I am a mathematician, so I am supposed to like algorithms. I love them. But not always.

I love algorithms that are used by traders in algorithmic trading. I don't believe in algorithms that replace humans in decision making. That buy and sell without human intervention. Yes, these algorithms can be useful, but they can also be very dangerous.

I do understand that algorithms and automated systems can be very quick and effective. For example, I like smart order routing algorithms, like “Guerrilla”, the algorithm developed by Credit Suisse that slices big orders into smaller unobtrusive sizes. Great algorithm, very effective.

I like “Sniper”, also developed by Credit Suisse, that detects dark pools of liquidity (hidden sources of liquidity that are not shown on conventional trading platforms provided by the stock exchanges).  I like “Benchmark” algorithms that achieve a specific benchmark.

The problem is that we take algorithmic trading far too seriously, we rely on it, and we run the risk of transforming it from a useful tool to a weapon of mass destruction (WMD). Why? All these algorithms trade according to well known or predictable rules and can be used against the free market or the firms that rely on them. This is a disaster waiting to happen. 

Traders do not really understand information security, deception management, information systems. I have never met them in Black Hut conference in Las Vegas. They have learned Euclidean geometry, and they strongly believe that "A Straight Line Is the Shortest Distance between Two Points". Not always, and definitely not in information security. A Straight Line is the most obvious and most predictable route, and this knowledge can be used against us.

Anti-Algorithmic Trading

Algorithmic trading is the use of computer systems, programs and advanced mathematical models for entering trading orders. Algorithms, not humans decide on aspects such as the timing, price and the quantity of orders.

Some algorithms initiate orders based on information received electronically, understood by the algorithms only. On the positive side, they are quick, so they can exploit opportunities (arbitrage, statistical arbitrage, trend following). I like statistical arbitrage, and I remember that I liked some algorithmic trading systems that really helped, but these days there are so many sophisticated systems and algorithms competing to exploit the same opportunities, that we have to find something more creative.

On the negative side, more and more trades are driven by automatic programs, and algorithms replace traders. At the London Stock Exchange for example, over 50% of all orders were entered by algo traders. American markets have an even higher proportion of algo trades (estimates range as high as 80% proportion in some markets).

Electronic platforms were supposed to execute simple trades, and leave hedge fund managers or traders at the financial firms and brokerages free to come up with new ideas for making money. These days electronic platforms tend to execute all trades, and leave humans free to find another job. Which one? Technical staff, as more and more firms have more people working in their technology area than people on the trading desk.

Computers not only learn what is new from firms such as Reuters, Dow Jones, Bloomberg and Thomson Financial, but also decide if the news is good or bad so that automated trading can work directly on the news stories.  “There is a real interest in moving the process of interpreting news from the humans to the machines” said Kiristi Suutani, global business manager of algorithmic trading at Reuters.

Jobs once done by human traders are being switched to computers. Every day we read about the speed and the processing power of computers and networks, and their ability for “lightning-quick trades”. When we read success stories about humans, like hedge fund managers, we also read about their high management and performance fee. We rarely speak about the cost of the systems that replace humans (tens of billions).

I do not like certain algorithms called “sniffers”, that sniff out algorithmic trading by others and the algorithms being used by them. They can “game” the system, and may trigger buy orders to generate a better market price into which to sell. These algorithms can be very dangerous. We move towards Information Operations and Information Warfare-like environment.

Information is no longer a staff function but an operational one. It is deadly as well as useful.
--- Executive Summary, Air Force 2025 report

No, I am not kidding. Information Operations is the integrated employment of the core capabilities of electronic warfare, computer network operations, psychological operations, military deception and operations security, in concert with specified supporting and related capabilities, to influence, disrupt, corrupt or usurp adversarial human and automated decision making while protecting our own.

The above definition of Information Operations should have nothing to do with trading. But it has. If you read the definition carefully, you will see that trading is very similar to war, and information is always a weapon.

Hedge funds and financial organizations of both, the buy side and the sell side, must remember that computers should help humans, not make decisions. Traders must not forget that they are not IT or Information Security experts, and that mathematicians are usually not born for risk management. So many firms rely on systems they do not understand.

No, these risks are not covered by your risk models. They are 15 standard deviations from the mean (nowhere). They are High Impact / Low Likelihood events, hidden under the "fat tail" of the distribution.

Systems should help humans, not replace them. I really like strategies and approaches that can not be programmed into systems. Creative, non-formulaic, anti-algorithmic. 

Privacy/Legal