5/11/ · The screening process can rate the universe by grade levels like or A-F, depending on the model. This makes the actual trading process very straightforward by investing in the highly-rated 7/21/ · In the first one fields are variable length ( and ), in the second case you define exact lengths for each field and pad with zeros if needed ( and ). In the above example, we know that EURUSD has 5 decimal places and 1 natural Estimated Reading Time: 12 mins 5/28/ · If you use a leverage rate and have 1, euros in your trading account, you can trade a currency pair with a $10, position size. If the trade is successful, leverage will maximise your profits by a factor of However, keep in mind that leverage also multiplies your losses to the same blogger.comted Reading Time: 8 mins
How to Trade Forex: 12 Steps (with Pictures) - wikiHow
Sign in. Jul 18, · 14 min read. Quantitative finance requires a significant amount of data engineering. This is especially true once you start dealing with periods smaller than daily data.
By data engineering, I define the methodologies, technologies, software, procedures and infrastructure used to retrieve, store, parse, ensure quality and distribute data to end clients. While this area shines less than the algorithms to o b tain successful trading strategies it is an important part and must be properly addressed. This infrastructure setup is part of the professional operation and it is one of the differences between an amateur and a professional approach to the field.
Defining the right infrastructure is part of business operations and plays an important role in the mid and long term journey of making money using quantitative trading. There are different approaches to cope with this data engineering need. All approaches can be equally valid but there are significant trade-offs among them and it is important to understand your resources and environment to choose the right one. I will describe what I have seen, the information comes from my experimentation, information gathered from industry people, information given by wealthy quantitative sole-traders and information that I have gathered from well-established trading companies prop-trading and commodities mainly, as unfortunately, I do not know that many players in the industry.
Large companies moving large amounts of trading capital not requiring high-speed or fine time granularities can choose a proprietary environment — such as Microsoft ecosystem — to move and store data around.
By doing that you count with friendly programming environment for whenever anything custom is needed C and Pythonintegrated cloud storage via Azure and the Microsoft ETL tools to build an easy to maintain data pipeline — Microsoft says so —. This approach has the advantage of using the same technology for everything and you can expect a smooth integration within the different components. Using a commercial solution provides also vendor support — which is always good —.
As a trade-off: it is expensive, you are tied to one vendor, it involves recurrent costs, and certain activities can not be properly done because you are using general-purpose tools. I have seen this approach being used in a commodities trading well-established company. It is probably not the best environment if you need to deal with high-speed or very custom or ML intensive strategies which was not the case there.
Another approach largely used in the industry is building up a pure Python solution. For those who had read in the past other articles you probably already know that my how to use quantitative methods in forex trading feelings on Python are mixed.
As an advantage Python is extremely easy to code and counts with many ML libraries, Jupyter notebooks can simplify the maintenance of the structures and it promotes self-documenting the procedures. It is not the best solution but in a mixed environment, I truly think that it can provide real benefits in terms of operations. I keep thinking that Python is not a good choice in terms of performance or speed, but it is extremely good to code high-level maintainable software layers. The benefit of shorter development times and easier collaboration among the team outperforms performance handicap, how to use quantitative methods in forex trading.
Experienced Python developers can also employ alternatives that can speed up Python, although you are pushing Python beyond the limits of its nature. I have seen this approach being used very successfully in a small hedge fund well-established firm, how to use quantitative methods in forex trading.
This is the approach used by firms operating intraday or high-frequency with large amounts of data. For tick data, you probably need this approach at least for certain areas of your infrastructure.
I am lately doing a lot of stuff in Java because I am not a particularly good programmer. Using Java in trading always involves coding in a way which is not that natural to Java programmers as you need to think always in terms of low-level programming and performance, hence a background in C is beneficial. Data itself can and it is usually stored in a database, but this might be a mistake. Both SQL and non-SQL approaches can be used.
I no longer use SQL for market data — I used it at the very beginning —but this is because my focus now is on intraday strategies with very few instruments, so I have to handle how to use quantitative methods in forex trading amounts of pretty homogeneous data. Relational databases provide no value in that area. An alternative is to use CSV files yes they are widely used, and there are reasons for that or other plain text methodologies such as the one I use and I describe later.
The advantages of this approach is that data can be consumed, reviewed and accessed easily and that you have effectively removed another point of maintenance and pain: the database. A common denominator of these described approaches is that they usually rely on a given language or technology rather than on a systems engineering approach, how to use quantitative methods in forex trading. This does not mean that there is no certain systems engineering involved, but often it is not the main approach.
An alternative can be successfully used, specially for the sole-trader, small hedge funds operating with limited resources or small prop-trading firms or startups is described here. Disclaimer: the approach will hurt feelings as it promotes reusing 40 years old technology. In my quest for simplicity, I have tried to remove as many layers and software as possible, and also reduce the amount of custom code that needs to be delivered. Anything that contributes to this can help to lower operational expenses and reduce the amount of total work and maintenance that needs to be done.
While thinking about this I found that reusing the classic UNIX approach of files and small cooperative tools might be highly beneficial to set up operations, based on UNIX systems engineering rather than on DevOps or programming language-based infrastructure. I always use the word UNIX because I use FreeBSD but it equally applies to Linux. But you can always stop and take a minute to think about: do you really need a database or you just assumed you need one because everyone told you so?
do you really need an API-based cloud storage or can you just work with a plain file system — which can be perfectly backup or stored on Cloud, nothing wrong against that —? do you really need to code API access in Python using the latest trendy framework or is it may be enough to install an HTTP service or a remote file server right on top of your data filesystem?
The first option even allows building a REST access system without programming a single line how to use quantitative methods in forex trading code. These are questions that are usually not warmly welcomed by biased professionals, especially among the ones who are specialised in one technology or language as it defies common bloated current practices with simpler than simple tools and approaches with zero maintenance, how to use quantitative methods in forex trading.
Zero maintenance is very important for those — like me — who had reached a certain age experience because we have already made the mistake of building complex stuff in the past. For smaller operations lacking both resources and team, deploying simple solutions is a necessity. I will describe in the following sections how to set up a 1-second aggregated FOREX data infrastructure service. This is part of my latest infrastructure setup to backtest and analyse quantitative strategies in FOREX and I will illustrate how relying on a mixed environment of small cooperative tools within a UNIX box can speed up operations.
In my last quantitative analysis, I want to work with Forex data, using 1-minute aggregated data. One minute aggregated data means that I want to explore how price only information can replace volume information which is not always available in Forex. This comes from merging the market concepts of Market Profile where time and price equals interest or value and Volume Profile where volume equals interest or value. As a consequence Time and How to use quantitative methods in forex trading can replace Volume and therefore can be used to successfully ride the markets that is my premise and what I want to analyse, it could be wrong or right but sounds reasonable.
This is my business need : to analyse if market profile over 1-minute candles information can be used to edge the market or not. This business need translates into a technical or how to use quantitative methods in forex trading need : I need to be able to consume market profile of 1-minute candles in Forex easily in my analysis. Therefore I need to store data grouped each 1-minute, and probably later process that data and generate additional files with the aggregated information.
Behind any technical need, there must be always a business need. These basic checks are not always done specially for people with technology-only backgrounds who might not have a natural understanding of mid and long-term operational costs. You always need a data provider, both for historical and real-time. It makes sense to have your how to use quantitative methods in forex trading stored locally or in your private cloud as cache if you are going to use it, but dedicated data companies will ensure continuity and reliability much better than you can do, and at the end, how to use quantitative methods in forex trading, you need to have access to market data and you can not pay or it makes no sense even if you can pay it the exchange market access fees and associated project costs involved.
oi API for this:. There are several alternatives to retrieve and store this data, how to use quantitative methods in forex trading, the first one that usually comes to mind is to use a programming language and a database. So Python and SQL could be an option.
As the number of records returned by Polygon. io is limited to The information is also retrieved as JSON, how to use quantitative methods in forex trading, but we definitively do not want to store or process JSON, because it is highly inefficient. Here are my tips for the task:. Here I will not use any database.
As we obviously need sort kind of random access we will separate this data in one file per natural day. For 20 years that poses a maximum of files, definitively a figure within the limits of what any modern OS can handle. Time zones matter, they are usually a challenge and a pain point. The best option I have found is to simplify them: I always use Eastern Time. I do so because New York cash session is likely the most important period of the day in terms of trading or at least a relevant one.
I do so because it is terribly simple to know that all your data, no matter what, is stored in Eastern Time. Shall I group my data according to the New York cash session? Maybe yes. But in my experience to store data it is much much better to use natural days in the Eastern Time zone.
If you want to analyse a particular time onwards for example you can how to use quantitative methods in forex trading that in your analysis. But the data shall be stored in natural days. I do so just because according to my experience is the easiest thing to do. All objections are valid, but again, the simplest answer I have found even when dealing with these questions is always the same: store your data grouped by natural days in Eastern Time.
A great achievement from the UNIX world is the directory structure. Use it, it is free and zero maintenance. So group your files in directories by year, by year and month or by year and month and day, how to use quantitative methods in forex trading.
In my case, I have chosen the latter because I intend to further deploy many more files with aggregated information. And if you want to read it you just do a cat over that file to display its contents:.
It is embarrassingly simple — and convenient—. Do not store data in CSV, use fixed-size fields. How to use quantitative methods in forex trading difference is subtle but has great performance benefits later. In the first one fields are variable length 1. In the above example, we know that EURUSD has 5 decimal places and 1 natural place, so each price takes exactly 7 characters.
This simplifies using low-level routines in C and Java which will make your backtesting data retrieval faster. Do not use commas because in UNIX columns are usually separated by spaces and because manually inspecting a file is easier when columns are separated by a space, by doing so you can always use CSV techniques but you will be able to get performance by reading fixed-width fields too. Write a simple, self-contained command-line tool to retrieve all data for a given day and store it.
As you have already defined where data for each day goes, you can do it easily.
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5/11/ · The screening process can rate the universe by grade levels like or A-F, depending on the model. This makes the actual trading process very straightforward by investing in the highly-rated 5/7/ · Step 1, Understand basic forex terminology. The type of currency you are spending or getting rid of, is the base currency. The currency that you are purchasing is called quote currency. In forex trading, you sell one currency to purchase another. The exchange rate tells you how much you have to spend in quote currency to purchase base currency. A long position means that you want to buy the base Step 2, Read a forex quote. You'll see two numbers on a forex 93%() 5/19/ · That will mean that any currently open trade will stay open until DominantPeriod() detects a shorter cycle, hopefully exploiting any cycles that turn into trends. Just replace the trade logic (lines ) with this code: // Trade logic if(DomPeriod Estimated Reading Time: 9 mins
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