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Journal articles on the topic 'Forex market'

Author: Grafiati

Published: 4 June 2021

Last updated: 11 September 2023

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1

Olufemi, Adeyeye Patrick, Aluko Olufemi Adewale, and Migiro Stephen Oseko. "Efficiency of Foreign Exchange Markets in Sub-Saharan Africa in the Presence of Structural Break: A Linear and Non-Linear Testing Approach." Journal of Economics and Behavioral Studies 9, no. 4(J) (September 4, 2017): 122–31. http://dx.doi.org/10.22610/jebs.v9i4(j).1827.

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This study examines the efficiency of foreign exchange (forex) market of 10 selected countries in sub-Saharan Africa in the presence of structural break. It uses data on the average official exchange rate of currencies of the selected countries to the US dollar from November 1995 to October 2015. This study employs Perron unit root test with structural break to endogenously determine the break period in the forex markets. It also employs the Kim wild bootstrap variance ratio test and BDS independence test to detect linear and nonlinear dependence in forex market returns respectively. In the full sample period, the Kim wild bootstrap joint variance ratio test shows that only two forex markets are efficient while the BDS independence test reports that all the forex markets are not efficient. The subsample period analysis indicates that the efficiency of the majority of the forex markets is sensitive to structural break, thus providing evidence in support of the adaptive market hypothesis. This study suggests that ignoring structural break and nonlinearity of returns may lead to misleading results when testing for market efficiency.

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Olufemi, Adeyeye Patrick, Aluko Olufemi Adewale, and Migiro Stephen Oseko. "Efficiency of Foreign Exchange Markets in Sub-Saharan Africa in the Presence of Structural Break: A Linear and Non-Linear Testing Approach." Journal of Economics and Behavioral Studies 9, no. 4 (September 4, 2017): 122. http://dx.doi.org/10.22610/jebs.v9i4.1827.

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This study examines the efficiency of foreign exchange (forex) market of 10 selected countries in sub-Saharan Africa in the presence of structural break. It uses data on the average official exchange rate of currencies of the selected countries to the US dollar from November 1995 to October 2015. This study employs Perron unit root test with structural break to endogenously determine the break period in the forex markets. It also employs the Kim wild bootstrap variance ratio test and BDS independence test to detect linear and nonlinear dependence in forex market returns respectively. In the full sample period, the Kim wild bootstrap joint variance ratio test shows that only two forex markets are efficient while the BDS independence test reports that all the forex markets are not efficient. The subsample period analysis indicates that the efficiency of the majority of the forex markets is sensitive to structural break, thus providing evidence in support of the adaptive market hypothesis. This study suggests that ignoring structural break and nonlinearity of returns may lead to misleading results when testing for market efficiency.

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Tsiaras, Konstantinos. "Contagion in Futures FOREX Markets for the Post- Global Financial Crisis: A Multivariate FIGARCHcDCC Approach." Journal of Quantitative Methods 4, no. 1 (February 28, 2020): 1. http://dx.doi.org/10.29145/2020/jqm/040102.

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This paper seeks to investigate the time-varying conditional correlations to the futures FOREX market returns. We employ a dynamic conditional correlation (DCC) Generalized ARCH (GARCH) model to find potential contagion effects among the markets. The under investigation period is 2014-2019. We focus on four major futures FOREX markets namely JPY/USD, KRW/USD, EUR/USD and INR/USD. The empirical results show an increase in conditional correlation or contagion for all the pairsof future FOREX markets. Based on the dynamic conditional correlations, KRW/USD seems to be the safest futures FOREX market. The results are of interest to policymakers who provide regulations for the futures FOREX markets. JEL Classification Codes: C58, C61, G11, G15

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Miśkiewicz, Janusz. "Network Analysis of Cross-Correlations on Forex Market during Crises. Globalisation on Forex Market." Entropy 23, no. 3 (March 15, 2021): 352. http://dx.doi.org/10.3390/e23030352.

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Within the paper, the problem of globalisation during financial crises is analysed. The research is based on the Forex exchange rates. In the analysis, the power law classification scheme (PLCS) is used. The study shows that during crises cross-correlations increase resulting in significant growth of cliques, and also the ranks of nodes on the converging time series network are growing. This suggests that the crises expose the globalisation processes, which can be verified by the proposed analysis.

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Bijoy, Kumar. "Stock and Currency Market Linkages: An Empirical Analysis from Emerging Economies." International Journal of Professional Business Review 8, no. 8 (August 9, 2023): e03357. http://dx.doi.org/10.26668/businessreview/2023.v8i8.3357.

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Purpose: The Causality relationship between forex and stock market in any economy is dependent on its economic fundamentals. This study examines return and volatility linkages between stock and currency markets for 28 emerging economies weekly MSCI stock index values (in local currency) and foreign exchange rates (indirect quotes) from 1988 to 2019. Theoretical Framework: The understanding of the relationship between forex and stock markets through return and volatility spillover will help in predicting behavior of one market on account of the knowledge of movements in another market. Impact of global financial crisis (GFC) on this relationship is another dimension of research. This study finds the causal relationship between forex and stock markets through return and volatility spillover for all emerging economies along with the effect of GFC on the relationship. Design/Methodology/Approach: The empirical analysis is conducted for the total period and three sub-periods namely pre-global financial crisis, crisis, and post-crisis periods by using the Granger Causality test (Granger 1969) followed by Vector Auto Regression (VAR) model and finally the Dynamic Conditional Correlations (DCC), a multivariate model proposed by Engle (2002). The volatility linkages are studied by employing BEKK-GARCH (Baba, Engle, Kraft, & Kroner, 1990) Findings: It is found that return spillovers are predominantly from Stock to forex markets during the pre-crisis and crisis period but from forex to stock market in the post-crisis period. The increasing presence of return relationships from 10 countries in the pre-crisis period to 19 countries during the crisis period, implying a contagion effect. The BEKK-GARCH result confirm that volatility spillovers are observed throughout from forex to stock markets. Research, practical & social implications: More extensive return and volatility associations between stock and forex market after the global financial crisis confirm the increasing importance of economic fundamentals. Return linkages exhibit contagion against the decoupling effect observed in volatility spillovers during the crisis period. Originality/Value: Based on empirical observations, the study attempts to provide important policy implications for Policy makers, global investors, and academic community.

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6

Piekunko-Mantiuk, Iwona. "Forex as an alternative for capital market." Zeszyty Naukowe Uniwersytetu Szczecińskiego Finanse Rynki Finansowe Ubezpieczenia 90 (2017): 81–93. http://dx.doi.org/10.18276/frfu.2017.90-06.

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7

Kumar, Anoop S., Chaithanya Jayakumar, and Bandi Kamaiah. "Fractal market hypothesis: evidence for nine Asian forex markets." Indian Economic Review 52, no. 1-2 (December 2017): 181–92. http://dx.doi.org/10.1007/s41775-017-0014-7.

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Zaitsev, O., and T. Dvorianova. "ACQUAINTANCE TO FOREX FOREIGN EXCHANGE MARKET." Vìsnik Sumsʹkogo deržavnogo unìversitetu, no. 1 (2020): 174–80. http://dx.doi.org/10.21272/1817-9215.2020.1-20.

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The article draws attention to the steady growth of the general trend of direct participation of individuals in financial transactions using electronic platforms. In particular, the article notes the increased interest in participating in operations in the Forex currency market. It is emphasized that relatively technically easy access to participation in financial transactions through the use of electronic platforms is currently a potential threat to financial security for the funds of participants in such transactions. This is a lack of professional training of most novice traders who voluntarily become participants in financial transactions. It is emphasized that stock exchange transactions on stock markets, purchase and sale of currency on electronic platforms, transactions with gold, etc. require, along with general, also special knowledge on certain specific areas of economic development and financial relations. Also, psychological and behavioral factors begin to "work" in such relationships. It is noted that only from the beginning of 2019 in Ukraine at the legislative level began a systematic regulation of the structure of the foreign exchange market and the procedure for trading in foreign currency. The article states that it is time to pay attention to digitalized trading activities from a professional point of view and start teaching in educational institutions the relevant disciplines for training and acquiring students' general skills in trade and financial transactions on electronic platforms. From this point of view, the article provides an introductory review of the Forex currency market, outlines the principles of its operation, pays more attention to trading strategies. As a result, the following conclusions are made that, first, the foreign exchange market is highly profitable provided that its trends are mastered; secondly, the foreign exchange market is high risk; it is necessary to understand not only in many terms, but, especially, in processes and situations in the financial-globalized world to confidently use charts of change of cost of currencies for profit; thirdly, there are many different strategies that can be used successfully in the currency market, from the simplest - for amateurs, to more complex - for experienced traders, but none of them will fit perfectly for a particular psychotype, professional level and amount of time a person - trader can pay trade. Of particular value, according to the authors, is the following conclusion: a trader creates his own strategy, which provides a greater likelihood of earnings in the international Forex market. Currency trader is a creative activity, but an activity based on mastering a large base of professional knowledge.

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Abednego, Luciana, and Cecilia Esti Nugraheni. "Forex Data Analysis using Weka." International Journal of Fuzzy Logic Systems 11, no. 1 (January 31, 2021): 23–36. http://dx.doi.org/10.5121/ijfls.2021.11103.

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This paper conducts some experiments with forex trading data. The data being used is from kaggle.com, a website that provides datasets for machine learning and data scientists. The goal of the experiments is to know how to design many parameters in a forex trading robot. Some questions that want to be investigated are: How far the robot must set the stop loss or target profit level from the open position? When is the best time to apply for a forex robot that works only in a trending market? Which one is better: a forex trading robot that waits for a trending market or a robot that works during a sideways market? To answer these questions, some data visualizations are plotted in many types of graphs. The data representations are built using Weka, an open-source machine learning software. The data visualization helps the trader to design the strategy to trade the forex market.

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Kavtaradze, Nino. "CURRENCY SYSTEM AND CURRENCY TRADING OF GEORGIA." PIRETC-Proceeding of The International Research Education & Training Centre 104, no. 1-2 (April 4, 2021): 70–75. http://dx.doi.org/10.36962/ecs104/1-2-70.

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The present empirical paper investigates the following issues: the formation of the Georgian currency system that started after the collapse of the Soviet Union, when the country has declared its independence, establishing the National Bank of Georgia and issuing the national currency. Also is discussed financial market where foreign exchange and transaction are made. As it is known today, in the international currency market, 90% of the world market holds the FOREX (Foreign Exchange Market), which makes it the largest foreign exchange market in the world. FOREX currency traders, together with traditional forms, offers the most modern and comfortable form of trade - Online trading. The existing currencies are largely proportional to the ongoing processes of the FOREX market. Keywords: Currency, Currency Exchange Rate, Currency Market, Interbank Exchange Market, Foreign Exchange, FOREX Market.

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11

Matha, Rajeev, Geetha E., Satish Kumar, and Raghavendra. "Dynamic relationship between equity, bond, commodity, forex and foreign institutional investments: Evidence from India." Investment Management and Financial Innovations 19, no. 4 (October 20, 2022): 65–82. http://dx.doi.org/10.21511/imfi.19(4).2022.06.

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The interrelationship between equity, bond, commodity and forex movements can provide investors with abundant trading opportunities regardless of whether one market is trending upward or downward. Hence, to understand the interlinkage between markets, this study examines the long-run and causal linkage between forex, G-sec bonds, oil prices, gold rates, foreign institutional investment (FII) flows, and equity market and sectoral index returns. Daily time-series data from August 2012 to August 2021 were considered for empirical analysis. Johansen’s cointegration test revealed that foreign exchanges like USD, Euro, GBP and Yen, oil and gold rates, G-bond returns and FII flows were significantly cointegrated with the stock market and sectoral indices in the long run. Further, Granger causality found a uni-directional relationship between forex rates (i.e., USD, Euro, Yen) and the market, as well as sectoral indices, except Nifty 50 and Nifty IT indices. Oil price movements were found to effectively predict future price changes of Nifty consumer durables, auto, IT indices. Gold prices are useful to predict Nifty-Auto, Bank, Financial Services, Oil &amp; Gas and PSU. The study also found a bi-directional relationship from FII inflows to the stock market and sectoral indices. The findings suggest that forex rates, oil prices and FII flows significantly affect India’s stock market and sectoral performance. The study contributes to the existing literature by comprehensively examining the interlinkage between commodities such as oil and gold, foreign exchanges like USD, Euro, GBP and Yen, G-bond, FII flows and the stock market, and fourteen sectoral indices in the Indian context.

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12

Delgado-Bonal, Alfonso, and Álvaro García López. "Quantifying the randomness of the forex market." Physica A: Statistical Mechanics and its Applications 569 (May 2021): 125770. http://dx.doi.org/10.1016/j.physa.2021.125770.

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13

Pasionek, Jolanta. "Countries of BRICS group on Forex market." Ekonomia i Prawo 19, no. 1 (March 31, 2020): 99. http://dx.doi.org/10.12775/eip.2020.008.

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14

Baruník, Jozef, Evžen Kočenda, and Lukáš Vácha. "Asymmetric volatility connectedness on the forex market." Journal of International Money and Finance 77 (October 2017): 39–56. http://dx.doi.org/10.1016/j.jimonfin.2017.06.003.

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15

Alanya, Willy, and Gabriel Rodríguez. "Asymmetries in Volatility: An Empirical Study for the Peruvian Stock and Forex Markets." Review of Pacific Basin Financial Markets and Policies 22, no. 01 (March 2019): 1950003. http://dx.doi.org/10.1142/s0219091519500036.

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Asymmetric autoregressive conditional heteroskedasticity (EGARCH) models and asymmetric stochastic volatility (ASV) models are applied to daily data of Peruvian stock and Forex markets for the period of 5 January 1998–30 December 2011. Following the approach developed in [Omori, Y, S Chib, N Shephard and J Nakajima (2007). Stochastic volatility with leverage: Fast likelihood inference. Journal of Econometrics, 140, 425–449], Bayesian estimation tools are used with Normal and [Formula: see text]-Student errors in both models. The results suggest the significant presence of asymmetric effects in both markets. In the stock market, negative shocks generate higher volatility than positive shocks. In the Forex market, shocks related to episodes of depreciation create higher uncertainty in comparison with episodes of appreciation. Thus, the Central Reserve Bank faces relatively major difficulties in its intention of smoothing Forex volatility in times of depreciation. The model with the best fit in both markets is the ASV model with Normal errors. The stock market returns have greater periods of volatility; however, both markets react to shocks in the economy, as they display similar patterns and have a significant correlation for the sample period studied.

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Utkin, A. I. "THE RELATIONSHIP BETWEEN THE RUSSIAN CURRENCY MARKET AND THE FOREX INTERNATIONAL CURRENCY MARKET." Ekonomické trendy 2, no. 1 (March 24, 2017): 93–97. http://dx.doi.org/10.24045/et.2017.1.17.

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17

Zvonova, E. A. "Scenario Analysis of the Russian Forex Market Development Strategies." Economics, taxes & law 11, no. 6 (December 26, 2018): 26–38. http://dx.doi.org/10.26794/1999-849x-2018-11-6-26-38.

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The subject of the research is the foresight into development strategies of the foreign exchange sector of the Russian financial market under the new geo-economic conditions and in the context of the international monetary system reform and sanctions on Russian transactions in the international financial market. The relevance of the problem is caused by the ruble volatility and strong fluctuations in the values of macroeconomic variables after 2014. The purpose of the research was to develop a scenario model for the development of the Russian forex market for the next three years based on three scenario forecasts: optimistic, pessimistic and conservative. A scenario model of the Russian foreign exchange market development was built by superimposing scenarios of the national economy development on the forex market development scenarios along with assessment of the possible impact of the forex market development on other national financial market segments. The model is based on international macroeconomic variables statistics, the state of Russia’s payment balance and also on a comparative analysis of the development indices of national economies of raw materials exporting countries and the national economy of Russia. For data aggregation and reduction to a single format, an information-logical model for formation of the research information base was developed. The obtained scenario model for the development of the Russian financial market forex sector has a high predictive capability. The paper concludes that, based on the scenario model, the forex sector of the Russian financial market will be fairly stable over the next three years, which should be taken into account by the Bank of Russia when making decisions on the forex policy and creation of international currency reserves.

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Yıldırım, Hakan. "Wrong Ways to Earn Money without Risk at Forex Market." International Academic Journal of Accounting and Financial Management 05, no. 01 (June 27, 2018): 01–07. http://dx.doi.org/10.9756/iajafm/v5i1/181000.

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Yıldırım, Hakan. "Wrong Ways to Earn Money without Risk at Forex Market." International Academic Journal of Accounting and Financial Management 05, no. 01 (June 27, 2018): 1–7. http://dx.doi.org/10.9756/iajafm/v5i1/1810001.

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Emilia Pascal, Carmen. "An Analysis of Romanian Capital, Forex and Monetary Markets: Volatilities and Contagion." INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND BUSINESS ADMINISTRATION 6, no. 6 (2020): 41–50. http://dx.doi.org/10.18775/ijmsba.1849-5664-5419.2014.66.1004.

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This paper focuses on stability relations for the Romanian main financial markets: capital, ForEx and monetary markets, as well as the intensity of the link between them and how they are interconnected, because this represents the best indicator of the situation of an economy, which is seen as a complex, adaptive and dynamic system, that is continuously changing. This analysis examines their deviation from the state of equilibrium, and what are the factors that modify this state. The study incorporates the markets evolution, their estimated volatilities, it shows that the most sensitive to the impact of a financial shock are the currency and the stock market. All the obtained results are correlated with events, news and market information from those particular moments to find explanations and understand the behavior of investors and how their decisions affected the market. Because of instability on some markets, investors started moving their finances to other markets, where they had more confidence, causing imbalances. Behavior of investors, as they react to the emergence of a shock, is decisive and extremely important in anticipating the effects that such a financial shock can produce. The values of the estimated volatilities were embedded into a volatility table to be easier to track their evolution over the period under review (2007 – 2018). Besides the financial crisis, there have been other events that have translated into a higher degree of volatility: raising the minimum wage, the Brexit, protests against corruption, the raise of salaries for the public workers which has created instability in the monetary market. The analysis continues with an estimate of a spillover index that only confirms the significant vulnerability period in the markets: 2010-2012, period during which the phenomenon of contagion may have occurred.

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ABUELFADL, MOUSTAFA. "INDIVIDUAL FOREIGN EXCHANGE INVESTORS, RETURN PREDICTABILITY AND MARKET TIMING." Annals of Financial Economics 12, no. 01 (March 2017): 1750001. http://dx.doi.org/10.1142/s2010495217500014.

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This study tests whether individual foreign exchange (Forex) investors can predict future returns, time the market and generate alpha after transaction costs. Using a sample of 1,231 Forex trading accounts and 72,072 trades, the results show that individual Forex investors can predict future returns up to eight days after trade execution, even after controlling for Volatility. The results of return predictability are significant because they support the idea that linear independence is rejected as well as provide empirical evidence that private information is available in the foreign exchange market.

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Majerčáková, Daniela, and Michal Greguš. "The Creation of the Convenient Investment Strategy in Forex." European Journal of Economics and Business Studies 5, no. 1 (April 30, 2019): 80. http://dx.doi.org/10.26417/ejes.v5i1.p80-88.

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Forex that belongs into the biggest and the most widespread financial markets in the world has the daily turnover that is assessed to more than 5 trillion USD. This fact is at the same time a temptation for investors and attracts them to trade in this market. Only the small percentage from this daily turnover is made of the business of governments and companies, that purchade in foreign countries or need to exchange foreign currency for the domestic one. The majority consists of the speculative business. Speculative business is based on the expectations of a speculator on the future rise or fll of exchange rate, that he plans to earn money on. In this case, we are talking about the market with unpredictable environment. It is controlled by the crowd of people who create the most extensive financial market of the world by their mutual purchasing and selling foreign currencies. The aim of this paper is to create the convenient investment strategy on the basis of the analysis of foreign exchange market. We have used the description for the fulfillment of this aim and consequently we have focused on business strategies as the fundamental and technical analysis and its use in the real trading. We have described the development of trading in the chosen market and period by means of fictitious account on the platform Metatrader4. Consequently, we have analysed the influence of the particular factors on the results of investing in Forex

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Ingalhalli, Varsha, and Prachi Kolamker. "Modelling volatility effects between stock, oil, gold and forex markets: Evidence from India." Investment Management and Financial Innovations 20, no. 2 (April 14, 2023): 53–65. http://dx.doi.org/10.21511/imfi.20(2).2023.05.

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Although several studies on the integration of diverse stock markets have been conducted in the financial literature, most of them have focused on the integration and volatility spillovers across established stock markets. The present study explores the dynamics of integration and volatility spillover across gold, oil, forex, and stock markets during four significant events in India: the pre-changed government regime, the post-changed government regime, the post-Brexit referendum date, and the COVID era. Daily data from 2010 to 2022 is divided into four categories using the Chow test. This is done to examine if these events’ financial turmoil affects market interconnectivity. The unit root test determines data stationarity. The ARCH LM test examines series volatility clustering, and the BEKK GARCH test examines market volatility spillover. Results indicate that gold cannot be considered a hedge or safe haven. Secondly, market interconnectedness increased during the crisis period. Third, domestic political and geopolitical conditions globally do not increase the scale of spillover amongst financial assets, though they impact the spillover’s magnitude. The results of this study have several important implications for portfolio diversification and risk management.

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Juszczuk, Przemysław, and Lech Kruś. "Supporting multicriteria fuzzy decisions on the Forex market." Multiple Criteria Decision Making 12 (2017): 60–74. http://dx.doi.org/10.22367/mcdm.2017.12.05.

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Mishina, V. Yu. "The Russian forex market: Moving toward world standards." Studies on Russian Economic Development 19, no. 5 (September 2008): 507–15. http://dx.doi.org/10.1134/s1075700708050079.

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توكـل, الدكتور فـــــادي, and الدكتور محمود فكري عبد الصادق الـشـاهـد. "التنظيم القانوني لتجارة الفوركس (Foreign Exchange Market) (FOREX)." مجلة العلوم القانونية والاقتصادية 65, no. 1 (January 1, 2023): 69–192. http://dx.doi.org/10.21608/jelc.2023.285811.

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Reddy, Y. V., and A. Sebastin. "Interaction Between Forex and Stock Markets in India: An Entropy Approach." Vikalpa: The Journal for Decision Makers 33, no. 4 (October 2008): 27–46. http://dx.doi.org/10.1177/0256090920080403.

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Interactions between the foreign exchange market and the stock market of a country are considered to be an important internal force of the markets in a financially liberalized environment. If causal relationship from a market to the other is not detected, then informational efficiency exists in the other whereas existence of causality implies that hedging of exposure to one market by taking position in the other market will be effective. The temporal relationship between the forex market and the stock market of developing and developed countries has been studied, especially after the East Asian financial crisis of 1997–98, using various methods like cross-correlation, cross-spectrum, and error correction model, but these methods identify only linear relations. A statistically rigorous approach to the detection of interdependence, including non-linear dynamic relationships, between time series is provided by tools defined using the information theoretic concept of entropy. Entropy is the amount of disorder in the system and also is the amount of information needed to predict the next measurement with a certain precision. The mutual information between two random variables X and Y with a joint probability mass function p(x,y) and marginal mass functions p(x) and p(y), is defined as the relative entropy between the joint distribution p(x,y) and the product distribution p(x)*p(y). Mutual information is the reduction in the uncertainty of X due to the knowledge of Y and vice versa. Since mutual information measures the deviation from independence of the variables, it has been proposed as a tool to measure the relationship between financial market segments. However, mutual information is a symmetric measure and does not contain either dynamic information or directional sense. Even time delayed mutual information does not distinguish information actually exchanged from shared information due to a common input signal or history and therefore does not quantify the actual overlap of the information content of two variables. Another information theoretic measure called transfer entropy has been introduced by Thomas Schreiber (2000) to study the relationship between dynamic systems; the concept has also been applied by some authors to study the causal structure between financial time series. In this paper, an attempt has been made to study the interaction between the stock and the forex markets in India by computing transfer entropy between daily data series of the 50 stock index of the National Stock Exchange of India Limited, viz., Nifty and the exchange rate of Indian Rupee vis- à- vis US Dollar, viz., Reserve Bank of India reference rate. The entire period–November 1995 to March 2007–selected for the study, has been divided into three sub-periods for the purpose of analysis, considering the developments that took place during these sub-periods. The results obtained reveal that: there exist only low level interactions between the stock and the forex markets of India at a time scale of a day or less, although theory suggests interactive relationship between the two markets the flow from the stock market to the forex market is more pronounced than the flow in the reverse direction.

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Zembura, Wojciech. "Forex market as the best possible way of investing money during an economic boom and recession." Financial Internet Quarterly 19, no. 1 (March 1, 2023): 8–20. http://dx.doi.org/10.2478/fiqf-2023-0002.

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Abstract Since the beginning of the 1980s, a continuous process of integration of national and regional markets into one global market for goods, services and capital can be noticed. Both economic theory and market practice indicate that the level of the exchange rate primarily depends on macroeconomic variables (such as interest rates or the number of new jobs in the non-agricultural sector). The results of the research presented in the article regard the importance of US macroeconomic data publications for the short-term volatility of EUR/USD exchange rate. The main purpose of the study was to show whether macroeconomic data from the United States affects the short-term development of the EUR/USD exchange rate and whether the Forex market is a good way to multiply capital. The following research questions have been posed: does the EUR/USD exchange rate react to the published macroeconomic data from the American economy? Second, is whether investing in the Forex market could be a way to multiply capital in times of economic boom and recession. This paper presents the effects of my own research and observations in terms of the impact of US macroeconomic data, on shaping exchange rates of the Forex market. Based on my own investment experience my goal is to prove, that Forex market is a perfect way to multiply capital. My investment decisions regarding future exchange rate fluctuations, were based on the presented macroeconomic data from the US economy, as well as on the basis of important leading economic indicators. The position was opened and closed on the same day. The trading contracts have been made throughout 7 working days. The underlying financial instruments were EUR/USD and OIL. The conclusions of this study are as follows. The USD/PLN exchange rate reacted to the published macroeconomic data from USA. The strongest exchange rate reaction was noticed after publications of data regarding US Non-farm Payrolls (NFP), Initial Jobless Claims and ISM Services PMI. Strong exchange rate reaction was recorded after ADP US Private Sector Jobs and Factory orders report. When taking described investment examples into account, it can be clearly stated that investing in the Forex market is an excellent alternative to stock investments.

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Taufik, Eza Herlambang, Muhammad Harlie, and Kurniaty Kurniaty. "PENGARUH KEMAMPUAN, PENGALAMAN DAN DISIPLIN KERJA TERHADAP KINERJA KARYAWAN." Al-KALAM JURNAL KOMUNIKASI, BISNIS DAN MANAJEMEN 4, no. 1 (July 22, 2017): 99. http://dx.doi.org/10.31602/al-kalam.v4i1.831.

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The evolution of the forex market is divided into two stages. World War IPeriod and the Bretton Woods period is included Fixed Rate Periodstage. At this stage, forex does not excite transactions because of exchange rate changes can only occur in a relatively narrow range. After a period of Bretton Woods, after the failure of Period Exchange Rates Remain in maintaining economic stability, forex transactions getting psyched. This occurs because the assessment of the exchange rate between countries be left entirely to the market mechanism. The market will determine whether the exchange rate is too expensive (over-valued) or too low (under-valued).This study aims to determine the effect of ability, experience and discipline together and partially on the performance forex trader in South Kalimantan. This type of research is quantitative method. The samples were obtained 56 votes. To determine the effect the ability, experience and discipline to the performance of the test statistic methods trader used multiple linear regression. Data processing was performed using IBM SPSS Statistics 23 program for Windows.Based on the results of the research show that together the ability, experience and discipline significant effect on the performance of forex traders in South Kalimantan. Partially, ability, experience and discipline positive and significant impact on the performance of forex traders in South Kalimantan.Keywords: Capability, Experience, Discipline and Performance

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Caporale, Guglielmo Maria, and Alex Plastun. "IS THERE A FRIDAY EFFECT IN FINANCIAL MARKETS?" Journal of Prediction Markets 11, no. 2 (January 19, 2018): 38–59. http://dx.doi.org/10.5750/jpm.v11i2.1364.

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This paper tests for the presence of the Friday effect in various financial markets (stock markets, FOREX, and commodity markets) by using a number of statistical techniques (average analysis, parametric tests such as Student's t-test and ANOVA analysis, non-parametric ones such as the Kruskal-Wallis test, regression analysis with dummy variables). The evidence suggests that stock markets are immune to Friday effects, whilst in the FOREX Fridays exhibit higher volatility, and in the Gold market returns are higher on this day of the week. Using a trading robot approach we show that the latter anomaly can be exploited to make abnormal profits.

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Islam, Md Saiful, Emam Hossain, Abdur Rahman, Mohammad Shahadat Hossain, and Karl Andersson. "A Review on Recent Advancements in FOREX Currency Prediction." Algorithms 13, no. 8 (July 30, 2020): 186. http://dx.doi.org/10.3390/a13080186.

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In recent years, the foreign exchange (FOREX) market has attracted quite a lot of scrutiny from researchers all over the world. Due to its vulnerable characteristics, different types of research have been conducted to accomplish the task of predicting future FOREX currency prices accurately. In this research, we present a comprehensive review of the recent advancements of FOREX currency prediction approaches. Besides, we provide some information about the FOREX market and cryptocurrency market. We wanted to analyze the most recent works in this field and therefore considered only those papers which were published from 2017 to 2019. We used a keyword-based searching technique to filter out popular and relevant research. Moreover, we have applied a selection algorithm to determine which papers to include in this review. Based on our selection criteria, we have reviewed 39 research articles that were published on “Elsevier”, “Springer”, and “IEEE Xplore” that predicted future FOREX prices within the stipulated time. Our research shows that in recent years, researchers have been interested mostly in neural networks models, pattern-based approaches, and optimization techniques. Our review also shows that many deep learning algorithms, such as gated recurrent unit (GRU) and long short term memory (LSTM), have been fully explored and show huge potential in time series prediction.

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Jamali, Hana, Younes Chihab, Iván García-Magariño, and Omar Bencharef. "Hybrid Forex prediction model using multiple regression, simulated annealing, reinforcement learning and technical analysis." IAES International Journal of Artificial Intelligence (IJ-AI) 12, no. 2 (June 1, 2023): 892. http://dx.doi.org/10.11591/ijai.v12.i2.pp892-911.

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Foreign exchange market refers to the market in which currencies from around the world are traded. It allows investors to buy or sell a currency of their choice. Forex interests several categories of stakeholders, such as companies that carry out international contracts, large institutional investors, via the main banks, which carry out transactions on this market for speculative purposes. One of the most important aspects in the Forex market is knowing when to invest by buying, selling, and this through the recorded trend of a currency pair, but given the characteristics of the Forex market namely its chaotic, noisy and not stationary nature, prediction becomes a big challenge for traders when it comes to predicting accuracy. This paper aims to predict the right action to be taken at a certain moment through the development of a model that combines multiple techniques such multiple regression, simulated annealing meta-heuristics, reinforcement learning and technical indicators.

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Sandubete, Julio E., León Beleña, and Juan Carlos García-Villalobos. "Testing the Efficient Market Hypothesis and the Model-Data Paradox of Chaos on Top Currencies from the Foreign Exchange Market (FOREX)." Mathematics 11, no. 2 (January 5, 2023): 286. http://dx.doi.org/10.3390/math11020286.

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In this paper, we analyse two interesting applications related to the dynamics of economic phenomena linked to the Efficient Market Hypothesis (EMH), informative surprises, and the Model-Data Paradox of Chaos in certain top currency pairs from the foreign exchange market (FOREX). On the one hand, we empirically show that the FOREX market reacts under the Efficient Market Hypothesis in some cases, creating a significant variation in a short period of time (15, 30, and 60 min) in the quotes of the main currencies from the most important economic regions in the West (the United States, Europe, and the United Kingdom). This variation would depend on the actual deviation of high-impact macroeconomic news reported by these markets in relation to trade balance, unemployment rate, Gross Domestic Product (GDP), retail sales, the Industrial Production Index (IPI), and the Consumer Price Index (CPI). On the other hand, by testing the Model-Data Paradox of Chaos, we empirically verify that if we consider all the information available in the financial markets of currencies (or at least, more desegregated data) instead of daily data, and we apply a robust chaotic behaviour detection method, we can find differences in relation to the detection of chaos on the same series but with different temporal frequencies. This allows us to confirm that behind these financial time series which show an apparently random irregular evolution, there would be a generating system which, although unknown in principle, would be deterministic (and nonlinear), and we could take advantage of that deterministic character to make predictions, even if only in the short term, understanding “short term” as the time it takes for the market to incorporate these informative surprises in the FOREX market analysed.

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Drożdż, Stanisław, Ludovico Minati, Paweł Oświȩcimka, Marek Stanuszek, and Marcin Wa̧torek. "Signatures of the Crypto-Currency Market Decoupling from the Forex." Future Internet 11, no. 7 (July 10, 2019): 154. http://dx.doi.org/10.3390/fi11070154.

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Based on the high-frequency recordings from Kraken, a cryptocurrency exchange and professional trading platform that aims to bring Bitcoin and other cryptocurrencies into the mainstream, the multiscale cross-correlations involving the Bitcoin (BTC), Ethereum (ETH), Euro (EUR) and US dollar (USD) are studied over the period between 1 July 2016 and 31 December 2018. It is shown that the multiscaling characteristics of the exchange rate fluctuations related to the cryptocurrency market approach those of the Forex. This, in particular, applies to the BTC/ETH exchange rate, whose Hurst exponent by the end of 2018 started approaching the value of 0.5, which is characteristic of the mature world markets. Furthermore, the BTC/ETH direct exchange rate has already developed multifractality, which manifests itself via broad singularity spectra. A particularly significant result is that the measures applied for detecting cross-correlations between the dynamics of the BTC/ETH and EUR/USD exchange rates do not show any noticeable relationships. This could be taken as an indication that the cryptocurrency market has begun decoupling itself from the Forex.

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Firli, Gresselda Sharen. "Sharia Business Ethics Online Forex Trading at Company Signal Providers Volatility 75 Index JR (VIXJR)." International Journal of Social Science, Education, Communication and Economics (SINOMICS JOURNAL) 1, no. 6 (January 31, 2023): 809–18. http://dx.doi.org/10.54443/sj.v1i6.92.

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This study aims to determine the practice and application of sharia business ethics in forex trading of JR Volatility 75 Index companies in the forex market and the dissemination of the results of the analysis and transactions to registered members. This research is qualitative research with the research object of corporate signal provider Volatility 75 Index JR. Data collection methods used are observation, in-depth interviews, and documentation. The results of the study show that JR's Volatility 75 Index has implemented sharia business ethics in its service business so as to make it feel safe and comfortable when using the forex market analysis services from the company.

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M., Robinson, and Kabari L.G. "Predicting Foreign Exchange Using Digital Signal Processing." British Journal of Computer, Networking and Information Technology 4, no. 2 (September 5, 2021): 1–11. http://dx.doi.org/10.52589/bjcnit-sqwfnrnd.

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The forex market is one associated with so much volatility and can lead to grave financial losses if not properly understood. To understand the market is to study the price patterns from previous years or months and make predictions from the rate of falling and rising. There have been so much researches aimed at developing a predictive model for the FOREX market, however, no model has been able to handle the market volatility while predicting future rates accurately. In this work, we have developed a digital processing model for predicting foreign exchange using ARIMA and Artificial Neural Network algorithms. We used price datasets for five currencies namely: USD, Swiss Pounds, Yen, Euro and Franc, gotten from the Central Bank of Nigeria (CBN) website. The data ranged from a period of 20 years. The model was simulated using MATLAB software. The study performed excellently in terms of time (26 seconds) and minimal errors (0.7). This work could be beneficial to FOREX traders and to the entire research community.

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Nguyen Thi Thu, Thuy, and Vuong Dang Xuan. "FoRex Trading Using Supervised Machine Learning." International Journal of Engineering & Technology 7, no. 4.15 (October 7, 2018): 400. http://dx.doi.org/10.14419/ijet.v7i4.15.23024.

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The exchange rate of each money pair can be predicted by using machine learning algorithm during classification process. With the help of supervised machine learning model, the predicted uptrend or downtrend of FoRex rate might help traders to have right decision on FoRex transactions. The installation of machine learning algorithms in the FoRex trading online market can automatically make the transactions of buying/selling. All the transactions in the experiment are performed by using scripts added-on in transaction application. The capital, profits results of use support vector machine (SVM) models are higher than the normal one (without use of SVM).

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Pongsena, Watthana, Prakaidoy Sitsayabut, Nittaya Kerdprasop, and Kittisak Kerdprasop. "Development of a Model for Predicting the Direction of Daily Price Changes in the Forex Market Using Long Short-Term Memory." International Journal of Machine Learning and Computing 11, no. 1 (January 2021): 61–67. http://dx.doi.org/10.18178/ijmlc.2021.11.1.1015.

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Forex is the largest global financial market in the world. Traditionally, fundamental and technical analysis are strategies that the Forex traders often used. Nowadays, advanced computational technology, Artificial Intelligence (AI) has played a significant role in the financial domain. Various applications based on AI technologies particularly machine learning and deep learning have been constantly developed. As the historical data of the Forex are time-series data where the values from the past affect the values that will appear in the future. Several existing works from other domains of applications have proved that the Long-Short Term Memory (LSTM), which is a particular kind of deep learning that can be applied to modeling time series, provides better performance than traditional machine learning algorithms. In this paper, we aim to develop a powerful predictive model targeting to predicts the daily price changes of the currency pairwise in the Forex market using LSTM. Besides, we also conduct an extensive experiment with the intention to demonstrate the effect of various factors contributing to the performance of the model. The experimental results show that the optimized LSTM model accurately predicts the direction of the future price up to 61.25 percent.

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Juszczuk, Przemysław, and Lech Kruś. "Supporting Decisions on the Forex Market Using Fuzzy Approach." Journal of Automation, Mobile Robotics and Intelligent Systems 14, no. 2 (July 6, 2020): 50–62. http://dx.doi.org/10.14313/jamris/2-2020/20.

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Shahbazi, Nima, Masoud Memarzadeh, and Jarek Gryz. "Forex Market Prediction Using NARX Neural Network with Bagging." MATEC Web of Conferences 68 (2016): 19001. http://dx.doi.org/10.1051/matecconf/20166819001.

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Juszczuk, Przemysław, and Lech Kruś. "Soft multicriteria computing supporting decisions on the Forex market." Applied Soft Computing 96 (November 2020): 106654. http://dx.doi.org/10.1016/j.asoc.2020.106654.

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Popović, Saša, and Andrija Đurović. "Intraweek and intraday trade anomalies: evidence from FOREX market." Applied Economics 46, no. 32 (August 13, 2014): 3968–79. http://dx.doi.org/10.1080/00036846.2014.948676.

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Geromichalos, Athanasios, and Kuk Mo Jung. "AN OVER-THE-COUNTER APPROACH TO THE FOREX MARKET." International Economic Review 59, no. 2 (April 26, 2018): 859–905. http://dx.doi.org/10.1111/iere.12290.

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Raj, Prithiv. "A Study on Macro Economic Factors Affecting Forex Market." International Journal of Economics and Management Studies 6, no. 10 (October 25, 2019): 181–86. http://dx.doi.org/10.14445/23939125/ijems-v6i10p124.

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Hansun, Seng, Farica Perdana Putri, Abdul Q. M. Khaliq, and Hugeng Hugeng. "On searching the best mode for forex forecasting: bidirectional long short-term memory default mode is not enough." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 4 (December 1, 2022): 1596. http://dx.doi.org/10.11591/ijai.v11.i4.pp1596-1606.

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Presently, the Forex market has become the world’s largest financial market with more than US$5 trillion daily volume. Therefore, it attracts many researchers to learn its traded currency pairs characteristics and predict their future values. Here, we propose simple three layers Bidirectional long short-term memory (Bi-LSTM) networks for Forex forecasting with four different merge modes. Moreover, the proposed model is also compared to the conventional long short-term memory (LSTM) networks with the same architecture. Five major Forex currency pairs, namely AUD/USD, EUR/USD, GBP/USD, USD/CHF, and USD/JPY, with more than ten years of historical records are considered in this study. It is revealed from the experimental results that among four available merge modes, the concatenation mode as the default merge mode in Bi-LSTM networks is actually the less preferred mode for Forex forecasting (Root mean square error 0.30685517, mean absolute error 0.27442235, mean absolute percentage error 0.827108%). Moreover, Bi-LSTM average mode gets the highest R2 score that could achieve 89.579%. Therefore, the proposed three layers Bi-LSTM networks could provide a baseline result for developing a good trading strategy in Forex forecasting.

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Marcelle Amelot, Lydie Myriam, Subadar Agathee Ushad, and Matthew Lamport. "Testing the Efficient Market Hypothesis in an Emerging Market: Evidence from Forex Market in Mauritius." Theoretical Economics Letters 07, no. 07 (2017): 2104–22. http://dx.doi.org/10.4236/tel.2017.77143.

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Ramasastri, A. S., D. Malathy, and L. V. L. N. Sarma. "Market efficiency in the Indian Stock, Forex and Call Money Markets: A Comparison." Review of Development and Change 8, no. 1 (June 2003): 25–40. http://dx.doi.org/10.1177/0972266120030102.

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Moşteanu, Narcisa Roxana, and Tatiana Flocea. "Revolutionizing Foreign Exchange Market: A Critical Analysis of Blockchain's Opportunities and Challenges." European Journal of Theoretical and Applied Sciences 1, no. 5 (September 1, 2023): 33–44. http://dx.doi.org/10.59324/ejtas.2023.1(5).04.

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The fast use of blockchain technology, cryptocurrencies, and electronic trading has had a profound influence on the world's foreign exchange market, creating both difficulties and potential for market regulation and exploitation. Blockchain has the capability to completely transform the foreign exchange business by bringing improved transparency, efficiency, and security. Blockchain allows for the construction of transparent, tamper-proof transaction records since it uses distributed ledger technology. Lately, Blockchain technology and Forex trading have experienced tremendous growth in popularity in recent years, but it's important to remember that they also include hazards that investors need to be aware of. The goal of this study is to determine how blockchain technology might be applied to boost the Forex market, highlighting the advantages of decentralization, efficiency, security, and transparency. This study aims to explore the potential contribution of blockchain technology to the foreign exchange market. The research employs a literature review and analysis approach to investigate the relationship between blockchain technology and the foreign exchange market. The findings of the study indicate that blockchain technology has the potential to revolutionize the foreign exchange market. The paper concludes that the use of distributed ledger technology enables the creation of transparent and tamper-proof transaction records, addressing existing challenges of transparency and security in the Forex market.

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Sekhar, Bichith C., and A. Umamaheswari. "A Study On Technical Analysis With Reference To International Forex." Think India 22, no. 3 (September 27, 2019): 1129–44. http://dx.doi.org/10.26643/think-india.v22i3.8470.

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The foreign exchange market (Forex, FX, or currency market) is a global decentralized market for the trading of currencies. The foreign exchange market assists international trade and investments by enabling currency conversion. Our study is to test the technical tools to analyze about the technical impact and its return in the market. For this purpose 13 cross currency pairs were taken as sample size and Jensen’s Alpha, Beta, Relative Strength Index, and Buy and Hold Abnormal Return were used as technical tool for analysis and the conclusion is that it’s not preferred to invest in JPY pairs as the volatility and the return are not up to the mark and its preferred to invest in EURCAD as the return was high when compared to other scripts and the market was moving accordingly to its cross currency pair.

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Murtza, Iqbal, Ayesha Saadia, Rabia Basri, Azhar Imran, Abdullah Almuhaimeed, and Abdulkareem Alzahrani. "Forex Investment Optimization Using Instantaneous Stochastic Gradient Ascent—Formulation of an Adaptive Machine Learning Approach." Sustainability 14, no. 22 (November 18, 2022): 15328. http://dx.doi.org/10.3390/su142215328.

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In the current complex financial world, paper currencies are vulnerable and unsustainable due to many factors such as current account deficit, gold reserves, dollar reserves, political stability, security, the presence of war in the region, etc. The vulnerabilities not limited to the above, result in fluctuation and instability in the currency values. Considering the devaluation of some Asian countries such as Pakistan, Sri Lanka, Türkiye, and Ukraine, there is a current tendency of some countries to look beyond the SWIFT system. It is not feasible to have reserves in only one currency, and thus, forex markets are likely to have significant growth in their volumes. In this research, we consider this challenge to work on having sustainable forex reserves in multiple world currencies. This research is aimed to overcome their vulnerabilities and, instead, exploit their volatile nature to attain sustainability in forex reserves. In this regard, we work to formulate this problem and propose a forex investment strategy inspired by gradient ascent optimization, a robust iterative optimization algorithm. The dynamic nature of the forex market led us to the formulation and development of the instantaneous stochastic gradient ascent method. Contrary to the conventional gradient ascent optimization, which considers the whole population or its sample, the proposed instantaneous stochastic gradient ascent (ISGA) optimization considers only the next time instance to update the investment strategy. We employed the proposed forex investment strategy on forex data containing one-year multiple currencies’ values, and the results are quite profitable as compared to the conventional investment strategies.

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