
In this paper, we propose a new model for pricing stock and dividend derivatives. We jointly specify dynamics for the stock price and the dividend rate such that the stock price is positive and the dividend rate nonnegative. In its simplest form, the model features a dividend rate that is mean-reverting around a constant fraction of the stock price. The advantage of directly specifying dynamics for the dividend rate, as opposed to the more common approach of modeling the dividend yield, is that it is easier to keep the distribution of cumulative dividends tractable. The model is nonaffine but does belong to the more general class of polynomial processes, which allows us to compute all conditional moments of the stock price and the cumulative dividends explicitly. In particular, we have closed-form expressions for the prices of stock and dividend futures. Prices of stock and dividend options are accurately approximated using a moment matching technique based on the principle of maximal entropy.
term-structure models, Computational Finance (q-fin.CP), Mathematical Finance (q-fin.MF), polynomial processes, FOS: Economics and business, Quantitative Finance - Computational Finance, Derivative securities (option pricing, hedging, etc.), Quantitative Finance - Mathematical Finance, Pricing of Securities (q-fin.PR), dividend derivatives, Quantitative Finance - Pricing of Securities, Interest rates, asset pricing, etc. (stochastic models)
term-structure models, Computational Finance (q-fin.CP), Mathematical Finance (q-fin.MF), polynomial processes, FOS: Economics and business, Quantitative Finance - Computational Finance, Derivative securities (option pricing, hedging, etc.), Quantitative Finance - Mathematical Finance, Pricing of Securities (q-fin.PR), dividend derivatives, Quantitative Finance - Pricing of Securities, Interest rates, asset pricing, etc. (stochastic models)
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