Relevant bibliographies by topics / Forex markets

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Forex markets'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Forex markets"

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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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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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Derrick, Simon, Neil Mellor, and Michael Woolfolk. "Global Markets 2006 Forex Outlook." Journal of Investing 15, no. 1 (February 28, 2006): 93–99. http://dx.doi.org/10.3905/joi.2006.616859.

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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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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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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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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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Meng, Terry Lingze, and Matloob Khushi. "Reinforcement Learning in Financial Markets." Data 4, no. 3 (July 28, 2019): 110. http://dx.doi.org/10.3390/data4030110.

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Recently there has been an exponential increase in the use of artificial intelligence for trading in financial markets such as stock and forex. Reinforcement learning has become of particular interest to financial traders ever since the program AlphaGo defeated the strongest human contemporary Go board game player Lee Sedol in 2016. We systematically reviewed all recent stock/forex prediction or trading articles that used reinforcement learning as their primary machine learning method. All reviewed articles had some unrealistic assumptions such as no transaction costs, no liquidity issues and no bid or ask spread issues. Transaction costs had significant impacts on the profitability of the reinforcement learning algorithms compared with the baseline algorithms tested. Despite showing statistically significant profitability when reinforcement learning was used in comparison with baseline models in many studies, some showed no meaningful level of profitability, in particular with large changes in the price pattern between the system training and testing data. Furthermore, few performance comparisons between reinforcement learning and other sophisticated machine/deep learning models were provided. The impact of transaction costs, including the bid/ask spread on profitability has also been assessed. In conclusion, reinforcement learning in stock/forex trading is still in its early development and further research is needed to make it a reliable method in this domain.
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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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Dissertations / Theses on the topic "Forex markets"

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Kolář, Jan. "Návrh automatického obchodního systému pro forex." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2016. http://www.nusl.cz/ntk/nusl-241445.

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The thesis deals with designing an automated trading system, especially for intra-day trading the currency markets. The aim is to create a comprehensive theoretical background, practical work knowledge can be used to develop appropriate automated trading system. The thesis is an emphasis on technical and partly a psychological analysis of currency markets. Designed system will be suitably optimized to maximize profits and stability of applications on the most liquid currency pairs.
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Dukov, Kristian, and Elena Kyriaki. "Triangular Arbitrage in the ForexMarket : Emerging versus Developed markets." Thesis, Umeå universitet, Företagsekonomi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-90714.

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Over the last decade, researchers have attempted to show how efficient the markets are by using Fama’s Efficiency Market Hypothesis (EMH). The theory states that an investor cannot increase his returns without taking additional risk. The markets can be efficient in different forms depending on the information included in the traded asset. It is quoted that: "There ain't no such thing as a free lunch". However, the topic still remains disputable since researchers have introduced controversial findings after investigating different markets. Overall, emerging markets have been characterized with higher volatility which consequently declares for market imperfections. Commonly, these market inefficiencies are quickly captured by the eye of the investors who are lurking for potential benefits through exploiting them. These are the so called arbitrage opportunities which exist on different level of impact, depending on the attitude of the market. The existence of arbitrage is clear evidence against Fama’s theory and it has been documented in numerous studies. Unfortunately those events occur rarely and disappear in a matter of seconds, thus; is highly competitive to capitalize. Over the last decade high frequency trading (HFT) became popular on different markets and it allowed traders to make decisions and execute transactions in a matter of milliseconds using algorithms. The market we are interested in is the Forex market which is a decentralized market where currencies from all over the world are traded. Main participants include multinational banks which rely heavily on HFT. The method used to benefit from inefficiency is called triangular arbitrage and it involves selling and buying 3 sets of currency pairs in times when a parity is violated. The goal of this study is to answer the following research question, “Is there a difference in triangular arbitrage opportunities between emerging markets and developed ones?” The main objective of this research is to examine how the number of arbitrage occurrences varies considering different market characteristics. Furthermore, the originality of the research stems from the comparison between strategies using currencies from developed economies and emerging ones. Moreover, the additional academic value comes from the analysis of a new dataset that has not yet been examined. Lastly, our results make an empirical contribution into a country’s economy by reducing market inefficiencies and increasing economic stability. Our sample consists of quantitative data totaling to 2.4 million observations per quotation taken from 2011 and 2013 for currencies picked using a non-probability convenience method based on their property to be converted to EUR and USD currency and availability of information. The research revealed that differences between the two types of market exist, and indicates that the “early” markets possess higher arbitrage activity in contrast to the mature economies. These results should boost the potential for a better trading management and upgrade the profit growth.
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Atiah, Frederick Ditliac. "Dynamic multi-objective optimization for financial markets." Diss., University of Pretoria, 2019. http://hdl.handle.net/2263/79571.

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The foreign exchange (Forex) market has over 5 trillion USD turnover per day. In addition, it is one of the most volatile and dynamic markets in the world. Market conditions continue to change every second. Algorithmic trading in Financial markets have received a lot of attention in recent years. However, only few literature have explored the applicability and performance of various dynamic multi-objective algorithms (DMOAs) in the Forex market. This dissertation proposes a dynamic multi-swarm multi-objective particle swarm optimization (DMS-MOPSO) to solve dynamic MOPs (DMOPs). In order to explore the performance and applicability of DMS-MOPSO, the algorithm is adapted for the Forex market. This dissertation also explores the performance of di erent variants of dynamic particle swarm optimization (PSO), namely the charge PSO (cPSO) and quantum PSO (qPSO), for the Forex market. However, since the Forex market is not only dynamic but have di erent con icting objectives, a single-objective optimization algorithm (SOA) might not yield pro t over time. For this reason, the Forex market was de ned as a multi-objective optimization problem (MOP). Moreover, maximizing pro t in a nancial time series, like Forex, with computational intelligence (CI) techniques is very challenging. It is even more challenging to make a decision from the solutions of a MOP, like automated Forex trading. This dissertation also explores the e ects of ve decision models (DMs) on DMS-MOPSO and other three state-of-the-art DMOAs, namely the dynamic vector-evaluated particle swarm optimization (DVEPSO) algorithm, the multi-objective particle swarm optimization algorithm with crowded distance (MOPSOCD) and dynamic non-dominated sorting genetic algorithm II (DNSGA-II). The e ects of constraints handling and the, knowledge sharing approach amongst sub-swarms were explored for DMS-MOPSO. DMS-MOPSO is compared against other state-of-the-art multi-objective algorithms (MOAs) and dynamic SOAs. A sliding window mechanism is employed over di erent types of currency pairs. The focus of this dissertation is to optimized technical indicators to maximized the pro t and minimize the transaction cost. The obtained results showed that both dynamic single-objective optimization (SOO) algorithms and dynamic multi-objective optimization (MOO) algorithms performed better than static algorithms on dynamic poroblems. Moreover, the results also showed that a multi-swarm approach for MOO can solve dynamic MOPs.
Dissertation (MEng)--University of Pretoria, 2019.
Computer Science
MSc
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Kovářová, Petra. "Obchodování na Forexu a srovnání vybraných obchodních platforem." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-81897.

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This thesis deals with the Forex and trading on it. The aim of this work is to evaluate the possibility of trading primarily for retail investors, for which this financial market is becoming increasingly popular. In the first two chapters, Forex, its characteristic and information about trading are presented. In the next chapter, analysis of exchange rate development is described , both fundamental and technical. More attention is paid to technical analysis. The demonstration of application of technical analysis is presented. The last chapter deals with comparing the selected trading platforms in terms of availability, technical analysis and trading opportunities.
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Kosek, Lukáš. "Technická analýza." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2014. http://www.nusl.cz/ntk/nusl-224762.

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This thesis deals with problems of the technical analyses and its usage during creation of the automated trading systems. Theoretical section explains the basic principles of functioning of the monetary market (Forex) and includes technical indicators. Portfolio of strategies, as output of this work, was applied onto monetary pairs of Euro/American dollar and British pound/American dollar. Computer program Adaptrade Builder was used for proposed commercial strategies with help of the genetic algorithms and subsequently tested on the MetaTrader 4 commercial platform.
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Ondo, Ondrej. "Návrh a optimalizace automatického obchodního systému." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2014. http://www.nusl.cz/ntk/nusl-224709.

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This thesis focuses on automated trading systems for foreign exchange markets. It describes theoretical background of financial markets, technical analysis approaches and theoretical knowledge about automated trading systems. The output of the thesis is set of two automated trading systems built for trading the most liquid currency pairs. The process of developing automated trading system as well as its practical start up in Spartacus Company Ltd. is documented in the form of project documentation. The project documentation captures choosing necessary hardware components, their installation and oricess of ensuring smooth operation, as well as the selection and installation of the necessary software resources. In the Adaptrade Builder enviroment there has been shown the process of developing strategies and consequently theirs characteristics, performance, as well as a graph showing the evolution of the account at the time. Selected portfolio strategy has been tested in the MetaTrader platform and in the end of the thesis is offered assessing achievements and draw an overall conclusion.
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Vlček, Tomáš. "Podpora v rozhodování pro investičního experta na měnových trzích." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2014. http://www.nusl.cz/ntk/nusl-224707.

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The thesis focuses on automated trading systems for trading on currency market. It describes basics of market analysis and deals with the design, optimization and identifying appropriate indicators of automatic trading system, which is based on the Fibonacci retracement. This system should serve as a decision support for trader's operations in the currency market. Furthermore, this thesis deals with the possibility of avoiding exchange rate risk by trading in the foreign exchange market.
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Cheng, Sai-ho. "Rolling Forex /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B19909135.

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Vrba, Patrik. "Využití prostředků umělé inteligence na finančních trzích." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2011. http://www.nusl.cz/ntk/nusl-222913.

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This Master's thesis focuses on applying artificial intelligence tools for the prediction of development financial markets. Major emphasis is placed on evaluating the usability of neural networks to determine the prediction in the foreign exchange markets. It is also provided suggestion for fully automated processing of market data and subsequent submitting of trading orders.
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Cheng, Sai-ho, and 鄭世河. "Rolling Forex." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31268663.

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Books on the topic "Forex markets"

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Bickford, Jim L. Forex shockwave analysis. New York: McGraw-Hill, 2008.

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Bickford, Jim L. Forex Shockwave Analysis. New York: McGraw-Hill, 2008.

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The Forex mindset: The skills and winning attitude you need for more profitable Forex trading. New York: McGraw-Hill, 2011.

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Currency trading in the forex and futures markets. Upper Saddle River, N.J: FT Press, 2012.

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Norris, Jay. Mastering the currency market: Forex strategies for high- and low-volatility markets. New York: McGraw-Hill, 2010.

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Al, Gaskill, and Bell Teresa, eds. Mastering the currency market: Forex strategies for high- and low-volatility markets. New York: McGraw-Hill, 2010.

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Forex patterns & probabilities: Trading strategies for trending & range-bound markets. Hoboken, N.J: John Wiley & Sons, Inc., 2007.

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Nekritin, Alex. Naked Forex: High-probability techniques for trading without indicators. Hoboken, N.J: John Wiley & Sons, 2012.

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The little book of currency trading: How to make big profits in the world of forex. Hoboken, N.J: John Wiley & Sons, 2011.

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Goyal, Ashima. Monetary policy, forex markets, and feedback under uncertainty in an opening economy. Mumbai: Dept. of Economic Analysis and Policy, Reserve Bank of India, 2009.

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Book chapters on the topic "Forex markets"

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Cofnas, Abe. "Understanding Central Banks and their Role in Moving Currency Markets." In Planet Forex, 33–39. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92913-2_3.

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Schnidman, Evan A., and William D. MacMillan. "FOREX Investing: Central Bank Sentiment Data across the Globe." In How the Fed Moves Markets, 99–111. New York: Palgrave Macmillan US, 2016. http://dx.doi.org/10.1057/9781137432582_11.

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Ahmad, Wasim, Shirin Rais, and Ritesh Kumar Mishra. "An Analysis of Dynamic Spillover in India’s Forex Derivatives Markets." In Theorizing International Trade, 351–84. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-1759-9_15.

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Kumar, Anoop S., and Bandi Kamaiah. "Co-movement Among Asian Forex Markets: Evidence from Wavelet Methods." In Current Issues in Economics and Finance, 53–63. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5810-3_4.

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Loginov, Alexander, and Malcolm I. Heywood. "On the Utility of Trading Criteria Based Retraining in Forex Markets." In Applications of Evolutionary Computation, 192–202. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37192-9_20.

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Goel, Sandeep. "Forex market." In Finance for Non-Finance People, 182–91. Second edition. | Abingdon, Oxon ; New York, NY : Routledge, 2019.: Routledge India, 2019. http://dx.doi.org/10.4324/9780429196669-11.

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Mostovoy, Jonathan, Tomás Domínguez, and Luis Seco. "On Arbitrage-Free Pricing in Numeraire-Free Markets: With Applications to Forex and Cryptocurrency." In Financial Mathematics and Fintech, 21–33. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8373-5_2.

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Korczak, Jerzy, Marcin Hernes, and Maciej Bac. "Collective Intelligence Supporting Trading Decisions on FOREX Market." In Computational Collective Intelligence, 113–22. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67074-4_12.

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Moscinski, Rafal, and Danuta Zakrzewska. "Building an Efficient Evolutionary Algorithm for Forex Market Predictions." In Intelligent Data Engineering and Automated Learning – IDEAL 2015, 352–60. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24834-9_41.

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Flôres, Renato G., and Bruno B. Roche. "Volatility Modelling in the Forex Market: An Empirical Evaluation." In Advances in Quantitative Asset Management, 275–94. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4389-3_12.

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Conference papers on the topic "Forex markets"

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Maknickienė, Nijolė, Ieva Kekytė, and Algirdas Maknickas. "COMPUTATION INTELLIGENCE BASED DAILY ALGORITHMIC STRATEGIES FOR TRADING IN THE FOREIGN EXCHANGE MARKET." In Business and Management 2018. VGTU Technika, 2018. http://dx.doi.org/10.3846/bm.2018.53.

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Successful trading in financial markets is not possible without a support system that manages the preparation of the data, prediction system, and risk management and evaluates the trading efficien-cy. Selected orthogonal data was used to predict exchange rates by applying recurrent neural network (RNN) software based on the open source framework Keras and the graphical processing unit (GPU) NVIDIA GTX1070 to accelerate RNN learning. The newly developed software on the GPU predicted ten high-low distributions in approximately 90 minutes. This paper compares different daily algorith-mic trading strategies based on four methods of portfolio creation: split equally, optimisation, orthogonality, and maximal expectations. Each investigated portfolio has opportunities and limita-tions dependent on market state and behaviour of investors, and the efficiencies of the trading sup-port systems for investors in foreign exchange market were tested in a demo FOREX market in real time and compared with similar results obtained for risk-free rates.
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Contreras, Antonio V., Sergio Navarro, Antonio Llanes, Andres Munoz, Horacio Perez-Sanchez, and Jose M. Cecilia. "The Forex Market as an Elastic Network Model." In 2017 International Conference on Intelligent Environments (IE). IEEE, 2017. http://dx.doi.org/10.1109/ie.2017.36.

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Oyemade, David Ademola, and David Allenotor. "A Trade Gap Scalability Model for the Forex Market." In 2014 IEEE 11th Intl Conf on Ubiquitous Intelligence & Computing and 2014 IEEE 11th Intl Conf on Autonomic & Trusted Computing and 2014 IEEE 14th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom). IEEE, 2014. http://dx.doi.org/10.1109/uic-atc-scalcom.2014.38.

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Slany, Karel. "Towards the Automatic Evolutionary Prediction of the FOREX Market Behaviour." In 2009 International Conference on Adaptive and Intelligent Systems (ICAIS). IEEE, 2009. http://dx.doi.org/10.1109/icais.2009.31.

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Masry, Shaimaa, Monira Aloud, Edward Tsang, Alexandre Dupuis, and Richard Olsen. "A novel approach for studying the high-frequency FOREX market." In 2010 2nd Computer Science and Electronic Engineering Conference (CEEC). IEEE, 2010. http://dx.doi.org/10.1109/ceec.2010.5606494.

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Makovský, Petr. "Market Efficiency Hypothesis Application in the Czech Republic – the FOREX Case." In International Days of Statistics and Economics 2019. Libuše Macáková, MELANDRIUM, 2019. http://dx.doi.org/10.18267/pr.2019.los.186.103.

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Weerathunga, H. P. S. D., and A. T. P. Silva. "DRNN-ARIMA Approach to Short-term Trend Forecasting in Forex Market." In 2018 18th International Conference on Advances in ICT for Emerging Regions (ICTer). IEEE, 2018. http://dx.doi.org/10.1109/icter.2018.8615580.

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Xing, Frank, Duc-Hong Hoang, and Dinh-Vinh Vo. "High-Frequency News Sentiment and Its Application to Forex Market Prediction." In Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences, 2021. http://dx.doi.org/10.24251/hicss.2021.191.

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Grover, Aruquipa A., and Rojas S. Gabriel. "Analysis of Algorithmic Trading with Q-Learning in the Forex Market." In 2021 International Conference on Emerging Smart Computing and Informatics (ESCI). IEEE, 2021. http://dx.doi.org/10.1109/esci50559.2021.9396948.

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Noertjahyana, Agustinus, Agustinus Noertjahyana, Zuraida Abal Abas, and Zeratul Izzah Mohd Yusoh. "Combination of Candlestick Pattern and Stochastic to Detect Trend Reversal in Forex Market." In 2019 4th Technology Innovation Management and Engineering Science International Conference (TIMES-iCON). IEEE, 2019. http://dx.doi.org/10.1109/times-icon47539.2019.9024485.

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Reports on the topic "Forex markets"

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Yamada, Masahiro, and Takatoshi Ito. Price Discovery and Liquidity Recovery: Forex Market Reactions to Macro Announcements. Cambridge, MA: National Bureau of Economic Research, April 2020. http://dx.doi.org/10.3386/w27036.

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Ito, Takatoshi, and Tomoyoshi Yabu. What Prompts Japan to Intervene in the Forex Market? A New Approach to a Reaction Function. Cambridge, MA: National Bureau of Economic Research, May 2004. http://dx.doi.org/10.3386/w10456.

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Reynoso, Alejandro. Can Subsidiaries of Foreign Banks Contribute to the Stability of the Forex Market in Emerging Economies? A Look at Some Evidence from the Mexican... Cambridge, MA: National Bureau of Economic Research, March 2002. http://dx.doi.org/10.3386/w8864.

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You might also be interested in the extended bibliographies on the topic 'Forex markets' for particular source types:
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