We consider the following online two-way trading problem: given some amount of money and a stock (security) of fluctuating prices, we want to perform a bounded number of speculative trades so as to make the most money. We assume a global fluctuation model, where global limits on the minimum and maximum possible prices are given. Previously, optimal algorithms were established in the deterministic case. In this paper we consider two models that improve the competitiveness: randomized algorithms, and algorithms with advice. In most cases we give close to optimal upper and lower bounds on the competitive ratios.

中文翻译：

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网上双向交易：随机和建议

我们考虑以下在线双向交易问题：考虑到一定数量的钱和价格波动的股票（证券），我们希望进行一定数量的投机交易，以赚取最多的钱。我们假设一个全局波动模型，其中给出了对最小和最大可能价格的全局限制。以前，在确定性情况下建立了最佳算法。在本文中，我们考虑了两种提高竞争力的模型：随机算法和带建议的算法。在大多数情况下，我们给出竞争比率的最佳上限和下限。