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on Corporate Finance |
| By: | Dominique Guégan (Centre d'Economie de la Sorbonne) |
| Abstract: | In this paper we deal with the problem of non-stationarity encountered in a lot of data sets coming from existence of multiple seasonnalities, jumps, volatility, distorsion, aggregation, etc. We study the problem caused by these non stationarities on the estimation of the sample autocorrelation function and give several examples of models for which spurious behaviors is created by this fact. It concerns Markov switching processes, Stopbreak models and SETAR processes. Then, new strategies are suggested to study locally these data sets. We propose first a test based on the k-the cumulants and mainly the construction of a meta-distribution based on copulas for the data set which will permit to take into account all the non-stationarities. This approach suggests that we can be able to do risk management for portfolio containing non stationary assets and also to obtain the distribution function of some specific models. |
| Keywords: | Non-stationarity, distribution function, copula, long-memory, switching, SETAR, Stopbreak models, cumulants, estimation. |
| JEL: | C32 C51 G12 |
| Date: | 2007–04 |
| URL: | http://d.repec.org/n?u=RePEc:mse:cesdoc:b07053&r=cfn |
| By: | Marco Da Rin; MarÃa Fabiana Penas |
| Abstract: | We examine a unique dataset of Dutch companies, some of which have received venture financing. The data include detailed information on innovation activities and other company characteristics. We analyse the role of venture finance in influencing innovation strategies. We find that venture capitalists push portfolio companies towards building absorptive capacity and towards more permanent in-house R&D efforts. By contrast, we find that public funding relaxes financial constraints, but does not lead to a build-up of absorptive capacity. Our results thus highlight the special role of venture capital in shaping companies' innovation strategies. |
| JEL: | G24 O32 O38 |
| Date: | 2007–11 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:13636&r=cfn |
| By: | Vladimir Atanasov; Vladimir Ivanov; Kate Litvak |
| Abstract: | Venture capital contracts give VCs enormous power over entrepreneurs and early equity investors of portfolio companies. A large literature examines how these contractual terms protect VCs against misbehavior by entrepreneurs. But what constrains misbehavior by VCs? We provide the first systematic analysis of legal and non-legal mechanisms that penalize VC misbehavior, even when such misbehavior is formally permitted by contract. We hand-collect a sample of over 177 lawsuits involving venture capitalists. The three most common types of VC-related litigation are: 1) lawsuits filed by entrepreneurs, which most often allege freezeout and transfer of control away from founders; 2) lawsuits filed by early equity investors in startup companies; and 3) lawsuits filed by VCs. Our empirical analysis of the lawsuit data proceeds in two steps. We first estimate an empirical model of the propensity of VCs to get involved in litigation as a function of VC characteristics. We match each venture firm that was involved in litigation to otherwise similar venture firm that was not involved in litigation and find that less reputable VCs are more likely to participate in litigation, as are VCs focusing on early-stage investments, and VCs with larger deal flow. Second, we analyze the relationship between different types of lawsuits and VC fundraising and deal flow. Although plaintiffs lose most VC-related lawsuits, litigation does not go unnoticed: in subsequent years, the involved VCs raise significantly less capital than their peers and invest in fewer deals. The biggest losers are VCs who were defendants in a lawsuit, and especially VCs who were alleged to have expropriated founders. |
| JEL: | G24 G34 K22 |
| Date: | 2007–11 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:13641&r=cfn |
| By: | Jörn Hendrich Block; Andreas Thams |
| Abstract: | A stronger long-term orientation is considered a competitive advantage of family firms relative to non-family firms. In this study, we use panel data of U.S. firms and analyze this proposition. Our findings are surprising. Only in when the family is involved in the management of the firm is the firm found to invest more in long-term projects relative to a non-family firm. We also find that investment in long-term projects in family firms is determined less by cash flow variations than for non-family firms. Managerial implications of our findings are discussed. Our hypotheses are tested using Bayesian methods. |
| Keywords: | Family Firm, Long-term Orientation, Myopia, Bayesian Analysis, Agency Theory, Stewardship Theory, Investment Policy |
| JEL: | C11 D21 G31 G32 L20 M31 O32 |
| Date: | 2007–10 |
| URL: | http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2007-059&r=cfn |
| By: | Elisabete Gomes Santana Félix (Universidade de Évora,Departamento de Gestão); Cesaltina Pires (Universidade de Évora,Departamento de Gestão); Mohamed Azzim Gulamhussenb (Instituto Superior de Ciências do Trabalho e da Empresa,Departamento de Finanças e Contabilidade) |
| Abstract: | This article analyzes the determinants of the European venture capital market, extending the equilibrium model from Jeng and Wells (2000). Our empirical model includes many of the determinants already tested in previous studies. In addition, we test whether the unemployment rate, the trade sale divestment and the market-to-book ratio are important factors in explaining venture capital. We use aggregated data from the European venture capital market as well as macroeconomic data, to estimate panel data models, with fixed and random effects. The random effects models revealed to be the most adequate. Our results confirm the importance of some of the already known factors and show that the unemployment rate and trade sale divestments are important determinants in the European venture capital market. |
| Keywords: | Venture capital, Europe, Venture capital determinants, IPO, Trade sale, Write-off, Unemployment rate |
| JEL: | C23 G24 G32 G34 M13 |
| Date: | 2007 |
| URL: | http://d.repec.org/n?u=RePEc:cfe:wpcefa:2007_01&r=cfn |
| By: | Balázs Zsámboki (Magyar Nemzeti Bank) |
| Abstract: | This study aims to analyse the sensitivity of capital requirements to changes in risk parameters (PD, LGD and M) by creating a ‘model bank’ with a portfolio mirroring the average asset composition of internationally active large banks, as well as locally oriented smaller institutions participating in the QIS 5 exercise. Using historical data on corporate default rates, the dynamics of risk weights and capital requirements over a whole business cycle are also examined, with special emphasis on financial stability implications. The purpose of this paper is to contribute to a better understanding of the mechanism of Basel II and to explore the possible impacts of prudential regulation on cyclical swings in capital requirements. |
| Keywords: | Basel II, credit risk, capital requirement, regulation, cyclicality, financial stability. |
| JEL: | G21 G28 G32 |
| Date: | 2007 |
| URL: | http://d.repec.org/n?u=RePEc:mnb:opaper:2007/67&r=cfn |
| By: | Dimitrios Thomakos; Tao Wang |
| Abstract: | We examine the `relative optimality' of sign predictions for financial returns, extending the work of Christoffersen and Diebold (2006) on volatility dynamics and sign predictability. We show that there is a more general decomposition of financial returns than that implied by the sign decomposition and which depends on the choice of the threshold that defines direction. We then show that the choice of the threshold matters and that a threshold of zero (leading to sign predictions) is not necessarily `optimal'. We provide explicit conditions that allow for the choice of a threshold that has maximum responsiveness to changes in volatility dynamics and thus leads to `optimal' probabilistic predictions. Finally, we connect the evolution of volatility to probabilistic predictions and show that the volatility ratio is the crucial variable in this context. Our work strengthens the arguments in favor of accurate volatility measurement and prediction, as volatility dynamics are integrated into the `optimal' threshold. We provide an empirical illustration of our findings using monthly returns and realized volatility for the S&P500 index. |
| Date: | 2007 |
| URL: | http://d.repec.org/n?u=RePEc:uop:wpaper:0006&r=cfn |