What Is Quant Trading and How It Works in Stock Markets

Have you ever wondered how the world of trading has changed greatly? Initially, people would go to brokers to have their trades executed. Now, some algorithms are helping with the trading, which is now known as algo trading. But that is not it. 

There is a term that is now quite frequently used with trading, which is quant trading. In the simplest terms, it is the method of trading where you use mathematical models and computer algorithms to execute trades for efficient outcomes.

Now, this might sound like algo trading, but these two are quite different. So, read this guide to know what quant trading is and know everything you need to stay ahead in trading. 

What Is Quant Trading?

Quant trading is also known as quantitative trading. It is a data-driven approach. It uses mathematical models, statistical techniques, and computer algorithms. These all work together to help you make trading decisions. 

Under Thai, the traders do not rely on emotions and intuitions. But they actually follow the logic and facts to ensure that trades are effective in nature. 

This method focuses on analyzing vast sets of financial data. This is based on the price, volume, and market trends. Once the same is checked, patterns can be identified. This helps in ensuring better trends with the help of algorithms. These are executed on our own and hence save time.

Since the emotions are not involved, the chances of ending with positive trends with precision are quite high. 

How Quant Trading Works

As a trader, you must have used multiple types of trading strategies. The focus points of each is different, but ensure that you get the right outcome, there are some steps that you must always follow. So, here are the steps to follow:

1. Data Collection

To ensure that you have a good quant trading session, you would need to work on a lot of data. This will include the historical data to check on the past movements. Some charts need to be analyse, and you would need to work on the actual market conditions as well. 

Some of the other factors are historical prices, trading volumes, and volatility indicators. For an effective outcome, you must ensure the accuracy data.

2. Strategy Development

Once data is gathered, traders create mathematical and statistical models. This helps identify and detect recurring market patterns. These models aim to forecast price movements.

By doing so, you can also identify the entry or exit points. Programming languages such as Python, R, and C++ help in building the strategies. This is quite similar to what you do when you develop the algo trading strategy. 

3. Backtesting

This is one of the most important stages that you must keep in mind. This is where you test your strategy on the past data to see how well it works. It is known as the backtesting trading strategy. This is done before you go ahead with the real-time trading.

This will help you to check the risks and potential opportunities that the strategy can capture. Also, ensure that you test it across market conditions. This will ensure that your strategy can work well in different situations. 

4. Trade Execution

Once validated, the algorithm is connected to a trading apps/platform or broker API. The system then executes trades automatically. This happens only when all the conditions are met positively. 

Logically, multiple small trades of a similar nature are done. This allows the trader to earn consistent profit over time and reduce the losses.

5. Continuous Optimization

Quant trading is not a one-time process. Traders regularly monitor performance so that they can tweak the strategies to ensure that the profitability is maintained. This is based on the very crucial market conditions. This helps in earning better profits and ensures that you can benefit from market trends.

Example of Quant Trading

To understand how quant trading works, here is a simple example for you.

Suppose a quant trader develops a model. Now, this model identifies short-term opportunities in NIFTY stocks. The model uses the following things for analysis:

• Historical price data

• Trading volume

• Simple moving averages

This helps to predict when a stock might rise by 1% within a day.

The algorithm scans hundreds of stocks simultaneously. Now, by doing this, it can find when a stock’s 10-day moving average crosses above its 30-day moving average. This often leads to short-term upward momentum. 

If everything is in line, the trade is executed. The stop-loss and exits are already mentioned that ensure the losses are reduced to the best.

Now, optimizing the strategy over time will ensure that you are using trades that are effective and useful.

Pros and Cons of Quant Trading

Quant trading comes with clear advantages and some limitations. Though you get precision and better control over the trades, there are certain limitations as well that you must keep in mind. So, here are the pros and cons of the quant trading that you must know of:

Pros of Quant Trading

• Uses mathematical logic for better accuracy and objectivity.

• Executes trades within milliseconds, capturing small price movements.

• No emotions are involved, which ensures the right decision based on logic.

• Supports backtesting, which ensures better trades.

• Can work with multiple strategies.

• Helps with diversification that reduces overall risk.

Cons of Quant Trading

• Advanced programming is hard for many.

• It cannot be done without deep analytical skills.

• The initial setup cost is high for tools, data, and the rest.

• Relies heavily on data quality and availability.

• Models may fail in real markets if over-optimized.

• Faces intense competition as more traders use similar algorithms.

Quant Trading vs Algo Trading

Although both quant and algo trading use automation. But when it comes to the approach and the purpose, these two are quite different. Knowing this difference is what helps you to decide which one of the two you need to select and work on.

So, here are the key differences that you must know:

Conclusion

Quant trading is a new type of trading in the market, but there is no doubt that it is one of the finest. It allows you to not just execute trades with efficiency but also ensure that the losses are reduced. By focusing on data and deep analysis, this ensures that all the trades done are effective in nature.

But at the same time, it is important to note that the trades will be effective only when you go for proper data and analysis. So, take your time when you plan to start on quant trading. Effective planning and analysis will be the key and ensuring your analytics are on point.

And if you are new to trading, look for a perfect platform. This is where you can start your trading journey with Rupeezy. This is where you will get all the support you need to start trading effectively.

FAQs

Is quant trading legal in India?

Yes. Quant trading is legal in India. You will find the rules defined by SEBI for the same. Ensure to follow them for the right trades and outcomes.

Do I need coding skills for quant trading?

Yes, coding knowledge is essential. You would need to create and execute strategies in this. The languages usually used are C, C++, or Python.

How is quant trading different from algo trading?

Quant trading's main focus is on data and analysis. Algo trading aims towards the pre-set rules. Both help with automation, but the aim is different. 

Can beginners start with quant trading?

Yes, beginners can start quant trading easily. First, start by learning financial data analysis and basic programming. Create the strategy and go for backtesting on demo platforms. Once sure, launch your strategy in the market for real-time trading.

Can quant trading be done without expensive software?

Yes, beginners can start with open-source tools like Python libraries, free data sources, and paper trading platforms before upgrading.