Using Heatmap Visualization to assess the performance of the DJ30 and NASDAQ100 Indices under diverse VMA trading rules

Abstract

We investigate whether using various VMA trading rules would improve investment performance due to the flexibility of VMA trading rules and the aid of Heatmap Visualization. Previously, investors frequently chose the best performance derived from limited VMA trading rules. However, our new design, which can display all results using Heatmap Visualization, shows that the NASDAQ100 index outperforms the DJ30 index and that weekly data outperforms daily data when measured by annualized return. These findings may be useful to those who trade index ETFs tracking the DJ30 and NASDAQ100 indices, as well as investors making investment decisions, and may contribute to the existing literature by evaluating the outcomes of VMA trading rules and providing insights for index ETF investors using a heatmap matrix, which is rarely explored and presented in the relevant literature.

Using Big Data Analytics and Heatmap Matrix Visualization to Enhance Cryptocurrency Trading Decisions

“…Such findings are somewhat similar in that the results using variable moving average (VMA) trading regulation are better than those using fixed moving average (FMA) trading regulation in the relevant studies [87,88]. Instead of cryptocurrency markets, Chen et al [89] apply VMA trading rules to US stock markets, showing that the NASDAQ 100 index outperforms the DJ30 index, providing useful information for those who purchase stocks that track the NASDAQ 100 and DJ30 (i.e., index ETF traders).…”

Mastery of “Monthly Effects”: Big Data Insights into Contrarian Strategies for DJI 30 and NDX 100 Stocks over a Two-Decade Period

“…In practical situations, the widely accepted EMH encounters a challenge from the domain of technical analysis [9,[29][30][31]. The application of technical trading rules can be attributed to herd behavior driven by investor sentiment [32,33], or to stock price overreactions that lead to subsequent price rebounds [34][35][36]. Consequently, the decision to use technical analysis is influenced by a variety of academic concerns, including market inefficiencies, herding behaviors, and stock price overreaction.…”

Navigating Energy and Financial Markets: A Review of Technical Analysis Used and Further Investigation from Various Perspectives

“…These patterns can indicate potential trend reversals or continuations, aiding traders in determining optimal entry and exit points. Additionally, technical trading rules, such as the RSI, SOI, and Ma trading rules, are mathematical calculations using historical price data [52][53][54][55], which would help identify over-reaction conditions, confirm trends, or signal reversals, supporting traders in their decision-making process.…”

“…For instance, candlestick charts are used in technical analysis to show price trends and reversals [71]. Similarly, heatmaps can visually depict market volatility and price changes across various periods and asset categories since heatmap visualization may help traders make proper decisions [39,42,52,57]. Furthermore, advancements in data visualization technologies, such as augmented reality (AR) and virtual reality (VR), hold promise for enhancing traders' ability to analyze and interpret complex market data [174,175].…”