Algorithmic Trading Strategies: the Good, the Bad, the Ugly

The legendary 1966 Spaghetti Western “The Good, The Bad and The Ugly” starred Clint Eastwood, Lee Van Cleef, and Eli Wallach as three Wild West gunslingers competing to find a fortune in buried treasure. It’s a fantastic film, and right till the very end, you’re never quite sure who – if anyone – is going to find the gold.


In some respects, algorithmic trading is a bit like that epic film. There’s the good (successful algorithmic trading), the bad (poor algorithmic trading strategies that result in losses), and the ugly (fraudulently manipulated algorithms, and other scams).


With “algo trading” as it’s sometimes called, a computer program is used to automatically generate trades in response to a certain set of market variables, such as price, timing, and transaction volumes. Unlike human beings, computers have the ability to respond in lightning quick time, process huge amounts of information seamlessly and accurately, and work without a break, 24/7. Those qualities are some of the main attractions of algorithmic trading systems.


There’s a subtle but significant difference between algorithmic trading and automated trading systems. An algorithmic trading system is typically associated with large trade volumes and uses a set of rules to decide when to buy or sell. The overall process isn’t always completely automated, and it’s perfectly feasible to perform an algorithmic trade manually. Compare that to an automated trading system, where the whole trading process is automated.


One interesting subset of algorithmic trading is called high-frequency trading (HFT), which takes the concept to its ultimate conclusion – transactions that happen at the speed of light, and which succeed because of the ability to react faster than the competition. HFT often aims to increase profitability by making huge amounts of small gains across multiple markets.


So is algorithmic trading for you? To continue with the movie metaphor, is the market full of reckless outlaws and cowboys, or is it a well-marshaled platform that’s a good way to generate decent returns on your investments? Saddle up, and read on to learn more!


The first algorithmic trading systems tended to be the preserve of big corporates like pension funds, insurance companies, and wealth management firms. This was due to the cost of building the algorithms, acquiring the high-performance computer infrastructure necessary, and sourcing the relevant data in real-time. But now individual customers can ask their broker to implement their own algorithmic trading strategies, or alternatively invest in algorithmic trading companies.


You can choose to invest over the short, mid, or long term, and there’s a wide variety of different investment options on offer. The choice includes using a market trend-following algorithm (invest in Company X when the price falls to $10.00, and sell when it reaches $20.00), mean reversion (buy when a share is under the average price, and sell when it’s above), or employing strategies based on arbitrage (buying and selling in different markets). You can also make investments based on other factors like index fund rebalancing, trade volumes, timing/size of trades, share price, unusual market patterns, and much, much more.


It goes without saying that if you’re working with algorithmic trading companies, you should always ensure that they’re fully registered, regulated, and licensed. That way, in the event of any questionable corporate behavior, at the very least, you should have some legal recourse.



Because algorithmic trading offers such a wide variety of choices, it can be difficult to decide on the best options and the most effective strategies. Every choice carries with it theoretical benefits and investment dangers.


The pros of the different strategies include stealing a march on the market by being the first to react to any new trends, the chance to make serious profits from millions of small trades as opposed to big margins on a limited number of transactions, and the removal of human emotion from investment decisions.


As with every form of trading, however, there are downsides. Notwithstanding any technical issues like power cuts or interrupted internet connections, there’s a chance of an algorithm having a fundamental flaw that isn’t discovered until it’s too late. It’s also possible that unscrupulous companies are acting unfairly and rigging the market, or that a certain trend is misinterpreted and causes a completely disproportionate ripple effect.


Computers are only as good as the information that’s put into them. And like humans, they’re not infallible: incorrect programming, power cuts or internet drop-outs can and do cause problems. And whether maliciously, deliberately, or mistakenly, algorithmic trading systems can cause huge market imbalances, massive losses, and catastrophic failures: a quick internet search will reveal many such examples.


Another frequently overlooked issue is that algorithmic trading systems may automatically invest in companies where there are serious flaws. If companies provide false information – think of Enron, WorldCom, or Bernard L. Madoff Investment Securities LLC – your money may inadvertently be invested in stocks that will ultimately end up being worthless. Sometimes a human being is far, far cleverer and more valuable than a computer!


Like every single form of financial trading ever, there’s the possibility that algorithms will be manipulated to make a trader or the end client lose. There are various ways in which this can happen. Spoof orders – which are placed and then canceled at the very last moment – can trick an algorithmic trading system into placing an order. And fake articles or social media reports can be used as a means to artificially drive up stock prices.


A major problem with such behavior is that whilst it may be immoral, it may not be illegal. In a market that moves so quickly, regulators and legislators often struggle to keep up with all that’s happening. Hacking, information theft and data breaches can also have a significant impact on the outcome of algorithmic trading strategies.


Common scams around algorithmic trading schemes include fake companies that take your money and deliver nothing in return, traders who make false promises and fail to return funds, and dishonest brokers deliberately rigging trades against you.

If you feel that you’ve been the victim of illegal trading or sharp business practices, in the first instance you should contact the company concerned, and also the relevant financial regulator. If those approaches aren’t appropriate or don’t work, you should consider using the services of a dedicated funds recovery company like PayBack. The experienced legal and financial experts often succeed in recovering assets where other approaches have failed. And as is the case with most movies, the goodies generally tend to win out over the baddies!

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