Forex Trading Research Articles

Understanding Financial Resiliency: A Qualitative Inquiry into the Experiences and Strategies of The Employees in an Engineering and Consultancy Firm

The purpose of this qualitative case study was to conduct an in-depth analysis of the potential of Forex Trading and investing in developing financial resiliency among the employees of an Engineering and Consultancy Firm in the Philippines. This is a qualitative single case study of 10 employees of the company that were interviewed regarding the potential of investing in forex trading as a means to attain financial resiliency. Qualitative data for this study were gathered through one-session, semi-structured interviews, focus group discussions, documents, journaling, and observations. Thematic analysis following Braun and Clarke’s method for analysing qualitative data was used in understanding the qualitative data. Results have shown that participants have identified several challenges that seem to slow them down in earning money for them to obtain their aspiration of becoming financially resilient. It was also shown that participants thought that venturing in new business, stock market and forex investments, and sideline jobs were the most frequent responses recorded that may serve as solutions to the challenges. It is important to note that most of the participants were affirmative upon being asked if they would try foreign exchange investments as a potential means of achieving financial resiliency. Among others, the most significant manner of addressing financial challenges lamented by the participants was having a well-conditioned mind so that a well-planned long-term goal will be established. It is recommended to explore more related literature that tackles financial education in the Philippines and note the statistical number of those who are financially literate as this could be a contributing factor why the participants of this study lack concrete saving plans. Moreover, further exploration on the trend of foreign exchange investment is also suggested including the use of digital platforms for information dissemination regarding finance.

The fallout from the forex cartels: what legacy for foreign exchange regulation?

ABSTRACT This article analyses infringement and settlement decisions issued by the European Commission in recent years in relation to cartels in the foreign exchange (‘forex’ or ‘FX’) sector, assesses what these decisions tell us about the susceptibility of the forex sector to anticompetitive behaviour and proposes how these risks might be reduced. This includes a focus on addressing the lack of transparency that characterises the sector. It is argued that preventing similar abuses occurring in future cannot be left to competition law alone, but rather requires greater ex ante regulation of the forex sector. As such, a crucial first step is the need for greater data gathering and analysis in relation to the purposes for which most forex trading is undertaken and it is proposed that there should be a stronger division between traders’ market-making activities and proprietary trading to try to minimise opportunities for collusive conduct and reduce information asymmetries.

Is attention all you need for intraday Forex trading?

AbstractThe main objective of this paper is to analyse whether the Transformer neural network, which has become one of the most influential algorithms in Artificial Intelligence over the last few years, exhibits predictive capabilities for high‐frequency Forex data. The prediction task is to classify short‐term Forex movements for six currency pairs and five different time intervals from 60 to 720 min. We find that the Transformer exhibits high predictive power in the context of intraday Forex trading. This performance is slightly better than for the carefully selected benchmark – ResNet‐LSTM, which currently is a state‐of‐the‐art algorithm. Since intraday Forex trading based on deep learning models is largely unexplored, we offer insight on which currency pair and time interval are amenable to devising a profitable trading strategy. We also show that high predictive accuracy can be misleading in real world trading for short time intervals, as models trained on OHLC data tend to report the highest accuracy when the spread cost is the highest. This renders assessment based on typical machine learning metrics overly optimistic. Therefore, it is critical to backtest frequent intraday Forex trading strategies with realistic cost assumptions, which is rarely the case in empirical literature. Lastly, sensitivity analysis shows that the length of the time interval used for training does not play a critical role in the Transformer's predictive capabilities, whereas features derived from technical analysis are essential.

The Generalised Extreme Value Distribution Approach to Comparing the Riskiness of BitCoin/US Dollar and South African Rand/US Dollar Returns

In this paper, the generalised extreme value distribution (GEVD) model is employed to estimate financial risk in the form of return levels and the value at risk (VaR) for the two exchange rates, BitCoin/US dollar (BTC/USD) and the South African rand/US dollar (ZAR/USD). The Basel Committee on Banking Supervision (BCBS) responsible for developing supervisory guidelines for banks and financial trading desks recommended that VaR be computed and reported. The maximum likelihood estimation (MLE) method is used to estimate the parameters of the GEVD. The estimated risk values are used to compare the riskiness of the two exchange rates and help both traders and investors to define their position in forex trading. This is to helping understanding the risk they are taking when they convert their savings/investments to BitCoin instead of the South African currency, the rand. The high extreme value index associated with the BTC/USD compared to the ZAR/USD implies that BitCoin is riskier than the rand. The BTC/USD has higher values of expected extreme/tail losses of 13.44%, 18.02%, and 23.41% at short (6 months), medium (12 months), and long (24 months) terms, compared to the ZAR/USD expected extreme/tail losses of 2.40%, 2.84%, and 3.28%, respectively. The computed VaR estimates for losses of USD 0.17, USD 0.22, and USD 0.38 per dollar invested in BTC/USD at 90%, 95%, and 99%, compared to ZAR/USD’s USD 0.03, USD 0.03, and USD 0.04 at the respective confidence levels, confirm the high risk associated with BitCoin. The conclusion drawn from this study is that BTC/USD is riskier than ZAR/USD, despite the rand being a developing country’s currency, hence perceived as being risky. The perception is that the rand is riskier than BitCoin and perceptions do influence exchange rates. Kupiec’s backtest results confirmed the model’s adequacy. These findings are helpful to investors, traders, and risk managers when deciding on trading positions for the two currencies.

Support Vector Machine for Predicting Candlestick Chart Movement on Foreign Exchange

Foreign Exchange, commonly called Forex, is a form of investment in the non-real sector in great demand. Forex is a marketplace that specializes in foreign exchange trading. Technology advancements have made it easy to monitor investment conditions in real time and present them in an easyto - understand graphical form. As a result, predictions are closely related to investment, starting from market sentiment and economic conditions to technical matters. One of the Artificial Intelligence methods that can be used in classifying is the Support Vector Machine (SVM). SVM is a machine learning classification method based on the Structural Risk Minimization (SRM) principle to find the best hyperplane that separates two classes in the input space that determines the classification decision function by minimizing empirical risk. This study used candlestick patterns to predict foreign exchange chart movements using the Support Vector Machine (SVM) classification method. The purpose of this study was to measure the accuracy of the Support Vector Machine method in making predictions using candlestick patterns so that it can assist traders in making decisions in forex trading. The accuracy level obtained from the data classification results reached 90.72% with a precision of 87.69%. With a relatively good level of accuracy, the Support Vector Machine (SVM) method can be used to predict chart movements in foreign exchange using candlesticks to indicate the current trend’s direction.

Communal Governance and Transnationalism: A Case Study of the Nigerien Forex Trading Community in Benin City

Migrant community associations are well-structured and often engage in political transnationalism with their countries of origin. Nigerien migrants in Benin City, Edo State, occupy a dominant position in the unofficial foreign exchange market. Their communal governance structures reveal interesting parallels in the way the migrants govern themselves in relation to their status and the local nationals they work with. The politics within the migrant association suggest that, even in the absence of status, migrants are able to govern and protect their interests while contributing to the societies they find themselves in. This article looks at examples of Nigerien transnationalism in Nigeria at the micro level to reveal a complex network of communal governance. By studying the organisational lives of the Nigerien migrant community, we aim to understand how this group contributes to the maintenance f ties with Niger and enables their integration into their host community.

Validity of Forex Trading Agreements Using Foreign Currency as the Object of Investment

Forex (Foreign Exchange) is better known in Indonesian as Forex trades between two currencies from two countries by many States Parties, institutions and individuals. Forex trading between market players that lasts Open 5 days a week, 24 hours a day. inner consistency Forex trading operations based on Article 1338 of the Legislative Code Civil. These provisions are less effective because there are still many brokers illegal brokers, unlicensed and unscrupulous companies with the intention of misleading investors. Due to the futures trading law Commodity has not yet implemented a complete forex trading system.Speaking of validity foreign exchange investment contract based on article 1320 of the civil code on the conditions of validity of the contract, foreign exchange as the object of the contract, not contrary to the objective conditions which have legal consequences, null and void history and characteristics of book iii of the civil code which regulates the commitment is open, so it is allowed to make one agreements other than those provided for in the civil code, provided that they are not contrary with the law, public order and good morals. This research advising the government and the legislator to make regulations related toforeign exchange investment regulations to prevent things that are not legal protection desired and guaranteed for investors

Currency exchange rate predictability: The new power of Bitcoin prices

We show that Bitcoin prices have surprisingly predictive power for nominal currency exchange rates, both in-sample and out-of-sample. The predictability follows from the fact that Bitcoin prices are forward-looking: Bitcoin efficiently incorporates expectations of currency exchange rates and their drivers, as exchange rates serve as a fundamental of Bitcoin. We examine the Bitcoin-based exchange rate prediction model in the autoregressive distributed lag (ADL) specification and the error correction specification. Forecasts based on both specifications outperform different benchmarks for some of the exchange rates. The outperformance is most pronounced at the daily horizon using the ADL model. Bitcoin-based forex trading strategies generate Sharpe ratio gains relative to the US risk-free rate and the carry trade. Bitcoin returns incorporate extra knowledge of future interest rate differentials after controlling for lagged exchange rate movements. Our result is inspiring for currency market participants, given the well-documented difficulty in exchange rate prediction.

Sharia Business Ethics Online Forex Trading at Company Signal Providers Volatility 75 Index JR (VIXJR)

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.

Forex, Cfds and Other Derivatives: Investments or Gambling?

The attractions to investors of forex and other derivatives derives from their simplicity: to bet on the direction of a price change. Unfortunately, many ‘investors’ do not realise that short term price changes are not predictable and, inevitably, they will lose their money. This paper explains why this is inevitable. It also argues that the regulation of forex should be handled by a gambling regulator (in the UK, the Gambling Commission) rather than a financial regulator (in the UK, the Financial Conduct Authority) as forex trading is a bet and not an investment.

Implementing Bisection Method on Forex Trading Database for Early Diagnosis of Inflection Point

Many people are trading in the forex market during the COVID-19 pandemic with the hope of earning money, but they are experiencing shortages due to the lack of information and technology-based tools for existing daily data. Sometimes traders only use moving averages in trading data, even though this information needs to be processed again to get the right inflection point. The objective of this research is to find inflection points based on Forex trading database. Another algorithm can also be used to determine the inflection point between two points on a moving average. This can be supported by the Bisection method used because it can guarantee that convergence will occur. The results show that the points resulting from the bisection calculation on the moving average provide a fairly accurate decision support for the location where the inflection point is located. From 10,000 data there is a standard deviation of 0.71 points which is very small compared to an average of 20 pips (points used as the difference in price values in forex). The use of the bisection method provides an accuracy of the results in seeing the inflection point of 87%.

РЕАЛИЗАЦИЯ ТОРГОВОГО СОВЕТНИКА ДЛЯ МУЛЬТИРЫНОЧНОЙ ПЛАТФОРМЫ METATRADER 5

The article describes the process of creating a flexible trading strategy for algorithmic tradingin a specialized development environment MQL5 IDE in the MetaTrader 5 multi-asset platform.The advantages and expediency of using the MetaTrader 5, MetaTrader 4 platforms andtheir respective trading applications Trade Assistant, Forex Trade Manager, Trade Time Manager,CAP Gold Albatross EA and Fast Copy are shown. A comparative analysis of the existing implementationsof trading advisors based on various indicators, as well as those created using intelligenttechnologies, has been carried out. In the previously implemented trading advisors, for predictingthe prices of the volatility of financial assets, flexible learning algorithms, compensatoryfuzzy logic models, and technical analysis tools are mainly used, which entails high time costs, inconditions of high financial market volatility. To solve this problem, the authors propose an integratedapproach based on the use of technical analysis tools built into the MetaTrader 5 multimediaplatform and the trading strategy automation algorithm, which makes it possible to obtain aforecast of a given accuracy for the selected instrument in real time. The paper substantiates theneed to introduce elements of automatic trading when analyzing the quotes of financial instrumentsand managing a trading account in order to avoid mechanical, analytical, organizationaland psychological mistakes made by traders. The study shows step by step the process of creating,debugging, testing, optimizing and executing the implemented trading advisor. An algorithm forautomating a trading strategy has been developed and its block diagram has been presented.The initial data for the trading strategy automation algorithm are determined, and the mathematicalapparatus for calculating indicators of limit orders of the TakeProfit and StopLoss types isdescribed. Since exchange trading is associated with many risks, we analyzed the impact of differentvalues of lots of TakeProfit and StopLoss limit orders on possible profit and drawdown limit(loss). As a result, the EA worked correctly in real time without human intervention for eightweeks using two trading strategies. The results of testing the developed software allow us to drawthe following conclusions: when the EA shows a high degree of recommendation, the actual financialassets show high efficiency.

Learning Nonstationary Time-Series With Dynamic Pattern Extractions

The era of information explosion had prompted the accumulation of a tremendous amount of time-series data, including stationary and nonstationary time-series data. State-of-the-art algorithms have achieved a decent performance in dealing with stationary temporal data. However, traditional algorithms that tackle stationary time-series do not apply to nonstationary series like Forex trading. This article investigates applicable models that can improve the accuracy of forecasting future trends of nonstationary time-series sequences. In particular, we focus on identifying potential models and investigate the effects of recognizing patterns from historical data. We propose a combination of the seq2seq model based on recurrent neural network, along with an attention mechanism and an enriched set features extracted via dynamic time warping and zigzag peak valley indicators. Customized loss functions and evaluating metrics have been designed to focus more on the predicting sequence’s peaks and valley points. Our results show that our model can predict 4-h future trends with high accuracy in the Forex dataset, which is crucial in realistic scenarios to assist foreign exchange trading decision making. We further provide evaluations of the effects of various loss functions, evaluation metrics, model variants, and components on model performance.

Efforts to Increase Customer Loyalty Forex Trading Judging from the Elements of Trust and Relationships Emotional

This study aims to determine the effect of trust and emotional relationships partially and simultaneously on customer loyalty in forex trading at the European Rexchanger Trading Company Graha Medan. The research approach used is quantitative research. The population in this study consisted of all customers of the European Rexchanger company Graha Medan Branch, amounting to 2700 people. The sampling technique used was accidental sampling where 96 regular customers at Rexchanger Europe Graha Medan Branch. Questionnaires were selected in this study as a data collection technique. The results of this study partially positive effect on customer trust and emotional relationships partially positive effect on customer trust. Simultaneous test results (Test f) trust and emotional relationships have a positive and significant effect on customer loyalty in Forex trading. The result of the determination test is that 72.7% of the variation in the dependent variable, namely Trust and Emotional Relationships, has a contribution to customer loyalty in Forex trading. While the remaining 28.3% is influenced by other variables outside the variables studied.

Assessment of the Effect of Social Participation on Financial Inclusion of Northern Rangeland Trust women groups, Kenya

Purpose: To assess the effect of social participation on financial inclusion of Northern Rangeland Trust women groups, Kenya.
 Methodology: The current study used descriptive research design to collect quantitative and qualitative data. The target population was 10 women groups registered in Northern Rangeland Trust in Laikipia County. The respondents were 10 chairladies, 10 secretaries, 10 treasurers, and 152 women members. Women group leaders were interviewed while the women who were members of self-help groups answered the questionnaire. The study conducted pre-test on 1 women group in Samburu County selected using simple random method. The study also sampled 1 chairlady, 1 secretary, 1 treasurer and 15 women members. Chairladies, secretaries and treasurers were selected using purposive sampling method while the members were selected using simple random sampling method. The descriptive statistics such as frequencies, percentages and median were computed. The findings were presented using descriptive tables, figures and narratives for ease of understanding the results. Inferential analysis to be generated included model summary to test the level of influence, analysis of variance to test hypothesis and regression coefficients to test the study’s model. Diagnostic tests such as normality, linearity, multicollinearity, heteroskedasticity, and autocorrelation were tested. The study used multiple regression analysis in order to determine the relationship between linking social capital and financial inclusion of women groups in northern rangeland trust, Laikipia county, Kenya.
 Results: The results from the questionnaires revealed, 39(29%) and 26(19%) strongly agreed and agreed correspondingly that women groups were able to access to financial services e.g., accounting services at subsidized rates after partnering with NGOs such as NRT. However, 80(60%) and 27(20%) strongly disagreed and disagreed correspondingly that there has been availability of financial opportunities on investments as a result of women groups selling products to internal and external promoters. The R coefficient was 0.863 while R-Square was 0.745. This meant that social networks had a 74.5% influence on financial inclusion. The significance value was 0.009 which was less than 0.05. The study therefore rejected null hypothesis that social participation does not have significant effect on financial inclusion of Northern Rangeland Trust women groups, Kenya.
 The results from the interviews revealed, the various types of financial knowledge women in groups were bound to get that enabled them have outstanding performances in their projects as book-keeping, reconciliation and auditing. Additionally, the ways that NRT linked women to access financial services included connecting them with various accounting firms, accountants, financial managers and auditors. Further, the selection criteria that they used to rule out women groups that got access to financial opportunities on investments included availability of memorandum of association, group minutes and application status to NRT.
 Unique contribution to theory, policy and practice: In as much as women were in a position of getting finances, the full access to financial opportunities was limited. This is whereby many groups of women had to rely on few economic activities that were majorly pegged on the directions given by both national and county governments. The study recommends that on social participation, there should be awareness raised by local leaders on available financial opportunities that women would engage locally to raise money. Various non-government organizations should encourage women to start various non-tradition business and explore wider on fields such as forex trading, online jobs, application of both local and international tenders among others. This would give an upper hand towards promoting more financial opportunities.

JUAL BELI UANG (FOREIGN EXCHANGE TRANSACTION) DITINJAU DARI PERSPEKTIF HUKUM EKONOMI ISLAM

Foreign exchange trading transactions are getting more and more in demand, Muslim investors/traders are no exception. Even recently, forex trading has been used as a speculation tool for traders to make a profit. Therefore, forex trading has become an important issue and has been in the spotlight of Muslim scholars and economists. In the study of fiqh, foreign exchange trading is known as al-sharf, namely buying and selling naqdain, gold for gold, silver for silver, or one of the two. This transaction is basically justified in Islam as long as it does not contain elements of usury. But unfortunately, the practice of foreign exchange trading is full of elements of usury, speculation, and gambling. According to the scholars, of these four forms of activity, only spot transactions are permitted, while forward, swap and option forms are prohibited.

Assessment of the Effect of Social Participation on Financial Inclusion of Northern Rangeland Trust women groups, Kenya

Purpose: To assess the effect of social participation on financial inclusion of Northern Rangeland Trust women groups, Kenya.
 Methodology: The current study used descriptive research design to collect quantitative and qualitative data. The target population was 10 women groups registered in Northern Rangeland Trust in Laikipia County. The respondents were 10 chairladies, 10 secretaries, 10 treasurers, and 152 women members. Women group leaders were interviewed while the women who were members of self-help groups answered the questionnaire. The study conducted pre-test on 1 women group in Samburu County selected using simple random method. The study also sampled 1 chairlady, 1 secretary, 1 treasurer and 15 women members. Chairladies, secretaries and treasurers were selected using purposive sampling method while the members were selected using simple random sampling method. The descriptive statistics such as frequencies, percentages and median were computed. The findings were presented using descriptive tables, figures and narratives for ease of understanding the results. Inferential analysis to be generated included model summary to test the level of influence, analysis of variance to test hypothesis and regression coefficients to test the study’s model. Diagnostic tests such as normality, linearity, multicollinearity, heteroskedasticity, and autocorrelation were tested. The study used multiple regression analysis in order to determine the relationship between linking social capital and financial inclusion of women groups in northern rangeland trust, Laikipia county, Kenya.
 Results: The results from the questionnaires revealed, 39(29%) and 26(19%) strongly agreed and agreed correspondingly that women groups were able to access to financial services e.g., accounting services at subsidized rates after partnering with NGOs such as NRT. However, 80(60%) and 27(20%) strongly disagreed and disagreed correspondingly that there has been availability of financial opportunities on investments as a result of women groups selling products to internal and external promoters. The R coefficient was 0.863 while R-Square was 0.745. This meant that social networks had a 74.5% influence on financial inclusion. The significance value was 0.009 which was less than 0.05. The study therefore rejected null hypothesis that social participation does not have significant effect on financial inclusion of Northern Rangeland Trust women groups, Kenya.
 The results from the interviews revealed, the various types of financial knowledge women in groups were bound to get that enabled them have outstanding performances in their projects as book-keeping, reconciliation and auditing. Additionally, the ways that NRT linked women to access financial services included connecting them with various accounting firms, accountants, financial managers and auditors. Further, the selection criteria that they used to rule out women groups that got access to financial opportunities on investments included availability of memorandum of association, group minutes and application status to NRT.
 Unique contribution to theory, policy and practice: In as much as women were in a position of getting finances, the full access to financial opportunities was limited. This is whereby many groups of women had to rely on few economic activities that were majorly pegged on the directions given by both national and county governments. The study recommends that on social participation, there should be awareness raised by local leaders on available financial opportunities that women would engage locally to raise money. Various non-government organizations should encourage women to start various non-tradition business and explore wider on fields such as forex trading, online jobs, application of both local and international tenders among others. This would give an upper hand towards promoting more financial opportunities.

Evaluation of FOREX trading Strategies based in Random Forest and Support Vector Machines

The Foreign Exchange (Forex) is the largest market in the world and has a daily trading volume of approximately 3.2 trillion dollars. The price movements are influenced by many exogenous factors, thereby it is difficult to predict. As a result, modeling its movement would enable high profitable investment strategies. Aiming at setting up a model that helps the market practitioner make better decisions for trading on Forex, Machine Learning algorithms (Random Forest and SVM) are adopted in this work. Classic technical indicators, like moving averages, are used as features for these algorithms. In order to evaluate these approaches, several simulations were carried out on the pairs Euro/Dollar, Pound/Dollar, Dollar/Swiss Franc and Dollar/Japanese Yen, using three different metrics. For virtually all scenarios investigated, the proposed algorithms outperform the traditional technical indicators.

A Novel Algorithmic Forex Trade and Trend Analysis Framework Based on Deep Predictive Coding Network Optimized with Reptile Search Algorithm

This paper proposed a short-term two-stage hybrid algorithmic framework for trade and trend analysis of the Forex market by augmenting the currency pair datasets with transformed attributes using a few technical indicators and statistical measures. In the first phase, an optimized deep predictive coding network (DPCN) based on a meta-heuristic reptile search algorithm (RSA) inspired by the intelligent hunting activities of the crocodiles is exploited to develop this RSA-DPCN predictive model. The proposed model has been compared with optimized versions of extreme learning machine (ELM) and functional link artificial neural network (FLANN) with genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE) along with the RSA optimizers. The performance of this model has been evaluated and validated through several statistical tests. In the second phase, the up and down trends are analyzed using the Higher Highs Higher Lows, and Lower Highs Lower Lows (HHs/HLs and LHs/LLs) trend analysis tool. Further, the observed trends are compared with the actual trends observed on the exchange price of real datasets. This study shows that the proposed RSA-DPCN model accurately predicts the exchange price. At the same time, it provides a well-structured platform to discern the directions of the market trends and thereby guides in finding the entry and exit points of the Forex market.

Manajemen Risiko dalam Transaksi Perdagangan Valuta Asing

Foreign exchange trading carries a high level of risk, so risk management is essential. This study aims to determine the risk of foreign exchange trading and to determine the application of risk management in foreign exchange trading. The research was conducted at PT Monex Investindo Futures Jakarta. The research method used a qualitative descriptive method. Based on the results of the study, it was found that the risk in forex trading is the risk of unexpected changes that cause market conditions to reverse direction, this can be due to economic or political events that affect market movements. The analysis used to determine the volatility of the foreign exchange market is to use technical and fundamental analysis. Fundamental analysis is based on data from economic and political news, while technical analysis is carried out using charts and indicators. There are five risk management implemented at PT Monex Investindo Futures to minimize losses resulting from price movements on the foreign exchange market, namely: moving average, bollinger band, parabolic SAR, Average Directional Movement Index and Robotics