Trading quantitative strategies explained
In this article, you will learn all about trading quantitative strategies used by institutions, what quant traders actually do and how to start using quantitative trading methods for yourself. Let's get started!
What is quantitative trading?
Quantitative trading often gets confused with algorithmic trading. A quantitative strategies trading system is drawn from 'quantitative analysis.' This type of analysis uses mathematical formulas and calculations to find patterns and trading opportunities. Quantitative trading and investment strategies are mostly used by hedge funds and large institutions who employ 'quant traders.'
These traders would conduct intensive research by building complex mathematical and statistical models to find an edge in the market that could turn a profit. While the quant trader would build the model, the algorithmic trader would build the system to execute the trades. Algorithmic trading quantitative strategies involve the 'algo trader' getting the system from the 'quant trader' first and then setting up an black box system to execute trades automatically and without human intervention.
Some of the most important differences between quantitative traders and algorithmic traders include:
- Algorithmic traders, such as those using the MetaTrader trading platform provided by Admirals, tend to use technical analysis and technical trading indicators to find profitable strategies. Quant traders tend to use more tools and datasets such as price, volume, probability scenarios, weather patterns, number correlations of different asset classes and more.
- Quantitative traders build models to help identify possible trading opportunities. They may trade the opportunities manually or pass it on to an algorithmic trader. An algo trader will always enter positions automatically from the trading robot they have created.
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How do quants trade?
Quant traders are usually highly versed in mathematics. Most institutional quant traders will have PHDs in mathematics, engineering or computer science. Many graduate students interested in this field ask the question: 'how can I learn quantitative trading?'. One of the most important skills is to have experience in coding languages such as C++, Python and Java.
This is because quant traders build mathematical data models to identify and exploit certain patterns. This would then be backtested over a large data sample to test the historical efficiency of the model to avoid any curve fitting. However, quant traders do not just build new models and strategies they may also customise and improve an existing one.
Most retail traders may perform some type of quantitative analysis in their trading if they too backtest certain patterns in the market. While retail traders would do the testing manually, quant traders build programs to do it automatically so they can quickly see the statistics and crunch the numbers.
The best quantitative trading strategies to start with
Trying to identify the best quantitative trading strategy to begin with requires analysing a lot of different variables such as what type of market access you have, capital resources, trading style, execution type and many others. Quantitative strategies for derivatives trading may differ from quantitative trading strategies Forex markets. This is because each market has individual characteristics which quant traders try to take advantage of.
One of the simplest forms of quantitative trading out there is seasonal trading. This is where traders would look at the monthly performance of a financial instrument over many different years to find the average probability of the instrument closing higher or lower by the end of the month. It is very similar to the well-known seasonal effects such as: 'Sell in May and go away' or the 'Santa Claus rally.' These are all based on quantitative analysis.
Let's take the price of gold as an example. Below is the percentage of months in which the price of gold closed higher than where it opened at the start of the month from 2006 to 2020:
A customised bar chart showing the percentage of months the price of gold closed higher than where it opened at the start of the month from 2006 to 2020.
In the above image, it shows that between the beginning of 2006 to the beginning of 2020, January tends to be one of the best performing months. This is the simplest type of quantitative analysis - crunching the numbers to find patterns which could provide a profitable edge in trading the financial markets.
Quant traders would then take this edge and crunch the numbers even further, using lots of different inputs. They may further refine by analysing the best performing days in the best performing months, or analyse weather patterns during that time, or output figures from commodity mines, or what the US dollar was doing during that time.
There are many different possible ideas to further build a possible quantitative strategy. This is time consuming work for most retail traders to do which is why quant traders are well versed in computer programming language so they can build a program to perform this quantitative analysis automatically and at great speed.
In the monthly chart below of gold, each dotted vertical line represents the month of January. While a quantitative analysis may be simple enough over measuring several historical bars, or data points, quant traders do this on different times with a variety of different inputs, thereby producing thousands to millions of data points for analysis.
Source: Admirals MetaTrader 5, GOLD, Monthly - Data range: from 1 May 2005 to 13 August 2020. Please note: Past performance is not a reliable indicator of future results.
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Admirals is a multi-award winning, globally regulated Forex and CFD broker, offering trading on over 8,000 financial instruments via the world's most popular trading platforms: MetaTrader 4 and MetaTrader 5. Start trading today!
This material does not contain and should not be construed as containing investment advice, investment recommendations, an offer of or recommendation for any transactions in financial instruments. Please note that such trading analysis is not a reliable indicator for any current or future performance, as circumstances may change over time. Before making any investment decisions, you should seek advice from independent financial advisors to ensure you understand the risks.