Amortized efficiency of list update and paging rules
Communications of the ACM
Competitive solutions for online financial problems
ACM Computing Surveys (CSUR)
Online computation and competitive analysis
Online computation and competitive analysis
The statistical adversary allows optimal money-making trading strategies
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
Optimal Buy-and-Hold Strategies for Financial Markets with Bounded Daily Returns
SIAM Journal on Computing
Competitive analysis of financial games
SFCS '92 Proceedings of the 33rd Annual Symposium on Foundations of Computer Science
How much is it worth to know the future in online conversion problems?
Discrete Applied Mathematics
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Based on the unidirectional conversion model, we investigate a practical buy-and-hold trading problem. This problem is useful for long-term investors, we use competitive analysis and game theory to design some trading rules in the securities markets. We present an online algorithm, Mixed Strategy, for the problem and prove its competitive ratio $1 + \frac{(n-1)t}{2}$, where n is the trading horizon and t is the daily fluctuations of securities prices. The Dynamic-Mixed Strategy is also presented to further reduce the competitive ratio. An investing example is simulated with the Mixed Strategy and Dollar Average Strategy based on the actual market data.