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Journal articles on the topic 'FX trading'

Author: Grafiati

Published: 4 June 2021

Last updated: 8 February 2022

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1

Evans, Martin D. D., and Richard K. Lyons. "Informational integration and FX trading." Journal of International Money and Finance 21, no. 6 (2002): 807–31. http://dx.doi.org/10.1016/s0261-5606(02)00024-4.

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2

King, Michael, and Dagfinn Rime. "Algorithmic Trading and FX Market Liquidity." CFA Institute Magazine 22, no. 3 (2011): 15–17. http://dx.doi.org/10.2469/cfm.v22.n3.5.

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3

Evans, Martin D. D. "FX Trading and Exchange Rate Dynamics." Journal of Finance 57, no. 6 (2002): 2405–47. http://dx.doi.org/10.1111/1540-6261.00501.

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4

Ulibarri, Carlos A., Peter C. Anselmo, and Mauro X. Trabatti. "Cournot model of brokered FX trading." Journal of International Financial Markets, Institutions and Money 15, no. 5 (2005): 425–36. http://dx.doi.org/10.1016/j.intfin.2004.09.003.

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5

Im, Eun-a., Hyoung-goo Kang, and Sang-gyung Jun. "The Effect of NPS‘s FX Trading on Exchange Rate." Journal of Derivatives and Quantitative Studies 24, no. 3 (2016): 399–421. http://dx.doi.org/10.1108/jdqs-03-2016-b0002.

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In June 2014, the asset under management of National Pension Service (NPS) of Korea reached over 444 trillion won. NPS forecasts that the asset size will gradually grow to around 2,561 trillion won until 2043. The NPS investment of domestic equities and fixed income securities have been already saturated. So the NPS started to expand in global investment. Accordingly, the worries have grown that NPS's trading in foreign exchange markets may lead to the instability in FX markets. This study has analyzed the influence of NPS's foreign exchange transactions in domestic FX market. The period of st

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6

James, Jessica. "FX trading models – how are they doing?" Quantitative Finance 5, no. 5 (2005): 425–31. http://dx.doi.org/10.1080/14697680500383813.

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7

Beilis, Alan, Jan W. Dash, and Jacqueline Volkman Wise. "Psychology, Stock/FX Trading and Option Prices." Journal of Behavioral Finance 15, no. 3 (2014): 251–68. http://dx.doi.org/10.1080/15427560.2014.943227.

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8

Siikanen, Milla, Ulrich Nögel, and Juho Kanniainen. "Trading too expensively in the FX market?" Quantitative Finance 19, no. 12 (2019): 1933–44. http://dx.doi.org/10.1080/14697688.2019.1615633.

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9

Fischer, Andreas M., and Angelo Ranaldo. "Does FOMC news increase global FX trading?" Journal of Banking & Finance 35, no. 11 (2011): 2965–73. http://dx.doi.org/10.1016/j.jbankfin.2011.03.024.

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10

Coakley, Jerry, Michele Marzano, and John Nankervis. "How profitable are FX technical trading rules?" International Review of Financial Analysis 45 (May 2016): 273–82. http://dx.doi.org/10.1016/j.irfa.2016.03.010.

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11

Eom, Cheoljun, Taisei Kaizoj, Jong Won Park, and Enrico Scalas. "Realized FX Volatility : Statistical Properties and Applications." Journal of Derivatives and Quantitative Studies 26, no. 1 (2018): 1–25. http://dx.doi.org/10.1108/jdqs-01-2018-b0001.

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This paper empirically examines the statistical properties of realized volatility and the relationships between volatility and correlation measurements of realized volatility by using intraday high-frequency foreign exchange (FX) rates. Results regarding the distributional and dynamic properties of realized volatility are in agreement with the findings of previous studies. However, the positive correlation present in previous studies is not found in the case of JPY. On trading days with low volatility in the FX market, realized correlation coefficients between JPY and other currencies have pos

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12

Hoque, Ariful, Thi Ngoc Quynh Le, and Kamrul Hassan. "Does currency smirk predict foreign exchange return?" Investment Management and Financial Innovations 17, no. 3 (2020): 219–30. http://dx.doi.org/10.21511/imfi.17(3).2020.17.

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This study examines the predictive power of implied volatility smirk to forecast foreign exchange (FX) return. The volatility smirk contains critical information, especially when the market experiences negative news. The Australian dollar, Canadian dollar, Swiss franc, Euro, and British pound options traded in the opening, midday and closing periods of the trading day are selected to estimate the currency smirk. Research results reveal that the currency smirk outperforms in forecasting FX returns. In addition, the steeper slope in the middle of the trading day suggests that the predictive powe

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13

Zarrabi, Nima, Stuart Snaith, and Jerry Coakley. "FX technical trading rules can be profitable sometimes!" International Review of Financial Analysis 49 (January 2017): 113–27. http://dx.doi.org/10.1016/j.irfa.2016.12.010.

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14

Rundo, Trenta, di Stallo, and Battiato. "Grid Trading System Robot (GTSbot): A Novel Mathematical Algorithm for trading FX Market." Applied Sciences 9, no. 9 (2019): 1796. http://dx.doi.org/10.3390/app9091796.

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Grid algorithmic trading has become quite popular among traders because it shows several advantages with respect to similar approaches. Basically, a grid trading strategy is a method that seeks to make profit on the market movements of the underlying financial instrument by positioning buy and sell orders properly time-spaced (grid distance). The main advantage of the grid trading strategy is the financial sustainability of the algorithm because it provides a robust way to mediate losses in financial transactions even though this also means very complicated trades management algorithm. For the

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15

Suh, Young Sook. "A Study on Foreign Banks‘ Short Borrowings and Volatilities of Stock Markets & FX Markets in Korea: Focus on aTe Derivatives." Journal of Derivatives and Quantitative Studies 23, no. 1 (2015): 125–53. http://dx.doi.org/10.1108/jdqs-01-2015-b0006.

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This study examines how FX OTC derivatives transactions of foreign banks’ branches funded by short term borrowings affect the volatility of stock markets and FX markets in Korea based on historical data. It founds that they use call money for FX-derivatives trading, rather than borrowings from their Head Quarter. This result also proves that their derivatives trading is funded by call market increasing stock markets’ volatility in Korea, even if foreign banks’ branches have been using various funding sources. Also the role of foreign banks’ branches as FX money supplier for the korean local ba

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16

Dempster, M. A. H., and V. Leemans. "An automated FX trading system using adaptive reinforcement learning." Expert Systems with Applications 30, no. 3 (2006): 543–52. http://dx.doi.org/10.1016/j.eswa.2005.10.012.

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17

Lestari, Uning, and Henderi Henderi. "SISTEM TRANSAKSI FOREX TRADING MENGGUNAKAN METAQUOTES LANGUAGE 4." CCIT Journal 5, no. 2 (2012): 207–22. http://dx.doi.org/10.33050/ccit.v5i2.153.

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Now a lot of online businesses is on offer on the internet, particularly in the field of business Forex Online Trading. Lots of software that is used by traders for trading such as FX Clearing. FX Clearing is a software that is often used to trade forex traders in particular that uses a mini account. However, traders often have floating lost in trading it is because emotions are not controlled by the traders themselves. One solution to solve this problem so that traders do not always have floating lost is using Expert Advisors, Expert Advisors are applications that traders use to trade automat

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18

Gould, Martin D., Mason A. Porter, and Sam D. Howison. "The Long Memory of Order Flow in the Foreign Exchange Spot Market." Market Microstructure and Liquidity 02, no. 01 (2016): 1650001. http://dx.doi.org/10.1142/s2382626616500015.

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We study the long memory of order flow for each of three liquid currency pairs on a large electronic trading platform in the foreign exchange (FX) spot market. Due to the extremely high levels of market activity on the platform, and in contrast to existing empirical studies of other markets, our data enables us to perform statistically stable estimation without needing to aggregate data from different trading days. We find strong evidence of long memory, with a Hurst exponent [Formula: see text], for each of the three currency pairs and on each trading day in our sample. We repeat our calculat

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19

Sulzbach, Vanessa Neumann, João Mergulhão, and Pedro L. Valls Pereira. "O Conteúdo Informacional das Transações no Mercado Futuro de Câmbio: uma investigação do caso brasileiro." Brazilian Review of Finance 14, no. 1 (2016): 7. http://dx.doi.org/10.12660/rbfin.v14n1.2016.56538.

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The microstructure approach to exchange rates have received special attention in recent years, particularly because it highlights the existence of asymmetric information in this market. The Brazilian future FX market data provided from BM&F was used to test the private information effects of trading on prices. The structural VAR results confirm the existence of asymmetric information in this market, indicating that roughly 50% of all efficient price variation is due to the private information of the order flow. Additionally, the order flow observation allows the informed and uninformed arr

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20

Kim, Hong Bae, and Sang Hoon Kang. "Price Discovery and Transmission Mechanism between CDS and FX markets." Journal of Derivatives and Quantitative Studies 19, no. 1 (2011): 37–58. http://dx.doi.org/10.1108/jdqs-01-2011-b0002.

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This study investigated the relationship between the CDS (credit default swap) market with the FX spot (FX swap) market, including the period of recent global financial crisis. A measure for market efficiency is the condition that the derivative markets dominate the asset market in price discovery. In our case, however, FX market should be leading the CDS market. We found FX (spot and Derivatives) market has co-integration relationship with CDS market. Looking at Gonzalo Granger (GG) and Hasbrouck's price discovery measure, we found the FX spot and derivatives market dominated CDS market in pr

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21

Dempster, M. A. H., T. W. Payne, Y. Romahi, and G. W. P. Thompson. "Computational learning techniques for intraday FX trading using popular technical indicators." IEEE Transactions on Neural Networks 12, no. 4 (2001): 744–54. http://dx.doi.org/10.1109/72.935088.

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22

Kablan, Abdalla, and Wing Lon Ng. "Intraday high-frequency FX trading with adaptive neuro-fuzzy inference systems." International Journal of Financial Markets and Derivatives 2, no. 1/2 (2011): 68. http://dx.doi.org/10.1504/ijfmd.2011.038529.

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23

Huang, Roger D., and Ronald W. Masulis. "FX Spreads and Dealer Competition Across the 24-Hour Trading Day." Review of Financial Studies 12, no. 1 (1999): 61–93. http://dx.doi.org/10.1093/rfs/12.1.61.

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24

Elaut, Gert, Michael Frömmel, and Kevin Lampaert. "Intraday momentum in FX markets: Disentangling informed trading from liquidity provision." Journal of Financial Markets 37 (January 2018): 35–51. http://dx.doi.org/10.1016/j.finmar.2016.09.002.

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25

Broumandi, Shadie, and Tobias Reuber. "Statistical arbitrage and FX exposure with South American ADRs listed on the NYSE." Financial Assets and Investing 3, no. 2 (2012): 5–18. http://dx.doi.org/10.5817/fai2012-2-1.

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An American Depositary Receipt (ADR) represents ownership in the shares of a foreign company trading in US financial markets. We test a pair trading rule based on the mean reversion assumption for six South American stocks and their ADR counterparts on the NYSE. In our opinion, such a strategy should separate the spread risk from the currency risk. This paper aims to challenge the positive results found in similar settings. The main achievement is to show that isolating FX exposure turns such strategies that were presented as profitable to unprofitable and abnormal returns are just due to an a

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26

Simotas, Philip. "Implementing an Active Currency Strategy Using FX Prime Brokerage and Electronic Trading." Journal of Trading 1, no. 1 (2005): 55–57. http://dx.doi.org/10.3905/jot.2006.618225.

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27

Levich, Richard M. "FX counterparty risk and trading activity in currency forward and futures markets." Review of Financial Economics 21, no. 3 (2012): 102–10. http://dx.doi.org/10.1016/j.rfe.2012.06.004.

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28

Miao, Jia, and Christian L. Dunis. "Volatility filters for FX portfolios trading: the impact of alternative volatility models." Applied Financial Economics Letters 2, no. 6 (2006): 389–94. http://dx.doi.org/10.1080/17446540600706783.

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29

Beine, Michel, Paul De Grauwe, and Marianna Grimaldi. "The impact of FX central bank intervention in a noise trading framework." Journal of Banking & Finance 33, no. 7 (2009): 1187–95. http://dx.doi.org/10.1016/j.jbankfin.2008.11.014.

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30

Pakhrudin, Khairul, Kamalia Azma Kamaruddin, and Fauziah Ahmad. "TRADER HUB SYSTEM DEVELOPMENT USING VAN K THARP EXPECTANCY THEORY TO ANALYSE RETAIL FOREX TRADING SYSTEM PERFORMANCE." MALAYSIAN JOURNAL OF COMPUTING 5, no. 2 (2020): 523. http://dx.doi.org/10.24191/mjoc.v5i2.8995.

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With the advance of technology, foreign exchange trading, known as forex or FX trading, has been conducted electronically using the Internet. Forex traders were using technical analysis to project the best price when buying or selling currencies, and by using the technical analysis tools, they have created their own trading system. Forex traders need to make consistent profitability in the long term to sustain in the forex market, therefore a good trading system is vital. In order to evaluate their trading system performance, forex traders can use the backtesting and forward testing methods. H

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31

Jung, Gunho, and Sun-Yong Choi. "Forecasting Foreign Exchange Volatility Using Deep Learning Autoencoder-LSTM Techniques." Complexity 2021 (March 31, 2021): 1–16. http://dx.doi.org/10.1155/2021/6647534.

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Since the breakdown of the Bretton Woods system in the early 1970s, the foreign exchange (FX) market has become an important focus of both academic and practical research. There are many reasons why FX is important, but one of most important aspects is the determination of foreign investment values. Therefore, FX serves as the backbone of international investments and global trading. Additionally, because fluctuations in FX affect the value of imported and exported goods and services, such fluctuations have an important impact on the economic competitiveness of multinational corporations and c

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32

Binh, Ki Beom, Sang-min Lee, and Won Seop Lee. "Evidences for Price Discovery between On- and Off-shore Won/Dollar Spot, Forward and NDF FX Rate." Journal of Derivatives and Quantitative Studies 24, no. 2 (2016): 339–63. http://dx.doi.org/10.1108/jdqs-02-2016-b0006.

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Using Hasbrouck’s (1995, 2002) information share method, we examine the mutual price discovery dynamics among Won/Dollar spot, forward, and NDF exchange rates in on- and off-shore FX markets. Our findings include : (i) During the entire period, the mutual price discovery between on-shore FX market and off-shore NDF market are significantly led by on-shore Won-Dollar spot and forward exchange rates. (ii) Within the period around the global crisis, NDF exchange rates have mutual influence on the price discovery, which is expecially greater than the any other period. The results show Won-Dollar s

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33

Chang, Kook-Hyun, and Byung-Jo Yoon. "Forecasting the Currency Spot with the Trading Volume and the Trading Volume Volatility of Currency Futures in Won/Dollar FX Market." Journal of Derivatives and Quantitative Studies 18, no. 3 (2010): 1–23. http://dx.doi.org/10.1108/jdqs-03-2010-b0001.

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This paper tries to empirically investigate whether the information contained in trading volume, volume volatility of Won/Dollar currency futures may be statistically useful in forecasting currency spot return. This paper uses both the jump-diffusion GARCH model and the bivariate GARCH type BEKK model to estimate the trading volume volatility of currency futures and the volatility of currency spot, sampled daily during 1/4/2000~12/30/2009 period. According to the findings of this study, previous information contained in both trading volume and the volume volatility of Won/Dollar currency futur

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34

Deng, Shangkun, and Akito Sakurai. "Integrated Model of Multiple Kernel Learning and Differential Evolution for EUR/USD Trading." Scientific World Journal 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/914641.

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Currency trading is an important area for individual investors, government policy decisions, and organization investments. In this study, we propose a hybrid approach referred to as MKL-DE, which combines multiple kernel learning (MKL) with differential evolution (DE) for trading a currency pair. MKL is used to learn a model that predicts changes in the target currency pair, whereas DE is used to generate the buy and sell signals for the target currency pair based on the relative strength index (RSI), while it is also combined with MKL as a trading signal. The new hybrid implementation is appl

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35

Pintar, Rok, Eva Jereb, Mladen Čudanov, and Marko Urh. "Interest in Currency Trading Learning – Preferred Methods and Motivational Factors." Organizacija 49, no. 1 (2016): 3–14. http://dx.doi.org/10.1515/orga-2016-0003.

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Abstract Background and purpose: This paper analyzes the interest of potential users for learning in the field of currency trading or foreign exchange (forex, FX). The purpose of our article is a) to present currency trading, b) to present different options, methods and learning approaches to educating in forex, c) to present the research results discovering the interest of potential users for learning in the field of currency trading. Methodology: For gathering data, an online questionnaire was used. It was distributed so that the survey sample covers socio-demographic variables (gender, age,

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36

Taranto, Aldo, and Shahjahan Khan. "Bi-directional grid absorption barrier constrained stochastic processes with applications in finance & investment." Risk Governance and Control: Financial Markets and Institutions 10, no. 3 (2020): 20–33. http://dx.doi.org/10.22495/rgcv10i3p2.

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Whilst the gambler’s ruin problem (GRP) is based on martingales and the established probability theory proves that the GRP is a doomed strategy, this research details how the semimartingale framework is required for the grid trading problem (GTP) of financial markets, especially foreign exchange (FX) markets. As banks and financial institutions have the requirement to hedge their FX exposure, the GTP can help provide a framework for greater automation of the hedging process and help forecast which hedge scenarios to avoid. Two theorems are adapted from GRP to GTP and prove that grid trading, w

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37

Kempa, Bernd, and Michael Nelles. "Nonfundamental FX trading and excess volatility in credible target zones Theory and empirical evidence." International Review of Economics & Finance 8, no. 1 (1999): 55–70. http://dx.doi.org/10.1016/s1059-0560(99)00005-2.

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38

Rundo, Francesco. "Deep LSTM with Reinforcement Learning Layer for Financial Trend Prediction in FX High Frequency Trading Systems." Applied Sciences 9, no. 20 (2019): 4460. http://dx.doi.org/10.3390/app9204460.

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High-frequency trading is a method of intervention on the financial markets that uses sophisticated software tools, and sometimes also hardware, with which to implement high-frequency negotiations, guided by mathematical algorithms, that act on markets for shares, options, bonds, derivative instruments, commodities, and so on. HFT strategies have reached considerable volumes of commercial traffic, so much so that it is estimated that they are responsible for most of the transaction traffic of some stock exchanges, with percentages that, in some cases, exceed 70% of the total. One of the main i

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39

Aravind M. "FX Volatility Impact on Indian Stock Market: An Empirical Investigation." Vision: The Journal of Business Perspective 21, no. 3 (2017): 284–94. http://dx.doi.org/10.1177/0972262917716760.

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Examining the interrelationship between currency market volatility and stock market volatility will create abundant trading opportunities to the investors irrespective of whether the return of one market is moving up or down. This research work intended to examine how the exchange rate volatility between Indian rupee and foreign currencies, such as US dollar, euro, Japanese yen and British pound, can influence the return and volatility of the Indian stock market. The research data extensively cover daily price observations of foreign currencies as well as Nifty index for 1500 days. The general

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40

Sekhar, Bichith C., and A. Umamaheswari. "A Study On Technical Analysis With Reference To International Forex." Think India 22, no. 3 (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 a

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41

Berlinger, Edina, Barbara Dömötör, and Balázs Árpád Szűcs. "Irrational risk-taking of professionals? The relationship between risk exposures and previous profits." Risk Management 23, no. 3 (2021): 243–59. http://dx.doi.org/10.1057/s41283-021-00076-5.

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AbstractThe risk attitude of investors is a key factor determining financial asset prices and market trends. Changes in risk attitude may be due to the interference of macro-level (business cycle) and micro-level (individual experience) effects. We investigate the impact of individual experience on the subsequent risk-taking attitude of professionals via the analysis of the trading activity of 351 non-financial firms and (non-bank) financial institutions (insurance companies, financial intermediaries, etc.) covering 57,039 FX forward transactions in a highly volatile period between January 200

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42

Cabej, Gerda, Manfred Gilli, Jonela Lula, and Enrico Schumann. "FX Trading: An Empirical Study." SSRN Electronic Journal, 2011. http://dx.doi.org/10.2139/ssrn.1885044.

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43

Somogyi, Fabricius. "Dollar Dominance in FX Trading." SSRN Electronic Journal, 2021. http://dx.doi.org/10.2139/ssrn.3882546.

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44

Evans, Martin D. "FX Trading and Exchange Rate Dynamics." SSRN Electronic Journal, 2000. http://dx.doi.org/10.2139/ssrn.251696.

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45

Fischer, Andreas M., and Angelo Ranaldo. "Does FOMC News Increase Global FX Trading?" SSRN Electronic Journal, 2008. http://dx.doi.org/10.2139/ssrn.1101583.

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46

Beilis, Alan, Jan Dash, and Jacqueline Volkman Wise. "Psychology, Stock/FX Trading, and Option Prices." SSRN Electronic Journal, 2012. http://dx.doi.org/10.2139/ssrn.1992016.

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47

Ranaldo, Angelo, and Fabricius Somogyi. "Heterogeneous Information Content of Global FX Trading." SSRN Electronic Journal, 2018. http://dx.doi.org/10.2139/ssrn.3263279.

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48

"Algorithmic Trading in the Global FX Market." Journal of Trading 3, no. 2 (2008): 49–55. http://dx.doi.org/10.3905/jot.2008.705634.

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49

Georges, Nicolas. "ANANTA: A Systematic Quantitative FX Trading Strategy." SSRN Electronic Journal, 2014. http://dx.doi.org/10.2139/ssrn.2419243.

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50

Bjonnes, Geir Hoidal, and Dagfinn Rime. "FX Trading... LIVE! Dealer Behavior and Trading Systems in Foreign Exchange Markets." SSRN Electronic Journal, 2000. http://dx.doi.org/10.2139/ssrn.244468.

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