International Journal of Academic and Practical Research
ISSN (Print): 2980-4116; ISSN (Online): 2980-4124
Charles Jordan V. Madulid College of Education, Arts and Sciences, National University, Manila, Philippines Angelo P. Lansang College of Engineering and Architecture, Technological Institute of the Philippines, Manila, Philippines
Abstract
With the sudden growth of cryptocurrency, the researchers decided to conduct this study that can help further understand cryptocurrency through different variables of understanding and analysis that can help determine the underlying growth and importance of cryptocurrency. Throughout the study, the researchers have gathered information to understand cryptocurrency, such as its definition, origin, and purpose. To address the problem, by answering the questions that linger in people’s minds about the functions, benefits, security, and diverse uses of cryptocurrency, the researchers solidified its credibility and viability as an investment vehicle. Regression analysis and time-series models were implemented through statistical data analysis, data collection, and forecasting of contextual data. Then, after getting the forecasting contextual data, the researchers compared the historical time series data and the forecast data to analyze and evaluate it. The findings confirm the influence of cryptocurrency on inflation, the similarities and differences between the historical price data and forecast data, and the visualization result of the forecasting with the given data. The research shows a clear understanding of how cryptocurrency works by providing information, gathering data for it to be analyzed and evaluated, and visualizing the data through forecasting as it can be considered a prominent study by both researchers and investors due to its important role in the economy. The study aimed to understand cryptocurrency by analyzing the behavior and movement of the market in order to achieve the best profit margins for investing while avoiding investment risk.
Article Information
Article History
Received: 08 Aug 2022;
Reviewed: 12 Sep 2022;
Revised: 10 Oct 2022;
Accepted: 24 Oct 2022;
Published: 24 Oct 2022
Keywords
cryptocurrency, digital generation, forecast data, historical time series data, regression analysis
Corresponding Author
Charles Jordan V. Madulid madulidcjordan@gmail.com
References Australian Bureau of Statistics (2022). Time series analysis: The basics. Methods, Standards and Classifications. Australian Bureau of Statistics. https://www.abs.gov.au/websitedbs/D3310114.nsf/home/Time+Series+Analysis:+The+Basics#:~:text=The%20irregular%20component%20%28sometimes%20also%20known%20as%20the,the%20series%20which%20are%20neither%20systematic%20nor%20predictable. Ball, R. (1995). The theory of stock market efficiency: accomplishments and limitations. Journal of Applied Corporate Finance, 8(1), 4-18. Ball, R. (1996). The theory of stock market efficiency: accomplishments and limitations. Journal of Financial Education, 1-13. Boudoukh, J., Feldman, R., Kogan, S., & Richardson, M. (2019). Information, trading, and volatility: Evidence from firm-specific news. The Review of Financial Studies, 32(3), 992-1033. Chen, J. (2022, April 19). Fiat money: What it is, how it works, example, pros & cons. Investopedia. https://www.investopedia.com/terms/f/fiatmoney.asp Chiu, J., & Koeppl, T. V. (2019). Blockchain-based settlement for asset trading. The Review of Financial Studies, 32(5), 1716-1753. Chuen, D. L. K., Guo, L., & Wang, Y. (2017). Cryptocurrency: A new investment opportunity?. The Journal of Alternative Investments, 20(3), 16-40. Faris, S. (2019, May 29). The theory of stock market efficiency. Zacks Investment Research. https://finance.zacks.com/theory-stock-market-efficiency-6295.html Frankenfield, J. (2022a, January 13). Digital currency types, characteristics, pros & cons, future uses. Investopedia. https://www.investopedia.com/terms/d/digital-currency.asp Frankenfield, J. (2022b, May 28). Cryptocurrency explained with pros and cons for investment. Investopedia. https://www.investopedia.com/terms/c/cryptocurrency.asp Huang, X. (2019). Mark Twain’s Cat: Investment experience, categorical thinking, and stock selection. Journal of Financial Economics, 131(2), 404-432. Jose, B. K. (2021, February 4). Time series forecasting using LSTM | code walkthrough. Medium. https://medium.com/apes-ai/time-series-forecasting-using-lstm-code-walkthrough-3aae01645491 Kakushadze, Z., & Russo, R. P. (2018). Blockchain: data malls, coin economies, and keyless payments. The Journal of Alternative Investments, 21(1), 8-16. Karra, S. (2020, July 20). Time series analysis. Medium. https://sailajakarra.medium.com/time-series-analysis-d655f0391d33 Khanna, A. (2012). Understanding digital marketing marketing strategies for engaging the digital generation. Global Journal of Enterprise Information System, 4(2), 50-51. Makarov, I., & Schoar, A. (2020). Trading and arbitrage in cryptocurrency markets. Journal of Financial Economics, 135(2), 293-319. Malkiel, B. G. (2003). The efficient market hypothesis and its critics. Journal of Economic Perspectives, 17(1), 59-82. Matvos, G., Seru, A., & Silva, R. C. (2018). Financial market frictions and diversification. Journal of Financial Economics, 127(1), 21-50. Minitab (2022). Methods and formulas for Moving Average. Minitab, LLC. https://support.minitab.com/en-us/minitab/21/help-and-how-to/statistical-modeling/time-series/how-to/moving-average/methods-and-formulas/methods-and-formulas/ NDTV Business Desk (2021a, August 09). No, digital currency is not same as cryptocurrency. NDTV Convergence Limited. https://www.ndtv.com/business/digital-currency-vs-cryptocurrency-how-are-they-different-2503481 NDTV Business Desk (2021b, August 14). What makes the cryptocurrency market so volatile? Find out. NDTV Convergence Limited. https://www.ndtv.com/business/why-is-the-cryptocurrency-market-so-volatile-2509836 Sethi, V. (2019, July 4). Time series analysis and forecasting of web service metrics. Medium. https://towardsdatascience.com/time-series-analysis-and-forecasting-of-web-service-metrics-1e15d7fb72c2 Tuarob, S., Wettayakorn, P., Phetchai, P., Traivijitkhun, S., Lim, S., Noraset, T., & Thaipisutikul, T. (2021). DAViS: a unified solution for data collection, analyzation, and visualization in real-time stock market prediction. Financial Innovation, 7(1), 1-32. Udemy, Inc. (2022). Technical analysis (finance) courses. Udemy, Inc. https://www.udemy.com/topic/technical-analysis/ Walther, T., Klein, T., & Bouri, E. (2019). Exogenous drivers of Bitcoin and Cryptocurrency volatility–A mixed data sampling approach to forecasting. Journal of International Financial Markets, Institutions and Money, 63, 101133. Wonglimpiyarat, J. (2017). FinTech banking industry: a systemic approach. Foresight, 19(6), 590-603
Details
- Primary Language: English
- Subject: Practical Research (Science, Technology, Engineering and Mathematics)
- Journal Section: Research Article
- Published in Issue: Year 2022, Volume 1, Issue 1
Cite (APA)
Madulid, C. J. V., & Lansang A. P. (2022). Engaging the digital generation through analyzing and understanding the growth and importance of cryptocurrency. International Journal of Academic and Practical Research, 1(1), 40 – 52.
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