The Pros and Cons of Algorithmic Trading

The Pros and Cons of Algorithmic Trading
The world of virtual market trading has experienced considerable diversification in recent times, with online platforms have revolutionised the way in which investors research and execute orders. Interestingly, the concept of algorithmic trading (or automated trading) represents the next stage of this evolution, and one that is already beginning to impact on liquid and high value entities such as the forex market. In simple terms, algorithmic trading enables investors to establish fixed rules for trade entrances and exits, which can in turn be repeated and executed automatically online. This can help to optimise efficiency and the volume of orders completed in real-time, potentially boosting returns for savvy investors. There are grey areas associated with algorithmic trading, however, and we’ll consider the pros and cons of this practice in the article below. Algorithmic Trading – The Pros of this Practice Aside from optimising the speed, efficiency and volume of order entry, algorithmic trading can also minimise the impact of emotions of investment decisions. Emotive trading can be highly detrimental to investors, as it tends to be knee-jerk and forces investors to abandon the keen sense of determinism that can serve them so well in the forex market (and similar entities). So, by establishing rational trading rules and applying these automatically, you can act solely on the data that you access and negate the temptation to buy and sell assets on impulse. Similarly, the core principles of algorithmic trading also help to preserve discipline and focus even in volatile and depreciating marketplaces. As each trade rule is established in advance and traders have no room for interpretation, the integrity and consistency of their strategy can be upheld and not derailed by irrational fears of loss or the impact of macroeconomic factors. Algorithmic trading systems also allow you the opportunity to back-test your strategy, as you apply specific rules to historical market data and scenarios.  Investors can then build a body of data that showcases their systems in the correct context, while also enabling them to fine-tune their approach and learn from historical market lessons. When combined with simulated demo accounts, this creates a huge learning opportunity for modern-day investors who can subsequently apply their theoretical knowledge in a practical setting. What About the Cons? While algorithmic trading may eliminate the impact of emotion in trading, it also makes investors entirely reliant on technology and the systems that they deploy. Although this may not necessarily be an issue, it can cause challenges if the automated system in question is set up on a computer rather than an underlying server. In this instances, the loss of a viable Internet connection or a network crash could prevent your order from being executed, causing you to miss out on market opportunities. Even if your strategies are integrated into serves and online trading platforms, you’ll at least need to monitor these trades to ensure that they’re being carried out in full. You should also be aware of the risk of over-optimization, which can create streamlined algorithms that look great on paper but fail to translate in real market conditions. With over-optimization, you can spend an inordinate amount of time refining and cultivating your strategy based exclusively on test results, only to find that this system is simply incapable of performing in a live and real-time marketplace. This is why test results should always be taken with a pinch of salt, and measured using common sense and your understanding of the market as a whole. The Last Word On a final note, it’s interesting to note that algorithmic trading also underpins so-called High Frequency trading (HFT) strategies. These have proven to be detrimental to highly liquid and changeable markets such as the foreign exchange, as they typically create further volatility and significant price shifts. In recent times, the speed with which orders are placed has become less important, making algorithmic trading less of a priority for investors. Still, the potential of this technology simply cannot be denied, and it will continue to evolve over time. With this in mind, investors should probably look to combine both traditional and algorithmic trading techniques in the modern age, depending on their experience and the nature of the market that they want to invest in.