Forex Trading Research Articles

JUAL BELI UANG (FOREIGN EXCHANGE TRANSACTION) DITINJAU DARI 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 become a sharp focus for 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.

Forex market forecasting with two-layer stacked Long Short-Term Memory neural network (LSTM) and correlation analysis

Since it is one of the world's most significant financial markets, the foreign exchange (Forex) market has attracted a large number of investors. Accurately anticipating the forex trend has remained a popular but difficult issue to aid Forex traders' trading decisions. It is always a question of how precise a Forex prediction can be because of the market's tremendous complexity. The fast advancement of machine learning in recent decades has allowed artificial neural networks to be effectively adapted to several areas, including the Forex market. As a result, a slew of research articles aimed at improving the accuracy of currency forecasting has been released. The Long Short-Term Memory (LSTM) neural network, which is a special kind of artificial neural network developed exclusively for time series data analysis, is frequently used. Due to its high learning capacity, the LSTM neural network is increasingly being utilized to predict advanced Forex trading based on previous data. This model, on the other hand, can be improved by stacking it. The goal of this study is to choose a dataset using the Hurst exponent, then use a two-layer stacked Long Short-Term Memory (TLS-LSTM) neural network to forecast the trend and conduct a correlation analysis. The Hurst exponent (h) was used to determine the predictability of the Australian Dollar and United States Dollar (AUD/USD) dataset. TLS-LSTM algorithm is presented to improve the accuracy of Forex trend prediction of Australian Dollar and United States Dollar (AUD/USD). A correlation study was performed between the AUD/USD, the Euro and the Australian Dollar (EUR/AUD), and the Australian Dollar and the Japanese Yen (AUD/JPY) to see how AUD/USD movement affects EUR/AUD and AUD/JPY. The model was compared with Single-Layer Long Short-Term (SL-LSTM), Multilayer Perceptron (MLP), and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise–Improved Firefly Algorithm Long Short-Term Memory. Based on the evaluation metrics Mean Square Error (MSE), Root Mean Square Error, and Mean Absolute Error, the suggested TLS-LSTM, whose data selection is based on the Hurst exponent (h) value of 0.6026, outperforms SL-LSTM, MLP, and CEEMDAN-IFALSTM. The correlation analysis conducted shows both positive and negative relations between AUD/USD, EUR/AUD, and AUD/JPY which means that a change in AUD/USD will affect EUR/AUD and AUD/JPY as recorded depending on the magnitude of the correlation coefficient (r).

The Accuracy of Relative Strength Index (RSI) Indicator in Forecasting Foreign Exchange Price Movement

This study aims to measure the accuracy of the Relative Strength Index (RSI) Indicator in predicting the direction of foreign exchange (forex) price movements. To achieve the research objectives, six foreign exchange currencies that fall into the major pair category were determined as samples. RSI data is collected from the Foreign Exchange Market which can be accessed via tradingview.com during the research period, January – September 2021. The data is analyzed using SPSS software with the Mann Whitney U Test which can prove statistically whether there is a significant difference between the predictions of forex price movements with the reality price movement. Thus, this study provides evidence of the accuracy of the Relative Strength Index (RSI) Indicator in predicting the direction of forex price movements. The findings of this study can be a reference for practitioners such as forex traders or business people who deal with foreign currencies in choosing technical analysis methods that can help make the right decisions.

Analysis Of Sharia Economic On Forex Trading Of Financial Broker Succes Traders

There are two issues studied in this thesis: (1) How to Trade Forex on a Financial Broker Succes Trader, (2) How to Analyze Sharia Economic Law on Forex Trading at a Financial Broker Succes Trader. This thesis aims to find out how to trade Forex on a Financial Broker Success Trader and the analysis of sharia economic law on Forex Trading at a Financial Broker Success Trader. This research is a type of field research with empirical normative research methods. From the results of this study, it was found that: (1) Forex Trading on a Financial Broker Success Trader has three aspects, namely; a forex trading contract made with the approval of both parties by filling in personal data before creating an FBS account, forex trading procedures on FBS from how to sell and buy, how to withdraw funds (profits and deposits) and how to freeze a temporary account for traders. Then regarding the object of forex trading transactions on FBS, namely by trading currency pairs of different types. (2) The analysis of sharia economic law on forex trading contracts on FBS is following the provisions of sharia economic law that forex trading is also called al-sharf, namely buying and selling foreign currencies and not trading in similar currencies at different prices but in different currencies at a different rate or value. Forex trading is the same as buying and selling in general, and there is nothing prohibited in Islamic economic law. The procedure for forex trading on FBS is also appropriate regarding how to sell, buy, and withdraw funds and does not include prohibitions in sharia economic law. Regarding the object of forex trading transactions on FBS, it follows the provisions of sharia economic law, namely not trading goods of the same value at different prices but foreign currencies (different types) with different prices.

Performance and Efficiency Analysis of Selected Private Sector banks in India

This paper discusses the performance and efficiency analysis of selected private sector banks in the light of tough competition and technology up gradation. Right from the establishment of Royal Chartered bank, Indian banking sector has seen a magnanimous growth especially after independence. The nationalization of banks in 1969 and 1980 had added fuel to the growth. The New Economic policy, 1991 has totally changed the facets of the banking sector. The doors are open to the private and foreign banks to India and the services are scattered and spread to various areas like wealth management, insurance, mutual funds, forex trading, financial services etc apart from the primary objective of accepting deposits and lending loans. This research paper focuses on evaluation of the performance and efficiency analysis of selected private sector banks with respect to some of the key indicators such as Total deposits, Total advances, Total Assets, Net Profit & Non-Performing Assets of last 10 years. The absolute figures and the average annual growth rates (AAGR) were calculated for each indicator over a period of 10 years and accordingly the rankings were assigned based on performance and efficiency analysis. Key area findings of the research were found and so incorporated in the study. The research found that has been performing well among the given three banks when compared with other two banks.

Relationship between Risk Management and Investment Strategy on Profit Forex Trading Online Gold

This study aims to analyze the effect of risk management and investment strategy on online forex trading, as well as the effect of risk management, investment strategy, and online forex trading on profit trading. The type of research used is an explanatory survey. The unit of analysis is members of the trader community in Banjarbaru, South Kalimantan, totaling 178 people with the sampling technique used is purposive sampling totaling 100 respondents. The variables used are risk management (X1), investment strategy (X2), online forex trading (Z), and profit trading (Y) using the path analysis method. The results of the study state that risk management has a significant effect on online forex trading, risk management has a significant effect on profit trading, investment strategies have a significant effect on online forex trading, investment strategies have a significant effect on profit trading, and online forex trading has a significant effect on profit trading.

An Ensembling Architecture Incorporating Machine Learning Models and Genetic Algorithm Optimization for Forex Trading

Algorithmic trading has become the standard in the financial market. Traditionally, most algorithms have relied on rule-based expert systems which are a set of complex if/then rules that need to be updated manually to changing market conditions. Machine learning (ML) is the natural next step in algorithmic trading because it can directly learn market patterns and behaviors from historical trading data and factor this into trading decisions. In this paper, a complete end-to-end system is proposed for automated low-frequency quantitative trading in the foreign exchange (Forex) markets. The system utilizes several State of the Art (SOTA) machine learning strategies that are combined under an ensemble model to derive the market signal for trading. Genetic Algorithm (GA) is used to optimize the strategies for maximizing profits. The system also includes a money management strategy to mitigate risk and a back-testing framework to evaluate system performance. The models were trained on EUR–USD pair Forex data from Jan 2006 to Dec 2019, and subsequently evaluated on unseen samples from Jan 2020 to Dec 2020. The system performance is promising under ideal conditions. The ensemble model achieved about 10% nett P&L with −0.7% drawdown level based on 2020 trading data. Further work is required to calibrate trading costs & execution slippage in real market conditions. It is concluded that with the increased market volatility due to the global pandemic, the momentum behind machine learning algorithms that can adapt to a changing market environment will become even stronger.

Geometric progression and relative strength index applied to FX hedging

This research aims at profit maximization and loss minimization in any FX market trading. A geometric progression (geometric sequence), is said to be a non-zero number progression or sequence in which each term following the first is obtained via multiplying the prior by the common ratio, which is a predetermined non-zero value. This method seeks to open an opposite position to an existing initial position in order to hedge that initial position in the event that the market moves against our trade. There are a number of mathematical models to develop new hedging strategies for Forex trading. Due to the apparent high level of unpredictability in price movement, forecasting the future of a stock price is a challenging endeavor. The research would like to study one with geometric progression in particular. In other words, every number can be entered as multiple integer of a different number. Thus, 1, 2, 4, 8,..., 2n is a step forward. Smart traders never take more risks than their capital, however, the otherwise is viewed and considered here.

FOREX ROBOT DEVELOPMENT IN THE PERSPECTIVE OF LAW ENFORCEMENT INTELLIGENCE AND INTELLIGENCE STRATEGY

In the development of technology in the financial world, we are also now familiar with trading robots. This robot works to make it easier to trade in cyberspace. Trading robots do not offer a solution to generate instant profitable transactions. Profitable long-term forex trading is much more than just tactical analysis of forex trading and the use of trading robots. Have a special program that does all the work to look tempting. But this is how trading robot’s work. Trading robot sellers who prefer to see a decent trading robot. Such a system requires constant human adaptation and supervision. The general public who wants to use trading robots well must know the risks and systems of the trading robot and there is no guarantee that using a trading robot will be 100% profitable. It should be emphasized again that the trading robot will make decisions based on the conditions that have occurred and the right decisions at that time. Thus, no foreign trade organizer dares to give absolute guarantees.

Intelligence Law Enforcement and Intelligence Strategy in Forex Robot Development in Indonesia

In the development of technology in the financial world, we are also now familiar with trading robots. This robot serves to facilitate trading in cyberspace. Trading robots do not offer a solution to generate profitable transactions instantly. Profitable long-term forex trading is more than just tactical analysis of forex trading and the use of trading robots. Have a special program that does all the work to make it look tempting. But this is how trading robots work. Trading robot sellers who prefer to see a decent trading robot. Such a system requires constant human adaptation and supervision. The general public who wants to use trading robots properly must know the risks and systems of trading robots and there is no guarantee that using a trading robot will be 100% profitable. It should be reiterated that the trading robot will make decisions based on the conditions that have occurred and the right decisions at that time. Thus, no foreign trade organizer dares to give absolute guarantees.

Jual Beli Mata Uang Sistem Trading Forex dalam Perspektif Hukum Islam

This research aims to find out and understand the laws of buying and selling currency online forex trading systems. The issues raised in this study are; First, how to buy and sell currency according to the Islamic view. Second, how to practice buying and selling currencies in an online forex trading system. Third, how to review Islamic law on the buying and selling of currencies in the forex trading system. The research method used is library research using normative and philosophical approaches and content analysis. The results of the study found that: First, buying and selling currencies in Islam is called currency exchange (al-Ṣarf), which is a type of muamalat allowed in Islam. Second, al-Ṣarf has several meanings that are almost the same, all indicating that the concept of exchange applies to the sale of two currencies in cash to each other even though the types are the same or different. Third, in the world of technology and communication in today's digital era, buying and selling currencies is often referred to as a forex trading system (foreign exchange), where the transaction model is divided into two ways, namely direct (offline) and indirect transactions (online). The law of offline forex trading is the law of disaster with two conditions, namely the handover directly in the assembly of the contract (should not be suspended) and if the type of currency is the same then it should not be overstated. However, the law of online forex trading is illegal because it leads to gambling, speculation, and buying and selling of garar, which can be seen from the transactions, types of goods, transaction actors, and systems that exist in online forex trading.

Predicting Foreign Exchange Using Digital Signal Processing

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

The future of work and uncertain labour alternatives as we live through the industrial age of possible singularity: Evidence from South Africa

This paper focused on uncovering the preparedness of the automobile labour force in embracing the outcome of technological domination in the motor industry in South Africa. Semi-structured in-depth interviews were initiated to generate data from three motor companies with purposively selected 30 participants. Findings revealed that auto employees who are not electrically inclined are self-encouraged to seek technical and electrical careers to secure a future in the automobile industry. These workers may also pursue careers in computer science. Many autoworkers have supplemented and stabilized their incomes through FOREX and Bitcoin mining trading. Simultaneously, these employees are receptive to changing careers in agriculture. Again, autoworkers prefer self-employment to the job insecurity associated with industrial positions. In general, motivation for upskilling for a future job in the automotive industry is low. Before the Covid-19 crisis, organizations were adopting new ways of doing business that tend to unready workers' readiness. This trend increased very steeply during the pandemic. Retraining and reskilling as steps for workers' readiness to face job automation are not outright answers that will lead to job security. Nonetheless, automobile workers have to treat their careers as businesses and invest in skills under the umbrella of non-automatable technical and non-technical job families.

Can altcoins become viable alternatives to African fiat currencies?

PurposeThe paper aims to examine the asymmetric response of three major altcoins to shocks in six African fiat currencies in a time-frequency space.Design/methodology/approachData are for the period 10th August 2015 to 2nd February 2019 at a daily frequency. The authors capture the time and frequency information in the return series of the currencies using the ensemble empirical mode decomposition. The authors implemented quantile regression and quantile-in-quantile regression on the decomposed series to test the response of altcoins to both positive and negative shocks in the fiat currencies across time to see if the altcoins are viable alternatives to African fiat currencies.FindingsThe outcome of the study suggests that altcoins behave differently from African fiat currencies and are viable alternative digital currencies and good hedges for African fiat currencies from the medium-term.Research limitations/implicationsPolicymakers in Africa and across the globe can follow this paper to mitigate currency crises by adopting altcoins as alternatives to fiat currencies. Forex traders can also mitigate trade risk by using altcoins to hedge dollar/African fiat currency exchange rate risk.Originality/valueThe research was conducted by the authors and has not been published in any journal.

Poverty on the rise: The impact of the COVID-19 lockdown on the informal sector of Gweru, Zimbabwe.

The informal sector in Zimbabwe employs more than 80 per cent of the population, whose livelihood strategies are under severe threat because of the COVID‐19 lockdown. This paper examines the effects of the lockdown on the informal sector in Gweru. Anchored within the legalist theory of informality, the paper analyses the response of government to the plight of the informal sector in Zimbabwe. A qualitative research design was applied and convenience sampling implemented to select 30 individuals whose livelihood depended on informal cross‐border trade, informal transport, forex trading, hairdressing, and street vending. Results reveal that despite many involved in the informal sector having lost their means of survival during the COVID‐19 lockdown, the government introduced additional restrictions on this sector, thus almost destroying it. In the absence of government assistance, many have adapted their operations, albeit through illegal activities. The study offers recommendations that may ensure the survival of the informal sector beyond the COVID‐19 pandemic. This is important, given that the informal sector is the largest contributor to household income and food security in Zimbabwe.

Optimasi Indikator Linear Weighted Moving Average Menggunakan Teknik Martingale sebagai Metode Peningkatan Profit Trading

Forex Trading is familiar to ordinary people as a way of investing, many of investor buying and selling transactions of foreign exchange or stocks using the MetaTrader software as a direct bridge to the forex or stock market. One method to find out the trends in the capital market is to use pre-installed indicator or directly listen to economic news. Linear Weighted Moving Average as one of the favorite indicators in forex or stock traders as it for individuals or bank managers, it is the most widely used for analyzing the direction of the capital market. The Linear Weighted Moving Average is not a holy grail whose are one hundred percent correct, it is because the volatile of forex and stock changes. The auto trading script (expert advisor) provided by Metatrader still has weaknesses due to incorrect predictions and resulting in reducing balance from investors' capital. The expectations from this research that martingale technique to optimize Linear Weighted Moving Average indicator in every forex transaction to increase profits in forex or stock trading.Keywords: Forex Trading, Martingale, Linear Weighted Moving Average

Perlindungan Konsumen Terhadap Penipuan yang dilakukan Broker Forex Ilegal

The phenomenon of Foreign Exchange (Forex) that runs in the investment sector and can help the development of Indonesia. Currently forex is a trend that is endemic and attracts the attention of many parties, both investors and the public in general. Foreign exchange or forex is a type of trade or transaction that trades the currency of a country against the currencies of other countries involving the main money markets in the world for 24 hours continuously, so in this case a legal protection is needed. The purpose of this research is to analyze legal protection in Forex transactions and legal sanctions imposed by the government on illegal Forex broker activities. This research uses a normative method that with a statutory approach. Sources of data used are primary data sources and secondary data sources. After primary legal data and secondary legal data are collected, the data will then be processed and analyzed using systematic legal data processing methods. The results showed that the alleged fraudulent investment fraud case under the guise of forex trading involved illegal brokers from the Guardian Capital Group (GCG) Asia, which harmed consumers. In line with that, the government issued a legal rule, namely Law No.8 of 1999 concerning Consumer Protection. The Consumer Protection Law that has been set by the government is the legal basis that is accurate and full of optimism in protecting consumer rights.

Comparison of Forecasting Using Fuzzy Time Series Chen Model and Lee Model to Foreign Exchange in EUR/USD and GBP/USD

Each country has a currency value that applies in its territory and can be adjusted to the value of the currency of other countries. In this adjustment, there is a difference in value when the transaction is made, and the difference in profit can be taken, usually referred to as foreign exchange (forex). In forex trading, analytical calculations are needed to plan a decision to get a significant difference so that the profits will increase. One analysis technique that can maximize the search for an enormous profit difference is by using the prediction method using the fuzzy time series. This method is a method that predicts future data based on historical data or past data. The fuzzy time series method has several models, including the Chen model and Lee model. In determining which model is the best, it is necessary to test using the AFER (average forecasting error rate) based on the level of accuracy of the smallest error value. By using historical data of EUR/USD and GBP/USD from 19 February 2019 to 19 February 2020, it is known that Lee’s fuzzy time series method predicts better accuracy because Chen’s model in foreign currency EUR/USD has a more significant error rate of 0.0018 (0.18%) or greater than Lee’s model which only has a value of 0.0016 (0.16%). Then the Chen model in foreign currency GBP/USD has an error rate of 0.00445 (0.445%) or greater than the Lee model, which only has an error rate of 0.00297 (0.297%).

Comparative analysis of naïve bayes and knn on prediction of forex price movements for gbp/usd currency at time frame daily

This study aims to analyze the comparison of the Naïve Bayes and kNN on the Prediction of Forex Price Movements for GBP / USD on Time Frame Daily. The data used is taken from the metatrader-4 application which is often used by forex traders when making transactions. There are 2,145 data rows consisting of the date, hour, open price, high, low, close, and transaction volume columns. From this data, a column for the target class is created with the name ‘result’. The result column is filled with increasing or decreasing values. The value of increase or decrease is obtained from the comparison of the previous closing price with the closing price of the next day. This study analyzes the results of the comparison of the data mining classification of algorithm between the Naïve Bayes algorithm and kNN. The 2,145 data were divided into 2 parts, namely 80% for training data and 20% for testing data. The analysis is done by comparing the precision, recall, and accuracy test results for each algorithm. The conclusion of this study is that the kNN algorithm is better than the Naïve Bayes algorithm in case of predicting forex price movements for GBP/USD currency at time frame daily.

Forex Data Analysis using Weka

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