Ever since the introduction of algorithmic trading, the operations of the trading market have changed significantly. Both the regulators and market participants are now more focused on improving market structure and implementing safeguards. Risk management can be handled either within the application or before an order is generated in the system. Risks related to the algorithmic trading platform can be divided into several categories, some of which are discussed here.
Interrupted Data Access
Traders need proper checks to ensure that they are getting access to the correct data points, based on the algorithms they are using for generating orders. If a trading strategy trades in multiple exchanges and one of them has down connectivity, then you may continue quoting and ordering on other exchanges. You may assume that there is nothing wrong, as there might be no activity in the exchange.
For managing such a risk, you have to distinguish between times when the connection is lost, and when there is no incoming data due to lack of activity. An algorithmic trading system will respond whenever you send a message, thereby giving you a confirmation in real-time.
Inconsistent Data Points
It is crucial to ensure that the data points you are receiving are the latest and not stale. If you use stale data to make your strategy, you will not make a wise decision. Since you would be paying a high amount to receive new data without delay, it is essential to ensure that your data is consistent over time.
Some exchanges send snapshot data to get information about the top few sellers or buyers to mitigate this risk. Others send tick-by-tick data, in which the exchange sends information about every tick happening in the exchange. Packets of market data have time-stamps on them, and some exchanges are adopting atomic clocks or time-syncs for risk management in platforms of algorithmic trading.
Risk at Algorithmic Level
Different types of checks are required at the algorithmic level. A minor coding error can lead to incorrect market execution. The risk limit may even exceed when you don’t receive an acknowledgment check before sending orders. For instance, if you wish to buy 20 lots and incorrectly enter 200 lots, you will make many more trades than you wanted.
The method of order throttle rate can be used to manage such a risk while managing orders. In this risk check system, the system drops whenever you enter a number less or more than your set limit. At such time, the system stops working in the market automatically, thus avoiding any risk beyond your reach.
Protocol Mismatch
When you want to install a couple of modules on all the servers, there may be times when only one module got installed, and others could not install, thereby resulting in a protocol mismatch. When you install a server-dependent on certain libraries may have specific indirect dependencies too. In such a case, you may end up trading much more stocks than planned within a short period.
Although an algorithmic trading platform largely depends on networking, hardware, software, and checks, they can be carried out, and rigid disk systems may fail. To minimize the chance of this risk, keep your systems checked and updated at frequent intervals.
Scalability
When you set up a strategy for one instrument and profit from it, you may replicate it for all other devices. But success is not assured when you move from one instrument to all. The best strategy is to test for different scenarios using just a single tool. When you apply it to more instruments, the trading may not work.
Here, you have understood a few risks involved in the algorithmic trading platform and a few ideas to mitigate them. With prudent risk management, you can trade safely and maximize your profits.
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