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Code how quantitative trading works guide

In recent years, quant trading has become very popular among traders. Still, many people are not familiar with it; they have no idea how it works, or how to get started with strategies or analysis with quant trading.

Published days ago on July 31, 2020
By Anton Kovačić

This helpful guide will help you get started. We are including some of the essential things you must know about quantitative trading to gain a good understanding.

Quant trading is a method of trading that uses quantitative analysis to learn when to purchase or sell. Quantitative analysis uses mathematical formulas by examining numbers and reviewing data.

Depending upon the results of your quantitative analysis, you can establish that a particular asset is going to gain or fall in value with the price.

In addition to quantitative trading, this strategy is also referred to as algorithmic trading.

Many times, quantitative analysis is as easy as studying two significant numbers in trading: volume and pricing. With instances that are more complex in quantitative analysis, it might take hundreds or thousands of different factors to determine your results.

Many of the world’s top investors make educated trading decisions using quant analysis. Hedge funds may have a team of investors dedicating to quant trading for a thorough, complete analysis of every trade. Based on this quantitative analysis, there could be billion-dollar trades made in the hedge fund.

The average investor may discover quant trading online before starting to trade. Because of all of the information available online, it’s easy for new investors to use these strategies on many different types of portfolios.

In reality, all trading requires some kind of quantitative analysis. Whenever you use statistics involving math to make predictions about performance in the future, this would be considered a quantitative analysis.

How Does It Work?

Fundamental quantitative analysis involves research into two basic data indicators: volume and price. These two factors are most commonly used in the study.

An analyst specializing in quantitative trading may use volume and pricing to calculate and make a prediction about the value of an asset.

With technology, there is also picture quantitative trading that combines complete databases and math. This type of analysis is comprehensive and extracts the data and results you need to decide on trades.

There are four main components to quantitative trading systems:

Identifying Strategies: You will want to start by discovering a strategy. You can research an approach or develop your own. Take advantage of an edge you may have, and choose how often the system will trade.

Backtesting Strategy:

Use your newly discovered strategy using historic market conditions and data. Test to see how well your strategy would work over 2016, or how profitable would your strategy had been in 1949?

Managing Risk:

Once your system is in place, make the most of allocating capital and practice risk management while continuously reviewing and improving your quantitative trading system.

Quant trading is a vast field of study. The method can be added to other trading strategies. Additional techniques that depend on quantitative trading involve algorithms, stats, and high-frequency trading.

System of Execution:

You will want to link to automate your trading strategy or to a brokerage to benefit from lower transaction costs.

Quantitative Traders – What Do They Do?

Traders that use a quantitative system develop a mathematical model and apply it to a trading strategy. They will also use the technique to gather data and results.

The quantitative trader will develop a program that combines the technique to historical market data. The method is tested against the historical data and optimized for improvements. If the trader is happy with the results, the strategy is used in real-time markets for trading with real funds.

Many times, quantitative traders can code and use programming languages to develop trading methodologies. They use languages like Python for low-frequency trading or C++ for high-frequency trading.

Quant Trading Examples

The focus of a great quant trader is to develop a computer program that accurately predicts the future.

In reality, there are no trading programs based on quantitative analysis that can accurately predict the future all of the time. There are quantitative trading programs that are accurate more times than not, and these programs are the ones with the ability to generate profits consistently.

An excellent example of quant trading is if an investor wants to beat the market by predicting a particular future stock price. She prefers to use momentum trading, so she decides to develop a program that selects the individual stocks that will increase in price during an upward swing in the stock markets. Her program purchases the shares she picked, and they become consistently profitable. This is an example of the quant trading process.

Generally, an investor will use many methods to select profitable stocks. In addition to quant analysis, they may use value investing strategies or technical and fundamental stock analysis. By combining these techniques, the investor can make the most of their returns.

Quant Trading – Pros and Cons

It should be noted that quantitative trading is not accurate all of the time, or every investor and trader would be using this strategy.


Takes the Emotions Out of Trading: Quant trading involved math, numbers, inputs, and formulas. There is no emotion with this trading strategy; it is all data.

Does Well with Other Trading Strategies: Some of the top traders use a few different techniques combine to create trading strategies.

Select Many Assets Confidently: Quantitative trading can help you study many assets simultaneously. You can simply enter the data into a formula to gain the information on the stocks.

Not 100% Accurate Every Time: There are no trading strategies that are 100% accurate every time, but the focus with quant trading is to get more trades right rather than wrong.


Data Overload: There are copious amounts of data available to quant traders. Traders can review stock trades for many different time frames to develop trading strategies. It can help to study data for long periods, it can also be overwhelming for some investors.

Many Adjustments: When becoming an astute quant trader, it’s best to adapt to the market conditions when developing trading strategies. The market is dynamic and ever-changing. Some trends climb and fall, and a smart investor will recognize these changes and adapt to them by making adjustments in their trading techniques.

Hedge Fund Competition: Hedge funds have quite a bit of money to acquire the best analysis tools and strategies. They can hire a network of analysts, programmers, and statisticians to find the best and most effective quant trading models. As an investor using quantitative trading strategies, you will be competing with them.

Finding and Developing Quant Trading Techniques

It is essential to find and develop quantitative trading strategies to start earning profits consistently with the stock markets.

The good news is that finding a good strategy is not difficult. There are many public resources available. Professionals and academics publish trading results based on theory using a variety of analyses and complex formulas. You can also find strategies for trading in trade journals and publications from the financial industry. Many of them share top secrets from some of the best performing hedge funds.

You might wonder why others would share profitable strategies in quantitative trading, and wouldn’t they want to keep this data secured? If everyone knows these strategies, wouldn’t they become less effective?

The answers lie in the fundamental information that is released by the hedge funds. They don’t share exact details and processes, and it is not a step by step detailed plan to wealth that is shared. You won’t find the exact parameters or tuning techniques used for the trading strategy, as these are key for profiting from the approach.

The following are some of the top free resources for finding quant trading techniques and strategies:

Seeking Alpha – https://seekingalpha.com/

arXiv Quantitative Finance - https://arxiv.org/archive/q-fin

Social Science Research Network - https://www.ssrn.com/

Elite Trader - https://www.elitetrader.com/et/

Quant Trading Strategy and Backtesting

Backtesting is an essential part of creating a quantitative trading strategy. Once you have identified your trading strategy, you will want to find out how it performs under real-world market conditions. There is an overwhelming amount of data available to test your strategy in many markets of your choosing.

New traders generally use free historical trading information that is offered by Yahoo Finance, MarketWatch, or the NASDAQ online. Experienced traders rely typically on paid data and subscription-based financial databases.

There are many reasons to consider purchasing market data for your quantitative strategies. With free data, you are getting a lot of useful information; however, there may be issues with accuracy and incomplete information.

Anton Kovačić

Anton is a finance graduate and crypto enthusiast.
He specializes in market strategies and technical analysis, and has been interested in Bitcoin and actively involved in the crypto markets since 2013.
Apart from writing, Anton’s hobbies and interests include sports and movies.