METHODS OF FORECASTING EXCHANGE RATES IN DIGITAL ASSET TRADING
DOI:
https://doi.org/10.55640/Keywords:
digital assets, exchange rates, fundamental analysis, quantitative analysis, sentimental analysis, market forecast, economic indicators, artificial intelligence, investment strategies.Abstract
In digital asset trading, there are different ways of forecasting exchange rates, among which fundamental, quantitative and sentimental analysis occupy the main place. Fundamental analysis predicts exchange rate fluctuations by studying economic, political and financial factors. Quantitative analysis, on the other hand, focuses on predicting based on past data using mathematical models and artificial intelligence algorithms. Sentimental analysis, on the other hand, allows you to predict the future actions of investors by analyzing the mood of market participants. The combination of these methods serves to more accurately predict the movements of exchange rates.
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References
1.Frankel, Jeffrey and Kenneth Froot, 1987a, “Using Survey Data to Test Standard Propositions Regarding Exchange Rate Expectations,” American Economic Review 77, 133–53.
2.Friedman, Milton, “The Case for Flexible Exchange Rates,” in his Essays in Positive Economics, (Chicago: University of Chicago Press, 1953).
3.Froot, Kenneth, and Takatoshi Ito, “On the Consistency of Short-run and Long-run Exchange Rate Expectations,” NBER Working Paper No. 2577, (May 1988). Forthcoming, Journal of International Money and Finance.
4.Rutledge, David, “Trading Volume and Price Variability: New Evidence on the Price Effects of Speculation,” in Futures Markets: Their Establishment and Performance, ed. by B.A. Goss, (New York: New York University Press, 1986).
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This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain the copyright of their manuscripts, and all Open Access articles are disseminated under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which licenses unrestricted use, distribution, and reproduction in any medium, provided that the original work is appropriately cited. The use of general descriptive names, trade names, trademarks, and so forth in this publication, even if not specifically identified, does not imply that these names are not protected by the relevant laws and regulations.
Germany
United States of America
Italy
United Kingdom
France
Canada
Uzbekistan
Japan
Republic of Korea
Australia
Spain
Switzerland
Sweden
Netherlands
China
India
