We employ the forward-looking implied dividend information contained in option prices to predict dividend cuts and omissions during the recent financial crisis. The large number of dividend cuts and omissions during the 2008-09 financial crisis period provides the opportunity to study the predictability of dividend cuts in a controlled environment. Implied dividends and implied volatility, based on put-call parity and computed from put and call option prices, prove to be effective in predicting those cuts, especially compared to only using the equity market and accounting variables conventionally used for this purpose. Options-derived variables (implied dividends and implied volatility) enhance the ability to identify firms more likely to reduce or omit dividend payments.
Credit union decisions on how funds are raised and invested and what services to provide are guided by their business models and should be reflected by credit union financial statements. We use cluster analysis to group credit unions using common size financial statement variables such that the financial statements are similar within credit union groups and distinct across groups. This allows the assignment of credit unions to groups by knowing their essential elements but without predefining the groups. In this paper, we present six credit union strategic groups differentiated from each other by their asset‐liability management choices and the services they provide members. Identifying the various credit union groups provides a clearer picture of their business models and the economic roles that different credit unions play.
While financial statement analysis is a rich tool, there is no widely used holistic measure of the amount of change in corporate financial statements. Statistical decomposition analysis has been employed as an index of the amount of change, but has fallen into disuse because it does not allow negative accounting numbers. As a remedy, this paper suggests three distance measures adapted from cluster analysis that avoid this critical data limitation. We successfully apply these proposed distance measures to explain the total and systematic risk of stock returns (in the CAPM and Fama–French model), corporate bond ratings, and corporate distress.
This paper explores the mathematics behind optimal portfolio construction when relative utility and risk are considered together in a general sense. I derive the portfolio optimization problems when subject to both a general liner constraint and a constraint to tracking error (a quadratic constraint), the most pervasive constraint placed on delegated portfolio managers. This unifies three very influential papers from the evolution of optimal portfolio theory. In addition, I also analyze the general linear constraint when applied to Sharpe Ratio maximization. When applied together, these formulations can allow principals and agents to better analyze alternatives and negotiate contracting in order to ensure that the constraints generate proper utility maximization.
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