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It is used to help determine the levered beta and, through this, the optimal capital structure of firms. It was named after Robert Hamada, the Professor of Finance behind the theory. Hamada’s equation relates the beta of a levered firm (a firm financed by both debt and equity) to that of its unlevered (i.e., a firm which has no debt) counterpart.
One possibility to "fix" the formula is use the stochastic collocation method and to project the corresponding implied, ill-posed, model on a polynomial of an arbitrage-free variables, e.g. normal. This will guarantee equality in probability at the collocation points while the generated density is arbitrage-free. [4]
APV formula APV = Unlevered NPV of Free Cash Flows and assumed Terminal Value + NPV of Interest Tax Shield and assumed Terminal Value : The discount rate used in the first part is the return on assets or return on equity if unlevered; The discount rate used in the second part is the cost of debt financing by period.
In finance, the beta (β or market beta or beta coefficient) is a statistic that measures the expected increase or decrease of an individual stock price in proportion to movements of the stock market as a whole. Beta can be used to indicate the contribution of an individual asset to the market risk of a portfolio when it is
Security characteristic line Positive abnormal return (α): Above-average returns that cannot be explained as compensation for added risk Negative abnormal returns (α): Below-average returns that cannot be explained by below-market risk
In probability theory and statistics, the beta distribution is a family of continuous probability distributions defined on the interval [0, 1] or (0, 1) in terms of two positive parameters, denoted by alpha (α) and beta (β), that appear as exponents of the variable and its complement to 1, respectively, and control the shape of the distribution.
The beta-binomial distribution is the binomial distribution in which the probability of success at each of n trials is not fixed but randomly drawn from a beta distribution. It is frequently used in Bayesian statistics , empirical Bayes methods and classical statistics to capture overdispersion in binomial type distributed data.
The dual-beta model attempts to differentiate downside risk (risk of loss) from upside risk (gain), both measured in terms of beta with respect to the market and not individual idiosyncratic risk. Mathematically, neither the two betas nor their average needs to be similar to the overall single beta.