Paper: arXiv 2604.26063

Authors: Luyun Lin, Lixing Lin, Zhen Zhang, Moxuan Zheng, Yiqing Wang

Abstract

Traditional moving average convergence divergence (MACD) trading rules are often constrained by signal lag and susceptibility to false signals. To address these limitations, this study develops a volume-price-adjusted MACD (VP-MACD) framework that incorporates volume, volatility, and intraday price structure into the conventional indicator, and introduces a sensitivity parameter to allow earlier trade entry and improve responsiveness to market movements. Using the S&P 500, Nasdaq-100, and Dow Jones Industrial Average as representative U.S. equity indices, the model is calibrated over historical records from 2018 to 2022 and evaluated out of sample over 2023 to February 2026. The results indicate that the proposed framework generally delivers better economic performance than the baseline MACD strategy in terms of profitability, risk-adjusted return, and downside-risk control, while generating fewer but more selective trading signals. These findings suggest that incorporating additional market information into technical trading rules may enhance signal quality in U.S. equity index markets.

Complexity vs Empirical Score

  • Math Complexity: 3.5/10
  • Empirical Rigor: 7.0/10
  • Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: The methodology relies on standard technical indicator modifications and basic time-series arithmetic rather than advanced mathematical modeling. However, the paper is categorized as Street Traders due to its strong focus on backtesting, walk-forward out-of-sample evaluation, and practical implementation for professional trading signal generation.

Research Flowchart

  flowchart TD
    A[<b>Goal:</b> Enhance MACD Signal Accuracy & Responsiveness] --> B[<b>Inputs:</b> S&P 500, Nasdaq-100, DJIA (2018-2026)]
    B --> C[<b>Methodology:</b> Integrate Volume, Volatility & Intraday Structure]
    C --> D[<b>Computational Process:</b> Sensitivity Calibration & Sensitivity Parameter Tuning]
    D --> E[<b>Validation:</b> Backtesting (Historical & Out-of-Sample)]
    E --> F[<b>Findings:</b> Higher Risk-Adjusted Returns & Selective Trading Signals]

Cited References (25)

  1. Security Analysis: Principles and Techniques (2023)
  2. The Moving Average Convergence-Divergence Trading Method (1979)
  3. Machine learning applied in the stock market through the Moving Average Convergence Divergence (MACD) indicator (2020)
  4. Stock market efficiency and the MACD. Evidence from countries around the world (2015)
  5. Simple technical trading rules and the stochastic properties of stock returns (1992)
  6. The Effectiveness Test of MACD in Chinese Stock Market (2021)
  7. Regime-Dependent Volatility Dynamics: Evidence from Time-Series Analysis (2026)
  8. A comparative study of the MACD-base trading strategies: evidence from the US stock market (2022) — link
and 17 more
  1. Technical analysis and the London stock exchange: testing the MACD and RSI rules using the FT30 (2008)
  2. Revisiting the Performance of MACD and RSI Oscillators (2014)
  3. The complexity of cryptocurrencies algorithmic trading (2022)
  4. Investment valuation: Tools and techniques for determining the value of any asset (2012)
  5. Technical analysis of stock trends (2018)
  6. Efficient capital markets: A review of theory and empirical work (1970)
  7. The profitability of moving average trading rules in South Asian stock markets (2001)
  8. Technical analysis: exploring MACD in the Lebanese stock market (2017)
  9. Improving MACD technical analysis by optimizing parameters and modifying trading rules: evidence from the Japanese Nikkei 225 futures market (2021)
  10. Optimal and Non-Optimal MACD Parameter Ranges with Stop-Loss and Take-Profit Rules: Evidence from the Gold Market (2026)
  11. The adaptive markets hypothesis: Market efficiency from an evolutionary perspective (2004)
  12. Technical analysis of the financial markets: A comprehensive guide to trading methods and applications (1999)
  13. The profitability of technical analysis: A review (2004)
  14. Technical analysis explained: The successful investor’s guide to spotting investment trends and turning points (2002)
  15. The Price-Trading Volume Relationship in the Brazilian Stock Market, the Impact of Stock Lending and a Role for Technical Analysis (2015)
  16. From efficient markets theory to behavioral finance (2003)
  17. Predicting stock price trend using MACD optimized by historical volatility (2018)

0 of 25 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.