In the emerging developments of automation around us, sophisticated algorithms dominate our everyday life right from traffic lights, train schedules, chromatography, and the likes. We also remain genius applying algorithms as a necessary means for trading. This brings the greater efficiency of financial markets that pass through ever-unexplored challenges, both present, and future. An English novelist, Eric Arthur Blair, known by his pen name George Orwell once said, “Who controls the past controls the future”.
The next question is how? Kelly B. McBride, an American writer, said “What you need is a certain critical literacy about the fact you are almost always subject to an algorithm. The most powerful thing in your world now is an algorithm about which you know nothing about”. Steven Sol Skiena, the author of “The Algorithm Design Manual”, and a distinguished professor of computer science at Stony Brook University said, “in algorithms, as in life, persistence pays off”. That is as good as true with the good, the bad, and the ugly of algorithmic trading.
Algorithm Popularity
Algorithmic trading has picked up great popularity in this automation age compared to a decade back. In the US, about 70 percent of overall trading volumes are generated by algorithmic trading. Emerging economies like India saw the overall trading volumes estimated at 40 percent. A recent report estimated the world market for algorithmic trading to grow by 10.3% CARG from 2016 to 2020. In the past, many investors and regulators were attracted to algorithmic and HFT trading. High-Frequency Trading will stay and set to become frequent, even if taxed or legislated. Algos will drift toward HFT when they take place with speed contrary to slow times trading.
What makes up Algorithmic Trading?
Algorithmic trading deals with buying or selling security basing on some pre-described set of rules tested on historical data. These rules can base on indicators, charts, technical analysis, or stock fundamentals. For instance, you have a plan to buy a specific stock assuming it ends in losses for five successive days. You can draw up this rule into the process of algorithmic trading and automate it so that your buy order is met when your condition is satisfied. You may still limit your stop loss, and put the target in the algorithm that can make your trading easier. The future of Algorithmic trading begins with resource allocation and is the main operator of its performance.
Advantages of algorithmic trading
Algorithmic trading eliminates human emotions that prevent investors’ behavioural problems in holding losses for a longer time and selling profitable securities too early. It also tests the trade ideas on historical data to eliminate bad trade ideas and retain the good ones. These are two major advantages of algo-trading. Retail traders tend to stay off algorithmic trading thinking it is complicated and beyond their reach. Setting up modus operandi for algorithmic trading can be a straightforward task if you know the basics behind it.
Automation of financial markets
Future can witness high-level automation of the financial markets that differ from what we witness today. We can witness algorithmic trading to adjust to different patterns using AI. For instance, you can program certain specific rules for trading into your strategy. If markets do not turn in your favor, the program alters to match the new market changes. Somebody still needs to monitor the progress of AI, though the system by itself becomes self-sustaining. You can expect to move deeper into practical machine learning that is set to do real-time interpretation and integration of data from many different sources.
Role of machine learning
In the future, machine learning will shape algorithms that can pick the techniques by themselves. Right now, large sums are being invested in automation intelligence and machine learning including on the algo-trading platform. Several algos continue to work on ‘Arbing’, a process offering variations in odds provided by different bookmakers. This process leads to the advantage of profit-making irrespective of the event’s outcome. Many large players have worked on automating the same methods.
Many have a belief in investing in a hedge fund that trade algorithm only. The strategy will not change in an investment made through a robot, as one can rely on its earlier performance depending on the market conditions. Investors need to learn which algorithmic procedures to trust to create a portfolio. Many fund managers and research firms expect a rising trend for 100 percent algorithmic trading by investors.
Role of Robots
Developments of ‘robots’ in algo-trading can play a key role. They can rule the future. However, like humans, not all robots are the same. Some become tricky, some become cautious. Robo-experts still exist in their inception, yet this is where algorithmic trading is progressing. Algorithms can be engraved in customized chips to have better robot-to-robot communication. Algo traders are expected to embed improved ‘algo-detecting’ capabilities to alter their systems. These can base on the real-time bids and offers made by traders, and information based on whether these bids and offers are rejected or accepted
The investors need to take due diligence as far as these latest classes of novel devices and become conversant with them. Robots are presented to investors as a trust fund product, like a hedge fund, or a structured product, or a commodity pool controlled by managers. An investor can buy a robot and have it self-managed loading it onto his account in another option.
In algorithmic trading, devising strategies is the most significant measure. Many are setting up several statistical techniques and modeling. In the growing period for automation where self-driving cars are on the anvil, and drones delivering pizzas, you can expect a fascinating race for investment through algorithmic trading.
Algorithms in other fields
Investment is not the lone field where we notice emerging algorithms. In his book ‘Automate This’, Christopher Steiner points out a few jingles, that start a customer service call with the words “this call may be monitored…”. It is not to give us an impression of measuring a person’s ability that seemed to help us, but this adds you to a database of a personality type. Big players in the technology field always strive to make their algorithms interpret every aspect of our life to give an impression that they can help us with our decisions.
Advanced algorithms, which are set to deal with enormous moving parts of data, appear appropriate for tackling responses to rising problems on a larger pragmatic level. These can be responses to natural disasters or taking care of daily traffic flows like traffic routing, or managing civic services something like IBM’s engineering projects ‘Smart Cities’.
What is in store?
David Easthope, a senior analyst with Boston-based consultancy Celent, says “As an overall market, I think algorithms are very much here to stay, especially if you look globally because of the increasing use of algorithms across the European equity markets”. He predicts continued heavy use of algorithms in the coming ages.
Matthew Samelson, a Senior Analyst with Aite Group, also a Boston-based consultancy, predicts “that new algorithm will continue to flood the market … It’s also going to be increasingly hard to evaluate them.” He also says. “The algorithms are going to become more advanced and more complicated, which means it becomes more important to understand what they do for you and how well they do it.”
The future has in store a bright and exponential growth for algorithmic trading. So far in the past two decades, large banks and large trading firms endured algorithmic trading. Nowadays, retailers also jumped on to the bandwagon of algorithmic trading that witnessed significant growth. A meteoric rise is expected as more and more retailers continue to learn the nuances of algorithmic trading.
In conclusion
Excellent courses are on offer for training to expertise algorithmic trading that covers subjects such as developing trading systems, risk management, backtesting, programming, statistics et al. Traders also have excellent access to the platforms of algorithmic trading to take care of their strategies. Many brokers are also expected to host servers at co-locations or in proximity locations to make orders to all their clients including retail.
