Quant trading, or quantitative trading, can loosely be translated to “let’s do some math and develop a trading strategy,” and it’s all the rage with your everyday money manager. Quantitative trading is not to be confused with algorithmic trading, as that is a subset and can be looked at more like a brother to quant trading. And as with most siblings, one may resemble the other but they tend to behave differently. 

Quantitative Trading versus Algorithmic Trading

By seniority rules, we shall begin with quantitative trading. It really comes down to two main factors for input; price and volume. To break that down further, price acts as a “tangible” number and volume acts as a unit of “opportunity.” A quantitative trader will observe, analyze and decide upon an arbitrage strategy based on less information, all without feeling overwhelmed to develop a mathematical strategy. After you’re introduced to the jargon, strategies, and practices, you will soon realize quant traders are essentially emotionally blind math wizards.  They’re borderline geniuses, but work at a slower pace. Unlike their brother, algorithmic trading. 

Algorithmic trading, or algo trading, is the implementation of fast and furious pre-programmed algorithms. Buying and selling goes from a casual quantitative trot through the woods to six-speed horsepower with a flux capacitor. This can be great when you want to see quick results, however, the aspect to be aware of is your technology used. Like the market, any tech platform or program used must be able to sustain itself throughout its time of servitude. 

Risks Associated with Quant and Algo Trading 

Algo trading has the ability to compile a whopping amount of information for its advantage within seconds, but this can have its own frustrations. Keep in mind, the average investor is not the only one with a computer. On the behalf of the quick wit of the internet and many computers trading at once, prices can change within milliseconds; which can lead to unsatiated buyers and strong volatility. 

Alternate risks with quant and algo trading could include system failure, futzed algorithms, connectivity issues, and time lags. Here’s the thing, the market has its highs and lows, bulls and bears. For this unpredictability, investors are constantly moving money around to match the opportunity their dollars could ultimately yield, but computers are moving even faster. Through constant buying and selling, the amount in an investor’s account could act like a roller coaster that rises in height after every loop-de-loop.

The Key Difference Between Quant and Algo Trading

In conclusion, the main difference between the two is, quantitative trading happens to be a little more personable as it keeps a keen eye on the market’s history and trends to develop a math-based strategy. Algorithmic trading can act rashly by utilizing those math-based strategies at rapid speeds to buy and sell, and the moments of robotic decision making can turn some promising sales into wastes of time and major selloffs. 

The 401(k) Optimizer® is a computer-based system that utilizes the HCM-BuyLine®, a quantitative model designed to help remove emotion from the investing process and determine when investments should be in or out of the market. Every subscriber’s portfolio is overlaid with the math-based tool. 

Now it’s time to ask yourself, “quant” do you want from your investments? 

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