classification of forex strategies
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Xe Currency Converter. These are the highest points the exchange rate has been at in the last 30 and day periods. These are the lowest points the exchange rate has been at in the last 30 and day periods. These are the average exchange rates of these two currencies for the last 30 and 90 days.

Classification of forex strategies list of the best forex brokers

Classification of forex strategies

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The portfolio theory appeared in by Harry Markowitz [ 57 ]. This theory aims at the rational constitution of a portfolio arbitrage between the gains and the risks. Indeed, the risk of a portfolio can be correctly measured by the variance of its profitability. The question is how to maximize the gains while minimizing the risks.

Due to the volatility of the Forex market, there are three types of portfolios: high-frequency traders, long-term investors, and corporations. This paper proposes a trading for high-frequency traders who speculate small intraweek price fluctuations [ 37 , 58 ]. In high-frequency trading strategy, we can separate between many types of traders [ 59 ]: i Scalpers: Forex Scalpers perform transactions of very short duration and take their gain very quickly, even when the market continues to evolve in the direction of their speculation.

Scalping requires a sufficient investment fund. The technical analysis of trends aims to determine when it is better to enter the market. For this, we consider that the Forex market follows a single direction over the long term. They use the monthly, weekly, and daily charts to accurately determine when a downturn may occur [ 60 ].

This analysis is based on the study of the economic and financial performance of a country in order to determine the real value of the market and the future evolution of its currency. This analysis is mainly based on economic information as well as important political events. Among indicators, we can quote the interest rate, the growth index, the inflation rate, the employment indicators, and the balance of trade. The observation and the evaluation of these indicators make it possible to know the state of the economy of a country.

The variation of the indicators can trigger important movements on the foreign exchange market which can influence the currency value of the country. With experience, traders combine those techniques to find a strategy to maximize their profit and they can include some unusual technique like the double-zero strategy. This strategy is entirely based on the phenomena of psychological values. This means that the majority of traders tend to simplify stock prices by taking a position on round values.

These values therefore very often become phenomena of support or resistance. In our previous works we adopted Evans et al. Once trained, we used the system predictions to manage the buy, hold, and sell actions: 1 If the system predicts a positive output, we buy. For each day, we use a time series composed of the 7 past days and the moving average of the last week and the last month. The second dataset is composed of a collection of Technical Indicators TI. A technical indicator is a value or a mathematical formula used to analyze stock market securities in order to predict price movements.

Figure 5 shows prediction outputs versus real outputs and Table 1 is related to the performance of results. Predicted values versus real values predicted values in red, real values in black ; for Random Forest regression using: tree and 8 variables tried for each split. The number of trees does not affect effectively the system performance while the best results were found for trees.

When analyzing the number of errors when Random Forest predicts an uptrend in the next day and in reality it was a downtrend and also if we take into consideration the degree of risks we found in Forex, it is very risky to consider regression results over time series as a unique input to decision making. In a second test, we used the first dataset composed of time series to train the Probit model in order to speculate next day values.

The second dataset composed of technical indicators is used to train Random Forest to predict global trend of the next 7 days; this choice comes after many experiments. The suitability of an estimated binary model can be evaluated by counting the number of true and false observations and by counting the number of observations equaling 1 or 0, for which the model assigns a correct predicted classification by treating any estimated probability above 0. For the Random Forest evaluation, we consider a week with positive evolution, if its number of days showing an uptrend is more than 4.

Tables 2 and 3 show classification results and Figure 6 shows a plotting example of predicted output versus real output using Probit regression. Predicted values versus real values predicted values in red, real values in black ; for Probit regression.

From Tables 1 and 2 we can notice that both classifiers can give us a clear idea about the market trends in different ways. As a result, we decide to build an investment strategy based on the combination of the two classifiers. In the next section, we are going to explain how we combined these two algorithms outputs to propose an efficient investment strategy.

To create an efficient strategy, we need to identify a personal risk profile, a realistic availability of time and resources, and a level of expectation during a trade. These characteristics of self-reflection can be identified by evaluating different strategies. In Forex investments, the leverage is any technique involving the use of borrowed funds in the purchase of an asset.

Online brokers offer their clients leverage. This tool actually allows the speculation with more money than the capital available in order to make the benefits more interesting. Currency exchange rate fluctuations are often very low. Without leverage, it would be very difficult to make profits, even with important investment capital.

The investment sequences are presented in Figure 7. First, we will invest only in weeks with positive trends and in each positive week we will check for next day positive trend to trade. This way, we can reduce the number of false investment rates. The strategy can be described as follows. The sequences of the proposed investment strategy. Step 1. For each currency we check for the week positive trend using the following rules: i Based on technical indicators, we check the market status for one of these situations [ 65 , 66 ]: a The oversold situation: it is a situation where the price of an asset has fallen sharply to a level below its real value.

It is a sign and probably the price should rebound. Probably it is an indication to sale. The indicator indicates an increase in the price of the asset, while the asset continues to fall. This can be analyzed by a possible reversal of the upward trend and by a future buy signal.

This is analyzed by a reversal of the downtrend and by a sales signal to come. Step 2. Step 3. We tested our investments strategy over 17 weeks and two years data from January to January to train our algorithms. For final results we calculate the cumulated gain over 17 weeks. The tables reveal that the proposed system demonstrates better results than Random Forest or Probit regression.

To validate our model, we choose to evaluate its efficiency over three currency pairs and for the three pairs the proposed strategy shows the best results. In addition, the proposed system needs less investment to make more benefit. The proposed model produces a quite promising profit with an average profit of 4.

We used only weeks with positive trends. The proposed system allows us to reduce the number of daily investment without losing profit opportunity. The true positive measures the proportion of actual positives that are correctly identified.

We should clarify that the previous results influenced the currency pair global trend during the next six months. This means it is related to macroeconomic and political situation. It was clear that we had a sideways trend. A sideways trend is a horizontal price movement. We also benefit from the fact that currency market is relatively stable and changes of more than even one percent are rare.

Simultaneously, an important issue that has not been mentioned so far is the trading cost. For each transaction, the currency market is a commission-free market. Instead of a commission, there is a pip spread. A pip spread is the difference between selling and buying price in the same moment. We consider a commission of 1 pip. From that fact and when using a leverage, we deduce that mostly some currency pairs resulted in modest gains and some resulted in excessive losses; an excessive gain is really rare.

Generally, Forex traders act emotionally with fear and hope. Through this work, we presented a trading strategy that allows putting emotions aside, avoiding trading errors greed, panic, or doubt and not missing the trading opportunities. Clearly our strategy gives inputs and outputs signals when the predefined rules coincide. In this moment, our system is triggering regardless of sentiment and performance of the last losing or winning position.

The results presented in this work show the benefits of our system compared to a simple use of regression or classification using Random Forest. Taking into account the obtained results, using a combination of classification and regression trees can be implemented as a successful algorithmic trading system. Our results indicate that further research on the consecutive combination of many algorithms for Forex portfolio management is useful. This combination helps traders to determine the moment when we can buy or sell the currency pair.

In Forex there are many currency pairs and many trading people and each pair is different from the other, and each person thinks in his own way. Finding the best trading strategy is really a complex preoccupation. In order to find an adequate solution, we have presented in this study a new strategy based on two data mining algorithms.

Our approach was to introduce a prediction and decision model that produces profitable intraweek investment strategy. The proposed strategy allows improving trading results in intraweek high-frequency trading. The results of the performed tests have demonstrated considerable advantage of our system versus a simple use of regression or classification using Random Forest.

Such results are promising for research on consecutive combination of many algorithms to Forex portfolio management. It is concluded that algorithmic trading based on combination of classification and Probit regression can be effective in improving the prediction accuracy. This combination helps to identify the good times to buy or to sell currency pairs.

The proposed system, based on this combination, helps traders to take profit from the many opportunities on the Forex market. The data used to support the findings of this study are available from the corresponding author upon request. This is an open access article distributed under the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article of the Year Award: Outstanding research contributions of , as selected by our Chief Editors. Read the winning articles. Journal overview. Special Issues. Academic Editor: Miin-Shen Yang. Received 18 Mar Revised 07 Jul Accepted 25 Jul Published 27 Aug Abstract In the Forex market, the price of the currencies increases and decreases rapidly based on many economic and political factors such as commercial balance, the growth index, the inflation rate, and the employment indicators.

Introduction The strong fluctuations in the financial markets make the stock market a risky area for investors. In this paper, we propose a secured investment strategy in two stages: Firstly, we have opted for a temporal approach without any prescriptive hypothesis on financial market trends.

Related Work Developments in the algorithm trading have improved recently. Trading Algorithms Approaches Trading strategy is an important financial method. Artificial Neural Networks Approaches Neural Networks are a key topic in several papers in order germane to trading systems. Genetic Algorithms Approaches Genetic algorithms GA , developed by Holland [ 39 ], are a type of optimization algorithms and they are used to find the maximum or minimum of a function.

Probit Model Our choice is the Probit model, which is a type of regression where the dependent variable can take only two values, for our case increased 1 or decreased 0 value of currencies [ 53 ]. The observed binary variable is defined by where the unobserved effect and the general error term. In the Probit model case, the cumulative distribution is a standard normal: The first equality states that is assumed to be strictly exogenous conditional on.

Random Forest algorithm: Input: description language; sample S Begin Initialize to the empty tree; the root is the current node Repeat Decide if the current node is terminal If the node is terminal then Assign a class Else Select a test and create the subtree End if Move to the next node unexplored if there is one Until you get a decision tree End Decision trees provide effective methods that work well in practice.

Figure 1. Figure 2. Figure 3. Figure 4. Investment strategy proposed in [ 7 ] for intraday foreign exchange. Number of Trees MSE 1. Table 1. Figure 5. Table 2. Classification results for next day speculation using Probit mode for days. Table 3. Classification of results for each week trend evolution results using Random Forest over 17 weeks.

Figure 6. Figure 7. Table 4. Table 5. Table 6. References R. View at: Google Scholar R. View at: Google Scholar L. Dubin and D. Baillie and D. Fusai and A. View at: MathSciNet P. Hooper and S. Yao, Y. Li, and C. El Shazly and H. Meese and K.

McNown and M. Baillie and R. Dooley and J. Moscinski and D. Taylor and H. Lui and D. Sahoo, K. Patra A, S. Mishra, and M. View at: Google Scholar C. Panda and V. Ni and H. Booth, E. Gerding, and F. Sorensen, K. Miller, and C. Boser, I. Guyon, and V. View at: Google Scholar J. Wang, X. Wu, and C. View at: Google Scholar H. He and X. View at: Google Scholar W.

Lv and R. Febrero-Bande, W. Kamruzzaman and A. Evans, K. Pappas, and F. Sezer, M. Ozbayoglu, and E. View at: MathSciNet H. Subramanian, S. Ramamoorthy, P. Stone, and B. Hirabayashi, C. Arahna, and H. View at: Google Scholar D. Garrido, J. Laviada, and A. Schoreels, B. Logan, and J. IAT , pp. View at: Google Scholar F. Tay and L. Henrique, V. Sobreiro, and H. Basak, S.

Kar, S. Saha, L. Unlike day traders who hold positions for less than one day, swing traders typically hold positions for several days, although sometimes as long as a few weeks. Because positions are held over a period of time, to capture short-term market moves, traders do not need to sit constantly monitoring the charts and their trades throughout the day.

This makes it a popular trading style for those who have other commitments such as a full-time job and would like to trade in their leisure time. However, it is still necessary to dedicate a few hours a day to analyse the markets. Swing traders as well as some day traders tend to use trading strategies such as trend trading, counter-trend trading, momentum and breakout trading.

Position traders are focused on long-term price movement, looking for maximum potential profits to be gained from major shifts in prices. As a result, trades generally span over a period of weeks, months or even years. Position traders tend to use weekly and monthly price charts to analyse and evaluate the markets, using a combination of technical indicators and fundamental analysis to identify potential entry and exit levels.

As position traders are not concerned with minor price fluctuations or pullbacks, their positions do not need to be monitored the same way as other trading strategies, instead occasionally monitoring to keep an eye on the major trend. This site uses cookies and will place cookies on your device. By continuing to use this website, you agree to our use of cookies.

You can view our cookie policy and read how to edit your settings here. Day trading For those that are not comfortable with the intensity of scalp trading, but still don't wish to hold positions overnight, day trading may suit. Swing trading Unlike day traders who hold positions for less than one day, swing traders typically hold positions for several days, although sometimes as long as a few weeks.

Position trading Position traders are focused on long-term price movement, looking for maximum potential profits to be gained from major shifts in prices. Read Next… How to place an order. Start trading in 3 easy steps Register Apply for a trading account. Deposit Fund your live trading account. Trade Start your trading journey.

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The screenshot shows that after entering on the signal candle, Take Profit is triggered on the third candle. It's a controversial question whether you should set a trailing stop. Due to the volatility of the pair, trailing stop may be triggered earlier than Take Profit. However, this is up to the trader. The conditions for opening a position on the next candle are similar.

The Stop Loss length here is nominal, as the trader has enough time on the daily interval to assess the situation by lowering the timeframe and using classic indicators. The probability of major movement in the opposite direction is small. Here we also close the position on the third candle by Take Profit with a profit of about points.

Positions are opened at the end of a strong movement towards a reversal, so the potential loss will be a consequence of the inertia of the price and it is better to wait it out. The DRP2 indicator is one of the leading forecasting tools. It analyzes the range of price fluctuations of the last candle, combines them with the High, Low, and Close values of the current candle and, based on the calculation results, draws the forecast location of the next candle a little to the right.

The final forecast range is drawn after the current candle closes. According to traders, the indicator is ambiguous, but it shows the best results on the daily interval. Day candles are associated with the sequence of operation of exchanges, strong and weak daily activity, etc. And while on short timeframes, different brokers sometimes have different opening and closing prices for candles on the same section, on daily intervals one can see clear patterns.

However, this is just one of the opinions to discuss in the comments. There are in fact no settings the formula is already built in the code , except for the number of bars in the history. You can view the history, but it is better to use the MT4 tester. If the range is less than 50 points i.

In this particular case, a suitable candle is shown by a vertical arrow. To the right of it, a range purple rectangle was formed using the indicator. Its center is indicated by a yellow dot for convenience. Since the closing price of the candle is closer to the lower edge, we place a pending Sell Limit order at the top of the range central horizontal red line. The top line is Stop Loss and the bottom one is Take Profit. Pay attention to the next black candle with a long body. Its upper shadow triggers the pending order in accordance with the forecast of the indicator and the position closes on the same candle.

If this candle did not reach Take Profit, we would close the position manually in full. The strategy may seem complex at first. Some time later, you will be able to very quickly identify the candlesticks where pending orders may work out with a moderate volatility. Based on the analysis of previous candles, it shows the volatility of the market.

This is the average parameter of the movement of the instrument per unit time. There is an interesting comparison in trader circles: ATR is the gas consumption of your car, which depends on the timeframe time on the road , type of engine trading asset and driving style speed of price change.

You can read more about it here. It has several versions. This is another version. The modification of the indicator whose template can be downloaded here is rather an arrow indicator. This strategy basically involves earning on a position reversal at the time of rebound off of the stop.

Since the example is reviewed based on historical data, we take one candle that has blue and red arrows as a basis. The levels for pending orders are indicated by yellow circles in the screenshot. You can also see that one of the orders Buy Limit was touched by the price. If a Stop Loss is triggered the price has gone in the opposite direction , we immediately reverse the position with a new fixed stop order at points.

As testing the indicator on history shows, the stop order is triggered only in case of a strong movement. In other words, if the first position turned out to be an error, when the price passes 30 points length of the stop order you will be able to say with confidence that this is not a correction, but rather a strong movement. Therefore, we simply open a position in this direction.

You can test the strategy on other pairs, choosing the stop order level depending on volatility. The daily timeframe is itself part of the strategy, as it eliminates local corrections and inertial price movement. In this strategy, you follow a proven path - use classic candlestick patterns, evaluating overbought and oversold zones using the Stochastic.

When you have found the optimal settings and obtained the skills of recognizing the pattern, you will get a good result. This strategy involves trading on a rollback after a strong movement deep correction or during a change in the main direction. After the growing candle closes, open a position.

It is also important that at this moment the Stochastic reverses and starts to leave its zone. We set a relatively small stop order — less than points. For example, points below the local low. We observe the candle on which the position was opened, we wait for it to close in growth.

You can add a trailing stop. The screenshot shows that on the first growing candle, the Stochastic is below the 20th level and its lines are turned up. On the candle indicated by the arrow pink rectangle , the Stochastic leaves the oversold zone, we open the position. After the falling candle closes, open a position.

Please note that in this case, the Stochastic has already moved out of the overbought zone on the signal candle. This is a leading signal, but it can be taken into account. You can test this for different pairs on historical data. The strategy will be interesting for novice traders. Although signals appear frequently, there is time to double-check them.

The conditions for opening trapositionsnsactions are basically unambiguous. There is controversy regarding the angle of exit of the Stochastic from overbought and oversold zones, which determines the signal strength. But after the signal candle closes in the opposite direction, the probability of error decreases sharply. To develop professional trading skills, you can add Fibonacci levels, indicators of resistance and support levels, and wave analysis. Long-term strategies can be applied to both the foreign exchange and the stock or commodity markets.

On larger timeframes, basic patterns are clearly visible, therefore, building strategies on them is considered a simpler task compared to intraday tactics. However, this is not for everybody. There is no rush, less emotion and excitement. In order to use the long-term strategies successfully, a trader requires patience and endurance, while many prefer speed trading and instant results. But who said you cannot combine scalping with long-term trading?

You can, and switching to daily charts will be a kind of relaxation. So go ahead, download the templates, test and share your opinion on the effectiveness of the proposed strategies in the comments. Good luck! Did you like my article? Ask me questions and comment below. I'll be glad to answer your questions and give necessary explanations. Home Blog Beginners Long-term Forex strategies: description and examples.

Long-term Forex strategies: description and examples. Rate this article:. Need to ask the author a question? Please, use the Comments section below. We recommend you to get acquainted with the theory of at least a dozen of strategies, test them on a demo account and try to develop something on your own. Someone offers their patterns of behavior in the foreign exchange market for free, and someone sells them for very good money. Indicators, stops, spreads and other do not always understand the termsand can easily confuse the novice investor.

We suggest after selecting a broker, to immediately pay attention to educational webinars, trainings and materials. If, after a deposit you have a personal advisor it is even better. Save my name, email, and website in this browser for the next time I comment. Ganz im Gegenteil, Karmen. Und ich glaube: ein Letssungstporiler, der nicht mit Druck umgehen kann, kann nicht erfolgreich sein.

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