980 -1999 years based on samples of the first LBO boom had their focus on reorganization benefits of leveraged buyout activity. In fact, agency and information asymmetries theories were core in explaining leveraged buyout transformation. High undistributed Cash flows and increased level of selling expenses accompanied by low potential future growth prospects (low Market-to book ratio) seemed to be main drivers to LBO activity, as buyouts were perceived as one of the most effective tools in the process of overcoming overinvestments and opportunistic managerial behavior. Actually, novel research conducted by Jesse Edgerton (2012) confirmed the viability of agency problems in public companies by evidence from corporate jets availability. J. Edgerton states that «In the cross-section, firms owned by private equity funds average 40% smaller fleets than observably similar public firms». Moreover, according to Edgerton, there is clear link between public to private decision and the reduction in target's fleet size.

The same time, second LBO surge was accompanied by innovation in the financial markets. Widespread implementation of new financial instruments (stock options compensation schemes) significantly enhanced managerial motivation and decreased the soundness of agency problem. As a result, key operating determinants of LBO activity such as selling expenses/sales, size of cash flows decreased the level of significance in studies devoted to second wave of LBO boom. Instead, underperforming and undervaluation hypothesis became more popular in academic research nowadays.

In turn, some common pre-transaction operating characteristics of LBO firms might be traced through academic studies, they are: hard assets, steady cash flows, low capital requirements, diversity, low Market-book ratio of target company. These econometrically proven determinants of leveraged buyout activity have clear practical explanation. For instance, banks used to extend credits on terms that are more favorable for those companies that can provide hard assets as collateral. Moreover, steady (not volatile) target's Cash flows (minimal business risk) is a signal for investors that borrower generates sufficient cash levels not only to maintain current operations, but also to service a debt (interest, principal debt payments) on a regular basis without solvency risks. Furthermore, there is no doubt, that the lower the level of required capital expenditures the more flexible business is. The same rule works when it comes to working capital requirements and RD&A expenditures. As a result, investors in the process of assessing target's viability for leveraged buyout transformation pay additional attention on determinants “Capex/Sales”, “Working capital/ Sales”. Moreover, high diversity level of a LBO candidate is also a good signal for potential investor. Indeed, institutional investors typically seek companies with suboptimal business structure (presence of non-core corporate subsidiaries, non-core assets) in order to `spin off” these non- profile division in post-LBO period, obtain cash and reinvest additional financial sources in-line with new post-buyout optimization strategy.

Financial characteristics

As we have mentioned earlier, the second LBO wave (2001-2007) was accompanied by sharp surge in trade volumes on financial markets along with increased quality of corporate governance. Easier access to capital markets fueled IPO activity. The same time, due to the presence of information asymmetry not all young listed firms succeeded in attracting and holding analysts' attention and whereby lost their stock market positions. According to financial visibility hypothesis, namely these “looser' companies became core candidates for leveraged buyout transformation in the second surge of LBO activity.

Hypothesis 2: Likelihood for a firm to be a LBO target relates to pre-transaction performance of this company on financial markets.

Table 4 presents summarized findings of researches devoted to estimation the link between pre-transaction target's performance on financial markets and the probability of making leveraged buyout decision. In other words, Table 5 presents additional common features of “ideal” LBO candidate revealed by different researchers using various samples and econometric techniques.

Table 4 (à). “Financial characteristics of LBO targets”

buyout transaction leverage

Table 4 (b). «Financial characteristics of LBO targets»

On the base of findings provided in table 4 we can conclude that financial visibility hypothesis is proven on estimated samples. To begin with, there is a negative link between stable growth in analyst coverage and the decision to opt out of public market. Indeed, investors prefer transparent stocks. Otherwise, outflow of securitized analysts leads to illiquidity of shares, rise in the degree of undervaluation and excess in transaction costs (related to stock market listing) prior to wealth gains of IPO activity.

When it comes to institutional ownership, empirical researches also confirm that the greater the share owned by institutional investors, the lower the probability of a company to be a buyout target. Actually, increased institutional ownership is a sign of satisfactory reputational position of a target company (sound market player) that indicates the absence of a need to go private. Another determinant of market visibility is stock turnover. According to financial visibility theory, non-transparent financial instruments lacking investors' attention used to loose liquidity. In other words, academic literature revealed a negative correlation between stock turnover and issuer decision to opt out of public markets through LBO.

Another group of determinant, designed to disclose the relationship between success in target's stock performance and the likelihood of leveraged buyout transformation, also obtained an empiric proof in academic literature. Table 4 (a) illustrates that there is a strong negative relation between stock volatility and probability of going private, what is in line with financial distress theory. In other words, private equity funds more likely seek for candidates that have failed to attract investor's interest but still shows stable stock returns. It is worth mentioning, proxy for absolute size of stock returns is insignificant, only the volatility level of stock returns matters.

As we mentioned earlier, the young IPO firms that have worse access to capital markets are more likely to perform leveraged buyout transformation. Otherwise, companies that have a rich history of successfully conducted secondary public offerings and wide experience in merger and acquisition transactions (in role of acquirer) are less likely to suffer from limited access to capital markets and therefore are less likely to go private through LBO.

Market-Wide factors

Hypothesis 3: Leveraged Buyout activity is driven by Economy-Wide factors

As it was mentioned earlier, LBO activity is characterized by “boom and bust” pattern, therefore Economy -Wide factors of LBO activity should be scrutinized with a double power.

Indeed, it becomes clear that not only endogenous individual firm's characteristics (operating, financial, etc.) determines the decision to go private through LBO, but also external, macroeconomic factors have a great degree of influence on leveraged buyout volumes in the economy. In other words, macroeconomic forces might influence (push, delay, etc.) firms decision to conduct leveraged buyout transformation.

Table 5 presents summarized findings of researches devoted to precise estimation of Economy-Wide factors fueling leveraged buyout activity.

Table 5. “Economy-Wide factors fueling leveraged buyout activity”

On the base of findings provided in table 5 we can conclude that modern academic literature states that LBO activity positively relates to risk-free rate, supply of bank loans, CDOs market volumes, GDP growth rates and negatively correlates with market risk premiums.

According to A. Shivdasani, Y. Wang “$535 billion of leveraged buyouts were completed from 2004 to 2007, what is more than 10 times of volume over the previous 8 years from 1996 to 2003” . The same time “aggregate CDO issuance rose to $1.3 trillion over 2004 to 2007, twice the total issuance volume over the previous 8 years”. Statistics makes clear that asset securitization explosion along with development of a secondary market for leveraged loans forced leveraged buyout activity during the second LBO boom. Indeed, when lending standards and requirements were simplified significantly, investors (especially private equity funds) got an attractive opportunity to borrow great bulk of financial resources on favorable conditions and invest them in leveraged buyout deals.

To sum up, we can conclude that assessing endogenous target' characteristics (operational, financial, etc.) along with exogenous ones (wide-market conditions) is crucial for professional deal managers. The wrong choice for a leveraged buyout target is a harbinger of disaster even if the most reputed private equity fund employed into transaction.

Aswath Damodaran (2007) conducted a deep analysis of failed Harman's LBO case, where Goldman Sachs and KKR were main players. Damodaran demonstrated that the ignorance of basic principles of valuation and corporate finance leads to prompt collapse of leveraged buyout transactions. Damodaran defined exact features of “ideal” LBO candidate and proved empirically, that almost none of these qualities Harman possessed. According to Damodaran, core pre-LBO transaction characteristics are: stock underperformance (in sector, in general market); lower margins and turnover ratios; costs of equity and capital should exceed returns on equity and capital respectively; poor management quality (high expected value of post-LBO control reform).

2.4 Determinants of the degree of leverage employed in LBO transactions

Once a target for a leveraged buyout transformation was selected, the question as for the optimal degree of leveraged employed in LBO transaction arise.

The next part of analysis (table 6a) will be devoted to a precise analysis of literature that estimates factors affecting financial structures of successfully completed LBO deals.

Table 6(a). “Drivers of leverage in leveraged buyouts”

Findings provided in Table 6 might be presented in more visualized form.

Table 6(b). “Drivers of leverage in leveraged buyouts”

On the base of findings provided in table 6(b) we can conclude that academic literature does not provide a common view on drivers of leverage in LBO transactions. Some studies proves significance of cross-sectional factors suggested by traditional capital structure theories (cash flow volatility, profitability). In turn, latest theories insist that only marked- wide factors (high yield spread) along with private equity group reputation have strong influence on the degree of leverage employed in LBO transaction.

2.5 The emergence of tech LBOs: the role of intellectual assets in value creation

Private Equity Financing of Technology Companies

There is no doubt that empirical researches contributed greatly to the comprehensive understanding of what companies are lucrative targets for leveraged buyout transformation and what firms are not. Further, the academic findings were successfully incorporated in practical manuals designed for private equity managers.

Thus, according to CFA Program Curriculum CFA Institute. “Alternative investment and fixed income”, CFA Program curriculum 2015, level 2, volume 5 - 2014, page 402, buyout investments should be directed to targets that: have steady and predictable cash flows, excellent market position, significant asset base as well as strong and experienced management team. Lucrative candidates, being mature businesses with established products and long operating history, are characterized by measurable risk and predictable exit opportunities. Potential for restricting and cost reductions, in addition to low working capital requirements are also important LBO indicators.

The basic “road map” of LBO candidate's screening provided by CFA Institute is widely reflected in other private equity manuals. Sofat, Rajni, Hiro, Preeti Manual's examples: Strategic Financial management, Second Edition; PHI Leraning Pvt. Ltd.,2016, page 386; Investment banking, page 140 Generally, authors suggest buyout funds to invest exclusively in mature companies with a transparent business cycle, leaving young, dynamic technology intensive targets for venture capital funds. Historically, private equity managers followed this strategy, “steering away from hi-tech and biotech companies”. David Stowell. “An Introduction to Investment Banks, Hedge Funds, and Private Equity”, 2014 Indeed, candidates known for innovations seemed to be “too volatile, too complicated, not leveragable, without tangible assets, and finally too risky to support buyouts” Tilman E. Pohlhausen. ”Technology Buyouts. Valuation, Market Screening Application, Opportunities in Europe”, Deutscher Universitats-Verlag GmbH, Wiesbaden - 2003, page 1. Technology targets “scared off” buyout managers not only because of their uncertain risk profile but also due to extended payback period on R&D investments, that exceeded average buyout holding horizon (five-seven years). On the contrarily, equity-intensive venture capital funds could afford tech targets with lower predictability of cash flows, shorter market history, poorer assets base and higher capital requirements.

Whereas, private equity, being rather dynamic and flexible industry, adjusts its screening, selection and managerial strategies in accordance with actual business environments, legal infrastructure and macroeconomics conditions on a regular basis. As a result, nowadays instead of focusing primary on financial leverage and corporate governance value drivers, buyout managers prefer to emphasize on operational improvements of the target companies. In other words, “The typical LBO model experienced a gradual shift towards more growth PE oriented investments and managerial criteria” Florian Schock. “Private equity financing of technology firms: a literature review”, EBS Business School Research Paper No. 14-06 - 2013, page 7. This sound shift in leveraged buyout philosophy changed the negative perception of intellectual property based candidates over the recent years. “A new wave of tech buyouts has begun - one in which smaller firms with less-developed products are being taken private with large amounts of debt and relatively scant equity” Greg Miller. “The new trend ripping through the tech sector”, Wall Street Daily, LLC. - February 2015.

A new tech buyout wave has its roots in the late 1990s, with the emergence of Silver Lake Partners and Menlo Park - funds, specializing on middle and large capital investments in “technology companies and tech-enabled businesses” http://www.silverlake.com/secondary.asp?pageID=1. The first truly successfully conducted technology buyout deal occurred in 2000 - Seagate Technology acquired by Michael dell with Silver Lake Partners gave return on investments ~700%. Greg Miller. “The new trend ripping through the tech sector”, Wall Street Daily, LLC. - February 2015 Since that time, transactions of different sized followed, constantly increasing the global portfolio of successful exits. Nowadays, the value of combined technology assets under the management of Silver Lake Partners exceeds $24 billion.

The next part of research devotes to a precise analysis of key drivers that fueled tech LBO market. As noted earlier, business environments, legal infrastructure and macroeconomics conditions are sound underlying factors fostering the general technology buyout trend.

Firstly, technology sector has undergone a significant shift in quality and risk profile characteristics. In other words, technology industry made a “sharp jump” from a niche segment of the global economy to a mature sector with a relatively predictable business cycle. There is no doubt, that, nowadays, key portfolio companies of Silver Lake Partners such as Dell (“computing solutions company”), SolarWinds (“provider of hybrid IT management software”) or Motorola Solutions (“communication solutions”) are able to produce strong predictable cash flows as well as lucrative growth prospects. Certainly, not each tech company suits for LBO transformation, whereas, mixing innovations and risk no more perceived as a recipe for a certain buyout failure.

Secondly, debt and equity financing became more affordable for technology and innovation-intensive firms.

Thirdly, a shortage of alternative mature buyout opportunities is enhancing technology leveraged buyout demand even higher. Indeed, after the ages of blockbuster LBOs, lucrative cash rich targets with a high cost reduction potential and a persistent desire to go private via leveraged buyout eventually made an LBO transformation. As a result, private equity funds forced to apply greater efforts, break into new markets (including technology sectors) in order to attract new perspective buyout candidates

Strong competition among buyout funds also had a significant impact on private equity's screening strategies. In other words, “it's becoming more difficult to ensure high returns from cost-cutting alone, so PE investors are seeking more entrepreneurial growth” Josh Lerner, Morten Sørensen, Per Strömberg. “Private Equity and Long-Run Investment: The Case of Innovation”, Harvard business school, Working Paper 09-075 - December 2008, page 45

The last driving force for innovation-intensive buyouts is a “knock on effect” of successfully closed leveraged buyout deals in technology sector. Such global leaders in technology investing as Silver lake Partners as well as Thoma Bravo proved that “it's now possible to take tech firms private and not kill them”. Greg Miller. “The new trend ripping through the tech sector”, Wall Street Daily, LLC. - February 2015

Intellectual Property Assets

As it was mentioned earlier, technology buyout transactions gained popularity and recognition among “sharks from Wall Street” for substantial growth potential. Thereby, another question arise: “What internal characteristics distinguish technology companies from classical ones”. The answer lies in the field of intellectual property assets monetization.

According to Baruch Lev, intangible asset “is a claim for future benefits that does not have a physical or financial (a stock or a bond) embodiment” Baruch Lev. «Intangibles: Management, Measurement, and Reporting», Brookings Institution Press, Washington, D.C. - 2001, page 79. Such assets as patents, trade secrets, trademarks, copyrights as well as brand, organizational structures form intangible asset class that usually interact with financial assets and tangibles in order to create value and facilitate growth. Furthermore, intangibles could be classified into three major groups according to the assets generators: innovation capital, organizational practices and human resources.

Baruch Lev insists that physical and financial assets generate an average return on investments, while abnormal profits and competitive advantages are the merit of intangible assets. The increasing role of intangible assets in modern economy could be illustrated in numbers: “In 1975, only 17 percent of the S&P 500 market value went to intangible assets; in 2010, the share of intangible assets in S&P market value increased to 80 percent. Bruce W. Burton, Scott Weingust. “Why Private Equity and Venture Capital Firms Should Care About Intellectual Property Assets”, Stout Risius Ross - 2012, page 41 Indeed, any sector in which firms invest heavily in R&D, technology and brands usually has a significant intangibles record.

Whereas, accounting regulation does not impose strict disclosure requirements to intangible assets, as a result, intangible assets generally recorded on unsystematic basis. This tendency leads to “invisible assets” book undervaluation, as well as information asymmetry. As long as “intangibles are in the dark” potential equity and debt sponsors miss the lucrative investment opportunities. Moreover, firms themselves typically lack reliable information as for the potential returns on intangible assets, as a result, misdirect operational and financial strategies.

Under conditions of poor transparency, technology buyout managers have opportunities to catch a “peach” - undervalued firm with highly exploitable intangible assets. In worth mentioning, that each IP asset (unlike most tangibles) can contemporaneously be leveraged to various scope of application. As a result, different external and internal opportunities of IP monetization arise: selling or exploiting IP internally, licensing-out or cross licensing of the IP to external parties, using as collateral for debt financing or even defensively in order to discourage competition.

The brief summary of core studies devoted to analyze the impact of LBO/IPO activity on target's innovating output (patenting activity).

On the base of findings provided we can conclude, that private equity managers, leveraging their wide network of contacts throughout the global technology and finance sector, are able to reduce capital market imperfections and enhance the efficiency of intangible assets utilization. For instance, historically, the practice of using intellectual property as collateral was almost unheard of. Bruce W. Burton, Emma Bienias, Candice K. Quinn. “Financing Alternatives for Companies: Using Intellectual Property as Collateral”, Stout Risius Ross - 2014In recent years, situation changed as different ways of IP collateralization arose: from intellectual property-backed loans and enhancement, royalty securitization to IP license -back transactions. Private equity managers use their expertise to engage the latest innovative financial engineering techniques to structure the LBO deal in the most effective way, varying debt levels in accordance with the certain risk profile of innovative target. Fortunately, nowadays, long-term viewed institutional investors have sufficient “dry power” to support buyout deals, as a result, private equity managers could use low debt levels and heavily hunt technology deals.

It worth mentioning, that not only private equity firms and institutional investors are unilaterally interested in technology buyout transactions. IP-intensive public companies, suffering from financial constrains (imposed by short-term market investors), usually prefer going private in order to focus predominantly on innovation activity instead of chasing for quarterly profits. According to Daniel Ferreira's (2012) paper “It is optimal to go public when exploiting existing ideas and optimal to go private when exploring new ideas.” Ferreira D., Manso G., Andre C. Silva. “Incentives to Innovate and the Decision to Go Public or Private”, The Review of Financial Studies, Vol. 27 (2014) Indeed, private equity firms, implementing sophisticated IP valuation techniques, forces target companies to focus innovation efforts primarily on the most perspective directions. Exploring the impact of private equity on economic growth in Europe, 2013 - psge 29

Despite the fact that, the increase in innovation activity after a buyout transaction was discovered in most latest related studies, one more question remained partially uncovered “whether private equity investors cause these changes or selectively invest in firms that are ripe for an increase in innovative activity” Josh Lerner, Morten Sørensen, Per Strömberg. “Private Equity and Long-Run Investment: The Case of Innovation”, Harvard business school, Working Paper 09-075 - December 2008. Indeed, the research part of current study is devoted to more precise ideal leverage buyout candidate estimation.

III. Empirical research: sample and data selection, methodology

3.1 Sample selection

Leveraged Buyout Sample

As we stated earlier, the aim of current research is to determine to which extent leveraged buyout activity is motivated by endogenous and exogenous factors. In order to provide an econometric proof of hypothesis examined we construct a complete sample of LBO deals from Capital IQ base. We designed the sample following strict requirements, they are:

1. The transaction is classified as “Leveraged Buy Out (LBO)”, Going Private Transaction or Management Buyout.

According to S&P Capital IQ classification of merger and acquisition transactions, Leveraged Buy Out is assigned when “a sponsor/management/individual acquires a mature business by combining equity with debt, raised by leveraging the business” https://www.capitaliq.com/help/sp-capital-iq-help/company-profiles/transaction-content-overview/definitions-features-mergeracquisition.aspx. This definition suits only for deals where “majority stake is being acquired (i.e. 50% or more)” https://www.capitaliq.com/help/sp-capital-iq-help/company-profiles/transaction-content-overview/definitions-features-mergeracquisition.aspx. As long as all shares held by shareholders are bought by an acquirer, and company goes private as a result of that deal, transaction re-classified in “Going Private Transaction”.

If a majority ownership of a company is required by target firm's management (either with financial sponsor or not), the deal is classified as “Management Buyout”.

Publicly listed companies as well as private entities can be involved in leveraged and management buyout transformation. Indeed, current study focuses primary on companies that once had been listed and after chose to make leveraged buyout transformation. We suppose that motives determining going private decision through LBOs differs much among public and private targets.

Moreover, the process of collecting pre-LBO transaction data for public targets is easier than for private ones.

2. We require Leveraged buyout transactions to be completed between January 1, 2004 and December 31, 2015. In other words, the sample includes closed deals in which a listed company becomes a buyout target between 2004-2015 years. Further, the list of transactions shortened, as our research focuses primarily on targets that went public after January 1, 2003.

3. Geographic location of target companies is strictly limited within developed markets: US and Canada, European Developed Markets or Asia/Pacific Developed Markets.

4. We excluded from estimated sample all LBOs in industry sector “Financials”: banks, insurance, real estate targets.

As a result, intermediate sample consisted of 464 closed deals. The aggregate characteristics of provided sample are described below.

Firstly, the number of leveraged buyout transaction is unevenly distributed among regions. Prevailing number of LBOs was conducted in United States and Canada - 251 transactions, when in European and Asia/Pacific Developed Markets closed only 109 and 104 deals respectively. We can suppose, that not only firm's characteristics along with economic climate conditions is of importance, but also legal system of a country matters when intensity of LBO activity is concerned. Jerry X. Cao (2010) empirically proved this statement stating that LBO activity is more dynamic “in countries with strong creditor's rights”, otherwise club deals prevails on LBO market. Following this logic, we trimmed sample (360 deals) by excluding Asia/Pacific Region

Picture 4. “Number of transaction by Sector”