淡江大學機構典藏:Item 987654321/125193
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/125193


    Title: Enhancing Crypto Success via Heatmap Visualization of Big Data Analytics for Numerous Variable Moving Average Strategies
    Authors: Chiu, Chien-liang
    Keywords: VMA trading rules;cryptocurrencies;Ethereum (ETH);investing strategies;heatmap visualization;big data analytics
    Date: 2023-11-29
    Issue Date: 2024-03-08 12:05:39 (UTC+8)
    Publisher: MDPI
    Abstract: This study employed variable moving average (VMA) trading rules and heatmap visualization because the flexibility advantage of the VMA technique and the presentation of numerous outcomes using the heatmap visualization technique may not have been thoroughly considered in prior financial research. We not only employ multiple VMA trading rules in trading crypto futures but also present our overall results through heatmap visualization, which will aid investors in selecting an appropriate VMA trading rule, thereby likely generating profits after screening the results generated from various VMA trading rules. Unexpectedly, we demonstrate in this study that our results may impress Ethereum futures traders by disclosing a heatmap matrix that displays multiple geometric average returns (GARs) exceeding 40%, in accordance with various VMA trading rules. Thus, we argue that this study extracted the diverse trading performance of various VMA trading rules, utilized a big data analytics technique for knowledge extraction to observe and evaluate numerous results via heatmap visualization, and then employed this knowledge for investments, thereby contributing to the extant literature. Consequently, this study may cast light on the significance of decision making via big data analytics.
    Relation: Appl. Sci. 13(23),　12805
    DOI: 10.3390/app132312805
    Appears in Collections:[Graduate Institute & Department of Banking and Finance] Journal Article

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