Forex for a trader
Buy sell forex api

Buy sell forex apiThis site uses cookies to deliver our services and to show you relevant ads and job listings. By using our site, you acknowledge that you have read and understand our Cookie Policy, Privacy Policy, and our Terms of Service. Your use of Stack Overflow’s Products and Services, including the Stack Overflow Network, is subject to these policies and terms. Exchange Rate API With Buy & Sell Rate Of Dollar? As you know Buy & Sell Rate of Dollar is different. Suppose If you go to buy Dollar in your local currency you will be cost 1000 Local Currency, but when you go to sell 100 Dollar you will get 900 in local curency. So I want Buy Rate of Dollar which is usually higher. I have used yahoo Finance Exchange rate service to get the exchange rate , but gives sell rate. Do you know any configuration or any other API which gives this facility ? I can also consider buying an API with moderate fee. Thanks in advance !!

:) DISCLAIMER: THIS IS NOT INTENDED AS A PROMOTION OF ANY SERVICE OR WEBSITE. Take a look at this sample feed from XE: There are two fields in the Xml - "crate" and "cinverse" that provide the forward and reverse rates. The feed is reliable and as near up to date as possible. Not sure if their subscription rates are within your budget though. Every currency has a bid and offer rate, usually to reflect the cost of providing liquidity, plus a margin. The spreads between bid and offer increase the lower the amount, i. e. from wholesale to retail FX and by competitive pricing between currency brokers for different volumes. Therefore the price to exchange 1mio USD will be a lot different to the price to exchange 100k USD or the price to exchange 10K USD or the price to exchange 1k USD or the price to exchange 100 USD. There are a lot of currency brokers out there. Good ones for API are interactive brokers, or FXCM. Know When to Buy or Sell a Currency Pair. In the following examples, we are going to use fundamental analysis to help us decide whether to buy or sell a specific currency pair. If you always fell asleep during your economics class or just flat out skipped economics class, don’t worry! We will cover fundamental analysis in a later lesson.

But right now, try to pretend you know what’s going on… In this example, the euro is the base currency and thus the “basis” for the buysell. By doing so, you have bought euros in the expectation that they will rise versus the U. S. dollar. If you believe that the U. S. economy is strong and the euro will weaken against the U. S. dollar, you would execute a SELL EURUSD order. By doing so, you have sold euros in the expectation that they will fall versus the US dollar. In this example, the U. S. dollar is the base currency and thus the “basis” for the buysell. If you think that the Japanese government is going to weaken the yen in order to help its export industry, you would execute a BUY USDJPY order. If you believe that Japanese investors are pulling money out of U. S. financial markets and converting all their U. S. dollars back to yen, and this will hurt the U. S. dollar, you would execute a SELL USDJPY order. By doing so you have sold U. S dollars in the expectation that they will depreciate against the Japanese yen. In this example, the pound is the base currency and thus the “basis” for the buysell. By doing so you have bought pounds in the expectation that they will rise versus the U. S. dollar. If you believe the British’s economy is slowing while the United States’ economy remains strong like Chuck Norris, you would execute a SELL GBPUSD order.

By doing so you have sold pounds in the expectation that they will depreciate against the U. S. dollar. In this example, the U. S. dollar is the base currency and thus the “basis” for the buysell. If you think the Swiss franc is overvalued, you would execute a BUY USDCHF order. By doing so you have bought U. S. dollars in the expectation that they will appreciate versus the Swiss Franc. If you believe that the U. S. housing market weakness will hurt future economic growth, which will weaken the dollar, you would execute a SELL USDCHF order. By doing so you have sold U. S. dollars in the expectation that they will depreciate against the Swiss franc. When you go to the grocery store and want to buy an egg, you can’t just buy a single egg; they come in dozens or “lots” of 12. In forex, it would be just as foolish to buy or sell 1 euro, so they usually come in “lots” of 1,000 units of currency (Micro), 10,000 units (Mini), or 100,000 units (Standard) depending on your broker and the type of account you have (more on “lots” later). “But I don’t have enough money to buy 10,000 euros! Can I still trade?” You can with margin trading!

This is how you’re able to open $1,250 or $50,000 positions with as little as $25 or $1,000. You can conduct relatively large transactions, very quickly and cheaply, with a small amount of initial capital. You can conduct relatively large transactions, very quickly and cheaply, with a small amount of initial capital. Listen carefully because this is very important! . , , , † (API) REST FIX. † . API OANDA : -. API. . , , , OANDA . . . . . . , . -. . , . . FIX. OANDA FIX. OANDA FIX 4.2, 4.3 4.4. [email protected] com. API REST HTTP-. REST OANDA , OANDA — , 20 (v20). — , . . OANDA, API? . ? ? ? API OANDA v20? ? - API? OANDA API? API REST HTTP 429. ? API REST v1, . ? API REST v20, . ? , OANDA? OANDA API Partner. OANDA API Partner . . , 1 30 2017 OANDA V20, , 4. . (CFTC) , - : 50 : 1 20:1 . OANDA Asia Pacific 50 : 1 . . OANDA Canada (IIROC) .

« ». API OANDA OANDA - . API , , API . © 1996–2017 OANDA Corporation. . OANDA, fxTrade fx OANDA Corporation. , , . . , . . , , . , . - . . « » . - OANDA Europe Ltd, . , 4 50:1 . , . OANDA Corporation — , ; , . № 0325821. . . OANDA (Canada) Corporation ULC . OANDA (Canada) Corporation ULC (IIROC), . cipf. ca. OANDA Europe Limited , 7110087, : Tower 42, Floor 9a, 25 Old Broad St, London EC2N 1HQ. , № 542574. OANDA Asia Pacific Pte Ltd (. № 200704926K) , , (IE Singapore). OANDA Australia Pty Ltd (ASIC) (. ABN 26 152 088 349, . AFSL 412981). () , . (FSG), ('PDS'), OANDA. . OANDA Japan Co., Ltd. — Kanto Local Financial Bureau (Kin-sho), . № 2137; , .

№ 1571. Learn about our API. NOTE: All API URLs should use the domain api. kraken. com . Public methods can use either GET or POST. Private methods must use POST and be set up as follows: Note: There is no way to reset the nonce to a lower value so be sure to use a nonce generation method that won't generate numbers less than the previous nonce. A persistent counter or the current time in hundredths of a second precision or higher is suggested. Too many requests with nonces below the last valid nonce (EAPI:Invalid nonce) can result in temporary bans. Note: Sometimes requests can arrive out of order or NTP can cause your clock to rewind, resulting in nonce issues. If you encounter this issue, you can change the nonce window in your account API settings page. The amount to set it to depends upon how you increment the nonce. Depending on your connectivity, a setting that would accomodate 3-15 seconds of network issues is suggested. API calls that require currency assets can be referenced using their ISO4217-A3 names in the case of ISO registered names, their 3 letter commonly used names in the case of unregistered names, or their X-ISO4217-A3 code (see ifex-project.

org). Responses are JSON encoded in the form of: Note: Care should be taken when handling any numbers represented as strings, as these may overflow standard data types. We have safeguards in place to protect against abuseDoS attacks as well as order book manipulation caused by the rapid placing and canceling of orders. Every user of our API has a "call counter" which starts at 0. Ledgertrade history calls increase the counter by 2. Placecancel order calls do not affect the counter. All other API calls increase the counter by 1. The user's counter is reduced every couple of seconds, and if the counter exceeds the user's maximum API access is suspended for 15 minutes. Tier 2 users have a maximum of 15 and their count gets reduced by 1 every 3 seconds. Tier 3 and 4 users have a maximum of 20; the count is reduced by 1 every 2 seconds for tier 3 users, and is reduced by 1 every 1 second for tier 4 users. Although placing and cancelling orders does not increase the counter, there are separate limits in place to prevent order book manipulation. Only placing orders you intend to fill and keeping the rate down to 1 per second is generally enough to not hit this limit. Result: Server's time. Note: This is to aid in approximating the skew time between the server and client. Result: array of asset names and their info. Get tradable asset pairs.

Result: array of pair names and their info. Note: If an asset pair is on a makertaker fee schedule, the taker side is given in "fees" and maker side in "fees_maker". For pairs not on makertaker, they will only be given in "fees". Get ticker information. Result: array of pair names and their ticker info. Note: Today's prices start at 00:00:00 UTC. Result: array of pair name and OHLC data. Note: the last entry in the OHLC array is for the current, not-yet-committed frame and will always be present, regardless of the value of "since". Result: array of pair name and market depth. Result: array of pair name and recent trade data. Get recent spread data.

Result: array of pair name and recent spread data. Note: "since" is inclusive so any returned data with the same time as the previous set should overwrite all of the previous set's entries at that time. Result: array of asset names and balance amount. Result: array of trade balance info. Note: Rates used for the floating valuation is the midpoint of the best bid and ask prices. Result: array of order info in open array with txid as the key. Note: Unless otherwise stated, costs, fees, prices, and volumes are in the asset pair's scale, not the currency's scale. For example, if the asset pair uses a lot size that has a scale of 8, the volume will use a scale of 8, even if the currency it represents only has a scale of 2. Similarly, if the asset pair's pricing scale is 5, the scale will remain as 5, even if the underlying currency has a scale of 8. Result: array of order info. Note: Times given by order tx ids are more accurate than unix timestamps. If an order tx id is given for the time, the order's open time is used. Result: associative array of orders info. Result: array of trade info. If the trade opened a position, the follow fields are also present in the trade info: Unless otherwise stated, costs, fees, prices, and volumes are in the asset pair's scale, not the currency's scale.

Times given by trade tx ids are more accurate than unix timestamps. Result: associative array of trades info. Result: associative array of open position info. Note: Unless otherwise stated, costs, fees, prices, and volumes are in the asset pair's scale, not the currency's scale. Result: associative array of ledgers info. Note: Times given by ledger ids are more accurate than unix timestamps. Result: associative array of ledgers info. Result: associative array. Note: If an asset pair is on a makertaker fee schedule, the taker side is given in "fees" and maker side in "fees_maker". For pairs not on makertaker, they will only be given in "fees". Private user trading. Errors: errors include (but are not limited to): See Get tradable asset pairs for specifications on asset pair prices, lots, and leverage.

Prices can be preceded by +, -, or # to signify the price as a relative amount (with the exception of trailing stops, which are always relative). + adds the amount to the current offered price. - subtracts the amount from the current offered price. # will either add or subtract the amount to the current offered price, depending on the type and order type used. Relative prices can be suffixed with a % to signify the relative amount as a percentage of the offered price. For orders using leverage, 0 can be used for the volume to auto-fill the volume needed to close out your position. If you receive the error "EOrder:Trading agreement required", refer to your API key management page for further details. Note: txid may be a user reference id. Below are sample API client code libraries that can be used when writing your own API client. Please keep in mind that Payward nor the third party authors are responsible for losses due to bugs or improper use of the APIs. Payward has performed an initial review of the safety of the third party code before listing them but cannot vouch for any changes added since then. If you have concerns, please contact support. Sorry, you have been blocked. You are unable to access poloniex. com. Why have I been blocked?

This website is using a security service to protect itself from online attacks. The action you just performed triggered the security solution. There are several actions that could trigger this block including submitting a certain word or phrase, a SQL command or malformed data. What can I do to resolve this? You can email the site owner to let them know you were blocked. Please include what you were doing when this page came up and the Cloudflare Ray ID found at the bottom of this page. Cloudflare Ray ID: 44fffafb1001821f • Your IP : 193.0.218.8 • Performance & security by Cloudflare • Know When to Buy or Sell a Currency Pair. In the following examples, we are going to use fundamental analysis to help us decide whether to buy or sell a specific currency pair. If you always fell asleep during your economics class or just flat out skipped economics class, don’t worry! We will cover fundamental analysis in a later lesson. But right now, try to pretend you know what’s going on… In this example, the euro is the base currency and thus the “basis” for the buysell. By doing so, you have bought euros in the expectation that they will rise versus the U. S. dollar. If you believe that the U. S. economy is strong and the euro will weaken against the U. S. dollar, you would execute a SELL EURUSD order. By doing so, you have sold euros in the expectation that they will fall versus the US dollar.

In this example, the U. S. dollar is the base currency and thus the “basis” for the buysell. If you think that the Japanese government is going to weaken the yen in order to help its export industry, you would execute a BUY USDJPY order. If you believe that Japanese investors are pulling money out of U. S. financial markets and converting all their U. S. dollars back to yen, and this will hurt the U. S. dollar, you would execute a SELL USDJPY order. By doing so you have sold U. S dollars in the expectation that they will depreciate against the Japanese yen. In this example, the pound is the base currency and thus the “basis” for the buysell. By doing so you have bought pounds in the expectation that they will rise versus the U. S. dollar. If you believe the British’s economy is slowing while the United States’ economy remains strong like Chuck Norris, you would execute a SELL GBPUSD order. By doing so you have sold pounds in the expectation that they will depreciate against the U. S. dollar. In this example, the U. S. dollar is the base currency and thus the “basis” for the buysell. If you think the Swiss franc is overvalued, you would execute a BUY USDCHF order. By doing so you have bought U. S. dollars in the expectation that they will appreciate versus the Swiss Franc. If you believe that the U. S. housing market weakness will hurt future economic growth, which will weaken the dollar, you would execute a SELL USDCHF order. By doing so you have sold U. S. dollars in the expectation that they will depreciate against the Swiss franc. When you go to the grocery store and want to buy an egg, you can’t just buy a single egg; they come in dozens or “lots” of 12. In forex, it would be just as foolish to buy or sell 1 euro, so they usually come in “lots” of 1,000 units of currency (Micro), 10,000 units (Mini), or 100,000 units (Standard) depending on your broker and the type of account you have (more on “lots” later). “But I don’t have enough money to buy 10,000 euros! Can I still trade?

” You can with margin trading! This is how you’re able to open $1,250 or $50,000 positions with as little as $25 or $1,000. You can conduct relatively large transactions, very quickly and cheaply, with a small amount of initial capital. You can conduct relatively large transactions, very quickly and cheaply, with a small amount of initial capital. Listen carefully because this is very important! This site uses cookies to deliver our services and to show you relevant ads and job listings. By using our site, you acknowledge that you have read and understand our Cookie Policy, Privacy Policy, and our Terms of Service. Your use of Stack Overflow’s Products and Services, including the Stack Overflow Network, is subject to these policies and terms. almost live forex currency rates closed I need to get live forex exchange rates for my personal application. I know that there's no free service that has this data available for download.

I've been using Yahoo Finance, but I've just found out that it has a delay of 15 minutes or so. Is there any way I could get fresher rates somewhere? Say, 5-minute old instead of 15? Many forex brokers offer free "informers" that autoload data in an interval of seconds, so maybe there's a few that allow this data to be downloaded in bigger intervals without the use of their informers strictly for personal use? closed as off topic by Bo Persson, egDwight, Mark, Don Roby, Martijn Pieters ¦ Sep 24 '12 at 23:08. Questions on Stack Overflow are expected to relate to programming within the scope defined by the community. Consider editing the question or leaving comments for improvement if you believe the question can be reworded to fit within the scope. Read more about reopening questions here. If this question can be reworded to fit the rules in the help center, please edit the question. TrueFX has free real-time (multiple updates per second) forex quotes, but only for a limited number of pairs: webrates. truefx. comratesconnect. html? f=html.

They also have free downloadable tick data for the same pairs, going back to May 2009: truefx. com?page=downloads. You can get real-time quotes for a larger selection of pairs from FXCM: rates. fxcm. comRatesXML. They also have free downloadable tick-data, going back to 2007, but you need to create a demo account and use a COM based Windows API called Order2Go to retrieve it. They promised that they will make available the same tick data in CSV format for free sometime this year here: forexcodesource. comindex. phpCategory:Historical_Data. Here are a bunch of equityfx data providers, however they are not free. If you're trying to keep everything free, then you'll probably have to hack something together. For example, in MT4 there is a DDE hook that you can use to broadcast the quotes. You'll need a windows box(or vm) running MT4 and an app listening to the DDE server, that would forward the quotes off to your linux server via a TCP socket, or even HTTP.

The lag should be less than a second if done right. Here's the. net library I use to receive the DDE quotes. Also, if you are looking for historical tick data , then this is a great source. Application Programming Interface - API. What is an 'Application Programming Interface - API' An application programming interface, or API, is a "go-between" that enables a software program to interact with other software. In the context of trading, an API often refers to the interface that enables your software to connect with a broker to obtain real-time pricing data or place trades. BREAKING DOWN 'Application Programming Interface - API' Application programming interfaces, or APIs, have become increasingly popular with the rise of automated trading systems. In the past, retail traders were forced to screen for opportunities in one application and separately place trades with their broker. Many retail brokers now provide APIs that enable traders to directly connect their screening software with the brokerage account to share real-time prices and place orders. Traders can even develop their own applications, using programming languages like Python, and execute trades using a broker's API. There are two types of traders that use broker APIs: Third-Party Applications - Many traders use third-party applications that require access to broker APIs for pricing data and the ability to place trades. For example, MetaTrader is one of the most popular foreign exchange (forex) trading applications and requires API access in order to secure real-time pricing and place trades.

Developer Applications - A growing number of traders develop their own automated trading systems, using programming languages like Python, and require a way to access pricing data and place trades. Despite the obvious benefits of APIs, there are many risks to consider. Most APIs are provided to a broker's customers free-of-charge, but there are some cases where traders may incur an extra fee. It's important to understand these fees before using the API. Traders should also be aware of any API limitations, including the potential for downtime, which could have a significant effect on trading results. The most popular brokers supporting API access in the traditional stock and futures markets include TradeStation, TDAmeritrade, and InteractiveBrokers, but many smaller brokers have expanded access over time. APIs are more common among forex brokers where third-party applications and trading systems - such as MetaTrader - have been commonly used for many years. Many brokers provide online documentation for their APIs, where developers can find out exactly how to authenticate with the API, what data is available for consumption, how to place orders through the API, and other technical details. It's important to be familiar with these details before choosing a broker when looking for specific functionality. Some brokers also provide libraries in various languages to make interaction with their API easier. For example, a broker may offer a Python library that provides a set of functions, or methods, for placing a trade rather than having to write your own functions to do so. This can help accelerate development of trading systems andor make them less costly to develop. This question appears to be off-topic. The users who voted to close gave this specific reason: "Questions asking us to recommend or find a tool, library or favorite off-site resource are off-topic for Stack Overflow as they tend to attract opinionated answers and spam. Instead, describe the problem and what has been done so far to solve it." – dasblinkenlight, Brad Larson If this question can be reworded to fit the rules in the help center, please edit the question.

AFAIK, TradeStation is the most famous of the lot. Most other trading softwares provide APIs (NinjaTrader, MetaStock etc). FWIW, there are even competitions of automated trading systems -- see this. Also, this is something that the exchange has to support and your broker has to allow. Most exchanges I know of, do not allow automated trading without prior permission. There are many brokers who will give you access to an API which lets you trade. Obviously you will be paying commissions to them as well as the bidask spread which may be wider than the direct markets. They will all differ in the types of instrument that they allow you to trade. If you want an easy way in, you can use shrink-wrapped software such as Tradestation (horrible proprietary language), NinjaTrader (a little better, C#-based), or SmartQuant (better, C#-based). These generally have pre-built interfaces to a number of brokerages who will actually execute the trades. InteractiveBrokers also has a direct API but they have a reputation for being a pain to deal with. I would recommend checking alternative forums, such as EliteTrader which has a wealth of information on the relative merits of different brokerages. There are also plenty of folks on there trading through APIs. Try TD Ameritrade - they have a nice API, relatively low trading fees, and a good help forum . Link to their API offering overview. Most electronic stock exchanges don't provide an API, they provide a message specification. To get them to accept your messages (i. e. to trade directly with them), you will have to spend a very large amount of money.

and become a member of the exchange - that's what IBs do. Even a live market data feed (which you would need in order trade sensibly) can be ridiculously expensive. This is similar to a question I asked a couple of years ago: What online brokers offer APIs? I would recommend looking into Interactive Brokers, which is the one I ended up choosing. Their API supports multiple languages including Java, C++, ActiveX and Excel's DDE. You can effectively do just about anything via the API that you can do using their fairly robust trading platform. As a broker alone it's hard to beat IB's crazy low commissions (most of my orders are so low they get rounded up to the $1 minimum commission per order). Combine that with a fairly straightforward API and it's hard to beat. Also, take a look at my question (linked above, and here) for more information on brokers that offer APIs. I've just started playing around with TradeKing's API. Its dead simple and uses oauth. The $5 trade commission isn't bad either. E-trade also has an api, but you have to go through some hoops to get production access. They also provide realtime streaming via a comet interface.

There don't seem to be any libraries out there for etrade either except for the java ones etrade provides. i suppose the newest, but has an online ide debugger visualizer, and integration with interactive brokers for paper trading and real trading. great community for R&D too. AlgoTrader is a Java based Algorithmic Trading Platform that enables development, simulation and execution of multiple strategies in parallel. The automated Trading Software can trade Forex, Options, Futures, Stocks & Commodities on any market. The system is based on Complex Event Processing (CEP) and Event Stream Processing (ESP) using Esper. Automate Trading Strategies based on Complex Trading Rules Develop, Simulate and Trade multiple Strategies in parallel Multiple Broker Interfaces and Market Data Providers Support for Forex, Options, Futures, Stocks, Commodities & more Support for Synthetic Instruments & Custom Derivative Spreads Several build-in Execution Algorithms Multi-Account Functionality Automated Forex Hedging & Options Pricing Engine Based on Open Source Technology like Esper, Spring & Hibernate Scalable Low Latency High Throughput Architecture and much more… For further details please visit algotrader. com. I believe there is an API for working with ETrade and some of the other trading software. I don't think you're going to find an API for executing trades without making use of a commercial product, though. If you're trying to do some analysis of trades, though, there are APIs available for retrieving quotes, listening to ticks, getting historical data for a symbol, etc. As I said at the beginning, many of the existing commercial products have an API for writing code to work with them. Contact your target Stock Exchange for trading API and test server. If your target Stock Excnage is on OMX platform, you will be provided with X-Stream API (unmanaged c++) and docs. Go through the links on this page. Lists a number of open source api's. Haven't tried any yet, but planning to check out active-quant. You may also want to take a look at TD Ameritrade.

NET SDK hosted at Github. I have used NinjaTrader and MetaTrader to trade currencies and futures products. Ninja trader is very easy to use. I don't have super in depth coding skills although I can hold my own, and it worked for me just fine. Their application is free to download. They have also created an "app" where you can choose different technical indicators to create trading strategies. Having traded for awhile using automated systems, winning and losing, I would highly suggest using TICK DATA when you trade. Automated trading in the sense where you are using technical indicators to make your trading decisions is very competitive and very fast. Meaning, if you are using data such as 1min data, you are going to be behind the profitable trades, if there are any for your system. I can tell you that as a day trader, the days of sitting at your screen and trading when the 1 min moving average crosses the 10 min, or something similar to that, are over. Not to say longer term strategies don't work, they do, on the daily charts. My point is, use tick data no matter what platform you use. Ninja Trader is pretty good. Sign up for the tick data, and use that to trade. You'll have a better shot at being profitable if you are using technical indicators. Forex Trading Diary #1 - Automated Forex Trading with the OANDA API. Forex Trading Diary #1 - Automated Forex Trading with the OANDA API. I previously mentioned in the QuantStart: 2014 In Review article that I would be spending some of 2015 writing about automated forex trading . Given that I myself usually carry out research in equities and futures markets, I thought it would be fun (and educational!

) to write about my experiences of entering the forex market in the style of a diary. Each "diary entry" will attempt to build on all those before, but should also be relatively self-contained. In this first entry of the diary I'll be describing how to set up a new practice brokerage account with OANDA as well as how to create a basic multithreaded event-driven trading engine that can automatically execute trades in both a practice and live setting. Last year we spent a lot of time looking at the event-driven backtester, primarily for equities and ETFs. The one I present below is geared towards forex and can be used for either paper trading or live trading . I have written all of the following instructions for Ubuntu 14.04, but they should easily translate to Windows or Mac OS X, using a Python distribution such as Anaconda. The only additional library used for the Python trading engine is the requests library, which is necessary for HTTP communication to the OANDA API. Since this is the first post directly about foreign exchange trading, and the code presented below can be straightforwardly adapted to a live trading environment, I would like to present the following disclaimers: Disclaimer: Trading foreign exchange on margin carries a high level of risk, and may not be suitable for all investors. Past performance is not indicative of future results. The high degree of leverage can work against you as well as for you. Before deciding to invest in foreign exchange you should carefully consider your investment objectives, level of experience, and risk appetite. The possibility exists that you could sustain a loss of some or all of your initial investment and therefore you should not invest money that you cannot afford to lose. You should be aware of all the risks associated with foreign exchange trading, and seek advice from an independent financial advisor if you have any doubts.

This software is provided "as is" and any expressed or implied warranties, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose are disclaimed. In no event shall the regents or contributors be liable for any direct, indirect, incidental, special, exemplary, or consequential damages (including, but not limited to, procurement of substitute goods or services; loss of use, data, or profits; or business interruption) however caused and on any theory of liability, whether in contract, strict liability, or tort (including negligence or otherwise) arising in any out of the use of this software, even if advised of the possibility of such damage. Setting Up an Account with OANDA. The first question that comes to mind is "Why choose OANDA?". Simply put, after a bit of Googling around for forex brokers that had APIs, I saw that OANDA had recently released a proper REST API that could easily be communicated with from nearly any language in an extremely straightforward manner. After reading through their developer API documentation, I decided to give them a try, at least with a practice account. To be clear - I have no prior or existing relationship with OANDA and am only providing this recommendation based on my limited experience playing around with their practice API and some brief usage (for market data download) while employed at a fund previously. If anybody has come across any other forex brokers that also have a similarly modern API then I'd be happy to give them a look as well. Before utilising the API it is necessary to sign up for a practice account. To do this, head to the sign-up link. You will see the following screen: OANDA sign-up screen. You will then be able to sign in with your login credentials. Make sure to select the "fxTradePractice" tab from the sign-in screen: OANDA sign-in screen. Once in you will need to make a note of your Account ID. It is listed underneath the black "My Funds" header next to "Primary". Mine is a 7-digit number.

In addition you will also need to generate a personal API token. To do this click "Manage API Access" underneath the "Other Actions" tab on the lower left: OANDA dashboard. At this stage you will be able to generate an API token. You will need the key for use later, so make sure to write it down as well. You will now want to launch the FXTrade Practice application, which will allow us to see the executed orders and our (paper!) profit & loss. If you are running a Ubuntu system you will need to install a slightly different version of Java. In particular, the Oracle version of Java 8. If you don't do this then the practice simulator will not load from the browser. I ran these commands on my system: You will now be able to launch the practice trading environment. Return to the OANDA dashboard and click the green highlighted "Launch FXTrade Practice" link. It will bring up a Java dialog asking whether you want to run it. Click "Run" and the fxTrade Practice tool will load. Mine defaulted to a 15-min candle chart of EURUSD with the Quote Panel on the left: OANDA fxTrade Practice screen. At this point we are ready to begin designing and coding our automated forex trading system against the OANDA API. Overview of Trading Architecture.

If you have been following the event-driven backtester series for equities and ETFs that I created last year, you'll be aware of how such an event-driven trading system functions. For those of you who are new to event-driven software, I would strongly suggest reading through the article in order to gain some insight into how they work. In essence, the entire program is executed in an infinte while loop that only terminates when the trading system is shut off. The central communication mechanism of the program is given via a queue that contains events. The queue is constantly queried to check for new events. Once an event has been taken off the top of the queue it must be handled by an appropriate component of the program. Hence a market data feed might create TickEvent s that are placed onto the queue when a new market price arrives. A signal-generating strategy object might create OrderEvent s that are to be sent to a brokerage. The usefulness of such a system is given by the fact that it doesn't matter what order or types of events are placed on the queue, as they will always be correctly handled by the right component within the program. In addition different parts of the program can be run in separate threads, meaning that there is never any waiting for any particular component before processing any other. This is extremely useful in algorithmic trading situations where market data feed handlers and strategy signal generators have vastly different performance characteristics. The main trading loop is given by the following Python pseudo-code: As we stated above the code runs in an infinite loop. Firstly, the queue is polled to retrieve a new event. If the queue is empty, then the loop simply restarts after a short sleep period known as the "heartbeat". If an event is found its type is assessed and then the relevant module (either the strategy or the execution handler) is called upon to handle the event and possibly generate new ones that go back onto the queue.

The basic components that we will create for our trading system include the following: Streaming Price Handler - This will keep a long-running connection open to OANDAs servers and send tick data (i. e. bidask) across the connection for any instruments that we're interested in. Strategy Signal Generator - This will take a sequence of tick events and use them to generate trading orders that will be executed by the execution handler. Execution Handler - Takes a set of order events and then blindly executes them with OANDA. Events - These objects constitute the "messages" that are passed around on the events queue. We only require two for this implementation, namely the TickEvent and the OrderEvent . Main Entry Point - The main entry point also includes the "trade" loop that continuously polls the message queue and dispatches messages to the correct component. This is often known as the "event loop" or "event handler". We will now discuss the implementation of the code in detail. At the bottom of the article is the complete listing of all source code files. If you place them in the same directory and run python trading. py you will begin generating orders, assuming you have filled in your account ID and authentication token from OANDA. Python Implementation.

It is bad practice to store passwords or authentication keys within a codebase as you can never predict who will eventually be allowed access to a project. In a production system we would store these credentials as environment variables with the system and then query these "envvars" each time the code is redeployed. This ensures that passwords and auth tokens are never stored in a version control system. However, since we are solely interested in building a "toy" trading system, and are not concerned with production details in this article, we will instead separate these auth tokens into a settings file. In the following settings. py configuration file we have a dictionary called ENVIRONMENTS which stores the API endpoints for both the OANDA price streaming API and the trading API. Each sub dictionary contains three separate API endpoints: real , practice and sandbox . The sandbox API is purely for testing code and for checking that there are no errors or bugs. It does not have the uptime guarantees of the real or practice APIs. The practice API, in essence, provides the ability to paper trade . That is, it provides all of the features of the real API on a simulated practice account. The real API is just that - it is live trading! If you use that endpoint in your code, it will trade against your live account balance. BE EXTREMELY CAREFUL!

IMPORTANT: When trading against the practice API remember that an important transaction cost, that of market impact , is not considered. Since no trades are actually being placed into the environment this cost must be accounted for in another way elsewhere using a market impact model if you wish to realistically assess performance. In the following we are using the practice account as given by the DOMAIN setting. We need two separate dictionaries for the domains, one each for the streaming and trading API components. Finally we have the ACCESS_TOKEN and ACCOUNT_ID . I've filled the two below with dummy IDs so you will need to utilise your own, which can be accessed from the OANDA account page: The next step is to define the events that the queue will use to help all of the individual components communicate. We need two: TickEvent and OrderEvent . The first stores information about instrument market data such as the (best) bidask and the trade time. The second is used to transmit orders to the execution handler and thus contains the instrument, the number of units to trade, the order type ("market" or "limit") and the "side" (i. e. "buy" and "sell"). To future-proof our events code we are going to create a base class called Event and have all events inherit from this. The code is provided below in events.

py : The next class we are going to create will handle the trading strategy. In this demo we are going to create a rather nonsensical strategy that simply receives all of the market ticks and on every 5th tick randomly buys or sells 10,000 units of EURUSD. Clearly this is a ridiculous "strategy"! However, it is fantastic for testing purposes because it is straightforward to code and understand. In future diary entries we will be replacing this with something significantly more exciting that will (hopefully) turn a profit! The strategy. py file can be found below. Let's work through it and see what's going on. Firstly we import the random library and the OrderEvent object from events. py . We need the random lib in order to select a random buy or sell order. We need OrderEvent as this is how the strategy object will send orders to the events queue, which will later be executed by the execution handler.

The TestRandomStrategy class simply takes the instrument (in this case EURUSD), the number of units and the events queue as a set of parameters. It then creates a ticks counter that is used to tell how many TickEvent instances it has seen. Most of the work occurs in the calculate_signals method, which simply takes an event, determines whether it is a TickEvent (otherwise ignore) and increments the tick counter. It then checks to see if the count is divisible by 5 and then randomly buys or sells, with a market order, the specified number of units. It's certainly not the world's greatest trading strategy, but it will be more than suitable for our OANDA brokerage API testing purposes! The next component is the execution handler . This class is tasked with acting upon OrderEvent instances and making requests to the broker (in this case OANDA) in a "dumb" fashion. That is, there is no risk management or potfolio construction overlay. The execution handler will simply execute any order that it has been given. We must pass all of the authentication information to the Execution class, including the "domain" (practice, real or sandbox), the access token and account ID. We then create a secure connection with httplib , one of Pythons built in libraries. Most of the work occurs in execute_order . The method requires an event as a parameter.

It then constructs two dictionaries - the headers and the params . These dictionaries will then be correctly encoded (partially by urllib , another Python library) to be sent as an HTTP POST request to OANDAs API. We pass the Content-Type and Authorization header parameters, which include our authentication information. In addition we encode the parameters, which include the instrument (EURUSD), units, order type and side (buysell). Finally, we make the request and save the response: The most complex component of the trading system is the StreamingForexPrices object, which handles the market price updates from OANDA. There are two methods: connect_to_stream and stream_to_queue . The first method uses the Python requests library to connect to a streaming socket with the appropriate headers and parameters. The parameters include the Account ID and the necessary instrument list that should be listened to for updates (in this case it is only EURUSD). Note the following line: This tells the connection to be streamed and thus kept open in a long-running manner. The second method, stream_to_queue , actually attempts to connect to the stream. If the response is not successful (i. e. the response code is not HTTP 200), then we simply return and exit. If it is successful we try to load the JSON packet returned into a Python dictionary. Finally, we convert the Python dictionary with the instrument, bidask and timestamp into a TickEvent that is sent to the events queue: We now have all of the major components in place.

The final step is to wrap up everything we have written so far into a "main" program. The goal of this file, known as trading. py , is to create two separate threads , one of which runs the pricing handler and the other which runs the trading handler. Why do we need two separate threads? Put simply, we are executing two "separate" pieces of code, both of which are continuously running. If we were to create a non-threaded program, then the streaming socket used for the pricing updates would never ever "release" back to the main code path and hence we would never actually carry out any trading. Similarly, if we ran the trade loop (see below), we would never actually return the flow path to the price streaming socket. Hence we need multiple threads, one for each component, so that they can be carried out independently. They will both communicate to each other via the events queue. Let's examine this a bit futher. We create two separate threads with the following lines: We pass the function or method name to the target keyword argument and then pass an iterable (such as a list or tuple) to the args keyword argument, which then passes those arguments to the actual methodfunction. Finally we start both threads with the following lines: Thus we are able to run two, effectively infinite looping, code segments independently, which both communicate through the events queue. Note that the Python threading library does not produce a true multi-core multithreaded environment due to the CPython implementation of Python and the Global Interpreter Lock (GIL). If you would like to read more about multithreading on Python, please take a look at this article.

Let's examine the rest of the code in detail. Firstly we import all of the necessary libraries including Queue , threading and time . We then import all of the above code files. I personally prefer to capitalise any configuration settings, which is a habit I picked up from working with Django! After that we define the trade function, which was explained in Python-pseudocode above. An infinite while loop is carried out ( while True: ) that continuously polls from the events queue and only skips the loop if it is found empty. If an event is found then it is either a TickEvent or a OrderEvent and then the appropriate component is called to carry it out. In this case it is either a strategy or execution handler. The loop then simply sleeps for "heartbeat" seconds (in this case 0.5 seconds) and continues. Finally, we define the main entrypoint of the code in the __main__ function.

It is well commented below, but I will summarise here. In essence we instantiate the events queue and define the instrumentsunits. We then create the StreamingForexPrices price streaming class and then subsequently the Execution execution handler. Both receive the necessary authentication details that are given by OANDA when creating an account. We then create the TestRandomStrategy instance. Finally we define the two threads and then start them: To run the code you simply need to place all the files in the same directory and call the following at the terminal: Note that to stop the code at this stage requires a hard kill of the Python process , via "Ctrl-Z" or equivalent! I've not added an additional thread to handle looking for the sys. exit() that would be needed to stop the code safely. A potential way to stop the code on a UbuntuLinux machine is to type: And then pass the output of this (a process number) into the following: Where PROCESS_ID must be replaced with the output of pgrep. Note that this is NOT particularly good practice! In later articles we will be creating a more sophisticated stopstart mechanism that makes use of Ubuntu's process supervision in order to have the trading system running 247. The output after 30 seconds or so, depending upon the time of day relative to the main trading hours for EURUSD, for the above code, is given below: The first five lines show the JSON tick data returned from OANDA with bidask prices. Subsequently you can see the Executing order!

output as well as the JSON response returned from OANDA confirming the opening of a buy trade for 10,000 units of EURUSD and the price it was achieved at. This will keep running indefinitely until you kill the program with a "Ctrl-Z" command or similar. In later articles we are going to carry out some much-needed improvements, including: Real strategies - Proper forex strategies that generate profitable signals. Production infrastructure - Remote server implementation and 247 monitored trading system, with stopstart capability. Portfolio and risk management - Portfolio and risk overlays for all suggested orders from the strategy. Multiple strategies - Constructing a portfolio of strategies that integrate into the risk management overlay. As with the equities event-driven backtester, we also need to create a forex backtesting module. That will let us carry out rapid research and make it easier to deploy strategies.



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