To tell the truth, both New York and London Stock Exchange floors really are only there for show. For the most part the actual trading is automated and carried out by robots. About 75% of the trades that happen on the New York Stock Exchange and NASDAQ are the result of algorithms – these are computer programs that carry out complex sets of rules.
In fact, the so-called “robo-trading” has directly influenced the investment world – everything from global hedge funds to personal savers. So what are the advantages and disadvantages of permitting computers to be in charge of managing the world’s trillions of dollars?
It’s a useful tool
The advantage for retail and personal investors is that these commanding tools help in making solid choices and managing a balanced portfolio of our investments. They also generally cost much less than traditional brokers or fund management companies. And if you aren’t really interested in using a DIY approach, most advisers utilize these tools as well. “Robo-advice” companies, such as Betterment and WiseBanyan in the US or Nutmeg and MoneyFarm in the UK, are trying to demystify the investment sphere by giving us access to such tools.
Vicki Zhou, co-founder of WiseBanyan, says that her platform allows to “invest algorithmically using a diversified portfolio made up of low-cost index funds.” She claims they don’t normally charge the management costs levied by traditional funds, since 88% of them were under-performing on their benchmark indexes over the last five years in the US.
Betterment’s Joe Ziemer states: “We look at 40 different variables – spousal situation, rental income, pensions – and from these we deliver you online, in seconds, a comprehensive retirement plan.” In the recent report, the UK’s Financial Conduct Authority said that online financial advice could “play a major role in driving down costs.”
While this is bad news for advisors, it is certainly good news for us – Royal Bank of Scotland also mentioned it would cut 220 face-to-face adviser jobs as a result of the implementation of this new technology.
The faster you are
The big financial institutions are continuously looking for a way to get the upper hand on their rivals so they would always opt for the more effective means of trading. Computers are able to run a multitude of operations in just a fraction of a second, exploiting tiny changes in the stock prices and indexes to make a profit.
Companies like New Jersey-based Tradeworx are creating line-of-site networks of microwave relays, with towers interspersed roughly 30 miles apart. This network is going to send financial information from Chicago to the New York Stock Exchange 2.3 milliseconds faster than fiber optic cables. While it may not seem like much, it is enough to provide traders with an advantage in this hyper-speed world of flash trading.
Fear & greed
Computers have no emotion. They never panic, they don’t become scared, and they don’t get greedy. They simply carry out well-written investment algorithms. They are also becoming smarter. Artificial intelligence can quickly scour endless amounts of social media, research, and news information and has the ability to learn and self-improve.
“When data was scarce, people would hoard information, and find their edge in investing that way,” says Dr. Thomas Wiecki, lead data scientist at Quantopian, a crowd-sourced hedge fund. “Now we take huge mountains of data a human could never analyze and automate it.”
California-based Sentient AI, in conjunction with New York-based Rebellion Research, is developing ways for these algorithms to learn from past mistakes and refine their rules – all with minimal human intervention if any at all.
Is it out of control?
Enthusiasts say algorithmic trading provides necessary liquidity, making buyers and sellers available to the market and reducing the costs. Critics are quick to proclaim that this type of training wastes the skills of educated physicists and mathematicians and destabilizes the markets in ways that are not yet clearly understood by regulators.
On May 6th 2010, a “flash crash” took place and was blamed by the regulators on high-frequency algorithmic trading. It resulted in a trillion-dollar drop in US stocks, which is the second-largest swing the market has ever experienced in a single day. 36 minutes later their value was recovered. US authorities blamed a 36-year old resident of London, who was using commercial algorithmic trading software.
The main concern is that these “flash crashes” could become a common occurrence in the trading world ran by self-learning robots. But it is somewhat fantasy-like to imagine a very smart computer would purposefully trigger a huge sell-off with the sole purpose of buying shares when they are cheap and making a profit as the market recovers.
Some believe a more believable scenario is that the self-learning trading algorithms, which are constantly accessing relevant market data, will eventually agree on a single view, leading to market stagnation. This would cause trading volumes and spreads to shrink. “The best and the worst scenarios would get pretty close,” says Dr. Kashdan.
Still others feel we will never get to that point, because the world is far too complex, and there are no algorithms that can predict the future. Quantopian chief executive John Fawcett says: “Everyone openly admits it’s impossible. But it’s too important to ignore.”
What is your opinion of this contradictory issue? Share your theories in the comments below!
Need more advice? Don’t hesitate to check out our complete guide to investing into stocks and bonds and learn how to anticipate market movements and navigate the trading field.