The Significance of Real-Time Data for Automated Trading

The speed of light is the fastest thing in the universe, and nothing can beat it. Trading probably comes a very close second, or at least feels like it. The demand for split-second decision-making is sometimes beyond the human capability to perform such tasks. There are so many variables to consider, each of which is changing rapidly in real-time to make matters more complicated.

This incredible swiftness has led to the adoption of an automated trading platform by everyone involved in the business. It is simply impossible to compete and perform otherwise. The main advantage these platforms offer is their ability to acquire and process market and company data in real-time. This makes all the difference, along with their other features.

The Importance of Real-Time Data in Automated Trading

Every trade is based on data that is available to brokers/traders. It is no different for automated trading platforms. And the fresher the data is, the better the outcome of the trade can be. There are numerous advantages in having the latest real-time data on hand, which is why this feature is built-into every such platform.

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Accurate Trade

The days of trading by looking at data that is hours or a day old are long over. Today's market dynamics are too erratic and inconsistent and are so on a near-instantaneous basis. When such is the case, using data acquired after a delay for the trade means failing before even starting with it.

As these automated software place trades based on the desired criteria, traders must ensure that the requirements are calculated based on the latest data accuracy. The software must also have the kind of connectivity that enables it to judge the criteria based on the latest data to get the maximum benefit.

Managing Large Volumes of Data

Gaining the latest data means not many resources need to be allocated towards storing old data, which is most likely to be outdated and useless. This is in contrast to the old model of operation, which uses large volumes of stored data to trade.

This greatly reduces costs associated with data storage and speeds up the execution as only a limited data set is used. Data security also improves as a result.

This is not to be confused, however, with historical data used for backtesting. That data will not be used for real-time trading, but just for testing strategies only.

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Beating the Competition

The trading ground is nothing short of a warzone with many players vying for the best deal all the time. Thus, a trader/broker must be armed with every trading tool to beat that competition and capture the desired deal for themselves.

Quick processing automated platform is one such important tool, but it is useless without gathering real-time data. And if the competition gets its hands on that data before you can, the battle is lost before it has begun, as the advantage will be hard to make up to.

Better Strategy Development

Speed alone won't help you get that deal. Get a good strategy at hand before heading out to trade. You can develop this strategy with the best data available about both the market and the company.

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Backtesting with histories will help with the preparation, but a strategy based on that alone won't hold up in the actual trade. The strategy must be flexible to change according to the present scenario at the time of the trade. And that change can only be made if real-time data is available.

Only real-time data will allow the software to clinch the best trade by utilizing the implemented strategy to its fullest. Any failures can be quickly zeroed-in on and rectified to improve the overall performance while in action simultaneously.

Improved Coordination and Integration

Automated software rarely works in isolation. It is accompanied by other solutions like fellow automated software used by brokers, leading software at the exchange, analytics for data interpretation and real-time trade situation monitoring, etc.

All the software needs to integrate and coordinate with one another seamlessly for successful trading outcomes. For that to happen, the data used by them must be the same. This is only possible when you use real-time data.

A lag in data acquisition means a miscalculated analysis report is presented, and an inaccurate trade follows. Attempts to correct this will introduce delays, which will again lead to lost opportunities. Thus, your situation's true broad picture is possible when the software uses real-time data.

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The world of trading is a game of cat and mouse between the trader and the stock price. Automated trading platforms with real-time data provide the best chance at making that critical catch.

(Disclaimer: The article is sponsored, and hence promotes some commercial links.)