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Capital Structure and external factors.

Discussion in 'Economy/Finance stuff' started by Chaupham, May 18, 2012.

  1. Chaupham

    Chaupham Member MBA Family

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    Hey folks,

    I bring up the topic because I really need your help. I am carrying out a research toward Capital Structure of firms. My main object is conferred as analysing the manager’s behaviour during financial distress, which is manifested by capital structure.

    Briefly, capital structure just the way a firm raises its funds: neither retain earnings, debt issuing or equity issuing given that firm likely arrange these options as retain earnings is priority, then debt issuing and equity issuing comes last due to adverse information. This is just pecking order theory. But I am expected to coming up with any idea being beyond that point.

    What I’ve been doing so far is investigating the relationship between capital structure and some external factors: liquidity, firm size, profitability and growth opportunity.

    What I can contribute to my originality up to the point is Public Relations, and credit crunch. However, now I fell like drying up and am going to have disastrous result over my research. So please help me, in terms of giving some more variables that I can put into my hypotheses.

    Many thanks.
     
  2. evol

    evol Member MBA Family

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    HA đọc thoáng qua chưa hiểu lắm. Châu muốn nghiên cứu các yếu tố quyết định capital structure nói chung hay chỉ trong thời điểm distress? Đối tượng là công ty ở developed market hay developing? nếu là latter thì còn phụ thuộc vào market infrastructure, bond market không sophisticated như the west nên chỉ high credit rating firms mới có access. Shareholder ownership cũng quan trọng, đặc biệt nếu có government ownership. Cái pecking order theory kia cũng không work ở developing mkt.
     
  3. Chaupham

    Chaupham Member MBA Family

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    Ah, may quá có Hồng Anh.

    Châu đang thực hiện đề tài: Capital structure policy under adverse information from 2006 to 2011.

    Trong đề tài này thì Châu sẽ tập trung và phân tích việc chọn external financing: debt or equity trong thời gian financial distress. Đối tượng là developed market thôi, em dùng Thomson One Banker để lấy số liệu.

    Hiện có 5 cái lý thuyết mà em tìm được: static trade-off theory, pecking order theory, agency cost theory, market timing theory, stakeholder co-investment theory. Nhưng trong số này chỉ có 2 cái là pecking order theory và market timing theory là giải thích hành vi của nhà quản lý ( try to understand how managers react to particular aspects of the environmental economics). Bởi vì POT thì như thế, còn market timing theory là đơn giản thị trường nào tốt hơn thì chọn (debt market or equity market).

    Bài này em chủ yếu dựa vào mấy cái journals phổ biến để lấy biến giải thích và lập hàm. Nhưng đang bị ngộp, nhiều quá, không biết nên chọn cái nào, bỏ cái nào. Đây là ý em muốn hỏi: Hồng Anh nghĩ trong thời gian financial distress, những yếu tố nào đủ mạnh để giải thích lựa chọn của nhà quản lý? HA cứ gợi ý, em nghiên cứu luôn.

    Em có sáng tạo thêm 3 giả thiết:
    _ Public Relations: tức là công ty có quan hệ tốt với khách hàng thì sẽ tránh được adverse information.
    _ Credit Crunch: khó khăn khi vay mượn tiền trong thời financial distress.
    _ Market Condition: Thằng này để giải thích cái market timing theory. Em nghĩ là trong thời gian khó khăn, nhà đầu tư sẽ trở nên nhạy cảm hơn, và tăng cường yếu tố adverse information.

    HA thấy được không?

    Cám ơn HA :D
     
  4. draculallvm

    draculallvm Member MBA Family

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    Hmm, seems like your research is now all over the place. You may want to narrow down the scope of the project or else this is gonna be too much work for one person to take on.

    A couple of crude ideas for your regression equations. You may already have done these things, so take them if you like. Otherwise, just tell me to f**k off:

    Dependent variable - capital structure: I think you can pick either the change in percentage of debt or equity for this one. I myself would use the change in Debt/Equity ratio, which is easier to come by in research databases. This is simple.

    Independent variables: This is tough, because usually researches are conducted with stock returns, so you can draw on Fama-French factors and business risk factors (treasury yield, GDP growth rates, etc.) to justify the control variables. I haven't done any research into this topic before. Nevertheless, I believe that literature review would be critical for you to properly explain how you pick independent variables.

    At least, you can probably try to control for two buckets of variables: accounting/internal variables (as you briefly mentioned before, such as HML, SML, Net Income, Dividends, Assets (as a proxy for collateral), etc.) and market/external variables (GDP growth, inflation, treasury yield, industry factor (use the SIC code as a proxy) and whatnot). Of course, you are probably gonna have to run multiple regressions and make a table to see how adding/removing each factor impacts the significance of the results. The aim is perhaps to get an as high R-squared as possible (?).

    http://mba.tuck.dartmouth.edu/ccg/PDFs/2004conf/CapStrDecisionsFrankGoyal.pdf
    http://www.eurojournals.com/IRJFE_71_09.pdf

    Then you can try adding your independent variables to the equation.
    - Liquidity: turnover rate (number of shares traded as a fraction of the number of shares outstanding) can be adopted as a proxy for liquidity (?)
    - Credit crunch: generate a dummy variable for 2008, 2009, 2010 to gauge the timing effect
    - Public relations: I am clueless about this. You gotta get more creative and come up with a proxy for good/bad publicity. You may just want to limit it to investor relations instead of PR, which is way too broad. As for negative investor relations, in the case of the US market, perhaps the number of warnings from the SEC can make a good proxy (I forgot the official name of the document).

    Processing the data for the regressions in this project would be a pain in the neck, which is why I said it's probably too much for one person to undertake.

    Limitations of the research: one issue that I can spot right away is you can only account for the change in the reported D/E, which may not capture the entire use of leverage by companies. There are off-balance-sheet items, e.g. operating leases, that may represent considerable sources of financing in certain industries.
     
    Last edited: May 18, 2012
  5. Chaupham

    Chaupham Member MBA Family

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    You know what? Sometimes it feels like I've bit more than I can chew. Fortunately, I am at the very first step in the project, hence I can narrow the scope easily. Once again, it is very impressive that you can see through my trouble at a glance.

    My dependent variable is Net Debt (debt issuance less debt reduction). I agree with you that we should not use Net Equity, because after an IPO, equity issues are only used in extreme circumstances [Shyam-Sunder and Myers (1999)].

    My independent variables are formed by the following steps (This is the literature review section)

    1) Capital structure: I'm gonna cover theory and narrow by bringing up the taxation and interest rate issues. First hypothesis: taxation can affect Net Debt.

    2) Adverse information: two theories that I mentioned before will be discussed here. At this point, I form my main equations: Liquidity, Firm size, Profitabily and Growth Opportunity.
    Liquidity, I might use the change in tangible asset to intangible asset ratio.
    Firm Size, there is an analogous option: market cap or log sale?
    Profitablity, I have no idea so far, actually. This is what I have to do tomorrow.
    Growth Opportunity, I might use the change in dividend to investment ratio, given that a firm that has some good projects to invest will not increase its dividend payout.

    These are my extra parts: Market Condition and Public Relations. Particularly PR, I assume that the more money a firm invests in PR, the stronger the firm can fight back adverse information.
    About Market Condition, do you think I should cross it out? Because somehow Credit Crunch is correlated to Market Condition.

    3) Financial distress: this part will explain why my data falls into 2006 - 2011. And I will use Credit Crunch as an independent variable. And astonishingly, I come up with an idea that is just the same yours.

    That's all what I have worked on the project so far. Would you give me some comments on it?

    Methodology:
    I will check stationary, robusness, biasedness, heteroskedasticity and auto correlation; of couse multiple regression. I may get back to this section after finish my Literature Review.

    Thank you so much, indeed.
     
  6. draculallvm

    draculallvm Member MBA Family

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    A few "issues" in your preliminary research:
    - Why use net debt? I don't get it. What if the management wishes to maintain the current capital structure and thus, decides to raise funds through both a seasoned offering of equity and a debt issue? The absolute value of net debt may change but the capital structure, which is the only thing that matters here, would remain intact in such a case. What you are trying to capture is the change in capital structure, meaning the relative relation between D and E, right? Then the change in D/E seems to be the appropriate measure here. Of course you can use D/(D+E) instead. I just think D/E is easier to handle because empirical finance researchers and economists use that ratio a lot.
    - Liquidity: what do you mean by liquidity? Is it the liquidity of a company's shares or the ability of a firm to meet short-term obligations? I just thought that the liquidity of shares should weigh a lot in the management's decision to use equity as a source of financing (due to the liquidity premium making the cost of equity higher) and is worth looking into.
    - Why dedicate so much effort to tax rates and interest rates? I myself would put taxes into the "limitations" of the research simply because it's too complicated. My belief is you should spend more time discussing the correlation between internal/ external factors and capital structure.
    - Growth prospects: have you seen your ratio used before in many research papers? Why not use book/market value of equity instead. Companies with higher growth potential have market value much higher than book value because investors have already priced the future growth in stock prices.
    -Market condition: what do you mean by market condition? As I said earlier, you can place the control variables into two buckets: internal and external. External factors reflect macro environment/market conditions. That's why you would probably need to include GDP growth rates, inflation rates, treasury rates, industry codes, etc. in the regression equation as well.
    - Credit crunch: it represents the timing effect in your regression. Put it next to other external business risk factors to see how significant it is. If you decide to use the liquidity of shares, you may also want to check the credit-crunch-conditional liquidity factor (crunch dummy variable*liquidity)
    - Size factor: first you may want to adjust for the size effect by dividing the accounting ratios (which represent internal operational factors) by average total assets. Typically, if you work with stock return series, definitely use SML from Fama-French database. But since you're working with D/E and panel data series rather than a time series here, I am not sure it's still applicable though. The first thing that popped up in my head is the book value of assets, which can be obtained from subscription-based databases easily.
    - Profitability: just use net income
    - Just out of curiosity, how are you gonna test stationarity and autocorrelation with panel data? I always thought that you only do that for time series data and for testing forecasting ability of models. Well, I was never good at econometrics anyway, so it's maybe just my ignorance :D
    - To narrow the scope of your project, answer the question "what is your thesis statement for the research?"
     
    Last edited: May 18, 2012
  7. Longatum

    Longatum Active Member MBA Family

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    I think the key point here is that you want to look at companies' behavior under distressed conditions. First thing people would want to know is what you mean by "financial distress". In the financial community, a company is deemed to be distressed financially if it's facing liquidity issues that would prevent or have already prevented it from meeting upcoming obligations.

    Under such circumstances, traditional fund raising options usually won't be available - i.e. you can't really take on additional borrowings, even at astronomical interest, and you'd also be hard pressed to find someone who'd be willing to fund via straight equity.

    You should also be clear on some definitions. First of all, retained earnings is not really a source of fund, i.e.: it's not a measure of cash flow. I think here you're thinking of operating cash, which is what a company generates in its usual course of business.

    You also don't / can't raise capital via way retained earnings (or operating cash for that matter). Think of it as your salary, you can't ask someone to put more $ into your salary, you can only work hard to raise it.

    Capital structure, simply put, is just debt and equity - whatever you use to buy assets. But in practicality there can be a million things underneath - senior debt, term loan, mezzanine debt, convertible preferred, preferred equity, equity etc.
     
  8. evol

    evol Member MBA Family

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    If you're in distress as defined by Long above, you take whatever the market gives you, be it debt or equity. Beggars can't be choosers. No need to analyze or do this thesis.

    But while you corner yourself to 'distress situations', your topic is too broad in terms of companies. Ngay một subsegment như banks/brokers thôi nhé, 2 variables quan trọng nhất là regulation và funding structure (wholesale or retail). Under current and upcoming regulation, funding structure is definitely not optimal on profitability metrics, but required for long-term sustainability.

    So first step is to come up with a more defined target. Sounds like you're still confused. Choose something small and dig deep, not broad but shallow.
     
  9. son2silver

    son2silver Member MBA Family

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    If I may follow up on a. Long's note: true "financial distress", as commonly understood, really limits management's options with regard to financing. Under such limitations, you can more or less throw a few of the aforementioned theories out of the window: tax-bankruptcy tradeoff theory (because staving off bankruptcy is the #1 goal here) and stakeholder co-investment theory (the company is already burdened with debt).

    Second observation: what your "original" propositions (public relations, credit crunch, market condition) imply seem already covered, in whole or in parts, by the first five theories. For example, credit crunch/market condition and market timing are NOT mutually exclusive.
     
  10. Chaupham

    Chaupham Member MBA Family

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    This is my decision:
    1) Capital structure policy.
    2) Financial approach – Differences in information.
    In details, adverse information can be conferred as a situation when existing the adverse selection problem which supported by asymmetric information.
    3) Normal firms during financial crisis, rather than financial distress firms.

    @Draculavn

    Why use net debt?
    The conventional leverage regression is intended to explain the level of leverage,
    while the pecking order regression is intended to explain the change rather than the
    level. As long as the shocks are uncorrelated across years, we can equally well run the
    conventional specification in first differences. Of course, a lower R2will be obtained.

    But I agree now for I changed my target, I use conventional Debt/capital. But two indices: short-term debt (bank loan), and long-term debt.

    What do you mean by liquidity?
    I misunderstood this factor due to similar meaning it provides. This is what I really mean.

    Collateral value of assets

    The early study on this independent variable indicated that the negative relation between collateral value and capital structure will be produced if firms consume over their optimal perquisites, according to Timan and Wessels (1988). Moreover, Rajan and Zingales (1995) has researched on tangibility of assets and confirm that the explanatory factor shows effect on leverage level of firm.

    Why dedicate so much effort to tax rates and interest rates?
    Yes, you are absolutely right. Under adverse information, taxation is useless. I do agree.

    Growth prospects:

    There are some evidence show that growth opportunities have a negative relation with capital structure [Smith and Watts (1992) and Barclay, Morellec, and Smith (2001)]. When the growth opportunity of financial distress firm declines, they tend to increase their use of debt financing. Besides many conventional explains, there is a case financial distress firms are very sensitive in terms of bankruptcy as their lenders may draw all capital invested in if they think these firms is about to bankrupt. Therefore, the cost of equity issuing may increase dramatically exceed of the cost of issuing debt. In other words, they desire to signal that they are able to reserve the last resort – equity issuing.

    Market condition: what do you mean by market condition?
    I mean credit squeeze period. And I wanted to assess market timing theory. But this is not the case.

    Credit crunch: it represents the timing effect in your regression.
    This is changed into credit quality. Price target!

    There has been a trend that balances between the class of young high-growing technology firms and old mature firms. The conventional standards seem to have less explanatory power over capital structure policy. However, one of some consistent credit quality variable is goodwill assets. Because good credit quality firms tend to have good reputation, they also tend to have high goodwill value. Moreover, the reputation of firms can change over time; I invented my sixth hypothesis and a time dummy variable.

    Size factor
    I use log sales. Because:
    Pecking order theory predicts that more profitable firms will have less leverage. The signs on firm size variables are ambiguous. Large firms might have more assets in place and thus have a great damage is inflicted by adverse selection as in Myers and Majluf (1984). However, large firms might have less asymmetric information and thus will suffer less damage by adverse selection as suggested by Fama and French (2002). If sales are more closely connected to profits than just firm size, then one might be inclined to expect a negative coefficient on log sales.

    How are you gonna test stationarity and autocorrelation with panel data?
    I desire to differentiate the leverage and test it. Because from 2006 – 2011 there is an extreme event and some variables seems to be autocorrelated.

    What is your thesis statement for the research?
    Capital structure policy under adverse information.

    @Longatum:
    What you mean by "financial distress".
    From the beginning, I want to check these beggars because the rich is difficult to predict what they want. But now I agree that beggars are special cases. Just normal firms are good enough.

    You also don't / can't raise capital via way retained earnings.
    Yes, I agree. But we can use the announcement earnings to check their credit quality.

    @ Son2silver:

    For example, credit crunch/market condition and market timing are NOT mutually exclusive.
    Yes, that why I did ask should I exclude some of them due to heavy autocorrelated. Now I changed my strategy, things get easier.

    After a week working on that, I now can handle the research confidently.
    Thank you so much, indeed. Gonna invite Khắc Sơn, Hồng Anh, Hoàng Long and Quan Nguyen a home-atmosphere dinner :X
     
  11. Chaupham

    Chaupham Member MBA Family

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    Hôm nay vui quá mọi người ạ, kể cho mọi người nghe chuyện này.
    Em đang làm phần data analysing với Results của topic này.
    Giáo viên hướng dẫn lúc đầu hỏi mày định dùng cái gì để phân tích, có dùng được Oxmetrics chạy PcGive không? Xong em bảo được, một phần là vì trong chương trình có dạy món này, với lão cũng ủng hộ.
    Topic này em dùng panel data analyse, tức là kết hợp cả cross-section với time-series luôn.
    Cả tuần vừa rồi em chiến đấu với cái phần mềm này, phát hiện ra PcGive phức tạp mà thiếu hàm test. Hỏi lão ấy, lão cũng chỉ qua loa. Bí quá, em tự học dùng Stata. Xong rồi bảo lão hướng dẫn của em: tao dùng stata đấy, nếu cần tao check luôn PcGive cho xem.

    Lão bảo là: thật ra tao cũng dùng Stata. Mày không phải lo đâu, cứ đúng công thức là được. Haha

    Tóm tại, kêu gọi đồng bào chiến đấu, thế rồi núp thế nào lại gặp nhau trong cùng một bụi cây. Buồn cười không chịu được.
     
    Last edited: Jun 28, 2012

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