Cash holdings and financing decisions under ambiguity
Abstract
EconStor is a publication server for scholarly economic literature, provided as a non-commercial public service by the ZBW.
Full text
Agliardi, Elettra; Agliardi, Rossella; Spanjers, Willem Working Paper Cash holdings and financing decisions under ambiguity Quaderni - Working Paper DSE, No. 979 Provided in Cooperation with: University of Bologna, Department of Economics Suggested Citation: Agliardi, Elettra; Agliardi, Rossella; Spanjers, Willem (2014) : Cash holdings and financing decisions under ambiguity, Quaderni - Working Paper DSE, No. 979, Alma Mater Studiorum - Università di Bologna, Dipartimento di Scienze Economiche (DSE), Bologna, https://doi.org/10.6092/unibo/amsacta/4111 This Version is available at: https://hdl.handle.net/10419/159817 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc/3.0/
ISSN 2282-6483 Cash holdings and financing decisions under ambiguity Elettra Agliardi Rossella Agliardi Willem Spanjers Quaderni - Working Paper DSE N°979
1 Cash holdings and financing decisions under ambiguity by Elettra Agliardi Department of Economics University of Bologna, Bologna, Italy email: [email protected] Rossella Agliardi Department of Mathematics University of Bologna, Bologna, Italy email: [email protected] Willem Spanjers Department of Economics Kingston University Kingston-upon-Thames, United Kingdom email: [email protected] Abstract: This paper addresses the following unresolved questions: Why do some firms issue equity instead of debt? Why did most firms retain their cash holdings instead of distributing them as dividends in recent times? How do firms change their financing policies during a period of severe financial constraints and ambiguity, or when facing the threat of an unpredictable financial crisis? We analyze how the values of the firm’s equity and debt are affected by ambiguity. We also show that cash holdings are retained longer if the investors’ ambiguity aversion bias is sufficiently large, while cash holdings become less attractive when the combined impact of ambiguity and ambiguity aversion is relatively low. Keywords: corporate finance decisions; ambiguity; cash holdings; optimal dividends JEL Classification Numbers: G30; G32; D01; D81;
2 1. INTRODUCTION Over the last three decades, there have been many developments in decision theory that improved our understanding of uncertainty. In line with Knight (1921), uncertainty can be divided into two welldefined distinct parts, risk and ambiguity. “Risk” is used to refer to any sort of uncertainty that can be defined through the existence of a probabilistic model based on one single probability assessment, which is known to the decision maker (DM). “Ambiguity” is used to refer to situations in which the DM appears to be not fully confident that his/her beliefs apply. Practically, risk is mostly used when uncertainty is calculable, i.e. both outcomes and a subjective probability distribution over outcomes can be specified. Ambiguity applies to situations where uncertainty is incalculable, i.e. where there is no clear perception of the possible outcomes or of an estimate of a single plausible probability distribution. At least since Ellsberg (1961), experimental studies in ambiguous settings have repeatedly shown that DMs usually prefer to deal with known, rather than unknown probabilities, thereby revealing a form of ambiguity aversion. Estimating a quantified opportunity cost of acting now rather than later is particularly difficult when dealing with financing decisions under significant ambiguity. Although the recent literature on ambiguity has provided a unified and elegant framework to address (and often solve) some financial puzzles (e.g. the equity premium puzzle and the interest rate puzzle, see Epstein and Schneider, 2010), there are still ill-understood phenomena in corporate finance. Recent studies document a secular increase in the cash holdings of some firms (Bates, Kahle and Stulz, 2009; Denis and Sibikov, 2010; Faulkender and Wang, 2006; Haushalter, Klasa and Maxwell, 2007; Holberg, Phillips and Prabhala, 2014). And yet, one would expect that the precautionary demand for cash should decrease when firms can hedge more effectively as more types of derivatives are available, e.g. as a consequence of improvements in information and financial technology since the early 1980s. The observed increase in cash holdings represents an anomaly that challenges existing theories. At the same time, it is not clear whether equity holders would rather increase or decrease equity and dividends in the presence of vague economic perspectives and different forms of uncertainty (see also Lins, Servaes and Tufano, 2010, about investor preferences and crosscountry differences in cash holdings). Various empirical studies are inconclusive about the hierarchy or “pecking order” among different sources of funds (see Leary and Roberts, 2010, and references there). Some have documented a significant heterogeneity in corporate decisions attributed to a divergence in beliefs about the firm’s value between managers and the market. Behavioural explanations of corporate decisions have recently come to consider “managers’ personality traits” (Hackbarth, 2008, 2009), which may include
3 their attitude towards ambiguity. But whether the choice between equity or debt finance is affected by managers’ personality traits and their perception biases is still controversial. This paper sets out to answer the following unresolved questions: Why do certain firms issue equity instead of debt? Why did most firms retain their cash holdings instead of distributing them as dividends in recent times? How do firms change their financing policies during a period of severe financial constraints and ambiguity, or when facing the threat of a financial crisis in the foreseeable future? Our paper tries to provide answers within the framework of a dynamic model which incorporates ambiguity and the investor’s attitude towards it. We model the corporate decisions as real options and apply the mathematics of mixed singular control/optimal stopping methods in stochastic settings under ambiguity. In particular, we analyse how the values of the firm’s equity and debt are affected by ambiguity (Propositions 1 and 2) and relate our results to the pecking order puzzle (Proposition 3); moreover, we show how ambiguity affects cash holdings and optimal dividend policies (Propositions 4 and 5). We find that the presence of a standard pecking order or its reverse may depend on the relative ambiguity aversion biases of the managers and the investors: if managers have a stronger ambiguity aversion bias than the market, then a reversal of the standard pecking order preferences can be obtained. Finally, we find that cash holdings are retained longer if the impact of the ambiguity aversion bias is sufficiently large, which is consistent with the observed change in cash holdings in periods of turbulence and vague uncertainty. Cash holdings become less attractive with relatively small ambiguity aversion biases, in which case the DM prefers to receive dividends instead. 2. MODEL SET-UP When considering a decision maker (DM) facing ambiguity, the Choquet Expected Utility approach represents his/her beliefs by a non-additive unit measure, which is referred to as a capacity. Applying the Choquet integral of a capacity to a given vector of outcomes (an ‘act’) generates an implied probability distribution over the outcomes, on the basis of which the expected utility value is calculated. But in contrast to subjective expected utility theory, there may no longer exist a single implied probability distribution over the states of nature that applies for all acts. Rather, the implied probability distribution may change according to the ranking of the states of nature regarding the desirability of the outcomes obtained for them. For acts that generate the same ranking of the states of nature, i.e. co-monotonic acts, the same implied probability distribution applies. So if attention is restricted to a set of co-monotonic acts only, the results are indistinguishable from subject expected utility, with the subjective probability distribution equalling the implied probability distribution (see a.o. Schmeidler, 1989).
4 In the Choquet Expected Utility model a capacity simultaneously represents the ambiguity experienced by the decision maker and his/her attitude towards this ambiguity. The resulting complications tend to be circumvented by assuming (full) ambiguity aversion. Under this additional assumption – which applies throughout this paper, unless stated otherwise – the capacity only describes the ambiguity experienced by the DM (see e.g. Ghirardato, Maccheroni and Marinacci, 2004, and Chateauneuf, Eichberger and Grant, 2007). We refer to the combined effect of the perceived ambiguity and the DM’s ambiguity aversion as his/her ambiguity aversion bias. When capacities are updated in the light of new information, it is natural for dynamic inconsistency to arise between the initial beliefs and the updated beliefs (see Gilboa and Schmeidler, 1993). Dynamic consistency typically requires the decision problem with non-additive beliefs to be equivalent to one with additive beliefs, as stated in Kast and Lapied (2010) discussing Sarin and Wakker (1998). The problem of dynamic inconsistency carries over to ambiguous stochastic processes. Accordingly, dynamic consistency requires the ambiguous stochastic process to be equivalent to an additive one. For ambiguous random walks represented by a binomial tree, Kast and Lapied (2010) assume independence of the conditional capacities in order to derive the associated additive random walks. They show that additive random walks converge to Brownian motions for which an increase in ambiguity decreases both the drift and the variance, as outlined below. Suppose that the firm’s asset value, t V , follows a Choquet–Brownian process1. It is defined on the basis of a binomial lattice, where for each st at time t, such that 0 ≤ t ≤ T, st+1u and st+1d denote the possible successors at time t + 1 for an “up” and a “down” movement, respectively. If “up” and “down” movements have the same capacity, then υ(stu|st) = υ(std|st) = c, where c, 0 < c < 1, is a constant that represents the DM’s ambiguity about the likelihood of the states to come. If the DM is ambiguity averse, the capacity is sub-linear, so that c < 1/2 (Gilboa, Postlewaite and Schmeidler, 2008). If the perceived ambiguity increases, the value of the parameter c moves further away from the anchor 1/2. Thus, the capacity becomes more convex (for an ambiguity averse DM) or more concave (for an ambiguity loving DM). The symmetric discrete process outlined above can be shown to converge to a continuous time generalized Wiener process with mean m = 2c – 1 and variance s2 = 4c(1-c). The absence of an ambiguity bias is obtained as a special case for c = 1/2. Thus, the firm’s asset value is given by2: dVt/Vt = ((r – q) + mσ)dt + sσdBt (1) 1 A Choquet-Brownian process is a distorted Brownian process, where the distortion derives from the nature and intensity of preferences toward ambiguity (Kast, Lapied and Roubaud, 2014) 2 Expression (1) is obtained from = tt VdV / t dWdtqr σ +− )( , where tt sBmtW+= and t B is a Wiener process.
5 where r is the risk–free interest rate, q is the instantaneous rate of return on the firm’s assets (determining the internal liquidity of the firm from its cash flows), σ is the volatility, and Bt is a Wiener process. For fully ambiguity averse DMs we have - 1 < m < 0 and 0 < s < 1, so r – q + m σ < r - q and 0 < s σ < σ . Both drift and volatility are reduced in comparison to the case where ambiguity is absent. We assume that the firm issues perpetual debt which pays a continuous coupon at the rate C. The firm uses its revenue to make the coupon payment or to pay equity holders’ dividends. When revenues are not sufficient and in the absence of cash balances, the firm can decide either to issue new equity or to declare bankruptcy. Thus, if the revenue rate exceeds the coupon rate (qV ≥ C), equity holders receive dividends; if the revenue rate falls below the coupon rate, the firm dilutes equity. Equity dilution is costly and we assume that the cost of equity dilution is proportional to the proceeds from issuance. Thus, following the argument about equity dilution in Asvanunt, Broadie and Sundaresan (2011), it is equivalent to a negative dividend of β (qV – C). Below a critical value B V the firm will declare bankruptcy: that is, B V denotes the firm’s endogenous default threshold and is obtained as a result of equity holders’ optimization, as in Leland (1994). In the event of default, debt holders receive (1α) B V , where α denotes the fraction of cash flows lost due to default costs. In the next section we compute the total values of the firm’s equity and debt in the presence of ambiguity, for the current value of its assets. 3. EQUITY AND DEBT UNDER AMBIGUITY AVERSION For a given value of the firm’s assets V, denote the total value of its equity by E(V) and the total value of its debt by D(V). Following the standard contingent claims literature, we derive the value of equity by solving the system: 0)()()('))(()('' 2 1 222 =−+−+−+ CqVVrEVVEmqrVE Vs βσσ if q C VVB<≤ (2) 0)()()('))(()('' 2 1 222 =−+−+−+ CqVVrEVVEmqrVEVs σσ if q C V≥ . (3) In addition, the following boundary conditions must be satisfied: BC: 0)( = B VE +− =)()(: q C E q C EVM
6 :SP +− =)(')(' q C E q C E that is, equity holders receive nothing at bankruptcy (BC), and the value matching (VM) and smooth pasting (SP) conditions hold at C/q (see also Asvanunt, Broadie and Sundaresan, 2011). Moreover, we impose the condition that E(V) behaves like V when the firm’s value approaches infinity. In the Appendix we derive the following expression for the value of the firm’s equity: E(V) = q C VifVA r C V q C VVifVAVA r C V B ≥+− <≤++− − −− 1 12 3 32 ˆ )( )( ω ωω r rβ (4) where: − + − − −= σω ω ωω ω β ω mq C r C q C A 1 1 21 1 2 1 )1( 2 2111 2 1 3 ωωωω rβ −+ − −−= BBB VAV r C VA ( ) 1 3 1 2 23 )( 1 ˆ121 ωσ β ω ωωωω mq C q C A q C AA − −−+ = − , with σ r mq q − = and ( ) 22 22 2 2222 2,1 2)( 22 σ σσ σσ σ ω s rsmqr ss mqr + +−−±−+− = . Here we use 1 ω to denote the positive solution and ω2 to denote the negative solution. The bankruptcy threshold VB is derived by maximizing the value of equity with respect to VB. Since E(V) depends on VB only through A3, the optimal level VB* is derived solving ∂A3/∂VB = 0 . This value is given by the following implicit expression: 0)()1()( 1 2211 1 12=−−+− −− − ω ωωrβωβω BB VAV r C (5) Straightforward computation on (4) leads to the following: Proposition 1. The value of the firm’s equity decreases as the ambiguity perceived by the ambiguity averse DM increases.
7 An example3 is depicted in Figure 1, where the equity curve shifts downwards monotonically as c decreases. Figure 1. Value of the firm’s equity under ambiguity C = 2.3, = σ 0.2, r =0.05, q = 0.03, = α 0.3, = β 1 This result contrasts with what is usually obtained for an increase in uncertainty as measured by the volatility σ : indeed, the value of the firm’s equity increases with volatility, while it decreases as ambiguity increases. Moreover, the results in Remarks 1 and 2 follow: Remark 1. The default threshold B V increases as the ambiguity perceived by the ambiguity averse DM increases. As perceived ambiguity increases, equity holders choose a higher default level and hence enter financial distress earlier. This occurs because the value of the option to keep the firm open decreases with a higher ambiguity aversion bias, which reduces the variance in the Choquet-Brownian motion. Remark 2. The value of the firm’s equity decreases as the cost of equity dilution ( β ) increases. Let us now determine the value of the firm’s debt. If the firm liquidates its assets upon bankruptcy, a fraction α is lost due to liquidation costs. Thus, due to limited liability, debt holders will only receive .)1()( BB VVD α −= The value of the firm’s debt D(V) is determined solving the following equation: 3 The parameter values are similar to Asvanunt, Broadie and Sundaresan (2011) and consistent with previous works (see Leland, 1994). 0 10 20 30 40 50 60 70 80 90 V E(V) c=0.5 c=0.4 c=0.3
14 6. CONCLUSION Providing empirical support for our results is not straightforward, due to the difficulty in finding a convincing proxy for the size of the ambiguity aversion bias. Recent work by Rieger, Wang and Hens (2014) employs a methodology to measure the average ambiguity aversion across different countries, and this methodology might be adapted to our framework in order to estimate the level of the ambiguity aversion. As a preliminary step we analyzed cross-country average leverage values - where leverage is defined as book value of long term debt (item 106 in Compustat Global database) over market value of total assets, calculated as book value of total assets (item 89) minus book value of equity (item 146) plus market value of equity (item MKVAL) - over a period of five years for 24 countries5 . The average ambiguity aversion across these countries is provided by Rieger, Wang and Hens (2014) and is mapped into the parameter c . We found a positive correlation (0.566) between leverage and ambiguity bias (see Figure 6), which is consistent with our results. Initial empirical evidence showing that ambiguity aversion is positively associated with cash holdings is provided in Neamtiu, Shroff, White and Williams (2014). They use the dispersion in forecas ts of corporate profits from the Survey of Professional Forecasters as a proxy for the level of ambiguity. In contrast, Breuer, Rieger and Soypak (2014) find that for financially constrained firms cash holdings decrease with increasing ambiguity aversion, while they get inconclusive results for unconstrained firms. Although such results seem conflicting, they might benefit from being interpreted within the context of our model, which offers a general framework for understanding corporate decisions under ambiguity. 5 Australia, Austria, US, UK, Finland, Germany, Colombia, Sweden, Italy, New Zealand, France, The Netherlands, Switzerland, Argentina, Denmark, Malaysia, Portugal, Spain, Japan, Mexico, China, Chile, Canada, Thailand.
15 Figure 6. Cross-country leverage vs ambiguity aversion REFERENCES Anderson, R. and A. Carverhill (2011), ‘Corporate Liquidity and Capital Structure’, Review of Financial Studies, Vol. 25, pp. 797 – 837. Asvanunt, A., M. Broadie and S. Sundaresan (2011), ‘Managing Corporate Liquidity: Strategies and Pricing Implications’, International Journal of Theoretical and Applied Finance, Vol. 14, pp. 369406. Bates, T., K. Kahle and R. Stulz (2009), ‘Why Do U.S. Firms Hold So Much More Cash than They Used To?’, Journal of Finance, Vol. 64, pp. 1985 - 2021. Breuer, W., M. Rieger and K. Soypak (2014), ‘Precautionary Cash Holdings and Ambiguity Aversion’, Manuscript, Department of Finance, University of Aachen, Germany. Chateauneuf, A., J. Eichberger and S. Grant (2007), ‘Choice under Capacities with the Best and the Worst in Mind: Neo-Additive Capacities’, Journal of Economic Theory, Vol. 137, pp. 538 – 567. Decamps, J. and S. Villeneuve (2007), ‘Optimal Dividend Policy and Growth Option’, Finance and Stochastics, Vol. 11, pp. 3 - 27. Decamps, J. and S. Villeneuve (2013), ‘Optimal Investment under Liquidity Constraints’, in: Ambiguity, Real Options, Credit Risk and Insurance, ed. by A. Bensoussan, S. Peng and J. Sun, IOS Press, Amsterdam. Leverage vs parameter 'c' A US FIN D CO S I NZ F NL CH RA DK MAL E J MEX CDN CN RCH T AUS IND 0,00 0,10 0,20 0,30 0,40 0,50 0,60 c Leverage
16 Denis, J. and V. Sibikov (2010), ‘Financial Constraints, Investment and the Value of Cash Holding’, Review of Financial Studies, Vol. 23, pp. 247 - 269. Driouchi, T. , L. Trigeorgis and Y. Gao (2014),’ Choquet-based European option pricing with stochastic (and fixed) strikes’, forthcoming in Operations Research Spectrum Ellsberg , D. (1961), ‘Risk, Ambiguity and the Savage Axioms’, Quarterly Journal of Economics, Vol. 75, pp. 643 - 669. Epstein L. and M. Schneider (2010), ‘Ambiguity and asset markets’, Annual Review of Financial Economics, Vol. 2, pp. 315-346. Faulkender, M. and R. Wang (2006), ‘Corporate Financial Policies and the Value of Cash’, Journal of Finance, Vol. 61, pp. 1957 - 1990. Fulghieri, P. and D. Lukin (2001), ‘Information Production, Dilution Costs and Optimal Security Design’, Journal of Financial Economics, Vol. 61, pp. 3 - 42. Ghirardato, P., F. Maccheroni and M. Marinacci (2004), ‘Differentiating Ambiguity and Ambiguity Attitude’, Journal of Economic Theory, Vol. 118, pp. 133 – 173. Giammarino, R. and E. Neave (1982), ‘The Failure of Financial Contracts and the Relevance of Financial Policy’, Working Paper No 82-3, Queen’s University, Kingston Ontario, Canada. Gilboa, I., A. Postlewaite and D. Schmeidler (2008), ‘Probability and Uncertainty in Economic Modelling’, Journal of Economic Perspectives, Vol. 22, pp. 173 - 188. Gilboa, I., and D. Schmeidler (1993), ‘Updating Ambiguous Beliefs’, Journal of Economic Theory, Vol. 59, pp. 33 – 49. Hackbarth, D. (2008), ‘Managerial Traits and Capital Structure Decisions’, Journal of Financial and Quantitative Analysis, Vol. 43, pp. 843 - 882. Hackbarth, D. (2009), ‘Determinants of Corporate Borrowing: A Behavioral Perspective’, Journal of Corporate Finance, 15, 389-411. Haushalter, D., S. Klasa and W. Maxwell (2007). ‘The Influence of Product Market Dynamics on the Firm’s Cash Holdings and Hedging Behavior’, Journal of Financial Economics, Vol. 84, pp. 797826
17 Halov, N. and F. Heider (2011), ‘Capital Structure, Risk and Asymmetric Information’, Quarterly Journal of Finance, Vol. 1, pp. 767 - 781. Hennessy, C., D. Livdan and B. Miranda (2010), ‘Repeated Signalling and Firm Dynamics’, Review of Financial Studies, Vol. 23, pp. 19812023. Holberg, G., G. Phillips and N. Prabhala (2014), ‘Product Market Threats, Payouts, and Financial Flexibility’, Journal of Finance, Vol. 69, pp. 293 - 324. Hugonnier, J., S. Malamud and E. Morellec (2013), ‘Capital Supply Uncertainty, Cash Holdings, and Investment’, Swiss Finance Institute Research Series Papers, Forthcoming in: Review of Financial Studies. Jeanblanc-Picquè, M. and A. Shiryaev (1995), ‘Optimization of the Flow of Dividends’, Russian Mathematics Surveys, Vol. 50, pp. 257 - 277. Kast, R. and A. Lapied (2010), ‘Dynamically Consistent Choquet Random Walk and Real Investments’, Document de Recherche No 2010-21, LAMETA, Montpellier. Kast, R, A. Lapied and D. Roubaud (2014), ‘Modelling under ambiguity with dynamically consistent Choquet random walks and Choquet-Brownian motions’, Economic Modelling, pp. 495-503. Knight, F. (1921), Risk, Uncertainty and Profit, Houghton Mifflin, Boston and New York. Leary, M. and J. Roberts (2010), ‘The Pecking Order, Debt Capacity, and Information Asymmetry’, Journal of Financial Economics, Vol. 95, pp. 332-255. Leland, H. (1994), ‘Corporate Debt Value, Bond Covenants and Optimal Capital Structure’, Journal of Finance, Vol. 49, pp. 1213 - 1252. Lins, K., H. Servaes and P. Tufano (2010), ‘What Drives Corporate Finance? An International Survey of Cash Holdings and Lines of Credit’, Journal of Financial Economics, Vol. 98, pp. 160 – 176. Myers, S. and N. Majluf (1984), ‘Corporate Financing and Investment Decisions when Firms have Information that Investors do not have’, Journal of Financial Economics, Vol. 13, pp. 187 – 221. Nachman, D. and T. Noe (1994), ‘Optimal Design of Securities under Asymmetric Information’, Review of Financial Studies, Vol. 7, pp. 1 – 44.
18 Neamtiu, M., N. Shroff, H. White and C.D. Williams (2014), ‘The Impact of Ambiguity on Managerial Investment and Cash Holdings’, Journal of Business, Finance and Accounting, doi: 10.1111/jbfa.12079 Radner, R. and L. Shepp (1996), ‘Risk vs Profit Potential: A Model of Corporate Strategy’, Journal of Economic Dynamics and Control, Vol. 20, pp. 1373 – 1393. Rieger, M., M. Wang and T. Hens (2014), ‘Risk Preferences around the World’, Management Science, http://pubsonline.informs.org/doi/pdf/10.1287/mnsc.2013/1869 Sarin, R. and P. Wakker (1998), ‘Dynamic Choice and Non-Expected Utility’, Journal of Risk and Uncertainty, Vol. 17, pp. 87 – 119. Schmeidler, D. (1989), ‘Subjective Probability and Expected Utility without Additivity’, Econometrica, Vol. 57, pp. 571 - 587.
19 Appendix Equity Value under Ambiguity We start by determining, the first and the second derivatives of the general solution to (2), 12 3210 )( ωω −− +++= VAVAVAAVE : 1 31 1 221 12 )(' −−−− −−= ωω ωω VAVAAVE 2 311 2 222 12 )1()1()('' −−−− +++= ωω ωωωω VAVAVE Substituting them into (2), we obtain: [ ] 2 311 2 222 222 1 2 )1()1( 2 1−−−− +++ ωω ω ωωωσ VAVAVs ( ) [ ] 1 31 1 221 12 )( −−−− −−+−+ ωω ωωσ VAVAAVmqr [ ] 0)( 12 310 =−+++− −− CqVVAVAAr β ωω Rearranging this expression by gathering the terms relating to V, and we find: −−−−+ − 22222222 22 )()1( 2 1 2 rAAmAqrAsV σωωωωσ ω + −−−−+ − 33131311 22 )()1( 2 1 1rAAmAqrAsV σωωωωσ ω + 0)( 011 =−−+− CrAAmqAqV βσβ Setting the coefficients equal to zero we obtain 0 A = r C β − , σ β mq q A− = 1 , and can determine ω1 and ω2 as specified in (4), where ω1 is positive and ω2 negative. Applying the same procedure to the general solution of (3), 12 3210 ˆˆˆˆ )( ωω −− +++= VAVAVAAVE , we find = r C − and = σ mq q − . Since ω2 is negative, it follows that 0 ˆ2=A . The remaining coefficients, A2, A3, and 3 ˆ A , as in (4), are now determined by solving the conditions: BC: β )( r C V mq qB− − σ + 2 2 ω − B VA + 1 3 ω − B VA = 0 VM: β )( r C mq C− − σ + 2 )( 2 ω − q C A + 1 )( 3 ω − q C A = r C mq C− − σ + 1 )( ˆ 3 ω − q C A
20 SP: β σ mq q − - 1 22 2 )( −− ω ω q C A - 1 13 1 )( −− ω ω q C A = σ mq q − - 1 13 1 )( ˆ −− ω ω q C A Debt Value under Ambiguity Considering 1 210 )( ω − ++= VBVBBVD as the general solution to (5), we obtain: 1111 21121121 2 2 2 1 2)()( 2 1 2 1 ωωωω σωσωωσωσ −−−− −+−−−++ VBmVBmVBqrVBqrVBVB 0 1 210 =+−−− −CVrBVrBrB ω The coefficients B0 and B1 are determined by gathering the constant and the coefficient of the V term and setting them equal to zero: r C BCrB =⇒=+− 00 0 .00)( 1111 =⇒=−+− BrBBmBqr σ Finally, the coefficient B2 is obtained from the boundary condition .)1()( BB VVD α −= Indeed, ⇒−=+ − BB VVB r C)1( 1 2 α ω 1 )1( 2 ω α BB V r C VB −−= .