Skip to content
All library documents

Wavelet-Based Trading Without Price Forecasts

Article arXiv papers · Author: Lanh Tran
Read the original

Summary

The paper outlines wavelet-based trading ideas for stocks and commodities, with its main focus on New York Stock Exchange equities. It frames three aims: trading price fluctuations to seek gains without an overall price rise, eventually outperforming the market, and outperforming a geometric Brownian motion benchmark. The proposed approach reads large and small price movements as waves and wavelets, then uses them to guide trading decisions without predicting future prices. Behavioral economics is also described as part of the decision process.

The document states that the paper presents strategies addressing these aims, but provides no rules for generating signals, position sizing, risk controls, or transaction costs in the supplied text. It also reports no data, tests, or quantitative evidence to support its claims of eventual outperformance. The description is therefore an overview of proposed ideas rather than enough detail to assess their validity or practical performance.

Key ideas

  • The strategies interpret large and small price fluctuations as waves and wavelets.
  • The approach is presented as trading price movements without forecasting future prices.
  • The paper discusses applications to stocks and commodities, especially US equities.
  • Behavioral economics is included in the trading decision process.
  • The supplied description makes outperformance claims but gives no supporting tests or implementation details.

Tags

EquitiesCommoditiesTechnical indicatorsUS markets
Full text
# 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.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.