Cover's Rebalancing Option With Discrete Hindsight Optimization
Alex Garivaltis

TL;DR
This paper analyzes a discrete set of rebalancing rules in Cover's rebalancing option, demonstrating that limiting to specific asset allocations reduces costs and ensures near-optimal long-term growth relative to the best hindsight choice.
Contribution
It introduces a simplified, discrete-hindsight optimization approach for Cover's rebalancing option, improving practicality and cost-effectiveness.
Findings
Restricting to a finite set of rebalancing rules lowers option prices.
Practitioners can achieve growth rates close to the best hindsight asset allocation.
The approach guarantees near-optimal long-term capital growth.
Abstract
We study T. Cover's rebalancing option (Ordentlich and Cover 1998) under discrete hindsight optimization in continuous time. The payoff in question is equal to the final wealth that would have accrued to a \1200\%-100\%\&$ Company in their brilliant theory of universal portfolios (1986, 1991, 1996, 1998), where one's on-line trading performance is benchmarked relative to the final wealth of the best unlevered rebalancing rule of…
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