Trading de Forex ou de opções binárias: 01/10/23

A pip in forex 7

Pip definition.

Pip has a particular significance in relation to IG's platform. Here, we define pip in general investing and explain what it means to you when trading with IG.

A pip is a measurement of movement in forex trading, defined as the smallest move that a currency can make.

Usually, a pip is 0.01% of a single unit of currency, or the fourth digit after the decimal point. In EUR/USD, for instance, a move of 1.0001 to 1.0002 would be a single pip move.

This isn't always the case however. Some currencies (such as the yen) delineate a pip as 1% of a single unit of currency. In USD/JPY, a move of 120.01 to 120.02 would be a single-pip move.

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Aprender Forex 7

¿Qué son los Lotes en Forex y otros mercados? Cómo calcularlos y a qué cantidad equivalen.

Quizá uno de los conceptos más importantes en trading que debes aprender es qué es y a cuánto equivale un lote en Forex .

Los "lotes" o el “lotaje” en trading es uno de los elementos básicos en la gestión de tu riesgo, ya que es la cantidad que inviertes en el mercado. Por esto, es necesario manejar y controlar este concepto es básico en el desarrollo de cualquier estrategia de trading.

En primer lugar, es importante tener en cuenta que este artículo no pretende decirte cuáles son las mejores estrategias de trading para convertirte en un Trader de éxito. El objetivo es explicar de manera detallada la noción de qué es un lote en Forex.

¿Qué es un lote en Forex? - Definición de Lote.

Los lotes en Forex son la unidad de valor que mide la cantidad de una transacción. Es el tamaño de un contrato financiero. En otras palabras, en función de la cantidad de lotes que negocies, la cantidad invertida será superior o inferior .

Existen 3 tipos de lotes diferentes:

1️⃣ El lote estándar.

2️⃣ El mini lote.

3️⃣ El micro lote.

Estos 3 tipos de lotes en trading se definirán y detallarán en el resto de este artículo. Pero antes de eso, es importante tener en cuenta que la respuesta a la pregunta "a cuánto equivale 1 lote" es diferente dependiendo de si estás operando en Forex, un índice, una materia prima, criptomoneda o una acción.

Además, Admirals ha desarrollado una herramienta eficaz y eficiente, la "calculadora de lotes Forex". Esta herramienta te permitirá calcular de manera fácil y rápida a cuánto equivale 1 lote, con independencia del instrumento financiero y el mercado en el que operes. Más adelante la explicaremos.

Cuánto vale un lote en Forex.

¿Quieres saber cómo se calcula el lotaje en el mercado de divisas?

1 lote en Forex equivale a 100 000 unidades de la moneda base.

Cálculo del valor del lotaje en Forex = Lotes * Valor de contrato.

➲ EJEMPLO.

2 lotes en EUR/USD= 2 * 100 000 euros = 200 000 euros.

20 lotes en EUR/USD= 20 * 100 000 euros = 2 000 000 euros.

Por lo tanto, tal y cómo puedes apreciar, no existe una relación entre lotes y cotización en Forex, como pueda ocurrir con otros activos, son independientes.

¿Y cuál es la relación entre lotes de Forex y pips? Esto nos sirve para calcular las pérdidas y ganancias que tendríamos al operar en el mercado de divisas. Por ejemplo, si abrimos 2 lotes en EURUSD y hay una variación en el precio a nuestro favor de 2 pips, la ganancia que obtendríamos sería :

2 lotes * 100 000 euros * 0.0001 (cantidad a la que equivale un pip) * 2 (nº de pips) = 20 EUR.

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Calculadora de lotes Forex.

Para determinar el tamaño de la posición que quieres abrir, dirígete a la calculadora y descubre cuánto es un lote en Forex.

Esta calculadora es una herramienta indispensable para tu operativa y fácil de usar. ¡Veamos un ejemplo!

Elige el par de divisas que deseas operar (EUR/USD), luego añade el lotaje (1 lote), y haz clic en "Calcular".

Como puedes observar, en la calculadora aparecen los valores de lotaje mínimos y máximos :

Valor mínimo del lote = 0.01 Valor máximo del lote = 100.

Una vez que se realiza el cálculo, el tamaño de la posición aparece automáticamente en la sección "Resultados de CFD y Forex", en la línea "Tamaño del contrato".

→ Ya hemos calculado el tamaño de un lote en Forex: 100 000 euros.

3 tamaños principales del Lotaje en Forex.

✅ 1 lote Forex: término utilizado en las finanzas para designar un contrato en los mercados financieros. Esta noción determina el tamaño de la operación.

Veamos los distintos tipos de lotes en Forex en la siguiente tabla:

1.00 significa 1 lote estándar o 100 000 unidades de la moneda base.

0.10 significa 1 mini-lote o 10 000 unidades de la moneda base.

0.01 significa 1 micro-lote o 1000 unidades de la moneda base.

El lote estándar en el mercado de divisas.

➤ Un lote estándar es la medida de referencia en el mercado de divisas y corresponde a 100 000 unidades de la moneda base, con independencia del par de divisas negociado.

En general, pocos traders operan con 1 lote en Forex porque requiere una gran capitalización de su cuenta de trading o, en el caso de que lo hagan, necesitan tener un apalancamiento significativo.

Ejemplo.

1 lote EURUSD = 100 000 EUR 2 lotes GBPUSD = 200 000 GBP 1 lote USDJPY = 100 000 USD 3 lotes AUDCAD = 300 000 AUD.

Qué es un mini lote en Forex.

Los traders utilizan de forma más común un mini lote porque ofrece la posibilidad de obtener retornos atractivos sin la necesidad de una gran inversión inicial.

➤ Un mini lote en Forex corresponde a 10 000 unidades de la divisa base, o (0.1 lotes).

Ejemplo.

0.1 lotes EURUSD = 10 000 euros 0.3 lotes GBPUSD = 30 000 GBP 0.8 lotes USDJPY = 80 000 USD 0.5 lotes AUDCAD = 50 000 AUD.

Qué es un micro lote en Forex.

El micro lote es el producto más utilizado por los traders de Forex. Esto permite limitar los riesgos inherentes al trading tanto como sea posible, limitando el riesgo de pérdidas y de apalancamiento.

El micro lote es, por lo tanto, muy recomendable para los traders principiantes.

➤ Un micro lote en Forex equivale a 1000 unidades de la moneda base, o (0.01 lotes).

Ejemplo.

0.07 lote EURUSD = 7000 euros 0.01 lote GBPUSD = 1000 GBP 0.02 lote USD JPY = 2000 USD 0.04 lote AUDCAD = 4000 AUD.

Puedes comprobar el valor del lotaje en MetaTrader descárgatela de forma gratuita a través de la siguiente imagen. ¡Pero siempre que sean pruebas utiliza una cuenta demo!

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Cuánto vale un lote en índices.

Para los CFDs sobre índices, 1 lote representa 1 contrato de CFD. Cada fluctuación de un índice CFD causa la variación del punto de índice.

En otras palabras, si el precio del IBEX 35 va de 9377.70 puntos a 9387.70 puntos, diremos que el índice ha aumentado en 10 puntos.

Además, el valor de un punto del IBEX35 equivale a 1 euro.

Con toda esta información podemos determinar la fórmula para calcular 1 lote en índices:

Valor de 1 lote = cotización del precio del índice * 1 euro Tamaño del contrato = nº de lotes * cotización del precio del índice * 1 euro.

Por tanto, en los CFDs del mercado de valores, los tamaños de los lotes no están estandarizados y dependen del precio del activo subyacente .

Para conocer el valor del lote de tu contrato de CFDs sobre índices, dirígete a la calculadora de trading CFD de Admirals, es rápido y fácil.

La tabla a continuación muestra qué es un lote en CFD DAX30.

Tamaño del contrato.

Cotización: 5000 puntos.

Cotización: 7500 puntos.

Cotización: 10000 puntos.

Cotización: 12500 puntos.

Se debe realizar el mismo cálculo para calcular el tamaño del lote en el trading de otros índices bursátiles, como los CFDs sobre CAC40, DJI20, IBEX35, JP225, NQ 100, etc.

➡ En los CFD de acciones, un lote es igual a una acción y su valor es igual al precio de la acción.

Cuánto vale 1 lote en materias primas.

Para CFDs como el oro (GOLD), 1 lote corresponde a 1 contrato de CFD, o 100 onzas de oro, por lo tanto:

1 lote = cotización del oro * 100 onzas.

En el caso de que nuestra operación tuviera otro tamaño la fórmula sería:

Valor del contrato = nº de lotes * cotización del oro * 100 onzas.

Hay que tener en cuenta que el oro cotiza en dólares, por lo que habría que hacer el cambio a euros, dependiendo del tipo de cambio que hubiera en ese momento.

Cuánto vale 1 lote en Criptomonedas.

En función de la criptomoneda que estemos operando el tamaño del lote será diferente. Esto se puede comprobar en la pestaña de Especificaciones del Contrato, en la página web de Admirals.

Para contratos de CFD de criptomonedas como Bitcoin (BTCUSD), 1 lote de CFD corresponde a 1 contrato de CFD, es decir, 1 Bitcoin.

Valor de 1 lote = cotización del Bitcoin.

Sin embargo, por ejemplo en el Ripple, 1 lote equivale a 1000 Ripples, por lo que:

Valor de 1 lote = cotización del Ripple * 1000.

Cómo calcular el Lotaje en Forex y otros mercados - Conclusión.

Ahora que conoces cuánto es un lote en Forex, índices bursátiles, materias primas y criptomonedas, ten en cuenta que cuanto más aumenta el número del lotaje en una operación más aumenta el riesgo en el mercado. Al haber más volumen aumentan, tanto las posibles ganancias, como las pérdidas.

Es recomendable operar con cuidado, especialmente promoviendo el uso de mini lotes o micro lotes. La clave del éxito en los mercados radica principalmente en la administración del dinero y un uso con criterio de tu apalancamiento.

Esperamos que te haya resultado de ayuda nuestra explicación de lotes en Forex. Pero recuerda, realiza todas las pruebas que necesites con una cuenta demo gratuita. Podrás operar en condiciones reales del mercado pero sin ningún tipo de riesgo ¡los fondos son virtuales!

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A pip in forex 6

Pip value definition.

Pip value is the value attributed to a one-pip move in a forex trade.

The definition of a pip can vary between currencies, but it is usually equal to the fourth figure after the decimal point in a currency listing. In GBP/USD, for instance, 0.0001 is one pip. Because pips are tiny in value, forex trades in micro lots, mini lots and lots: 1,000, 10,000 or 100,000 units of currency.

To calculate pip value, divide one pip (usually 0.0001) by the current value of the currency pair. Then, multiply that figure by your lot size: the number of base units that you are trading.

Pip value example.

If GBP/USD is trading at 1.5000 and you are trading the equivalent of $100,000 then one pip would equal $6.6666, as:

(0.0001/1.5000) x 100,000 = 6.6666.

The value of a pip in dollars would be calculated as the value of one pip multiplied by the exchange rate (1.5000), in this instance $9.9999.

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A pip in forex 5

What is a Pip in Forex?

You’ve probably heard of the terms “ pips ,” “ points “, “ pipettes ,” and “ lots ” thrown around, and now we’re going to explain what they are and show you how their values are calculated.

Here is where we’re going to do a little math. Just a little bit.

Take your time with this information, as it is required knowledge for all forex traders.

Don’t even think about trading until you are comfortable with pip values and calculating profit and loss.

What the heck is a Pip?

The unit of measurement to express the change in value between two currencies is called a “ pip .”

If EUR/USD moves from 1.1050 to 1.1051, that .0001 USD rise in value is ONE PIP .

A pip is usually the last decimal place of a price quote.

Most pairs go out to 4 decimal places, but there are some exceptions like Japanese yen pairs (they go out to two decimal places).

For example, for EUR/USD, it is 0.0001 , and for USD/JPY, it is 0.01 .

What is a Pipette?

There are forex brokers that quote currency pairs beyond the standard “4 and 2” decimal places to “5 and 3” decimal places.

They are quoting FRACTIONAL PIPS , also called “points” or “pipettes.”

If the concept of a “pip” isn’t already confusing enough for the new forex trader, let’s try to make you even more confused and point out that a “point” or “pipette” or “fractional pip” is equal to a “ tenth of a pip “.

For instance, if GBP/USD moves from 1.3054 2 to 1.30543 , that .00001 USD move higher is ONE PIPETTE.

Here’s how fractional pips look like on a trading platform:

On trading platforms, the digit representing a tenth of a pip usually appears to the right of the two larger digits.

Here’s a pip “map” to help you to learn how to read pips…

How to Calculate the Value of a Pip.

As each currency has its own relative value, it’s necessary to calculate the value of a pip for that particular currency pair.

In the following example, we will use a quote with 4 decimal places.

For the purpose of better explaining the calculations, exchange rates will be expressed as a ratio (i.e., EUR/USD at 1.2500 will be written as “1 EUR / 1.2500 USD”)

Example #1: USD/CAD = 1.0200.

To be read as 1 USD to 1.0200 CAD (or 1 USD/1.0200 CAD)

(The value change in counter currency) times the exchange rate ratio = pip value (in terms of the base currency)

[.0001 CAD] x [1 USD/1.0200 CAD]

[(.0001 CAD ) / (1.0200 CAD )] x 1 USD = 0.00009804 USD per unit traded.

Using this example, if we traded 10,000 units of USD/CAD, then a one pip change to the exchange rate would be approximately a 0.98 USD change in the position value (10,000 units x 0.00009804 USD/unit).

We say “approximately” because as the exchange rate changes, so does the value of each pip move.

Example #2: GBP/JPY = 123.00.

Here’s another example using a currency pair with the Japanese Yen as the counter currency.

Notice that this currency pair only goes to two decimal places to measure a 1 pip change in value (most of the other currencies have four decimal places). In this case, a one pip move would be .01 JPY.

(The value change in counter currency) times the exchange rate ratio = pip value (in terms of the base currency)

[.01 JPY] x [1 GBP/123.00 JPY]

[(.01 JPY ) / (123.00 JPY )] x 1 GBP = 0.0000813 GBP.

So, when trading 10,000 units of GBP/JPY, each pip change in value is worth approximately 0.813 GBP.

How to Find the Pip Value in Your Trading Account’s Currency.

The final question to ask when figuring out the pip value of your position is, “What is the pip value in terms of my trading account’s currency?”

After all, it is a global market and not everyone has their account denominated in the same currency .

This means that the pip value will have to be translated to whatever currency our account may be traded in.

This calculation is probably the easiest of all; simply multiply/divide the “ found pip value ” by the exchange rate of your account currency and the currency in question.

If the “found pip value” currency is the same currency as the base currency in the exchange rate quote:

Using the GBP/JPY example above, let’s convert the found pip value of .813 GBP to the pip value in USD by using GBP/USD at 1.5590 as our exchange rate ratio.

If the currency you are converting to is the counter currency of the exchange rate, all you have to do is divide the “found pip value” by the corresponding exchange rate ratio:

.813 GBP per pip / (1 GBP/1.5590 USD)

[(.813 GBP ) / (1 GBP )] x (1.5590 USD) = 1.2674 USD per pip move.

So, for every .01 pip move in GBP/JPY, the value of a 10,000 unit position changes by approximately 1.27 USD.

If the currency you are converting to is the base currency of the conversion exchange rate ratio, then multiply the “found pip value” by the conversion exchange rate ratio.

Using our USD/CAD example above, we want to find the pip value of .98 USD in New Zealand Dollars. We’ll use .7900 as our conversion exchange rate ratio:

0.98 USD per pip X (1 NZD/.7900 USD)

[(0.98 USD ) / (.7900 USD )] x (1 NZD) = 1.2405 NZD per pip move.

For every .0001 pip move in USD/CAD from the example above, your 10,000 unit position changes in value by approximately 1.24 NZD.

Even though you’re now a math genius–at least with pip values–you’re probably rolling your eyes back and thinking, “Do I really need to work all this out?”

Well, the answer is a big fat NO. Nearly all forex brokers will work all this out for you automatically, but it’s always good for you to know how they work it out.

If your broker doesn’t happen to do this, don’t worry! You can use our Pip Value Calculator! Aren’t we awesome?!

In the next lesson, we will discuss how these seemingly insignificant amounts can add up.

A pip in forex 4

PIP (Forex)

A pip is a unit of measurement for price movements of currencies in foreign exchange (FX) markets. Pip stands for “percentage in point” or “price interest point.” It represents the smallest price variation that a particular exchange rate experiences based on typical FX market convention.

Currency pairs are generally traded on a pricing convention that includes four decimal places (called the “big figures” or “big figs”), with the pip representing the very last digit. Therefore, we can see that a pip is equivalent to 0.0001. It is also the same as a basis point (bps), which is another common unit of measurement for 1% of 1% percentages.

As an example, if the CAD/USD exchange rate were to move from 1.2014 to 1.2022, the change in value would represent one pip.

Summary.

A pip is a unit of measure for price movements in foreign exchange (“forex” or “FX”) markets. Most commonly in FX market convention, pricing includes four decimal places and a pip is the last digit, or 0.0001. Pips are very important in forex markets because price movements are constant and fast-paced, so pips are needed to track these movements to a fine degree of accuracy.

Why Use Pips.

Since FX markets are highly liquid with a high volume of transactions, the units of measurement for transactions are important. Furthermore, since units are typically quite small, a larger number of decimals are needed to capture variations in exchange rates to a greater degree of accuracy.

Pips cannot be used in every context though, and in an environment of hyperinflation in currencies, exchange rates become difficult to calculate with pips. Hyperinflation refers to a period where prices of goods and services are increasing excessively and in an out-of-control fashion. When FX movements become extremely high, pips lose their utility.

A strong example was recorded in Zimbabwe in the year 2008, where monthly inflation rates exceeded 79 billion percent in the month of November. When hyperinflation occurs, units of currency increase at an extraordinary rate which makes the small measurement of pips useless.

How are Pips Used in FX Markets?

An important measure in trading is the bid-ask spread. It represents the difference between what price a buyer pays at and what price a seller receives at.

In FX markets, the spread would be represented in the difference between these numbers would be the spread, measured in pips. This bid-ask spread also represents the profit that will be made by the FX broker of a transaction if they are able also to find a matching transaction on the other side.

For fast-moving markets, the big figs in the pricing of an FX price are largely omitted as the market makers assume that it is understood. As the market now moves towards electronic trading, it isn’t as much of an issue, even in volatile markets, but on voice trades, there is a higher chance of execution error, so experienced market practitioners will always confirm big figs after the trade to ensure both parties agree.

So, for example, if we look at an example EUR/USD quote of 1.1009/14, the bid/offer spread is 5 pips, or 5 basis points.

While the bid/offer 1.1009/14 in entirety, a spot FX trader via a voice trade may quote the pips as “09-14” and the counterparty is expected to know the rest.

More Resources.

Thank you for reading CFI’s guide to Pip. To keep learning and developing your knowledge base, please explore the additional relevant resources below:

Basis Point (BPS) Foreign Exchange Gain/Loss Hedging Forex Trading.

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A pip in forex 3

What Is a Pip in Forex? Using Pips.

If you are interested in Forex you have likely come across the term 'pip' or 'pips', a very common concept in Forex trading. But what is a pip in Forex ? This article will address what a pip is in forex trading , explaining the meaning of Forex pips and how useful a concept it is when trading Forex.

Table of Contents.

What is a Pip in Forex Trading? Pips Explained How Do You Calculate the Value of a Pip? An Example of a Pip in Trading What About Currencies That Are Not Quoted to Four Decimal Places? What Does Pip Stand For? MT4 pips - How To Count Pips in MT CFD Pips.

What is a Pip in Forex Trading? Pips Explained.

What is a pip in Forex trading ? A Forex pip is an incremental price movement, with a specific value dependent on the market in question. Put simply, it is a standard unit for measuring how much an exchange rate has changed in value.

Originally, a Forex pip was effectively the smallest increment in which an FX price would move, although with the advent of more precise methods of pricing, this original definition of a Forex pip no longer holds true.

Traditionally, FX prices were quoted to a set number of decimal places – most commonly four – and, originally, a Forex pip was a one-point movement in the final decimal place quoted.

The meaning of pips in Forex has changed slightly. Many brokers now quote Forex prices to an extra decimal place; however, this means that a pip in Forex is frequently no longer the final decimal place within a quote. It remains a standardised value across all brokers and platforms, making it very useful as a measure that allows traders to always communicate in the same terms without confusion.

Without such a specific unit of the Forex pip, there would be a risk of comparing apples to oranges, when talking in generic terms such as points or ticks. This is a basic answer to the question, 'what are pips in Forex?'.

How Do You Calculate the Value of a Pip?

The next step in answering the question, 'what are pips in Forex?' and understanding the meaning of pips, is to understand how to calculate Forex pips. For most currency pairs, one Forex pip is a movement in the fourth decimal place. The most notable exceptions are those pips in Forex pairs involving the Japanese Yen. For pairs involving the JPY, one Forex pip is a movement in the second decimal place. The Forex pip points table below shows Forex pips rates for some common currency pairs.

To further understand the meaning of Forex pips, let's look at an example of a Forex pip. Multiplying your position size by one pip will answer the question of how much a pip is worth. For example, let's say that you want to trade the EUR/USD currency pair, and you decide to purchase one lot.

One lot is worth 100,000 EUR. Here, one Forex pip is 0.0001 for EUR/USD. The currency value of one Forex pip for one lot is therefore 100,000 x 0.0001 = $10. Hence, we can calculate that the profit or loss will be $10 per pip for this forex pair.

Here's a simple example of a pip in Forex to illustrate the pips meaning:

Let's say you buy the EUR/USD at 1.16650, and later close your position by selling one lot at 1.16660. The difference between the two is:

1.16660 - 1.16650 = 0.00010.

In other words, the difference is 1 Forex pip. You will have made a profit of $10. If we work through these sample numbers from a different angle, we can further illustrate the answer to, 'what is a pip in Forex trading?'.

Forex pip value (1 lot)

Let's look a more detailed example of Forex pip in trading.

An Example of a Forex Pip in Trading.

Let's say that you opened your position at 1.16650, and you bought one contract. This is equivalent to buying 100,000 EUR. Notionally, you are selling dollars to purchase Euros. The value of the dollars that you are notionally selling is naturally dictated by the exchange rate.

EUR 100,000 x 1.16650 : USD/EUR = USD 116,650 You closed your position by selling one contract at 1.16660. Notionally, you are now selling the Euros and buying the Dollars. EUR 100,000 x 1.16660 : USD/EUR = USD 116,660 That means that you originally sold $166,650, and ended up with $166,660, for a profit of $10. From this, we can see that a one-pip movement in your favour made you $10.

Are you still struggling with the answer to the question, 'what are pips in Forex?' Don't worry. It may feel complicated at first, but this is natural. In fact, this trading Forex pips value is consistent across all FX pairs that are quoted to four decimal places.

A movement of one Forex pip in the exchange rate is worth 10 units of the quote currency (i.e. the second-named currency) if you are dealing in a size of one lot (which is always 100,000 units of the base currency - the first-named currency).

A move of 10 pips in Forex is worth 100 units of the quote currency. A move of 100 pips in Forex is worth 1,000 units of the quote currency, and so on.

If you would like to learn more about Forex quotes, you can do so by reading the following article: Understanding and Reading Forex Quotes.

What About Currencies That Are Not Quoted to Four Decimal Places?

The most notable currency here is the Japanese Yen. Currency pairs involving the yen were traditionally quoted to two decimal places, and Forex pips for such pairs are therefore governed by the second decimal place.

So, let's take a look at how Forex pips are calculated with the USD/JPY currency pair: If you sell one lot of the USD/JPY, a downward move of one FX pip in the price will enable you to earn 1,000 yen.

Let's work through an example of such a pip in Forex to see why:

The USD/JPY Currency Forex Pip Example.

Suppose that you sell two lots of the USD/JPY currency pair at 113.607. One lot of the USD/JPY is worth 100,000 USD. You are therefore selling 2 x 100,000 USD = USD 200,000 in order to purchase: 2 x 100,000 x 113.607 = 22,721,400 JPY. Let's say the price moves against you and you decide to cut your losses. You close out at 114.107. One Forex pip for the USD/JPY is a movement in the second decimal place. The price has moved against you by 0.50, or 50 pips. You proceeded to close your position by purchasing 2 lots of the USD/JPY at 114.107. To buy back $200,000 of USD at this rate costs: 2 x 100,000 x 114.107 = JPY 22,821,400. This is 100,000 JPY more than your original sale of Dollars gave you, so you have a shortfall of 100,000 JPY. Losing 100,000 JPY for a 50-pip movement means that for each Forex pip you lost 100,000/50 = 2,000 JPY. Since you sold 2 lots, this is a pip value of 1,000 per lot.

If your account is denominated in a currency that is different to the quote currency, it will affect the Forex pip value. You can use our Trading Calculator to calculate forex pip values and profits with ease. This information above covers most of the basics of the answer to, 'what is a pip in Forex trading?'.

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What Does Pip in Forex Stand For?

Now that we've answered the question, 'what is a pip in Forex?', let's answer another question, 'what is the meaning of pip ?'. Some say that the "pip" meaning in Forex originally stemmed from Percentage-In-Point, but this may be a case of false etymology. Others claim it stands for Price Interest Point. Whatever the meaning of pip, they allow currency traders to discuss small changes in exchange rates in readily understandable terms.

This is similar to how its cousin – the basis point (or bip) – allows easier discussion of small changes in interest rates. This provides us with the most basic answer to what is a pip in currency trading – it is much easier to say ''cable has risen 55 pips'', for example, than to say ''it's increased by 0.0055''.

Let's take a look at how to read pips in MT4 and how FX prices appear in MetaTrader 4 (MT4) to further answer the question 'what is a pip in Forex trading?'.

MT4 pips - How To Count Forex Pips in MT.

The image below shows an 'Order' screen for the GBP/USD currency pair in MetaTrader 4:

Depicted: MetaTrader 4 platform - pricing from Admirals - GBP/USD order ticket - Disclaimer: Charts for financial instruments in this article are for illustrative purposes and does not constitute trading advice or a solicitation to buy or sell any financial instrument provided by Admirals (CFDs, ETFs, Shares). Past performance is not necessarily an indication of future performance.

The quote shown in the image is: 1.31190/1.31208. We can see that the figures for the last decimal place are smaller than the other numbers. This is to show that these are fractional Forex pips. The difference between the bid and the offer is 1.8 pips. If you instantaneously bought and sold at this quote, the pip cost would be 1.8. If you look at the screenshot below of a different order ticket, you can see that the selected 'Type' is 'Modify Order':

When learning how to read pips in MT4 , note that the Modify Order part of the window contains drop-down menus that allow you to quickly select levels that are a certain number of 'points' away. There is, therefore, an important distinction to be made between points and pips. The points in these drop-downs are referring to the fifth decimal place, in other words, one-tenth of a pip.

If you select 50 points here, you will be choosing an order level that is just 5 Forex pips away. A really good way to familiarise yourself with pips in Forex prices is to test the MT4 platform using a Demo Trading Account. This account allows you to view and trade on live market prices but with zero risk, because you are only trading with virtual funds, so your capital is not at risk. You can click the banner below to sign up for your FREE demo account now:

CFD Pips in Forex.

So far, we've focused on the question, 'what are pips in Forex?'. If you are interested in trading shares, you may be wondering if there is such a thing as a pip in trading stocks. There is no term 'pips' in trading shares because this market uses other terms for communicating price changes: 'pence' and 'cents'.

For example, the image below shows an order ticket for IBM:

Depicted: MetaTrader 4 platform - pricing from Admirals - IBM order ticket - Disclaimer: Charts for financial instruments in this article are for illustrative purposes and does not constitute trading advice or a solicitation to buy or sell any financial instrument provided by Admirals (CFDs, ETFs, Shares). Past performance is not necessarily an indication of future performance.

The whole numbers in the quote represent the price in USD and the decimal numbers represent cents. This is readily understood and familiar for most traders.

Therefore, there is no need to introduce any other terms, such as pips in Forex, though sometimes market lingo may include a generic term such as 'tick', to represent a movement of the smallest increment possible – in this case, one cent. This is similar to a pip in Forex.

Whatever you are planning to trade, whether it's CFDs in Forex, or CFDs on shares, you will want to be using the best trading platform available. This is why you should try out using the MetaTrader Supreme Edition (MTSE) plugin for MetaTrader 4 and MetaTrader 5. MTSE is a cutting-edge plugin that offers a much wider selection of indicators and trading tools compared to the standard versions.

Experience benefits such as the addition of the Market Heat Map, so you can compare various currency pairs to see which ones might be lucrative investments, access real-time trading data, and so much more. Click the banner below to start your FREE download of the MTSE plugin!

Final Words.

Now that you understand the pip meaning and have an answer to the question of 'what a pip is in Forex trading?', we wish you luck in your Forex journey!

Understanding this unit of measurement for changes in FX rates is an essential step on the path to becoming a proficient trader. If you enjoyed this discussion about the meaning of pips in Forex and what are pips in Forex, why not take a look at our article on the best currency pairs to trade in Forex?

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A pip in forex 2

What Are Pips in Forex Trading and What Is Their Value?

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and behavioral finance. Adam received his master's in economics from The New School for Social Research and his Ph.D. from the University of Wisconsin-Madison in sociology. He is a CFA charterholder as well as holding FINRA Series 7, 55 & 63 licenses. He currently researches and teaches economic sociology and the social studies of finance at the Hebrew University in Jerusalem.

Updated May 25, 2022.

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Gordon Scott has been an active investor and technical analyst of securities, futures, forex, and penny stocks for 20+ years. He is a member of the Investopedia Financial Review Board and the co-author of Investing to Win. Gordon is a Chartered Market Technician (CMT). He is also a member of CMT Association.

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What Is a Pip?

"Pip" is an acronym for percentage in point or price interest point. A pip is the smallest whole unit price move that an exchange rate can make, based on forex market convention.

Most currency pairs are priced out to four decimal places and a single pip is in the last (fourth) decimal place. A pip is thus equivalent to 1/100 of 1% or one basis point.

For example, the smallest whole unit move the USD/CAD currency pair can make is $0.0001 or one basis point.

Key Takeaways.

Forex currency pairs are quoted in terms of pips, short for percentage in points. In practical terms, a pip is one-hundredth of one percent (1/100 x .01) and appears in the fourth decimal place (0.0001). A pip equals one basis point. The bid-ask spread of a forex quote is measured in pips. The Japanese yen is an exception because its exchange rate extends only two decimal places past the decimal point, not four.

What Is A Pip?

Understanding Pips.

A pip is a basic concept of foreign exchange (forex). Forex traders buy and sell a currency whose value is expressed in relation to another currency. Quotes for these forex pairs appear as bid and ask spreads that are accurate to four decimal places.

Movement in the exchange rate is measured by pips. Since most currency pairs are quoted to a maximum of four decimal places, the smallest whole unit change for these pairs is one pip.

Calculating Pip Value.

The value of a pip depends on the currency pair, the exchange rate and the trade value. When your forex account is funded with U.S. dollars and USD is the second of the pair (or the quote currency), such as with the EUR/USD pair, the pip is fixed at .0001.

In this case, the value of one pip is calculated by multiplying the trade value (or lot size) by 0.0001. So, for the EUR/USD pair, multiply a trade value of, say, 10,000 euros by .0001. The pip value is $1. If you bought 10,000 euros against the dollar at 1.0801 and sold at 1.0811, you'd make a profit of 10 pips or $10.

On the other hand, when the USD is the first of the pair (or the base currency), such as with the USD/CAD pair, the pip value also involves the exchange rate. Divide the size of a pip by the exchange rate and then multiply by the trade value.

For example, .0001 divided by a USD/CAD exchange rate of 1.2829 and then multiplied by a standard lot size of 100,000 results in a pip value of $7.79. If you bought 100,000 USD against the Canadian dollar at 1.2829 and sold at 1.2830, you'd make a profit of 1 pip or $7.79.

Japanese yen (JPY) pairs are quoted with 2 decimal places, marking a notable exception to the four decimal place rule. For currency pairs such as the EUR/JPY and USD/JPY, the value of a pip is 1/100 divided by the exchange rate. For example, if the EUR/JPY is quoted as 132.62, one pip is 1/100 ÷ 132.62 = 0.0000754. With a lot size of 100,000 euros, the value of one pip (in USD) would be $7.54.

Fractional pips are smaller than pips and, thus, a more precise measurement. They appear as a superscript numeral at the end of a quoted exchange rate. A fractional pip is 1/10 of a pip.

Pips and Profitability.

The movement of the exchange rate of a currency pair determines whether a trader makes a profit or loss at the end of the day. A trader who buys the EUR/USD will profit if the euro increases in value relative to the U.S. dollar. If the trader bought the euro for 1.1835 and exited the trade at 1.1901, they would make 66 pips on the trade (1.1901 - 1.1835).

Now, let's consider a trader who buys the Japanese Yen by selling the USD/JPY pair at 112.06. The trader loses 3 pips on the trade if they close out the position at 112.09. They profit by 5 pips if they close it out at 112.01.

While the difference may look small, in the multi-trillion dollar foreign exchange market, gains and losses can add up quickly. For example, on a $10 million position that closed at 112.01, the trader would make ¥500,000. In U.S. dollars, that's $4,463.89 ( ¥500,000/112.01).

Real-World Examples of Pip.

A combination of hyperinflation and devaluation can push exchange rates to the point where they become unmanageable. In addition to impacting consumers who are forced to carry large amounts of cash, this can make trading unmanageable and the concept of a pip loses meaning.

A well-known historical example of this took place in Germany's Weimar Republic, when the exchange rate collapsed from its pre-World War I level of 4.2 marks per dollar to 4.2 trillion marks per dollar in November 1923.

Another case in point is the Turkish lira, which reached a level of 1.6 million per dollar in 2001, which many trading systems could not accommodate. The government eliminated six zeros from the exchange rate and renamed it the new Turkish lira. As of January 2021, the average exchange rate stands at a more reasonable 7.3 lira per dollar.

What's a Pip?

A pip is the smallest whole unit measurement of the difference between the bid and ask spread in a foreign exchange quote. A pip equals 1/100 of 1%, or .0001. Thus, the forex quote extends out to four decimal places. Smaller price increments are measured by fractional pips. A fractional pip is 1/10 of a pip.

How Are Pips Used?

They are a part of a currency pair's exchange rate market quote. Pips represent the change in the quote and value of a position in the market you may have taken. Say, hypothetically, you bought a currency pair for 1.1356 and sold it for 1.1360. You made 4 pips on your trade. You'd have to then calculate the value of a single pip and multiply that by your lot size for the dollar value of your profit.

Does the Japanese Yen Forex Rate Use Pips?

Yes, it does. However, the yen is an exception. A quote for the yen normally extends two decimal places past the decimal point. So, a single whole unit pip is .01 rather than the .0001 for other currency pairs.

Aprender Forex 6

NFP and Forex: What is NFP and How to Trade It?

The non-farm payroll (NFP) figure is a key economic indicator for the United States economy. It represents the number of jobs added, excluding farm employees, government employees, private household employees and employees of nonprofit organizations.

NFP releases generally cause large movements in the forex market . The NFP data is normally released on the first Friday of every month at 8:30 AM ET. This article will explain the role NFPs play in economics and how to apply NFP release data to a forex trading strategy.

How does the NFP affect forex?

NFP data is important because it is released monthly, making it a very good indicator of the current state of the economy. The data is released by the Bureau of Labor Statistics and the next release can be found on an economic calendar .

Employment is a very important indicator to the Federal Reserve Bank. When unemployment is high, policy makers tend to have an expansionary monetary policy (stimulatory, with low interest rates). The goal of an expansionary monetary policy is to increase economic output and increase employment.

So, if the unemployment rate is higher than usual, the economy is thought to be running below its potential and policy makers will try to stimulate it. A stimulatory monetary policy entails lower interest rates and reduces demand for the Dollar (money flows out of a low yielding currency). To learn exactly how this works, see our article on how interest rates effect forex .

The chart below shows how volatile forex can be after an NFP release. The expected NFP results for March 8, 2022 were 180k (job additions), the actual result disappointed with only 20k jobs being added. As a result, the Dollar Index (DXY) depreciated in value and volatility increased.

Forex traders must be wary of data releases like the NFP. Traders could get stopped-out due to the sudden increase in volatility. When volatility increases, spreads do too, and increased spreads can lead to margin calls .

Which currency pairs are most affected by NFP.

The NFP data is an indicator of American employment, so your currency pairs that include the US Dollar ( EUR/USD , USD/JPY , GBP/USD , AUD/USD , USD/CHF and others) are most affected by the data release.

Other currency pairs also display an increase in volatility when the NFP releases, and traders must be aware of this as well, because they may get stopped out. The chart below shows the CAD/JPY during the NFP data release. As you can see, the increase in volatility could stop a trader out of their position even though they are not trading a currency pair linked to the US Dollar.

Non-farm payroll release dates.

The Bureau of Labor statistics normally releases the NFP data on the first Friday of each month at 8:30 AM ET. The release dates can be found on the Bureau of Labor Statistic’s website .

Due to the volatile nature of the NFP release, we recommend using a pull-back strategy rather than a breakout strategy. Using a pullback strategy, traders should wait for the currency pair to retrace before entering a trade.

Using the same example as above (NFP results 20k vs 180k expected) we expect the US Dollar to depreciate. In the example below, we use the EUR/USD . Because the NFP data came out worse than expected, we forecast the EUR/USD to appreciate.

A pip in forex 1

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A pip in forex

Pips in forex.

In trading, a ‘pip’ is a very small price movement. The term is short for ‘percentage in point’. A pip is essentially the smallest move that a currency could make in the forex market and it is an important unit of measurement in currency trading.

Traders use pips to measure price movements in currencies. Determining the number of pips in a certain price movement is a straightforward process, although it depends on the forex pair being traded.

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What are ‘pips’ in forex trading?

In forex trading , the smallest price change is the last decimal point. Given that most major currency pairs, such as those involving USD, EUR and GBP, are priced to four decimal places, a pip in this scenario is a price movement of 0.0001. For example, if GBP/USD moved from 1.4000 to 1.4001, it has moved by one pip. Comparatively, currency pairs using the Japanese yen (JPY) are only quoted to two decimal places. In this case, a pip is a price movement of 0.01. For instance, if GBP/JPY moved from 150.00 to 150.05, it has moved by five pips.

You can trade on the forex market through financial instruments such as spread betting and trading CFDs (contracts for difference). This involves opening positions based on the prediction that one currency will strengthen against another. For example, for every pip or point that a currency’s value varies, this will result in profits or losses for the trader, depending on the direction that the market heads.

Pips and pipettes.

To view an even tighter spread, currency pairs can be given in fractional pips, or ‘pipettes’, where the decimal place is at 5 places, or 3 places if dealing JPY. A pipette is therefore equal to one tenth of a pip.

EUR/USD example:

EUR/USD = 1.607 3 1 – 0.0003 is the pip.

EUR/USD = 1.6073 1 – 0.00001 is the pipette.

The fourth decimal place is the pip, and the fifth decimal place is the pipette.

How to use pips in forex trading.

If a trader enters a long position on GBP/USD at 1.5000 and it moves to 1.5040, the price has moved 40 pips in the trader’s favour, potentially leading to a profit if the trade is closed. On the other hand, if the trader goes long on GBP/USD at 1.5000 and the exchange rate falls to 1.4960, the price has moved 40 pips against the trader, potentially leading to a loss on the trade if it is closed.

Similarly, if a trader goes long on GBP/JPY at 145.00 and it moves to 145.75, the price has moved 75 pips in the trader’s favour. If the exchange rate goes against the trader, and GBP/JPY falls to 144.25, the price would have moved 75 pips against the trader.

As well as measuring price movements and profits and losses, pips are also useful for managing risk in forex trading and for calculating the appropriate amount of leverage to use. For example, a trader can use a stop-loss order to set the maximum amount he is willing to lose in terms of pips on a trade. Having a stop-loss in place will help to limit losses if the currency pair were to move in the wrong direction.

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Forex position size calculator.

Pips can be used for the calculation of position size. If a trader’s combined position sizes are too large and they experience a number of losses, their capital could be wiped out. Therefore, trading with an appropriate position size is essential.

There are several steps involved in calculating position size:

A trader must determine the amount of capital they are willing to risk per trade. If this is 1% per trade, they could make a minimum of 100 trades before their capital is wiped out. If the trader’s account has a balance of $5,000 and they are willing to risk 1% per trade, this equates to $50 per trade. Traders can determine a stop-loss in pips. For example, if a trader goes long on EUR/USD at 1.3600, they could place a stop-loss at 1.3550. This stop-loss equates to 50 pips. The last step depends on what lot size is being traded. A standard lot refers to 100,000 units of base currency and equates to $10 per pip movement. A mini lot is 10,000 units of base currency and equates to $1 per pip movement. A micro lot is 1,000 units of base currency and equates to $0.10 per pip movement.

If the trader risks 1% of his $5,000 balance per trade for a micro lot ($0.10 per pip movement), the position size would be $50 / (50 pips x $0.10) = 10. Therefore, the trader’s position size would be 10 micro lots.

Pip value calculator.

How much profit or loss a pip of movement produces is dependent on the value of each pip. In order to learn how to work out pip value, we need to know the following three things: the currency pair being traded, the trade amount, and the spot price.

Pip value formula.

The formula to calculate the value of a pip for a four-decimal currency pair is:

Pip value = (0.0001 x trade amount) / spot price.

How to calculate pips.

Example 1:

Let’s say a trader places a $100,000 long trade on USD/CAD when it’s trading at 1.0548.

The value of USD/CAD rises to 1.0568. In this instance, one pip is a movement of 0.0001, so the trader has made a profit of 20 pips (1.0568 – 1.0548 = 0.0020 which is the equivalent of 20 pips).

The pip value in USD is (0.0001 x 100,000) / 1.0568 = $9.46.

To calculate the profit or loss on the trade, we multiply the number of pips gained by the value of each pip.

In this example, the trader made a profit of 20 x $9.46 = $189.20.

Example 2:

Let’s say the trader places a $10,000 long trade on USD/CAD when it’s trading at 1.0570.

The value of USD/CAD falls to 1.0540. In this instance, one pip is a movement of 0.0001, so the trader has made a loss of 30 pips (1.0570 – 1.0540 = 0.0030 which is the equivalent of 30 pips).

The pip value in USD is (0.0001 x 10,000) / 1.0540 = $0.94.

In this example, the trader made a loss of 30 x $0.94 = $28.20.

Pip value indicator on MT4.

Pip values can be difficult and take time to calculate, while some traders would rather be focusing on perfecting their forex trading strategy. This is why they have developed a pip value indicator for MetaTrader 4, an internationally recognised trading platform that we host via our own platform. A wide range of MT4 indicators are available to download separately to your account.

Forex pips can be calculated using the formula above and displayed on our own trading platform, Next Generation, in the form of forex price charts and graphs. These can be customised with our drawing tools. We have a wide range of technical indicators to help you with your forex trading strategy.

What causes pip values to change?

The base value of a trader’s account will determine the pip value of many different currency pairs. For a USD-denominated account, which is common for the most traded currency pairs, if the currency pair has USD as the second (quote) currency, the pip value will always be $10 on a standard lot, $1 on a mini lot and $0.10 on a micro lot.

Pip values would only change if USD was either the first (base) currency in the currency pair, or not involved in the pair, and if the value of USD moved significantly by more than 10% in either direction.

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Summary: pips in trading.

In the forex market, traders use pips to measure price movements and profit and loss. Pips also play an important role in risk management. For example, a trader can identify a stop-loss for a trade in terms of pips, which can limit the potential losses on a losing trade. Pips can help forex traders to calculate the most appropriate position size in order to ensure that they are not taking excessive risks by opening positions that are too large with the potential for great losses. Learn more about developing your own forex trading strategy, such as swing trading, day trading and forex scalping.

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Atual forex 9

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 2022, and subsequently evaluated on unseen samples from Jan 2022 to Dec 2022. The system performance is promising under ideal conditions. The ensemble model achieved about 10% nett P&L with −0.7% drawdown level based on 2022 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.

1. Introduction.

Being able to make a profit consistently in Forex trading continues to remain a challenging endeavour, especially given the numerous factors that can influence price movements [1]. To be successful, traders have to not only predict the market signals correctly, but also perform risk management to mitigate their losses in the event the market moves against them [2]. As such, there has been increasing interest in developing automated system-driven solutions to assist traders in making informed decisions on the course of action they should take given the circumstances [3]. However, these solutions tend to be rule-based or require the inputs of subject matter experts (SMEs) to develop the knowledge database for the system [4]. This approach would negatively impact the performance of the system in the long run given the dynamic nature of the market, as well as making it cumbersome to update [5].

Most recently, newer innovations have introduced more intelligent approaches through the use of advanced technologies, such as ML algorithms [6]. Unlike the traditional rule-based approach, machine learning is able to analyze the Forex data and extract useful information from it to help traders make a decision [7]. Given the explosion of data and how it is becoming more readily available nowadays, this has been a game-changer in the field of Forex trading with its fast-paced automated trading since it requires little human intervention and provides accurate analysis, forecasting, and timely execution of the trades [8].

This study proposes a complete end-to-end system solution, coined as AlgoML, that incorporates both trade decisions as well as a risk and cash management strategy. The system is able to automatically extract data for an identified Forex pair, predict the expected market signal for the next day and execute the most optimal trade decided by the integrated risk and cash management strategy. The system incorporates several SOTA reinforcement learning, supervised learning, and optimized conventional strategies into a collective ensemble model to obtain the predicted market signal. The ensemble model gathers the output predicted signal of each strategy to give an overall final prediction. The risk and cash management strategy within the system helps to mitigate risk during the trade execution phase. In addition, the system is designed such that it makes it easier to train and back test strategies to observe the performance before actual deployment.

The paper is structured as follows: Section 2 explores related works on prediction based models for the Forex market. Section 3 presents the high-level architecture of the system and its individual modules. Section 4 elaborates on the ML model designs used in the system. Section 5 provides the results on the performance of the system.

2. Related Works.

Over the past decade, there have been a number of works in the literature proposing various prediction-based models for trading in the Forex market. One of the most popular time-series forecasting models was Box and Jenkins’ auto-regressive integrated moving average (ARIMA) [3], which is still explored by other researchers for Forex prediction [9,10]. However, it is noted that ARIMA is a general univariate model and it is developed based on the assumption that the time series being forecasted are linear and stationary [11].

With the advancement of machine learning, most of the research works have been focused on the use machine learning techniques to develop the prediction models. One such area is the use of supervised machine learning models. Kamruzzaman et al. investigated artificial neural networks (ANNs)-based prediction modeling of foreign currency rates and made a comparison with the best known ARIMA model. It was discoverd that the ANN model outperformed the ARIMA model [12]. Thu et al. implemented a support vector machine (SVM) model with actual Forex transactions, and outlined the advantages of the use of SVM compared to transactions done without the use of SVM [13]. Decision trees (DT) have also seen some usage in Forex prediction models. Juszczuk et al. created a model that can generate datasets from real-world FOREX market data [14]. The data are transformed into a decision table with three decision classes (BUY, SELL or WAIT). There are also research works using an ensemble model rather than relying on single individual models for Forex prediction. Nti et al. constructed 25 different ensembled regressors and classifiers using DTs, SVMs and NNs. They evaluated their ensembled models over data from various stock exchanges and showed that stacking and blending ensemble techniques offer higher prediction accuracy of (90–100%) and (85.7–100%) respectively, compared with that of bagging (53–97.78%) and boosting (52.7–96.32%). The root mean square error (RMSE) recorded by stacking (0.0001–0.001) and blending (0.002–0.01) was also lower than to that of bagging (0.01–0.11) and boosting (0.01–0.443) [15].

Apart from supervised machine learning models, another area of machine learning technique that is employed for Forex prediciton is the use of Deep Learning models. Examples of such models include long short-term memory (LSTM) and convolutional neural networks (CNNs). Qi et al. conducted a comparative study of several deep learning models, which included long short-term memory (LSTM), bidirectional long short-term memory (BiLSTM) and gated recurrent unit (GRU) against a simple recurrent neural network (RNN) baseline model [16]. They concluded that their LSTM and GRU models outperformed the baseline RNN model for EUR/GBP, AUD/USD and CAD/CHF currency pairs. They also reported that their models outperformed those proposed by Zeng and Khushi [17] in terms of RMSE, achieving a value of 0.006 × 10 − 3 as compared to 1.65 × 10 − 3 for the latter.

Some research works have attempted a hybrid approach by combining multiple deep learning models together. Islam et al. introduced the use of a hybrid GRU-LSTM model. They have tested their proposed model on 10-mins and 30-mins timeframes and evaluated the performance based on MSE, RMSE, MAE and R 2 score. They reported that the hybrid model outperforms the standalone LSTM and GRU model based on the performance metrics used [18].

Reinforcement learning (RL) is another area of interest that has been tapped for Forex prediction. It involves training an agent to interact with the environment by sequentially receiving states and rewards from the environment and taking actions to reach better rewards. In the case of Forex trading, the reward function can be based on maximising prediction accuracy or profit. Carapuço et al. developed a neural network with three hidden layers of ReLU neurons are trained as RL agents under the Q-learning algorithm by a novel simulated market environment framework, which includes new state and reward signals. They tested their model on the EUR/USD market from 2010 to 2022, and the the system yielded an average total profit of 114.0 ± 19.6% for an yearly average of 16.3 ± 2.8% over 10 tests with varying initial conditions [19]. Other works have been done in deep reinforcement learning (DRL) techniques, which combines machine learning and reinforcement learning. Thibaut and Ernst presented a deep reinforcement learning (DRL) approach inspired by the popular Deep Q-Network (DQN) algorithm [20]. Yuan et al. found that proximal policy optimization (PPO) is the most stable algorithm to achieve high risk-adjusted returns, while (DQN) and soft actor critic (SAC) can beat the market in terms of Sharp ratio [21]. Rundo proposed an algorithm that uses a deep learning LSTM network with reinforcement learning layer for high-frequency trading in the Forex market. The model was reported to achieve an accuracy of 85%. The algorithm was further validated on the EUR/USD market, achieving a return of investment of 98.23% and reduced drawdown of 15.97% [22].

Although there has been extensive research work done in trying to develop prediction models for Forex prediction, especially in the use of machine learning techniques, it is noted that the results are heavily focused on accuracy metrics. As such, there is a lack of profitability results, which is important to consider as well since the main goal of Forex trading is to generate profits. However, generating profits is not just dependent on the model getting most of the predictions right. In a real-world trading context, there are many other factors that come into play that can significantly impact profit such as transaction costs [23,24], which can quickly erode profits if many trades are conducted in a short time span. Furthermore, there is little to no research work conducted for a complete end-to-end system solution that includes features such as comprehensive back testing and optimization, which is important for actual deployment on the real world Forex trading environment. Hence, this study aims to address the shortcomings identified in this field through a proposed complete end-to-end system solution for Forex trading.

3. Methods.

3.1. Overall Architecture.

The high level architecture of the proposed system is illustrated in Figure 1, and consists of the following 5 main modules:

System Interface module: UI interface that traders can use to communicate with AlgoML to obtain trade action recommendation and execute trades through broker websites.

Pre-processing module: includes the extract, load and transform pipeline together with data cleaning, feature extraction and feature engineering.

Action Predictor module: gives a final predicted buy/sell action output.

Trader module: simulator environment to replicate market trading and execute orders based on model predictions. Also performs actual trade through broker websites.

Optimizer module: optimizes parameters for strategies to improve system profitability.

With reference to Figure 1, the general process flow of the system starts out at the System Interface module. Traders will use the UI to ask AlgoML to provide a recommended action for their desired Forex pair. Upon receiving the request, the system proceeds to the Pre-processing module, where market data is harvested through broker websites and processed accordingly. The processed data is then passed into the Action Predictor module, specifically into the various models/strategies included within it. Each model/strategy takes in the processed data and outputs their predicted action to take. The predicted action from each model/strategy is then collected into the ensemble model to obtain a single final predicted action. The predicted action to take will then be reflected to the user via the System Interface UI. Here, the user can choose to instruct AlgoML to execute the predicted action on their behalf. If so, the system will proceed to the Trader module, which takes in the predicted action signal and uses an included money management strategy to execute the most optimal course of action to take. The result of the actual action taken by the Trader module will be reflected back to the user through the UI. The Optimization module of the system helps to optimize parameters for strategies within the system such as the money management strategy in the Trader module, and those used in the Action Predictor module. More details about how each module functions is explained in Section 3.2, Section 3.3, Section 3.4, Section 3.5 and Section 3.6 below.

3.2. System Interface Module.

The System Interface module consists of a front-end UI built using Python’s tkinter package. Using the UI, traders can select the Forex pair that they wish to trade using AlgoML. After selecting the desired Forex pair, traders will command AlgoML to extract the most update-to-date OHLCV data available for that Forex pair through broker websites. After that, traders can request AlgoML to make a prediction of whether they should “BUY” or “SELL” based on the data available at hand, which will be reflected on the UI once the prediction is completed. If traders wish for AlgoML to execute the trade on their behalf, it can be done so through the UI.

3.3. Pre-Processing Module.

3.3.1. Data Preparation.

The Pre-processing module first performs extract, transform and load (ETL) to obtain the raw data of the identified Forex pair (EUR/USD) through the broker websites. Data that are extracted come in the form of “Open, High, Low, Close and Volume” (OHLCV). In total, 8 years’ worth of daily OHLCV data from January 2010 to December 2022 were selected as training data set, while test data were from January 2022 to December 2022. Data from year 2022 were intended to leave as a gap between training and test data set to prevent data leakage due to some technical indicators requiring lookback, for example moving average.

Labels are generated to train the models. Since the expected market signal output from the system is either a “BUY” or “SELL” signal, the labels are denoted as “1” for “BUY” signals and “−1” for “SELL” signals. The labels are generated by taking the difference in ‘Close’ price between the next day ( t + 1) and current day (t) as shown in (1) and (2). If the difference is positive, then the label is “1” since the close price is expected to go up the next day. Otherwise, the label is “−1” since the close price is expected to go down the next day.

Δ C l o s e = C l o s e t + 1 − C l o s e t.

L a b e l t = 1 , if Δ C l o s e ≥ 0 − 1 , otherwise.

After generating the labels, it is important to check for class imbalance within the data. This is to prevent biased performance of the trained model towards a certain set of labels [25]. The presence of class imbalance can be observed by checking the labels distribution for each year as shown in Figure 2. A good class distribution would have a relatively similar number of labels for each year and overall total for the entire time range as well, which can be observed from the graph. As such, class imbalance is not expected to be major factor negatively affecting the performance of the trained supervised models.

3.3.2. Eliminating Trend and Seasonality in Data.

Times series data is different from independent and identically distributed (IID) data. The conventional preprocessing methods cannot be applied directly to this data. Furthermore, financial price data follows a stochastic process which adds a further level of complexity. As such, it would be extremely difficult to model or forecast the data [26,27]. Hence, when dealing with time-series data, it is recommended to make the data stationary before passing it into the model for training and testing. Stationary data is where the mean, variance and autocorrelation structure do not change over time, which means that there should be no clear trend observed within the data [28]. The motive behind making data stationary is that ML models learn based on particular patterns. Due to regime changes or external factors, the market changes and so do the patterns in the data. As such, predictive results are going to be worse, as the ML model is unable to generalize well to this change in pattern. To test whether a time-series is truly stationary or not, the augmented Dickey–Fuller (ADF) test is utilized [29]. The main objective of the test is to reject the null hypothesis that the data is nonstationary. If the null hypothesis can be rejected, it means that the data is stationary. The test consists of a Test Statistic and some Critical Values for different confidence levels. If the ‘Test Statistic’ is less than the ‘Critical Value’, then the null hypothesis can be rejected. When applied to the raw OHLCV data, the results as seen in Figure 3 show that the data is indeed nonstationary.

To make the OHLCV data stationary, a combination of log transformation and fractional differencing is used. The reason for this is that it was discovered that solely applying a log transform does not make the data stationary based on the ADF test; thus, fractional differencing was also used in conjunction to make the data stationary. Log transform attempts to reduce trend and seasonality by penalizing higher values more than smaller values. Fractional differencing is chosen instead of integer differencing because the latter unnecessarily removes too much memory to achieve stationarity, which could affect the predictive performance of the ML models. Thus, fractional differencing helps to achieve stationarity while maintaining the maximum amount of memory compared to integer differencing. The formula for fractional differencing [30] is outlined in (3).

Δ d y t = y t − d y t − 1 + d ( d − 1 ) 2 ! y t − 2 − d ( d − 1 ) ( d − 2 ) 3 ! y t − 3 + ⋯ + ( − 1 ) k + 1 d ( d − 1 ) ∗ ⋯ ∗ ( d − k ) k ! y t − k.

where Δ d denotes fractional differencing of order d .

Since the differencing order is fractional, each of the lags has a weight, and they converge to zero in absolute value (faster convergence towards zero happens in higher orders of differencing), a cutoff value is required for the absolute value of the coefficients such that the series is not theoretically infinite. Larger time series would allow smaller cutoff values in order to preserve more memory, it ends up being a trade-off between memory conservation and computational efficiency. For this study, a differencing order of 0.8 is used, which will cut off around 2% of data entries from the raw nonstationary dataset. This is to establish a good balance between making the data stationary and preserving as much memory as possible. After applying both log transform and fractional differencing, the results of the ADF test as seen in Figure 4 indicates that the the null hypothesis of the test can be rejected and the data is now deemed to be stationary.

3.3.3. Feature Engineering.

In real world trading, traders do not just depend on analyzing OHLCV signals to predict market movement. Instead, they also employ the use of technical indicators, which are heuristic or pattern-based signals produced by the price or volume data. Examples of commonly used technical indicators include moving average (MA), Bollinger bands (BB) and Heikin Ashi candles. Some notable technical indicators that are used to train the ML models in the system are seen in Figure 5, which have been used in other research works for Forex trading as well [31,32]. The chosen technical indicators are mostly oscillators and trend-based financial time-series filters which are used by [32]. In those studies, different intervals are used for the technical indicators (3, 7, 14 and 20 days), which are commonly preferred by short-to-medium-term traders. The conclusion drawn from [33] reveals that using long-horizon forecasts potentially contributes to negative prediction results and short-term results in better prediction. This is based on the fact that out of the 39 studies, 27 papers used both middle-term and short-term predictions. The technical indicators are generated using Python packages finta [34] and pandas-ta [35].

The technical indicators selected from Figure 5 along with the Open, High, Low, Close, Volume are being normalized using MinMax scaler from scikit-learn preprocessing library. A total of 19 parameters were used to train the deep learning models.

3.4. Action Predictor Module.

The Action Predictor module uses an ensemble technique, where results from several ML models are combined together to give a final predicted buy/sell action output. As compared to single-model based predictions, ensemble models have the advantage to potentially reduce the variance of predictions and reduce generalization error, resulting in better performance than the former approach [25]. This makes it applicable for the Forex markets as they tend to be very volatile, which makes predictions very prone to high-variance errors. Various works have incorporated ensemble methods to achieve state-of-the-art performance [36,37]. Other studies involved in stock market price prediction have reported that ensemble models produced a higher accuracy prediction as compared to single models [38,39].

The three key criteria while designing the ensemble were the choice of base learners, the combination techniques used to aggregate the predictions and the quantum of classifiers to be ensembled. The Action Predictor module consists of two main parts: the base learner module, which includes the various ML models, and the Ensemble module, to combine the predictions and output a single final predicted action.

With reference to Figure 6, the base learner module consists of various machine learning classifier models. All models/strategies will receive the preprocessed input from the preprocessing module. The predicted output of each model/strategy will go into the Ensemble model module to make the final prediction. A total of 7 models/strategies are used in the ensemble for this study, which include: