In this paper, the application of the intuitionistic fuzzy rule-base evidential reasoning (IFRBER) to the development of a new optimized automated trading system (ATS) for the Forex market is ...presented. The used IFRBER approach represents the intuitionistic fuzzy sets in the framework of the evidence theory that allows us to avoid the revealed drawbacks of the IFS operational laws and enhance the overall performance of the IFRBER approach. It is shown that the IFRBER approach extracts from an analyzed system considerably more of useful for the decision making information than the usual fuzzy rule-base evidential reasoning (FRBER). Then based on the IFRBER, a new approach to make the justified transaction buying and selling decisions was proposed. This approach was used to develop a new optimized ATS for the Forex market. It is shown that due to the ability of a new approach to use more of useful information that present implicitly in the problem formulation than the proposed earlier usual fuzzy rule-base evidential reasoning method, the developed ATS provides a considerably more profitable and comfortable (with a higher percent of winning trades and with low risks) trading than the earlier developed ATS.
•Intuitionistic fuzzy rule-base evidential reasoning for generating trading decisions.•Automated trading system for the currency exchange (Forex) market.•Two-loops approach to the trading system optimization.•Fuzzy technical analysis indicators and their optimization.•Multiple criteria fuzzy optimization of the entire trading system.
The aim of this paper is to model a network and predict the exchange price of United States Dollar to Indian Rupees using daily exchange rates from Dec 18, 1991-Jul 19, 2007. In this paper, Water ...Cycle Optimization (WCA) technique has been used to optimize the Artificial Neural Network (ANN) for Foreign Exchange prediction on the basis of their predictive performance. The performance metrics considered for the evaluation of the models are root mean square error (RMSE) and mean absolute error (MAE). The tabulated outcome shows the efficiency of the model over other popular models.
This paper proposes a novel interconnected multilayer network framework based on variance decomposition and block aggregation technique, which can be further served as a tool of linking and measuring ...cross-market and within-market contagion. We apply it to quantifying connectedness among global stock and foreign exchange (forex) markets, and demonstrate that measuring volatility spillovers of both stock and forex markets simultaneously could support a more comprehensive view for financial risk contagion. We find that (i) stock markets transmit the larger spillovers to forex markets, (ii) the French stock market is the largest risk transmitter in multilayer networks, while some Asian stock markets and most forex markets are net risk receivers, and (iii) interconnected multilayer networks could signal the financial instability during the global financial crisis and the COVID-19 crisis. Our work provides a new perspective and method for studying the cross-market risk contagion.
•Interconnected multilayer networks linking 40 stock markets and 30 forex markets are built.•Stock markets transmit the largest spillovers to forex markets.•The French stock market is the largest risk transmitter in multilayer networks.•Most Asian stock markets and forex markets serve as net risk receivers.•Cross-market and within-market spillovers show different behaviors during GFC and COVID-19.
•High-dimensional volatility connectedness networks for 65 forex markets are constructed using the LASSO-VAR approach.•Global forex markets are highly interconnected compared with many other ...financial markets or assets.•Oil exports and forex regimes increase systemic importance of weak currencies in terms of volatility transmission.•USD and Euro are major volatility transmitters while most currencies including JPY and GBP are net volatility receivers.•Renminbi's volatility connectedness decreases significantly after China's exchange rate reforms.
We statically and dynamically measure total and directional volatility connectedness in global foreign exchange (forex) markets. We use the volatility spillover index and LASSO-VAR approaches in the variance decomposition framework to construct high-dimensional volatility connectedness network linking 65 major currencies. Empirical results indicate that the US dollar (USD) and Euro are major volatility transmitters while other currencies including Japanese yen and British pound are basically net volatility receivers. In volatility connectedness network, currencies tend to be clustered according to geographical distributions. Dynamically, total volatility connectedness reacts sensitively to changes in international economic fundamentals and increases during crisis periods. Directional volatility connectedness of Renminbi has decreased significantly since the reforms of the Chinese exchange rate regime (which shifts from a USD-pegged exchange rate regime to a regulated, managed floating exchange rate regime). Generally, oil exports, forex regimes and monetary policies are major factors driving volatility transmission across global forex markets.
Forex jest największym rynkiem finansowym na świecie. Szacowane dzienne obroty w kwietniu 2013 r. wynosiły około 5,3 biliona dolarów amerykańskich. Forex dzięki swoim cechom wyróżnia się na tle ...innych rynków i przyciąga miliony inwestorów na całym świecie. Jednocześnie należy podkreślić, że jest to bardzo trudny rynek i zanim przystąpi się do inwestowania, dobrze jest zdobyć jak najwięcej wiedzy
w tym zakresie. W artykule skupię się na istocie Forexu oraz odpowiem na pytanie, jak można uchronić się przed utratą pieniędzy, skutecznie zarządzając ryzykiem na tym rynku finansowym.
Forex is the largest financial market in the world. Estimated daily turnover in April 2013 was approximately $ 5.3 trillion. Forex is distinguished by its features in comparison with other markets and attracts millions of investors around the world. At the same time, it is a very difficult market, and before investing, it is good to get as much knowledge as possible. In this article I will focus on the essence of Forex
and will answer the question of how you can prevent yourself from losing money effectively managing the Forex market risk.
EUR/USD Q4 2021 TECHNICAL OUTLOOK Manunggal, Bagus
International Journal of Business, Law, and Education (Online),
09/2021, Volume:
2, Issue:
3
Journal Article
Peer reviewed
Open access
During the months of July to August, reports on the US economy were not very good. Many of the results did not match the expectations of economists. On the other hand, EUR exceeded expectations, but ...the trend is likely to decline. Meanwhile, in 2021, only Q4 remains. This study attempts to describe the opportunities in Q4 2021 and how to optimize profits on EUR/USD trading. Overall, EUR/USD tends to be bearish. However, with the unfavorable report on the US economy, the upward trend was quite significant throughout July-August. So there is a short sell opportunity, but by first testing the 1.1900 level. If the price is able to break through this level, EUR/USD will continue to be bullish. However, if the price is unable to penetrate that level, the price will have a bearish opportunity according to the major trend.
•A novel trading strategy based on the event-based concept of directional changes.•The trading strategy includes classification and regression algorithms.•Algorithm tested on 1000 datasets from 20 FX ...currency pairs.•Proposed approach is able to generate new and profitable trading strategies.•Proposed approach significantly outperforms all other benchmarks.
Most forecasting algorithms in financial markets use physical time for studying price movements, making the flow of time discontinuous. The use of physical time scale can make traders oblivious to significant activities in the market, which poses a risk. Directional changes (DC) is an alternative approach that uses event-based time to sample data. In this work, we propose a novel DC-based framework, which uses machine learning algorithms to predict when a trend will reverse. This allows traders to be in a position to take an action before this happens and thus increase their profitability. We combine our approach with a novel DC-based trading strategy and perform an in-depth investigation, by applying it to 10-min data from 20 foreign exchange markets over a 10-month period. The total number of tested datasets is 1,000, which allows us to argue that our results can be generalised and are widely applicable. We compare our results to ten benchmarks (both DC and non-DC based, such as technical analysis and buy-and-hold). Our findings show that our proposed approach is able to return a significantly higher profit, as well as reduced risk, and statistically outperform the other trading strategies in a number of different performance metrics.
Most cities in Iraq provide drinking water by purifying river water of physical and chemical contaminants. It uses energy from petroleum (electricity). As it seeks to get drinking water from the ...rivers with clean and renewable technologies and energy, the State of Iraq plans to use one of its most abundant resources to address the shortage of fresh water, namely hydropower. This study is based on the use of hydraulic energy (environmentally friendly) in the purification of water instead of the use of electricity. The use of electrical energy in water purification has a lot of problems, including the continuous interruption of the current and therefore stop the station from work and that it needs periodic maintenance and need to staff specialized for operation and maintenance, so it is expensive while the use of hydraulic energy will help to solve most of these problems. The possibility of replacing the rapid-mechanical mixing basin to the rapid hydraulic mixing, which operates according to the principle of forced forexes, where the study of the performance of the drinking water treatment plant in the eastern district of Al-Hamzah On the ADiwaniyah River in the southern province of ADiwaniyah, where concentrations of pollutants in the river are high in the study area. Where samples were taken from different locations for water in the drinking water treatment plant of Al-Hamzah for different treatment stages. Where the pollutants were examined in the laboratories of the Environment Directorate of ADiwaniyah and the laboratories of the Faculty of Engineering. All concentrations of physical and chemical contaminants were higher than the standards of Iraqi standards and the efficiency of treatment was not as low as 83%. This is due to the continuous interruption of electrical current and the failure of the mechanical equipment of the rapid mechanical mixing basin, which requires periodic maintenance and the continuation of the addition of high coagulant doses which cause high processing costs as well as the high concentration of aluminum used for coagulation. Therefore, a hydraulic mixing basin was used by conducting experiments in the fluid laboratory In the Faculty of Engineering using the Free and Forced Vortex, which has been developed and adjust suit the requirements of the study. There have been various experiments to obtain the best dimension of hydraulic mixer and best amount of coagulant to remove the turbidity and the best mixing speed and the best value of the pH, which achieved processing efficiency of up to 98.0%.
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•Develops a hybrid system with SVM and Evolutionary Computation.•The SVM categorizes the market into three different types.•The GA optimizes an investment strategy with dynamic ...approaches.•The algorithm invests in the Forex market with high leverage.
This work proposes a new approach, based on Genetic Algorithms and Support Vector Machine to trade in the forex market. In this work, a new algorithm capable of generating technical rules to make investments with a given amount of leverage depending on the certainty of the prediction is presented. To forecast those predictions, a combination of a Support Vector Machine (SVM) algorithm – to identify and classify the market in three different stages –, and a Dynamic Genetic Algorithm – to optimize trading rules in each type of market, is used. The optimization of the trading rules is based on several technical indicators. Forex data for the EUR/USD currency pair, in a timeframe between the years of 2003 and 2016, is used as training and test data. The proposed architecture for the machine learning system, as well as the implementation and study of the proposed system is described in detail. The use of an hybrid system, combining a SVM and a GA with dynamic approaches such as hyper-mutation and adaptability approaches by training three different GA’s for each type of market, provide a new approach for FOREX trading, where it is possible to classify trends using price sequences and therefore using the same classification for optimizing investment strategies with the most appropriate GA. Finally, the work shows promising results during the test period between the 2nd of January of 2015 until the 2nd of March of 2016, where the Return on Investment obtained is 83%.
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