Incorporating Technology: Innovating Your Forex Mining Strategy In The City – A comparative study of the accuracy of internal crown surfaces made of three types of lithium disilicate blocks.
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Incorporating Technology: Innovating Your Forex Mining Strategy In The City
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By Francesco Rundo Francesco Rundo Skillit Preprints.org Google Scholar 1 , * , Francesca Trenta Francesca Trenta Skillit Preprints. Google Scholar 2
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Received: 7 March 2019 / Revised: 23 April 2019 / Accepted: 27 April 2019 / Published: 29 April 2019
(This article is on the special issue of Advanced Bio-Inspired Mathematical Modeling and Machine Learning Algorithms for Quantitative Finance Applications)
Grid algorithmic trading has become very popular among traders because it exhibits several advantages over similar approaches. Basically, a grid trading strategy is a method that seeks to profit from the market movement of an underlying financial instrument by placing buy and sell orders at time intervals (grid distances). The main advantage of the grid trading strategy is the financial sustainability of the algorithm because it provides a strong way to reconcile losses on financial transactions, although this means a more complicated trading management algorithm. For these reasons, grid trading is certainly one of the best approaches to use in high frequency trading (HFT) strategies. Due to the high volatility of the financial markets, many investment funds and institutional traders choose HFT (High Frequency Trading) systems that allow them to achieve high performance due to the large number of financial transactions executed in a short period of time. time frame. The combination of HFT strategies using machine learning methods for financial time series forecasting has significantly improved the capabilities and overall performance of modern automated trading systems. With this in mind, the authors present an automated HFT grid trading system that works in the FOREX market. The performance of the proposed algorithm along with the reduced failure rate proved the effectiveness and robustness of the proposed approach.
Algorithmic trading is a new method of trading that involves the use of powerful automated algorithms known as trading robots or expert advisors, which help traders monitor specific market conditions to identify the best opportunities to buy or sell traded instruments. An order may or may not be opened according to the special rules made by the trading robots mentioned above. In particular, the trading robot may indicate a certain stop loss and/or a certain profit level to maximize its performance and minimize its loss or total loss. At the same time, a valid algorithmic transaction may decide to close an operation or control a grid of trades if such an approach is acceptable. In this context, the aim of this work is to demonstrate an innovative grid trading algorithm that can negotiate the complex OTC (over the counter) market. Basically, a grid trading strategy is a financial method in which trades of the same symbol are opened (all long or short) right after each other until the total balance of all operations (including open trades) is reached. The required profit. The distance between one trade and the next represents the grid radius, which can be defined statically or dynamically. The main advantage of the trading system is financial stability, because if the trading system determines the direction of the trend incorrectly, the opening of other positions in the same direction (grid orders) will average out the loss, on the contrary, the trend forecasting system will correctly determine the direction of the trend, opening many positions will allow you to quickly reach the desired profit goal. Obviously, the direct consequence of this strategy is related to the need to have enough funds in the securities account to cover the total financial exposure due to the number of transactions opened at the same time. Therefore, the financial sustainability of the aforementioned grid marketing approach should be related to the funds available in the business account. Reportedly, the introduced grid approach is used in OTC financial instruments. In the OTC market, especially if CFD (Contract for Difference) instruments are traded, the trades are not made in the official market because the broker-dealer becomes your trading partner [1]. One of the most traded instruments in the OTC market is the so-called FOREX (foreign exchange) market – also known as the FX market – where investors and speculators bid to convert a currency into cash, reflecting the volatility of the decentralized global financial market. Other [1]
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Before the explosion of online trading a few years ago, FOREX trading was the exclusive domain of large financial institutions. Nowadays, online trading platforms have opened up the market to all small investors who want to buy or sell currencies, especially CFD instruments that follow the real market currency exchange.
The main advantage of the FOREX OTC market is related to its high liquidity and practically uninterrupted international trading activity once it starts, every week, it closes on Sunday night and Friday night. same week. According to the current GMT adjustment, forex trading hours on major financial exchanges around the world such as the New York Stock Exchange take place between 01:00 pm and 10:00 pm GMT and at 10:00 pm GMT the Sydney Exchange comes online. Tokyo opens at 00:00 am and closes at 09:00 am GMT; And to complete the loop, London opens at 08:00 am and closes at 05:00 pm GMT. As a result, the FOREX market does not have a central place for trading and currency traders make predictions on global economic indicators and each FOREX broker offers a quote based on the current market price.
Although the foreign exchange market is very efficient, it offers higher profit opportunities compared to other financial markets because of the high volatility and unpredictability of currency exchange rates. In fact, currency markets are heavily influenced by monetary policies and central bank interventions, which lead to market imperfections that are difficult to model with accounting approaches and are difficult to predict accurately. For the reasons explained so far, the authors have designed a precise algorithm to solve the aforementioned FOREX market inefficiencies by exploiting the strengths of the Forex market rather than optimizing the overall performance of the trading system. It can be found in the most liquid of the market.
In Part 2, we will introduce the prior art of automated trading systems, particularly related to the FX market. An overview of the proposed pipeline will be discussed in Section 3. Section 4 presents the results, validation and benchmark comparison of the proposed approach. Finally, in Section 5, we present conclusions and future work.
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Many approaches have been developed in the scientific literature to predict stock market behavior. In particular, the science of heuristics, which took the name of technical analysis, was widely used to solve financial problems and create effective trading strategies. However, the results of applying technical analysis to financial markets are very poor in terms of performance and reduction, so recently this approach has been greatly improved by advanced financial mathematical modeling and the use of innovative and powerful machine learning algorithms. 2]
In recent years, neural networks have become popular in the field of technical analysis to predict the financial market. In particular, their ability to extract complex and interactive effects makes them very powerful for modeling informal economic relationships. Accordingly, there is much recent work on its use.
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