Scarf's max-min order formula for the risk-neutral and ambiguity-averse newsvendor problem is a classical result in the field of inventory management. In this article, we extend Scarf's formula by deriving an analogous closed-form order formula for the risk- and ambiguity-averse newsvendor problem. Specifically, we provide and analyze the newsvendor order quantity that maximizes the worst-case expected profit versus risk trade-off (risk-averse) when only the mean and standard deviation of the product's demand distribution are known (ambiguity-averse), and the risk is measured by the standard deviation of the newsvendor's profit. We provide both analytical and numerical results to illustrate the combined effect of considering risk aversion and ambiguity aversion in computing the newsvendor order.

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Miners in various blockchain-backed cryptocurrency networks compete to maintain the validity of the underlying distributed ledgers to earn the bootstrapped cryptocurrencies. With limited hashing power, each miner needs to decide how to allocate their resource to different cryptocurrencies so as to achieve the best overall payoff. Together all the miners form a hashing power allocation game. We consider two settings of the game, depending on whether each miner can allocate their fund to a risk-free asset or not. We show that this game admits unique pure Nash equilibrium in closed-form for both settings.