Sunday, September 25, 2011

Women in Islam: Development and Integration (the real priority)

During the last forty years (the age of the blessed awakening ) had made many efforts have been made to reform the situation of Muslim women, and I can say that the order of 80% of these efforts were allocated on specific issues, namely: women's hijab, and mixing with men and conditions of her work and function and to prove (nominaly) that Islam had liberated and had honoured her in its very very early stage, and much before many other nations. The efforts made in the development of women and her integration in the midst of the social movement did not reach 20%, which resulted in the marginalization of women's role in the rebirth of the nation and community development. I imagine that what is required is the opposite: 80 percent of the effort on women development ... The remaining 20 percent be spent on the maintenance and preservation of the women identity, protection, and modesty."

Au cours des quarante dernières années (l'âge de l'éveil béni) avait fait de nombreux efforts ont été déployés pour réformer la situation des femmes musulmanes, et je peux dire que l'ordre de 80% de ces efforts ont été alloués sur des questions spécifiques, à savoir: les femmes hijab, et le mélange avec les hommes et les conditions de son travail et de la fonction et de prouver (nominalement) que l'islam avait libéré et lui avait honoré dans son stade très très tôt, et bien avant beaucoup d'autres nations. Les efforts consentis dans le développement de la femme et son intégration dans le milieu du mouvement social n'a pas atteint 20%, ce qui conduit à la marginalisation du rôle des femmes dans la renaissance de la nation et le développement communautaire. J'imagine que ce qui est requis est le contraire: 80 pour cent de l'effort sur le développement des femmes ... Les autres 20 pour cent sera consacré à l'entretien et la préservation de l'identité des femmes, la protection et la modestie. "

Durante los últimos cuarenta años (la edad del despertar bendito) había hecho muchos esfuerzos se han hecho para reformar la situación de las mujeres musulmanas, y puedo decir que el orden del 80% de estos esfuerzos se destinaron sobre temas específicos, a saber: las mujeres hijab, y la mezcla con los hombres y las condiciones de su trabajo y función, y para demostrar (nominalmente) de que el Islam había liberado y había honrado en su etapa muy temprana, y mucho antes de que muchas otras naciones. Los esfuerzos realizados en el desarrollo de las mujeres y su integración en el medio del movimiento social no supera el 20%, lo que dio lugar a la marginación del papel de la mujer en el renacimiento de la nación y el desarrollo comunitario. Me imagino que lo que se requiere es lo contrario: el 80 por ciento del esfuerzo en el desarrollo de las mujeres ... El 20 por ciento restante se gasta en el mantenimiento y la preservación de la identidad de la mujer, la protección y la modestia."


خلال الأربعين سنة الماضية (هي عمر الصحوة المباركة) بُذلت جهود كثيرة في سبيل إصلاح حال المرأة المسلمة، ويمكن أن أقول إن نحواً من 80% من تلك الجهود كان يصب في مسائل محددة، هي: حجاب المرأة، واختلاطها بالرجال وشروط ممارستها للعمل والوظيفة وإثبات أن الإسلام حررها وكرمها في وقت مبكر جداً، وقبل كثير من الأمم. أما الجهود التي بُذلت في تنمية المرأة وزجها في خضم الحركة الاجتماعية فإنها لا تزيد على 20%، وهذا يعني بالضرورة تهميش دور المرأة في نهضة الأمة وتطوير المجتمع. وأتصور أن المطلوب هو العكس: 80% من الجهد في تنمية المرأة ... أما 20% الباقية فتصرف على صون المرأة وحفظها وحشمتها."

عبدالكريم بكار بعنوان (هي هكذا: كيف نفهم الأشياء من حولنا)

 

Monday, September 19, 2011

Academic Job Market: How To?

Critiques on some Finance papers

  • Can book-to-market, size and momentum be risk factors that predict economic growth? 
  • The Debt-Equity Choice 
  • The Expiration of IPO Share Lockups  
  • Dividends, Share Repurchases, and the Substitution Hypothesis   
  • Debtor-in-Possession Financing and Bankruptcy Resolution:Empirical Evidence  
  • Asset Pricing with Conditioning Information: A New Test 

https://docs.google.com/document/pub?id=1PgPaI7Oj_WIDi0BHQov7kuf2MNaeQWsUfvfNvJqWcvQ

Can book-to-market, size and momentum be risk factors that predict economic growth?

Jimmy Liew and Maria Vassalou
Journal of Financial Economics 57 (2000) 221-245
Summary
Fama and French (1992) show that the Capital Asset Pricing Model (CAPM) cannot explain the cross-section of asset returns in the US. They propose an alternative model which includes, apart from the market factor, a factor related to book-to-market (B/M) which they call High-Minus-Low (HML), and a factor related to size (MV) called Small-Minus-Big (SMB). In a series of articles, Fama and French (1992, 1993, 1995, 1996) show that their model does a good job explaining average equity returns. Nevertheless, it still remains unknown whether their book-to-market and size-related factors have any economic interpretation. Researchers have found little evidence of a relation between these three return-based anomalies and intuitive economic risk factors.
In this paper, the authors test whether the profitability of HML, SMB, and WML can be linked to future Gross Domestic Product (GDP) growth.  They construct return-based factors for ten developed markets. In addition to HML and SMB factors, they also include the WML (winners minus losers) factors which are returns to long-short portfolios constructed using momentum information. Using regression analysis, Liew and Vassalou find that the HML and SMB portfolios are related to future growth in the real economy.  High portfolio returns precede periods of high GDP growth. Similarly, low portfolio returns are associated with low future GDP growth. Also, their inclusion of other business cycle variables did not eliminate the forecasting ability of HML and SMB.  Moreover, the authors showed that a positive relation also exists between the returns of HML and SMB and future economic growth.  Finally, they have also shown that the HML, SMB, and WML zero investment portfolios provide positive returns and that the HML and SMB strategies generate significantly lower turnover than the WML strategy.
Comments
This paper by Liew and Vassalou was the first to suggest that HML and SMB contain information useful in predicting future GDP growth. I believe that a good literature review would have been helpful in order to introduce the different contributions in this area.
My first comment concerns the data selection process.  The authors did not specify on which basis they were selecting the foreign countries. Fama and French (1998) based their selections on the countries with MSCI accounting ratios (B/M, E/P, C/P and D/P) for at least ten firms in each.  Moreover, MSCI includes only a subset of the firms in any market, mainly those in Morgan and Stanley’s EAFE index or in the MSCI index for a country’s market, and this means that most of these firms are large.  A test for size effect should have been performed in order to control for the significance of the results.  In addition, the returns that are calculated from MSCI data are not without problems.  
As the information about dividends is only available from the dividend yield (which is the ration of a trailing year of dividends to the end-of-month stock price), we can calculate the annual return with accuracy which are enough to estimate expected returns.  However, the test for the asset pricing models will be imprecise unless returns for shorter intervals are used.  The authors calculated monthly total returns in local currency by spreading evenly the monthly dividends throughout each year.  On the other hand, this approach assumes that the capital gain component of monthly returns reproduces the volatility and covariance structure of total monthly returns. In addition, because their portfolio construction procedure results in the creation of 27 portfolios, some of the portfolios for Italy, the Netherlands, and Switzerland, in which the number of securities is much smaller than for the other countries, may contain as few as one to three stocks. Therefore, the results for these countries cannot be meaningful.  Moreover, their portfolio construction uses three sequential sorts, which differ from the independent sort used by Fama and French (1993), and this makes their results specific to this sorting procedure. Also, the authors did not discuss any possible correlation of returns across markets.  The existence of such correlation might produce biased results as well.
Other possible areas that could be covered in this paper in order to make it different from the Fama and French paper would be to use multivariate models to help clarifying the fundamental roles played by correlated macroeconomic factors examined in prior research, as well as assessing the role of other factors.  Furthermore, the authors can identify the incremental information contained in the market portfolio, after controlling for the selected macroeconomic fundamentals. The prior literature focused on only partially overlapping sets of macroeconomic state variables such as growth expectations, default risk, the term structure of risk–free interest rates, and inflation. If the state variables included in different studies are uncorrelated, this will not cause any problems. However, when the state variables studied are correlated, the significance of included macroeconomic instruments as fundamental risk factors will be ambiguous and results will be biased, because of a correlated omitted variable problem.
Some innovations can provide possible solutions.  For example, since GDP data is only reported quarterly, one can use instead industrial production data as a proxy for economic growth as it is reported monthly.  This can be done by using future realized economic growth as a proxy for innovation in economic growth expectations. Although this creates an errors–in–variables problem rendering model parameter estimates unreliable (Petkova and Zhang, 2004; Greene, 2003), one can avoid this by adopting an approach similar to Vassalou (2003) which creates a factor–mimicking portfolio to capture the change in industrial production growth expectations over the next year. The factor mimicking portfolio is constructed by regressing log changes in realized industrial production growth over the next year on the excess returns of a set of base assets and a set control variables capturing information on expected asset returns and growth (Lamont, 2001; Breeden et al., 1989).  Moreover, it would be interesting to see ho the results are affected when we use log(GDP) (as it has been always used in economics) instead of GDP with no transformation.
        Finally, momentum does require frequent trading. Annual winners and losers will not change that often, but the winning and losing portfolios must still be turned over at least once per year.  Carhart (1997) calculates transactions costs and concludes that momentum in not exploitable after those costs are taken into account.  Maskowitz and Grinblatt (1999) note that most of the apparent gains come from short positions in small, illiquid stocks, and positions that also have high transactions costs.  They also find that a large part of momentum profits come from short positions taken November, anticipating tax-loss selling in December.  These findings point to the importance of small microstructure effects for the risk and return in asset market that one should also consider.
 Critical Review of

The Debt-Equity Choice

Armen Hovakimian, Tim Opler and Sheridan Titman
Journal of Financial and Quantitative Analysis Vol 36 (1), Mar (2001) 1-24
Summary
A firm's history plays an important role in determining its capital structure. Cross-sectional studies of leverage ratios reveal that a firm's past profitability provides about as much explanatory power as proxies for firm attributes suggested by theories that trade-off the various costs and benefits of debt financing. The authors in this paper employ a two stage regression procedure that allows them to gauge the relative importance of a firm's history, its attributes and market conditions in the determination of its capital structure choice. In the first stage, debt ratios from a sample of Compustat firms during the 1979 – 1997, are regressed cross-sectionally on many of the variables used in earlier cross- sectional studies. The difference between a firm's actual debt/assets ratio and its predicted ratio is then included in the second stage logit regression as a predictor of whether the firm issues debt or equity. The second stage logit regression also includes variables that measure the extent to which asymmetric information and market conditions affect the debt/equity choice. Among their conclusions, one indicates that the choice of the form of financing should be examined separately from the choice of the size of financing.
Comments
The authors examined one debt/asset ratios which is the book value of short-term plus long term debt divided by the book value of debt plus the market value of equity. This ratio probably provides the better specification if managers focus on market value ratios when determining their capital structure choices.   However, since there is at least anecdotal evidence suggesting that managers often focus on book values in making these choices the book value of short-term plus long term debt divided by the book value of total assets should have been studied as well.
Their two stage approach differs from the empirical strategy of Mackie-Mason (1990) and others who estimate a similar model, but all in one stage. Mackie-Mason includes, for example, R&D spending/sales in his logit regression since there are theories which suggest that high R&D firms tend to use less debt financing. However, for issues that are relatively small, this argument implicitly assumes that high R&D firms tend to be overlevered prior to the issue, and we have no reason to believe ex ante.
Moreover, since they are sampling firms that issued debt or equity rather than a combination, the two step procedure will also be misspecified when a large amount of new capital is raised. This also means that the size of the offering needs to be included in their specification and that it should be interacted with the debt ratio of the firm. This might be done through inclusion of a dummy variable, equal to one, for those observations where the new financing increases the assets of the firm by a certain amount and the product of this dummy variable and the firm's debt ratio.
The authors could also get further insights from an analysis of various subsets of their sample. For example, they would expect that smaller firms may be more subject to asymmetric information problems than large firms and explore this possibility by separately estimating their second stage regression on size stratified subsets of their sample. If asymmetric information has a large effect on the debt/equity choice, then the choices of smaller firms should be more influenced by their past stock performance and by market conditions. They can also split the sample by other indices of the severity of informational asymmetry including a dummy for whether a firm is paying a dividend and the extent to which their stocks are followed by analysts.
Most of the studies of the firms’ debt-equity issuance (reduction) choice utilize the standard Probit model. Meng and Schmidt (1985) show that Bivariate Probit estimation is more efficient than that of independent Probit equations when the error term of the two decisions are correlated. On one hand, when unobservable factors that encourage firms to issue debt also could lead them not to issue equity, the error term of the interdependent decisions will be highly correlated, which in return justifies the use of the Bivariate Probit estimation method. Moreover, using the independent Probit equations model to study the firms’ debt-equity issuance (reduction) choice leads to a loss of information due to exclusion of combined issues of debt and equity. On the other hand, the unobservable factors that encourage firms to issue debt or equity could also affect the issuance (reduction) size as proportion of the firms’ financing deficit (surplus). In this case the Tobit estimation method is justified due to the censoring in the data and to incorporate these unobservable factors into the estimation. One can study the factors affecting the firms’ choice of the form of financing (repurchase) and the size of issue (repurchase) using a two stage Bivariate Probit – Tobit model. The first stage would examine the factors affecting the firms’ choice of the form of financing (repurchases) using Bivariate Probit model. Simultaneously, the second stage would examine the factors that affect the size of issue (repurchases) given that the firm decides to use a particular form of financing (repurchases).  The diagnostic tests might prove that using the independent Probit equations model to study the debt-equity choice yield inefficient estimators. Using the two stage Bivariate Probit-Tobit model might rejects Hovakimian, Opler, and Titman's (2001) finding, due to correlation between the factors affecting the choice of financing and the size of issue.
Debt-equity choice analysis, used in Hovakimian et al. (2001), does not allow us to test how the deviation from the target affects each type of security issue or repurchase. It is possible, for example, that firms issue (retire) debt primarily when they want to adjust their leverage toward a higher (lower) target, but that they issue (repurchase) equity primarily to take advantage of favorable market conditions.  One can test the target leverage hypothesis separately for equity issues, debt issues, equity repurchases, and debt reductions. This can be done by examining the pattern of changes in leverage ratios and their deviations from target ratios around these corporate financing events.
Finally, some comments concern the data selection.  The period includes the hot market period in 1983, 1991-1996, where seasoned equity issuance is high.  This means that such a deviation should be interpreted very cautiously or excluded from the sample.  In addition, the measure of short term debt and long term debt are biased as firms frequently report revolving bank debt and commercial paper (short tem debt) as long term debt when they plan to roll it over. Multicollinearity and error-in-variables problems, due to the two stage regression technique, and multiple appearances of the same firms in the sample, can be the source of some results bias in this paper and can cause inconsistent conclusions with previous literature.
 Critical Review of

The Expiration of IPO Share Lockups

Laura Casares Field, Gordon Hanka
Journal of Finance Vol 56 (2), Apr (2001) 471-500
Summary
IPO lockup agreements prevent insider sale of shares for a specific period of time (often 180 days). This paper examine the share price reactions around the expiration of IPO share lockups and try to find several hypothesis that might explain its existence.  Their results indicate statistically significant negative abnormal return (AR) (-1.5%) in the event window surrounding the expiration date and a permanent 40 percent increase in trading volume.  These effects were also three times larger in venture-backed firms compared to non-venture backed firms. When they looked at insider share sales in the year after the IPO, they found direct evidence that venture-capital (VC) investors sell more aggressively than other pre-IPO shareholders.  The authors also found permanent, parallel declines in both the bid and ask price and they conclude that the AR is not caused by a change in the proportion of trades at the bid price, temporary price pressure, or increased trading costs.  Their cross-sectional tests showed that the AR may be partly caused by downward sloping demand curves or by consistently larger-than-expected insider sales.  These results provided only a lower bound on the frequency of early share sales, as the data did not include sales by low-level employees, share distributions by VC partnerships, or effective share sales via hedging techniques such as forwards, puts, collars, or borrowing against shares. Their sample consisted of 1,948 IPO lockup agreements in the 10-year period from 1988 through 1997.  
Comments
My first concern in this article is about the data that was used.  As it was mentioned by the authors, the SDC data and those that were present in the IPO prospectuses differed by a large percentage when they looked at the number of shares offered, the length of lockup period, and the number of shares locked up.  They also showed that the SDC data are wrong or missing in 45% of the cases.  Thus, even by using the fraction of shares not sold in the IPO as a proxy for the fraction locked up (correlation 0.7), the results might still be inaccurate.  The fact that they claim that their results are not different when they use the noisier measure, might be due to another variable which they don’t know to affect both cases.  Using the data they collected from the IPO prospectuses would have been safer in this case.
Another point concerns the measure of AR.  It would have been interesting to see whether or not the results were affected by time variation in betas.  One possible way to do that is to use two estimation approaches for AR as was performed by Brau et al (2004).  The first one would rely on beta estimates obtained from regressing company daily stock returns beginning for 90 days prior and ending 11 days prior to lockup date on the CRSP equally-weighted return index, and the second approach utilizes a beta estimate obtained from a 200-day window commencing 11 days after the lockup expiration date.
The authors looked at many hypotheses to explain the negative abnormal return but did not find a conclusive one.  The lockup expiration date has institutional characteristics that are similar to those at the IPO date, and asymmetric information has been suggested as an important determinant of IPO underpricing.  We can try to see whether or not we should expect the same factors that affect underpricing to have explanatory power at the lockup expiration date.  Ibbotson and Ritter (1995) state that investors are willing to pay more for a firm with lockup agreement for two reasons:
  1. any negative information being withheld is likely to be divulged before the lock-up shares can be sold, reducing the benefit of withholding information
  2. as long as insiders retain large holdings, their incentives are aligned with outsiders’ incentives.
Moreover, many empirical works have found that retained ownership by insiders at the date of the IPO is positively related to firm value.  However, lockup periods can be relatively short and this means that little mandated information is disclosed between the IPO and the lockup expiration date. Therefore, the lockup agreement cannot mitigate informational asymmetries that exist between insiders and outsiders.  In addition, lockup expiration will increase the potential for unaligned insider and outsider incentives, and this makes the potential agency costs decrease investor demand for shares, assuming that this lack of alignment adversely affects general shareholders.  Thus, any withheld information about future prospects is more likely to be negative than positive and this will in negative AR in days preceding lockup expiration date.  Bank (1999) explains the cause of the negative stock price reaction to be cause by the expectation of the sale of newly-released lockup shares in the open market, and Browning (1999) reports that investors worry about a ‘flood of sales’ and sell stocks in advance of lockup expiration.  
It is thus interesting to look at evidence for information asymmetry between insider and outside shareholders at the lockup expiration date.  Some proxies that can be used for asymmetric information are the underwriter reputation(as underwriter prestige is associated with marketing of lower risk IPOs (Carter and Manaster 1990, Hanley 1993), size (as larger firms are expected to have greater information available to markets and we would expect less uncertainty surrounding the pricing of these firms (Barry and Brown 1984), growth opportunities (as there is more uncertainty regarding the valuation of high growth firms (Garfinkel 1993), and offer price (as offer price data constitute a measure of risk of the IPOs (Beatty and Ritter 1986, Tinic 1988).
Other lockup parameters that the authors could have used to increase the significance of their results and help them assessing their hypotheses are the number of days in the lockup period as the longer the period the more information that will be available for the market, and the percentage of shares in lockup as those with less than 100% in lockup can signal to the market with their trading of unlocked shares.  
Some other related works to be looked at are the ones by Brav and Gompers (2000 and 2003), and Tolia and Yip (2003).    Brav and Gompers (2000) provide evidence on the role of analysts around lockup expiration.  They show that analysts, both affiliated and unaffiliated, tend to issues more optimistic earning forecasts at the time of the lockup expiration.  Brav and Gompers (2003) find support for the notion that lockup serve as a commitment device to overcome moral hazard problems subsequent to the IPO.  Firms that are unprofitable, with low B/M ratio, and that go to public with lower-quality underwriters and are not venture capital-backed have significantly longer lockups.  Finally, Tolia and Yip (2003) try to investigate whether the stock price behavior around the lockup expiration date is different for “hot” (with first day returns between 10 and 60%) and “cold” (with zero or negative first day returns) IPOs.  Their methodology; however, need to be further explored in order to account for other factors that will affect this difference in the AR.
 Critical Review of

Dividends, Share Repurchases, and the Substitution Hypothesis

Gustavo Grullon, Roni Michaely
Journal of Finance Vol LVII (4), Aug (2002) 1649-1684
Summary
The three goals of this paper are to analyze the recent trend in share repurchases, to determine if share repurchase is a substitution for paying out dividends, and to try to explain the reason why firms did not substitute repurchases for dividends earlier.  The authors use a sample of 15,843 firms over the period 1972 to 2000 from Industrial Compustat files.  When assessing the first objective, the authors find that in the last 15 years, the majority of the firms used share repurchases instead of dividends to initiate cash payouts.  The larger firms did not cut the amount of dividends paid, but the growth rate of the dividends was found to be lower than what it used to be in mid 1980, while the amount of repurchases was higher.  When looking at the second objective of the paper, the authors  find that the marked increase in share repurchase programs in  the United States has been financed with potential increases in dividends, and that the payout ratio of the firms has remained relatively stable, which supports their substitution hypothesis.  Using Lintner’s (1956) dividend model to generate expected future dividends payments, Grullon and Michaely find that dividend forecast errors are negatively correlated with share repurchase activities.  The authors also report that the market reaction around the announcement of dividends decreases is significantly less negative for repurchasing firms than for non repurchasing firms. They also show that differential taxes between dividends and capital gains seem to matter in hat the market reaction to repurchases is more positive when the tax gains from them relative to dividends are larger.  Finally, when looking at the third goal of the paper, the authors conclude that share repurchase activity experienced a upward shift after the adoption of Rule 10b-18, which is consistent with the idea that share repurchase were restricted in the past.
Comments
The question of how corporations choose their payout policy between the two has attracted considerable attention from researchers in the last two decades. One of the most significant trends in corporate finance during the 1990s was the increasing popularity of open-market stock repurchase programs. Share repurchases have increased over time, and now constitute an economically important source of payouts. There are several comments that the authors of this paper can address to better understand the interaction between dividends and share repurchases.
First, as a preliminary step to investigating the substitution hypothesis between dividends and share repurchase, the authors could have regressed share repurchases (RP) on dividend changes (ΔD), repurchase payout ratios (RP/Y) on dividend payout ratios (D/Y), and repurchase payout ratios (RP/Y) on dividend changes (ΔD).  This would help determining whether these two are real substitutes or complements. Share repurchases can also complement dividends as a method of returning cash to shareholders. These two methods are not necessarily close substitutes:
 
  1. Dividends received may be subject to income tax, whereas repurchase receipts may be subject to capital gains tax. The so-called ‘Dividend Policy Puzzle’ in the US is founded on this difference. Dividends dominate share repurchase as a method of distribution in spite of the fact that tax on capital gains is lower. (However, in 2003 President Bush proposed the abolition of taxation on dividend income. This would serve to remove the tax disadvantage of dividends.)
  1. The signalling properties may differ. For example, variation in the rate of change in dividends may signal good or bad news. Share repurchases, on the other hand, are generally interpreted positively.
  2. Share repurchases are relatively lumpy and subject to greater managerial discretion. Dividend payments are regular and generally smoothly increasing.  
  1. Share repurchases may involve greater ‘out-of-pocket’ expenses such as fees to merchant bankers
  1. Repurchases may be associated with wealth transfer between shareholders because, unlike dividends, they are non-proportional.
Consistent with the above, Jagannathan, Stephens and Weisbach (2000) found that, for US companies, repurchase and dividends are used at different times from one another by different kinds of firm. Repurchases are very pro-cyclical, while dividends increase steadily over time. Dividends are paid by firms with higher ‘permanent’ operating cash flows, while repurchases are used by firms with higher ‘temporary’ non-operating cash flows. Repurchasing firms also have much more volatile cash flows and distributions. Finally, firms repurchase stock following poor stock market performance and increase dividends following good performance. The authors comment that ‘these results are consistent with the view that the flexibility inherent in repurchase programs is one reason why they are sometimes used instead of dividends’.
Second, there are three ways to look at dividend and share repurchases policies. The methodology must allow for different decision-making processes. It should be possible to test three structures, (i) unrelated decisions (i.e., dividend and share repurchases choice are not related), (ii) simultaneous decisions (i.e., dividend and share repurchases choices are mutually related), and (iii) sequential decisions (i.e., firms first decide on whether to pay out or not, and thereafter choose between dividends and share repurchases). In order to do that, one can use three different logit models to capture these three decision-making processes.
Third, share repurchases can be simultaneously motivated by various combinations of many reasons that are not mutually exclusive. Grullon and Ikenberry (2000) provide five theoretical explanations for stock repurchases. These are: to distribute funds in excess of investment opportunities (free cash flow or agency motivation); to signal the market that its shares are undervalued or simply to take advantage of such undervaluation to increase the wealth of the remaining shareholders (information asymmetry motivation); to fend off unwanted takeovers (anti-takeover motivation); to achieve or maintain target leverage ratios, when such ratios fall below perceived optimal levels (target-leverage-ratios motivation); and to avoid the negative impacts of dividends on stock options’ values or to impact or manipulate reported EPS in one or both of its reported forms primarily due to the presence of ESOs (stock options motivation).
Grullon and Michaely report in this paper that, by repurchasing stock rather than increasing dividends, firms are substituting share repurchases for cash dividends, although the authors do not attempt to empirically link such substitution to the presence of ESOs. Another way posits that share repurchases are motivated by management’s desire to “undo” the dilution created by stock options. The concept of the undo dilution hypothesis, as defined by Weisbenner (2000), is that, by buying back shares and thus decreasing the denominator in EPS calculations, the effects of the additional shares which are included in the denominator due to stock options can be offset or undone. Weisbenner (2000) concludes that stock option grants result in increased share repurchases and increased total payouts, with the size of the option grants predicting the amount of repurchases.
In the past, each hypothesis tended to be addressed separately (or independently) using a different framework. Thus, it is best to provide a unified framework and treatment of various hypotheses on share repurchases so that we obtain a comprehensive evaluation of them. One can use the VAR framework as a common methodology for examining various hypotheses regarding the two payout policies. Each hypothesis would be formulated based on a VAR of relevant variables and characterized as restrictions on the VAR of the variables.
Fourth, the authors can investigate payout policy in a time-series VAR context so that the dynamic and multi-dimensional nature of the two payout policies is accounted for. Other studies tend to focus on examining various motives for share repurchases using cross-sectional data, and they have contributed to understanding of share repurchases. However, they often provide conflicting evidence. Given that share repurchases are not a regular event for individual firms, the authors can focus their analysis on an aggregate time-series analysis between the two payout policies (see Dittmar and Dittmar (2002) for a recent study on aggregate patterns in repurchases).
Finally, if their sample period was larger, this would allow them to estimate the impact of macro-economic parameters on the distribution of corporate payout.  A possibility would be to spans the years from 1950 through 1997 (the full set of years for which COMPUSTAT data are available on any of the COMPUSTAT tapes).
 Critical Review of

Debtor-in-Possession Financing and Bankruptcy Resolution:

Empirical Evidence

Sandeep Dahiya, Kose John, Manju Puri, Gabriel Ramírez
Journal of Financial Economics Vol 69 (2003) 259-280
Summary
This paper starts by addressing what distinguishes firms that obtain DIP financing from firms that do not. Dahiya et al. find that larger firms are more likely to obtain DIP financing.  They also find that firms, which obtain DIP financing, are more likely to emerge from the Chapter 11 process than firms, which do not. The authors conclude that these results are consistent with DIP lenders having an information based role; playing a screening role in which they are able to identify distressed firms that are strong and likely to emerge quickly, as well as a monitoring role in which the DIP lenders help firms to emerge quickly. The authors then explain how is DIP financing related to the probability and speed of bankruptcy resolution and investigate whether or not it makes a difference if the DIP financier is an existing creditor with a prior lending relationship with the firm. They find that firms that receive DIP financing take a shorter time to resolve their Chapter 11 filing. They explain that it suggests that DIP lenders finance positive NPV projects and help the company emerge from bankruptcy, but if things do not go well with the firm then they are quick to liquidate to preserve the value of the underlying assets. Dahiya et al. also find that while many firms receive DIP financing from an existing lender, a significant number obtain it from a lender with whom they have no existing lending relationship.  The authors use the Bankruptcy DataSource from New Generation Research Inc. (NGR) to assemble their sample which consists of 538 firms that filed for Chapter 11 protection between January 1988 and December 1997 of which 165 received DIP financing.
Comments
The first point is with respect to the characteristics of firms obtaining DIP financing.  The authors look at leverage, assets level, prepackaged Chapter 11 and retail as independent variables.   One also expects that a lender will be more inclined to provide DIP financing if the Chapter 11 debtor has the right people who would lead to higher probability of reorganization given the quality of the business.   These two characteristics should have been included in this analysis to give a better conclusion.
Several measures should be examined as well, including income over sales and the ratios income/assets, and revenue/assets (using log) measured at the year-end prior to filing for bankruptcy, in order to see if DIP firms are more profitable than non-DIP firms, as it is expected. Moreover, as Gilson (1989) observed that bank lenders frequently initiate top management changes in financially distressed firms. This management turnover is expected to have a positive impact on the value of the firm. Moreover, Chatterjee et al. (2001) argue that the evidence of management turnover in firms with DIP financing is not significantly different from non-DIP firms. Since the DIP lender is usually a bank with considerable expertise in the DIP financing market and the bankruptcy process, one should expect a larger monitoring and disciplining role in DIP firms, and eventually more management turnover, with firm value-enhancement (Jensen, 1989). A dummy with a value of 1 in case of changes of CEO during bankruptcy and 0 otherwise can be used.
When the authors looked at the relationship between DIP financing and bankruptcy outcomes, they used a Probit model.  They could have separated the sample into two categories: (1) and without DIP financing (2) and firms who got DIP financing only. The relative loan size should also be examined as a possible variable affecting the outcome. Other characteristics might include the DIP loan coming from a bank versus non-bank as banks invest in information gathering technology and may have a competitive advantage relative to other non-bank institutions in evaluating lending opportunities.  Moreover, a measure of solvency/profitability should be included as the more solvent/profitable the firm, the more likely it is that it will reorganize successfully. Since equity committees are typically appointed when the firm is solvent, we should expect their presence to be associated with successful emergence from bankruptcy. Several measures can be used, including assets/liabilities, revenue/assets and income/assets, measured at the year-end prior to filing for bankruptcy. Other good indicators would be the ratio of total distribution/estimated total debt and a dummy with a value of 1 in case of equity committee and 0 otherwise.
Furthermore, since Gilson et al. (1990) argue that financial distress is more likely to be resolved through a private renegotiation in three situations: 1) the larger the loss of going concern value if a private renegotiation failed. 2) the larger the proportion of bank & insurance companies debt in terms of the total liabilities. 3) the smaller the number of classes of debt outstanding (see also Betker, 1995), one might argue that these variables also determine the likelihood of a successful emergence, following a Chapter 11 filing. The ratio of bank & insurance companies’ debt/liabilities, the ratio of the market value of common equity to its liquidation value and the (log) number of creditor classes, respectively, can be used in order to examine this relation.  One should be careful when using these variables and look at the possibility of muticollinearity.
        
Although, Schwarcz (1985) argues that obtaining new financing can act as a good signal to trade creditors and encourage them to re-establish the terms of the trade credit with the company, the positive impact of DIP financing should be reduced in two circumstances. First, when the new loan is secured by a lien on already encumbered assets with equal or senior priority to the existing liens (priming liens). Secondly, when the DIP lender is a pre-existing creditor and obtains an increase in the seniority of his prepetition debt. In fact, these situations suggest a lack of confidence of the DIP lender in a successful reorganization of the firm. Two dummy variables with a value of 1 in case of DIP financing (DIP priming liens) and 0 otherwise can be used. Moreover, one important feature of DIP financing is the time it takes the court to approve an order. Many times we can have a ‘filing on a pillow’, but other times the approval might take longer. One can hypothesize that the more time it takes to obtain DIP financing, the more likely the firm is to reorganize successfully in Chapter 11, as a careful analysis of the situation of the bankrupt firm should be required. The variable ‘time to obtain DIP financing after filing for bankruptcy’ in days should also be used.
Finally, trustees are typically appointed in cases when the management is guilty of fraudulent behavior (under Subsection 1104(a)), but this is usually a temporary measure, until the company appoints new management. So, the appointment of trustees is closely related to management turnover during bankruptcy, thus compounding all the complexity of the process. A dummy variable with a value of 1 in case of a trustee being appointed and 0 otherwise can be added as well.
Critical Review of

Asset Pricing with Conditioning Information: A New Test

Kevin Wang
Journal of Finance, Vol. LVIII, No. 1, Feb 2003, p161
Summary
        This paper develops a new approach to testing dynamic linear factor models, which aims at time-variation in Jensen's alphas while using a nonparametric pricing kernel to incorporate conditioning information. In application we find that the conditional CAPM performs substantially better than the static CAPM, but still it is statistically rejected. Theoretically, it is well known that the conditional CAPM could hold perfectly – that is, conditional alphas are always zero – but that time-variation in beta might lead to unconditional pricing errors. In general, a stock’s unconditional alpha will differ from zero if its beta covaries with the market risk premium or with market volatility. The conditional CAPM exhibits time-varying Jensen's alphas that have a strong size pattern in volatility and a clear book-to-market pattern in time-series average. These features are well captured by a simple dynamic version of the Fama and French (1993) three factor model. In fact, the market portfolio might be conditionally mean-variance efficient in every period yet, at the same time, not on the unconditional mean-variance frontier.  Several recent papers argue, in fact, that time variation in beta helps explain the size, B/M, and momentum effects. Zhang (2002) develops a model in which high-B/M stocks are riskiest in bad times, and co movement between betas and the risk premium leads to an unconditional value premium (even though conditional CAPM alphas are exactly zero).
        
        The author uses a methodology that avoids specification of time-varying betas.  Instead he uses a nonparametric technique that will enable him to avoid misspecification about dynamics of conditional betas.  He found that for the conditional CAPM, the nonparametric technique performs better than the unconditional CAPM.  He also finds that the pricing errors of the conditional CAPM are positively correlated with stock market.  Moreover, the use of labor income risk factor of Jagannathan and Wang (1996) and the size and book-to-market factors of Fama and French in this paper did not seem to explain satisfactorily the CAPM pricing errors.  Finally, when he challenged the conditional CAPM and the conditional Fama and French model with momentum portfolios, Wang finds that the conditional expected returns of the winners are higher than those of the losers.

Comments
        The paper focused on modeling the variation in betas using theoretical framework of the conditional CAPM in a very intelligent way.  The literature overview was thorough and specific.  The author was very explicit in his model, his assumptions, and the data he used.  Every step in his methodology was very sound and supported by arguments.  I can only add few comments to this paper.
        Ghysels (1998) discussed the problem of time variation in betas and risk premia in detail and stressed the impact of misspecification of beta risk dynamics on inference and estimation. Also, he argued that betas change through time very slowly and linear factor models like the conditional CAPM may have a tendency to overstate the time variation. Further, he showed that among several well-known time-varying beta models, a serious misspecification produces time variation in beta that is highly volatile and leads to large pricing errors. Finally, he concluded that it is better to use the static CAPM in pricing when we do not have a proper model to capture time variation in betas correctly.
        
        Large pricing errors could be due to the linear approach used in a nonlinear model.  Therefore, by treating a non-linear relationship as a linear one would lead to serious prediction problems in estimation. In order to overcome these problems, some nonlinear models were suggested in the literature.
In this article, Wang explored a nonparametric form of the SDF model as a new way for dealing with the misspecification errors and conducted a test based on the nonparametric model. Parametric models for time-varying betas can be most efficient if the underlying betas are correctly specified. However, a misspecification may cause serious bias and model constraints may distort the betas in local area. A nonparametric modeling is appealing in these situations. One of the advantages for nonparametric modeling is that no or little restrictive prior information on betas is needed. Further, it may provide useful insight for further parametric fitting.
        The conditional CAPM is typically well supported by the data, and thus, it is important that we test  (as it is done in this paper) whether all coefficient functions are actually varying (namely, if a linear beta CAPM is adequate); if a parametric model fits the given data such as testing for structural breaks as in Ghysels (1998) or testing a threshold model as in Akdeniz, Altay-Salih and Caner (2003) or a specific parametric form as in Ferson and Harvey (1998, 1999); if there is no β0(.) at all; and whether some or all coefficient functions are constant or zero or in a certain parametric form.  
        In empirical finance, different models impose different constraints on the SDF. Particularly, the SDF is usually assumed to be a linear function of factors in various applications. Further, when the SDF is fully parameterized such as linear form, the general method of moments (GMM) of Hansen (1982) can be used to estimate parameters and test the model.  Recently, some more flexible SDF models have been studied by several authors. Wang pointed out that one of the shortcomings is that it is difficult to obtain the distribution theory and the effective assessment of finite sample performance. To overcome this difficulty, instead of considering the nonlinear pricing kernel, Ghysels (1998) focused on the nonlinear parametric model and used a set of moment conditions suitable for GMM estimation of parameters involved. Wang, in this paper, studied the nonparametric conditional CAPM and gave an explicit expression for the nonparametric form of conditional CAPM for the excess return.  Wang suggested estimating b(.) by using the Nadaraya-Watson method. Also, he conducted a simple nonparametric test about the pricing error. He also extended this setting to multifactor models by allowing b(.) to change over time; that is, b(Xt) = b(t).
Another way that might be interesting to study would be to consider the nonlinear SDF without specifying a particular form of the nonlinear pricing kernel using the estimation method of GMM.

References

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Wednesday, February 10, 2010

Excel VLOOKUP() returns wrong results

I was trying VLOOKUP with a huge array of numerical data and it was returning the wrong results. I did some search on the internet but the results were not really helpful.
I turned to the Excel 2007 help and I found the solution as the following:

range_lookup  Optional. A logical value that specifies whether you want VLOOKUP to find an exact match or an approximate match:
  • If range_lookup is either TRUE or is omitted, an exact or approximate match is returned. If an exact match is not found, the next largest value that is less than lookup_value is returned. Important  If range_lookup is either TRUE or is omitted, the values in the first column of table_array must be placed in ascending sort order; otherwise, VLOOKUP might not return the correct value.
    For more information, see Sort data.
    If range_lookup is FALSE, the values in the first column of table_array do not need to be sorted.
  • If the range_lookup argument is FALSE, VLOOKUP will find only an exact match. If there are two or more values in the first column of table_array that match the lookup_value, the first value found is used. If an exact match is not found, the error value #N/A is returned.

So omitting the range_lookup value would be interpreted as true which leads approximate matching. It seems excel prefers to use approximate matching instead of exact matching when the range_lookup is not specified. This is werid and against the common sense :)

Tuesday, January 26, 2010

General notes for linking databases

I was thinking of writing about this linkage issues between financial databases. However, I found out that Jie Cao was faster than me. So I quoted him instead of rewriting what he has documented already (http://ihome.cuhk.edu.hk/~b121456/tools.html).

  • NCUSIP is the historical CUSIP and changes over time. CUSIP is the current CUSIP and does not change over time. A historical NCUSIP during a specific period will correspond to only one current CUSIP. [www.cusip.com]
  • The NCUSIP in Thomson, I/B/E/S, ISSM, TAQ and  Option-Metrics is labeled as 'CUSIP'.
  • In Compustat, CNUM + first 2 digit of CIC is the CUSIP.
  • The major matching variable across databases are NCUSIP and then Ticker.  
  • The CUSIP-NCUSIP transition file builds a link between NCUSIP and CUSIP as well as PERMNO at a specified time interval. [Download the transition file here]
  • For ISSM database, all NYSE and AMEX stocks from 1983 to 1992, and NASDAQ stocks after 1990 can be matched by NCUSIP. NASDAQ stocks before 1990 could be matched by SMBL, which at a given month & exchange corresponds to the Ticker in CRSP.
  • For TAQ databse, stocks can be matched by the first 8 digits of TAQ's 12-digit NCUSIP.
  • Mutual Fund Links (MFLINKS) connects CRSP mutual fund information to Thomson (S12) mutual fund holding data. 
  • Matching by company or fund name is difficult as the last resort. The SAS function 'SPEDIS" can determine the likelihood of two words matching.  
  • Extra efforts are needed for a precise matching. See this sample SAS Code to generate a link between I/B/E/S and CRSP using multiple identifiers. (Internet connection and access to both I/B/E/S and CRSP data at WRDS are required)

Wednesday, January 6, 2010

CUSIP and CFMRC Dataset

If you would work with Canadian stocks info data, you would notice that CFMRC (the leading database for Canadian securities and the equivalent of CRPS (for US stocks) does not always list the CUSIP identifier with the data.

CUSIP is highly important to link the CFMRC data with other databases as tickers are not always reliable. In CFMRC (the Windows client), CUSIP is not produced in all formats. One has to select the extended format to get CUSIP in the output.

Wednesday, December 31, 2008

Researh tools

I have noted earlier that going into academia is a long quest and require high levels of dedicaiton, perseverance and commitment. This is not enough, one needs a toolbox to proceed with.

I would put here a lot of the items that are extremly important for any research discsipline. I will follow with another list of tools that are needed for financial reaserch.

For any kind of research one needs:
  1. Strong exposure to research methodology, ethics, and norms
  2. Solid comprehension of statistics and statistical measures, tests and appropriate interpretation
  3. Clear style for reviewing the literature
  4. Access to academic scholary databases and libraries 
  5. Critical understanding and assessement of literature
  6. Ability to narrow down on a resaerch topic that is not too wide and not too narrow. 
  7. Ability to classify and organize readings on the go
The approaches I suggest to fulfil the above:
  1. Following a strong reaseach methodology course with an experiences professor. Unfortunately, I have seen so many methodology courses that fit anywhere but in a methodological paradigm. Students coming from different backgrounds into the Phd program, needs refined methodological courses that help them find their way into the academic research areana and fix their feets. I had to read a lot on my own to cover this gap in my studies. Yet, I can not claim that I mastered the methodology I should follow.

  2. Invest enough time to grasp all the required stastical concepts and know the ins and outs of the statistal package mostly used for that discsipline. It would save you tens of hours in modeling and debugging if you really know the tool you are using extremly well.

  3. Work with an experienced researcher on the literature review part in order to improve your skills and learn the tricks that others are following. This would be a great step to get you on track with something that is easier to collect, classify, digest and then reproduce from your resaerch point of view. There are a lot of tools that would help succeed in doing a great literature review. One of my supervisor advised me to get this book: "Fink, A. (1998). Conducting Research Literature Reviews: From Paper to the Internet. Sage Publications, Inc.". It is available on amazon but I have borrowed it from Concordia University library. There is another resource to hint on how to conduct your own review at this page:
    The Literature Review: A Few Tips On Conducting It

  4. The last point I woudl like to mention in this area is the access to a rich collection of books and electronic resources. Your unversity library should have a lot of what you are looking for. Do not let books sitting on cold dark shelves. Go on and use those books. We are paying a lot for these collections and more than 80% of it goes by unnoticed for many years. In the golden age of libraries, we used to find books with torn pages. Now, I get a lot of books untouched. Really brand new. I would like to note that Concordia Library has one of the richest collections I have even seen in a Library especially for some disciplines that students rearely goes into. We are very lucky in Montreal, if the book is not available in Concordia, McGill is there, HEC or even UQAM. A wealth of knowlege waiting for someone to dig and mine into its pages.
In addition to that, one needs real tools to get the job done. I will not talk about these tools in details now. I would just list them:
  • Fink's book
  • Statistical Packages (Matlab in my case)
  • Firefox and Zotero (For bibliographical referncing). I prefer Zotero over RefWorks or EndNotes.
  • mediaWiki (Really? Are you sure? Yes absolutely)