英国金融学essay：论在商业融资中所有权结构理论

一般来说,在金融理论中所有权结构尚未分化。然而,在个人公司中利益相关者被广泛分散到各个不同的组。在大多数情况下,股东通过任命管理者代表来对公司活动进行控制。但是来自外部收购的威胁导致内部管理保留对所有权的控制。(Manne (1965), Martin and McConnell (1990))。这种观点认为,公司的业绩取决于受雇于该公司的所有权结构的分布。 Jensen和Meckling (1976)以及Berle和Means (1932)证明所有权结构如何影响公司的价值。

 

此外, Stulz(1988)通过他的模型解释了内部股权和公司价值之间的关系。 Morck, Shleifer and Vishny (1988)认为在内部股权和公司的价值中间有一个非线性关系。也有证据表明股权结构与公司绩效之间的联系。((Demsetz and Lehn (1985), Morck, Shleifer and Vishny (1988), Holderness and Sheehan (1988) and Hermalin and Weisbach (1987)).

 

在商业融资中所有权结构理论-The Ownership Structure theories in Business Finance

 

Conventionally, the ownership structure has not been differentiated in the theory of finance. However, the stakeholders in the individual firms are widely dispersed into different groups. In most cases, shareholders exercises control over firm activities by appointing managers to act on behalf of them. But the threat of outside takeovers induces the management to retain ownership control internally (Manne (1965), Martin and McConnell (1990)). This view has been argued that the firm performance depends on the distribution of ownership structure employed by the firm. Jensen and Meckling (1976) and Berle and Means (1932) demonstrate how value of firm is influenced by the ownership structure.

 

Additionally, Stulz (1988) explains through his model the relationship between the insider equity ownership and value of the firm. Morck, Shleifer and Vishny (1988) argue that there is a non-linear relationship between the insider equity ownership and value of the firm. There are also evidence to show link between equity ownership structure and corporate performance ((Demsetz and Lehn (1985), Morck, Shleifer and Vishny (1988), Holderness and Sheehan (1988) and Hermalin and Weisbach (1987)).

 

The investment management firms control huge amount of wealth and provide diversified portfolio management services to accredited investors like pension funds and other high net worth individuals. Regardless of enormous amount managed by such firms, there has been a very little academic research developed with respect to different ownership structures and their relationship with superior alpha generation. Some of the papers published are in regard to directors’ ownership (Chen, Goldstein and Jiang (2008)), portfolio manager ownership (Khorana, Servaes and Wedge (2007)), management ownership (Morch, Shleifer and Vishny (1988)) and equity ownership (McConnell and Servaes (1990)). In particular, the study of employee ownership in institutional investment management firms has been done recently by Dimmock, Gerken and Westberg (2009). This is the first paper to study the role of employee ownership and their relationship with the firm performance.

 

The purpose of this paper is to investigate the relationship between the employee ownership structure and superior alpha generation, by taking into account the global equity funds of the investment management firms. This paper further investigates whether such employee ownership structure of investment management firms perform better in different periods of cyclical events. In section 2 of this paper, I review the empirical literature related to the topic. For this purpose, I divide the discussion into two parts i.e on employee ownership and measures of fund performance. In section 3, I present data used in my analysis and explain methodologies by showing construction of variables and performance measurement techniques used. In section 4, I discuss the results. In section 5, I conclude by providing summary of the paper.

 

文献综述-Literature review

 

This chapter is discussed into two parts. In the first part, I discuss the published academic research of different types of ownership structures. In particular, I show ownership structure of portfolio manager, directors, management, equity and employee. Further, I try to relate these structures with the performance. Since this paper mainly focus on employee ownership, I further extend my literature in regard to relationship between employee ownership and agency problems, performance and portfolio risk. In the second part of literature review, I discuss different techniques in fund performance measurement including those which are used in this paper for calculating performance metrics.

 

所有权结构-Ownership Structures
 

 

There have been a few literature reviews on the board compensation and ownership. For instance, Tufano and Sevick (1997) show that board directors with greater incentives charge higher fund cost, resulting in lowering the performance of the fund. Cremers et.al. (2006) illustrate that fund performance is positively influenced by the independent board of directors. Since the responsibility of the fund returns lies with the fund manager, their incentives have an effect on the performance. Additionally, the fund manager would increase his ownership stake in the fund when he is more likely informed about the better performance of the fund. Khorana, Servaes and Wedge (2007) suggest a few incentive mechanisms to the fund manager. First, the bonus and salary of the fund manager is related to the fund performance. Second, the fund manager is dismissed for poor performance. This view is also supported by the Chevalier and Ellison, 1999 and Ding and Wermers (2005). Third, board should dissolve the fund management company which leads to removal of fund manager for bad performance. However, Kuhnen 2005 and Khorana, Tufano and Wedge, 2007 say that this mechanism is applied only in a very few cases. Khorana, Servaes and Wedge (2007) discover that the fund performance is also explained by the other characteristics and not only on the ownership. They find that fund managers who hold a significant stake in minor funds, have performed better and hence they hold such stake for longer time period.

 

Overall, Khorana, Servaes and Wedge (2007) study the research in three areas. Firstly, the investigation on the fund manager ownership and fund performance is very limited apart from the Chevalier and Ellison, 1999; who have mixed evidence in forecasting returns on fund. Second, the governance mechanisms would help align fund manager’s interest in the better performance of the fund. Third, they study relationship between the performance and ownership but there exists lot of arguments on whether the same theory applies if the fund changes its value by altering its ownership structure (e.g. Morck, Shleifer and Vishny, 1988 and McConnell and Servaes 1990).

 

员工所有制-Employee ownership:

 

Employee ownership is common and varies across different investment management firms. It is the amount invested in the firm by employees of such firm to acquire a share of ownership. This is different from the assets under management held by the firm. In some countries, mainly US where employee stock ownership plans (ESOP’s) are set up by the companies. It is presumed that employee ownership increases productivity and profitability of the firm. The key benefit is that there are tax benefits for the employee owned companies. Dimmock, Gerken and Westberg (2009) explain that employee ownership reduces the need for external monitoring. On the other hand, employee ownership creates a moral hazard problem as it rewards the collective effort and diversifies the responsibilities among all the employees.#p#分页标题#e#

 

Dimmock, Gerken and Westberg (2009) test employee ownership in the firm through different hypothesis. First, the cost to the firm decreases as employee importance increases and the value of the firm is dependent on the efforts of all employees. Second, employees with multiple roles are likely to be the owners, which is a result of optimal allocation of employees’ efforts across different tasks. Third, the cost of termination is less as the employee quality is known in the employee owned firm. Fourth, overall firm performance is rewarded which persuade a better cooperation among the employees. Overall findings suggest that executives, employees and portfolio managers who manage major proportion of firms’ total assets for longer duration tend to have higher ownership.

 

Dimmock, Gerken and Westberg (2009) show that employee ownership will not generate alpha if employees are optimally allocated to different tasks due to two reasons. First, marginal benefits will be eroded as the firms would change their ownership if employee ownership generated alpha. Second, clients’ investment allocations would affect irrespective of whether employee ownership generated alpha or was correlation with factors predicting alpha. Berk and Green (2004) illustrates that active management do not outperform passive benchmarks because of the decreasing returns to scale in investment management. However, chasing performance results in lack of persistence. Dimmock, Gerken and Westberg (2009) find that employee ownership does not generate alpha performance and hence the relation between the two is insignificant. They also test the relation between employee ownership and portfolio risk. The firm’s risk taking ability is altered by employee ownership by two different ways. First, employees try to avoid risk as they hold a major proportion in the firm. Second, employees have lower career concerns as their possibility of termination is low which causes them to take risk. Hence the portfolios managed by the individual employees of employee owned firms have high tracking errors, betas and standard deviations. The findings suggest that there is a positive correlation between employee ownership and tracking error due to lower career concerns resulting in higher portfolio risk taking.

 

员工所有制和代理问题之间的关系-Relationship between Employee ownership and agency problem

 

A large amount of literature has been in existence studying agency problem between investors and investment management firms. But only few have studied the agency conflict between employees and investment management firms. Agency problem arises as a result of separation between owners of the firm and those who have effective authority over the firm. Dimmock, Gerken and Westberg (2009) use employee ownership as a solution to reduce agency problems within the firms. The assumption is that higher employee ownership by way of employees managing larger proportion of assets under management, control over products and managerial responsibility for the executives over the firm will have a considerable impact on the firm value. However, such ownership may not always solve the agency conflict. But there exists other alternatives to the employee ownership.

 

The most common alternative is by way of direct compensation such as monetary benefits to employees. The main difference between the direct compensation and employee ownership is that the former is linked to individual performance and the latter with combined performance of all employees. Thus, the employee ownership is ineffective when the number of employees is high because the individual employee’s marginal contribution will be low. This results in agency problem. Therefore, employee ownership can be used as a solution to agency problem only when employee strength is low, the firm has fewer products and business segments.

 

Although Employee ownership reduces the individual performance incentives, it rewards the joint efforts of all employees. As a result there is a perfect distribution of incentives across the firm. This kind of distribution becomes important when employee has multiple roles to perform such as managing various products and holding different designations. As shown by Pomorski (2008) that funds having similar styles must have information sharing among them. Therefore, higher employee ownership is expected when the firms have fewer investment style products.

 

Dimmock, Gerken and Westberg (2009) show external monitoring by clients as another alternative for reducing agency problems between firm and employees. However, external monitoring is difficult in case of portfolios with active management as argued by Chen, Goldstein and Jiang (2008) and Cremers, Driessen, Maenhout and Weinbaum (2009). Cremers et al support the notion that higher employee ownership is mainly in smaller firms. There are also career concerns linked with poor performance among employees. The main concern is termination threat. The same is documented by Chevalier and Ellison (1999) and Khorana (1996) wherein they show that relationship between termination and performance is dependent on age of a portfolio manager whose ability to perform better will improve with age. Hence an older employee will have a low probability of termination than the younger ones. Dimmock, Gerken and Westberg (2009) also show that there is a negative relation between employee ownership and termination. Thus it is predicted that with increase in employee term will increase the employee ownership in the firm.

 

There are other explanations of employee ownership not related to agency matters. Fama and Jensen (1983b) and Demetz and Lehn (1985) explain that higher employee ownership exist in the firms with lower risk. This is because, in case of non-existence of agency issues, employees hold concentrated portfolios which make employee ownership unproductive. This lack of diversification alters incentives and forces the firm even to make low quality investments low risk projects and reduce employee risk. Lakonishok, Shleifer and Vishny (1992) show that firms with specialized products have higher ownership than the ones offering range of basic and low cost products.

 

员工所有制和性能之间的关系-Relationship between Employee ownership and Performance

 

There is a literature showing positive relation between skill of a portfolio manager and employee ownership (eg: Swenson 2000). it explains that employee ownership does not generate alpha even though there is a positive correlation between skill and ownership. This is due to two reasons. First, firms are selected by clients on the basis of net-of- fee alpha which would have an impact on fund flows if employee ownership predict alpha. Berk and Green (2004) show that if marginal returns are decreasing then clients will distribute funds with positive alpha to firms which will happen until there is zero alpha. Second, competition of products would alter employee ownership of firms till there is a zero marginal benefit if ownership generated alpha. Dimmock, Gerken and Westberg (2009) test if employee ownership generates alpha performance because of the fact that there may be a possibility of changes in employee ownership due to external industrial shocks which may result in imbalance of employee ownership.

 

员工所有制和投资组合风险之间的关系-Relationship between Employee ownership and Portfolio Risk

 

Many studies have focused on the employee features and portfolio risk such as Brown, Harlow and Starks (1996) and Chevalier and Ellison (1997) show inverse relation between portfolio risk incentive taking and performance. In the asset management sector, Del Guercio and Tkac (2002) show that alpha performance and fund are directly proportional that removes the need for incentives in risk taking. As Dimmock, Gerken and Westberg (2009) show that terminating an employee owner is difficult and hence employee ownership reduces career concerns. On the contrary, Chevalier and Ellison (1997) show that riskier portfolios are linked to lower career concerns. Hence the net result is unclear. Thus, employee ownership has positive and negative results. But a high risk and lower termination possibility are the two contradictory effects on the negative results of employee ownership.

 

II.基金业绩的措施-II. Measures of Fund Performance

 

The development of Capital Asset Pricing Model (CAPM) by the Sharpe (1964) and Lintner (1965) provided the practitioners and financial economists the tool to price the assets and adjust the returns against the risk. CAPM states that in equilibrium, expected returns are linearly related to the beta or systematic risk. To this day the CAPM is the most basic and primary models when it comes to asset pricing models. However, CAPM experienced many critiques from academics on the use of security market line to measure performance (Roll, 1978). Another important model developed by Jensen (1968) on the portfolio performance evaluation has been a controversy with respect to benchmark efficiency, timing and statistical significance.#p#分页标题#e#

 

The empirical studies have identified several asset pricing tests using non-beta factors such as size (e.g. Banz, 1981) and book to market factors (e.g. Rosenberg, Reid and Lanstein, 1985 and Fama and French, 1992) are relevant in explaining the variation in expected returns. These studies resulted into the development of multifactor models in evaluating the performance. Fama and French (1993) developed three-factor model including these additional factors for measuring the equity portfolio performance. An extension to Fama and French three-factor model is Carhart (1997) model, also known as Four-factor model. In this model, an additional factor of one year momentum anomaly is incorporated. This factor is captured from Jegadeesh and Titman’s (1993) momentum strategy which is robust to different time periods. This 4-factor model is consistent with model of market equilibrium and thus it is interpreted as performance attribution model.

 

Issues in fund performance measurements

 

There are key issues in measuring fund performance which affect the performance benchmarks (Kothari and Warner, 1997).

 

证券市场线(SML)-Security Market Lines (SML)

 

The security market line is represented in any linear factor pricing models. For example: in the CAPM, the expected returns on assets are a linear function of a beta with the market portfolio. Any deviation from the security market line is measured as alpha. This deviation is developed by Jensen (1968) as known as “Jensen alpha”. The SML is also applied to other multi-factor models such as Arbitrage pricing theory where asset returns are a linear function of factor sensitivities plus a non-diversifiable economic factor. In Fama- French model, excess returns are regressed against the size and book-to-market factors and the intercept in the regression is measured as alpha. In the absence of abnormal performance, the intercept in the regression should be zero (Kothari and Warner, 1997). They investigate the intercept properties involving CAPM, Jensen alpha and Fama- French model. They find that that intercepts are highly sensitive to choice of index and can be systematically nonzero.

 

Market Timing

 

The market timing is another property which depends on the fund manager’s ability, to shift to high beta stocks when returns on market are expected to be high. Tests on market timing ability have been on single and multi-factor asset pricing models. Jensen (1968) show that the non-stationarity in beta will have a downward bias on Jensen alpha. Kothari and Warner, 1997 perform simulations without involving market timing ability to test the importance of that on performance benchmark. They find that timing ability is a critical factor in explaining the time-varying expected returns and their findings is in line to the explanation of Ferson and Schadt, 1996.

 

Reward-risk ratios

 

The reward-risk ratios are sometimes measured by Sharpe ratio. It is a ratio of excess market returns to standard deviation. Graham and Harvey, 1997 explain that the Sharpe ratio measures performance for dynamic asset allocation strategies. Such strategies are evaluated using benchmark returns which are weighted average of the riskless and value-weighted market returns having the same standard deviation as the portfolio. Kothari and Warner, 1997 explain how the Sharpe ratios are higher than the value-weighted index when there is a departure from CAPM. They find that in formulating a mutual fund benchmark, too much reliance on the value-weighted index will have implications.

 

There are enormous amount of academic literature discussed and debated on the fund performance techniques. It is an area of interest which is not as straight forward as one can imagine. This paper focuses on standard performance measures in addition to the simple techniques.

 

Jensen’s alpha

 

There have been many models and tests conducted to price the assets and time the market. Most of the fund managers are interested in the abnormal performance of their portfolios. Hence they look for alpha. Jensen’s alpha is perhaps the most convenient method most practitioners use. However, there are other models developed by Treynor and Mazuy (1966) and Henriksson and Merton (1981) which is based on Jensen’s alpha (Jensen 1968).

 

Jensen’s alpha is used to measure the performance relative to security market line. It is also the intercept from the Sharpe-Lintner CAPM regression of portfolio excess returns on the market excess returns over the sample period. The performance measure used by Jensen’s alpha is based on the following regression:

 

Where,

 

= is the excess return of portfolio p over risk free rate in period t.

 

= is the regression intercept and measure of performance (Jensen’s Alpha)

 

= is the regression slope coefficient and systematic risk.

 

= is the excess return on the market portfolio.

 

= is the white noise error term.

 

Black, Jensen and Scholes (1972) used Jensen’s alpha to test CAPM. If CAPM holds in equilibrium then all assets on SML and the alpha would be equal to zero. If the alpha is positive after the regression is performed would mean that the portfolio has outperformed the market after adjusting for risk.

 

An altered model of Jensen’s alpha has been developed by Fabozzi and Francis (1979) to test the market timing ability. In this model alphas and betas are open to varying market conditions. They find that there is no considerable change in alphas to varying market conditions and also could not find evidence on manger’s ability to time the market. The model is given as below:

 

Where,

 

= is a dummy variable i.e. one if it is a bull period and zero otherwise.

 

= is a bear market beta.

 

= is the difference between the bear and bull market so that bull market beta is .

 

= is the bear market alpha

 

= is the difference bear and bull market alphas so that bull market alpha is .

 

Fama- French three factor model alpha

 

An extension to CAPM regression is Fama-French three factor model alpha. This model includes the additional factors to help explain better the excess returns on asset than the traditional CAPM. The model is given below:

 

Where,

 

= is the expected average return on three small portfolios less the average return on three big portfolios.

 

= is the expected average return on two value portfolios less the average return on two growth portfolios.

 

SMB and HML are referred to as high minus low book-to-market portfolio return and small minus big size portfolio return in a period. The detailed construction of these additional factors is illustrated in Fama and French (1993).

 

The above three-factor model received critiques from the academics which turned out to be very similar to CAPM i.e. the factors did not explain the variation in stock returns. A further extension to Fama- French model is referred to as Carhart model (1997) or four-factor model. The additional factor of one year momentum anomaly is captured from Jegadeesh and Titman (1993). The model is as follows:

 

Where,

 

= the expected average return on the two high prior return portfolios less the average return on the two low prior return portfolios.

 

Carhart (1997) notes that the time variation in stock returns is better explained through the correlations between these four factors and market proxies. He states that the four-factor model can "be interpreted as a performance attribution model, where the coefficients and premia on the factor-mimicking portfolios indicate the proportion of mean return attributable to four elementary strategies: high versus low beta stocks, large versus small market capitalization stocks, value versus growth stocks, and one-year return momentum versus contrarian stocks" Carhart (1997, p. 61).

 

Sharpe Ratio

 

Sharpe ratio also known as Sharpe measure is the most widely used risk adjusted performance tools in the academic research. The Sharpe ratio was introduced by William Sharpe in 1966. It is a ratio of average excess return of portfolio divided by standard deviation of returns. Excess returns are calculated by subtracting risk-free rate from the average return of a portfolio. It is a measure that provides reward to volatility trade-off (Sharpe, 1966). Sharpe ratio is used by many research firms and in particular it is most popular in hedge fund industry. In order to be statistically accurate, minimum of 3 years of monthly data is used in computing this measure. The ratio is given as:

 

Sharpe Measure =

 

Where,

 

= is the average return on a portfolio#p#分页标题#e#

 

= is the average risk free rate of return

 

= Standard deviation of excess return

 

In spite of wide use of Sharpe ratios in practice, it has been identified with noteworthy drawbacks. For instance, when there are non-normal returns, it is considered to be inappropriate (Goetzmann, Ingersoll, Spiegel and Welch (2002)) and when there are different investment horizons, it cannot be compared (Sharpe, 1994 and Lo (2002)). Richard Michaud (1989) says that the limitation in Sharpe ratio is in “inputs” namely expected returns and standard deviations as these have estimation error. On the other hand, Lo (2002) derived the distribution of Sharpe ratios under various assumptions but did not consider the statistical difference between the two Sharpe ratios in the existence of estimation error. Jobson and Korkie (1981) failed to find the difference between Sharpe ratios under the assumption of multivariate normality as their test lacked power.

 

参考比率(IR)-Information Ratio (IR)

 

Information ratio is a performance tool used by the managers to assess the risk adjusted return on the portfolio. IR is measured as the difference between the portfolio returns and benchmark returns divided by the standard deviation of those returns. It measures the skill of the manager to generate benchmark relative excess returns. The higher the ratio implies that manager has better skill as the active returns i.e. difference between the return on portfolio and return on benchmark are higher at a certain level of risk. The ratio is shown as below:

 

Information ratio =

 

Where,

 

= is the return on the portfolio

 

= is the return on the benchmark

 

= is the risk or volatility of the active returns.

 

The difference between the information ratio and Sharpe ratio is that the former measures active return against benchmark return and the latter measures excess return against risk free rate. Both are divided by their standard deviation of the differences between the returns. Information ratio is not to be confused with the Jensen’s alpha or risk adjusted excess return.

 

Clarke, Silva and Sapra (2004) demonstrate that a portfolio has various constraints due to which an investor cannot fully make use of the information resulting into information loss. Grinold and Kahn (2000) describe the effect on portfolio due to long only constraint. However, Clarke, Silva and Sapra (2004) show an improvement in information efficiency by lifting these constraints to a maximum possible extent. This is done by implementing transfer coefficient (Clarke, de Silva and Thorley (2002)). Transfer coefficient (TC) is computed as correlation between the risk-adjusted return and risk-weighted securities in the portfolio. A higher TC implies that portfolios are efficiently constructed as it captures constraints on the information ratio. Therefore, information ratio is shown as below:

 

IR = TC*IC*Sqrt(N)

 

Where,

 

TC = is the transfer coefficient

 

IC = Information coefficient i.e. correlation between expected and actual returns

 

N = is the number of independent securities in a portfolio.

 

The above equation is an extension to the fundamental law of active management as developed by Grinold (1989). It indicates the effect of transfer of investor’s information into weights of portfolio and also resembles the quality of information.

 

Tracking Error (TE)

 

Tracking Error is an integral aspect of fund management. It is a measure of how closely portfolio behaves like an index or benchmark. It is formally defined as the standard deviation of the difference between the portfolio returns and benchmark returns. A portfolio with TE close to zero is presumed to replicate the index movement, normally; an index fund will have almost a zero tracking error, while an actively managed portfolio would have a higher tracking error. The tracking error is calculated as below:

 

Tracking Error =

 

Where,

 

= is the returns on portfolio

 

= is the returns on index or benchmark.

 

Tracking error can be measured historically to report the performance or can be used to forecast the tracking error which is used by portfolio managers as risk management tool. However, dividing this tracking error by the active return will give the information ratio (as discussed above).

 

In order for the tracking error to be more accurate, the benchmark must be specified in the investment mandate and hence the portfolio managers must have benchmark portfolio which is investible in nature (Rennie and Cowhey (1990)). The restrictions on the portfolio selection due to tracking error constraints have been examined by Roll (1992) and Jorion (2003). Korkie and Turtle (2002) find a solution to the portfolios having constraints by adding up the optimal portfolio and “self-financing” portfolio. A.Almazan et.al (2004) shows the worldwide appearance of these constraints in the US context.

 

In the third and fourth quarter of 2009, the fund flows of investment management firms have increased due to the normalization of global capital markets and rise in corporate profits. The total net inflows of such investment management firms worldwide were over $200 billion as of December 2009. The negative impact on global equity indices during late 2007 and 2008 was reversed in second half of 2009, but such recovery remains 73% below peak levels of $759 billion in late 2006. The rise in the global equity market and resulting net inflows benefited the non-US equity products, increasing their total assets under management roughly by 3.2% in 2009.