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无需价格预测的小波交易方法

文章 arXiv papers · 作者: Lanh Tran
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总结

本文概述了股票和大宗商品的小波交易思路，重点关注纽约证券交易所股票。文章提出三个目标：交易价格波动以寻求收益，而不要求价格整体上涨；最终跑赢市场；以及跑赢几何布朗运动基准。该方法将大小不同的价格变动视为波和小波，并据此指导交易决策，而不预测未来价格。文中还将行为经济学纳入决策过程。

文中称论文提出了针对这些目标的策略，但所给文本未提供信号生成、仓位规模、风险控制或交易成本方面的规则。文中也未报告任何数据、测试或量化证据来支持最终跑赢市场的说法。因此，这段描述只是对拟议思路的概述，信息不足以评估其有效性或实际表现。

核心观点

  • 这些策略将大小不同的价格波动解读为波和小波。
  • 该方法声称可以交易价格走势而无需预测未来价格。
  • 论文讨论股票和大宗商品的应用，尤其是 US 股票。
  • 该交易决策过程纳入了行为经济学。
  • 所提供的描述提出了跑赢市场的主张，但没有给出支持性测试或实现细节。

标签

股票大宗商品技术指标美国市场
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# How Wave - Wavelet Trading Wins and "Beats" the Market


# How Wave - Wavelet Trading Wins and "Beats" the Market









The purpose of this paper is to showcase trading strategies that give solutions to three difficult and intriguing problems in business finance, economics and statistics. The paper discusses trading strategies for both commodities and stocks but the main focus is on stock market trading at the New York Stock Exchange. Problem 1: Buy Low and Sell High. The buy low and sell high problem can be summarized like this: suppose the price of a commodity or stock fluctuates indefinitely, is there any explicit strategy for a trader to "ride the price waves" by buying low and selling high to eventually win even if price does not increase? Problem 2: "Beat" the Market. In Part 2, the trading system presented in Part 1 is transformed into a strategy that always outperforms the market eventually. Problem 3: Can a Trader Outperform a geometric Brownian Motion? The general belief is that it is impossible to "beat" a GBM since technical analysis of historical prices is useless in predicting future prices. The last part of the paper shows that the answer to Problem 3 is actually a "YES", which is quite surprising. The trading strategies presented are based mainly on information obtained from the movements of waves and wavelets created by large and small fluctuations of market prices. They do not involve any forecasting or prediction of future prices. Behavioral economics also plays a role in the decision making process of the Wavelet Trading program. My website AgateTrading.com is available to the public.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。