Optimal search with bounded daily returns

Esther Mohr
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引用次数: 1

Abstract

The `reservation price policy' of [1] is based on the assumption that asset prices are arbitrary drawn from a pair of upper an lower bounds, that is, m and M. By defining a set of constants the maximum interday price fluctuation can be bounded in order to reduce market volatility. Arbitrary price movements like a sudden drop from M to m are excluded. We present and analyze online conversion algorithms under bounded daily returns. Results show that an investor solely requires the a-priori information whether the price function is symmetric or not to choose the algorithm with the smallest competitive ratio.
日收益有限的最优搜索
[1]的“保留价格政策”是基于资产价格从一对上界和下界(即m和m)中任意提取的假设,通过定义一组常数,可以对最大的日间价格波动进行限制,以减少市场波动。不包括任意的价格变动,比如从M点突然降到M点。我们提出并分析了有界日收益下的在线转换算法。结果表明,投资者只需要价格函数是否对称的先验信息,就会选择竞争比最小的算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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