Qualitative vs Quantitative Trading, which is best?
At the very beginning, during Jesse Livermore's era as the boy plunger, shares were traded through the medium of stock certificates. That's why it took so long for brokers and financial institutions to process an order.
Then came the discovery of the Internet in the 1980s, which sent the world into a technological revolution. And among the products that came to life because of this revolution is the wide-reaching adoption of something called a computer.
One step after another, tech enthusiasts have pushed the boundaries of software and hardware, making it a competitive edge for those who understand how to take full advantage of it.
Because of that, the financial world benefitted from it as the physical share certificate quickly became digital certificates. Not only that, but those that have the knowledge also leveraged the power of computers to help them achieve the returns they couldn't have otherwise.
As of today, there are two predominant trading/investing styles - qualitative and quantitative - and a number of hybrids that exists in between this spectrum.
With that, this article is aimed to differentiate qualitative trading and quantitative trading and answer the commonly debated inquiry of which one is better.
Key takeaways:
Types of quantitative trading strategies
Alternative data analysis
High-frequency trading
Machine learning
What is qualitative analysis?
Qualitative analysis doesn't mean that the analyst doesn't look at the historic numbers or reported earnings at all. It simply pivots on the idea that "No event will happen exactly the same twice."
A qualitative analyst looks at not only the numbers but also the subjective parts of the company such as quality of management, corporate governance practices, ethics, brand value, reputation, long-term plans, etc.
The quantitative approach really puts the concentration on the quality of the asset. Investors commonly associate this approach with Warren Buffett as they know Buffett for buying "wonderful companies" as value prices.
Because of this, research has found that qualitative investors and funds have a more concentrated bet and follow the underlying asset more closely.
What is quantitative analysis?
Quantitative analysis is equivalent to taking a bet by looking at the rear mirror.
Quantitative analysis is an objective analysis based on quantifiable data. For example, it can be how many times a setup occurs in a year, the win rate of a certain strategy, using Bollinger bands, or the standard deviation of it.
A quantitative analyst takes all of this into account and establishes a set of rules to govern their next moves. Let's say if the strategy requires a stock to fulfil 20 out of 30 criteria, it will ignore any stock that only fulfils 19 criteria and below.
An extremely beneficial advantage of being a quantitative analyst is that they get to leverage the power of computers. It owes to the fact that decisions are made with numbers and not human judgement.
In other words, because the parameters have already been set, programmers can give this set of instructions to a computer and have it automatically executed within fractions of a second.
Examples of qualitative approaches:
I have read a lot about cryptocurrencies, the problem they can solve and the potential demand for this asset. I can foresee a future where cryptocurrency is one of the main transaction options. Hence, I am confident that the price will go up.
This stock is currently sitting on a major support level. I am going to go long on this because they also reported good earnings in the most recent quarter. I feel like there is a much higher chance that the price will go up.
Recently, I noticed that many of the household items that I am buying have gone up in prices. That must mean inflation has gone up since last year, which leads me to believe that interest rates must go up. Because of the higher interest rates, it is more than likely that stock prices will be negatively affected. I'm taking a short position.
Examples of quantitative approaches:
I have read a lot about cryptocurrencies and the idea sounds solid, but I need some figures to prove that there is actually a potential for this asset. Not only that, but I also want to know the exact supply and demand of the specific cryptocurrency. And before taking the trade, I will need to have a plan, a specific level that indicates my idea was wrong and that I need to get out.
This stock is currently at a major support level, but I need to find out the volume that was traded at this level, if the current volume is greater than the previous, and what happened the last time was at support. I'll also need to know the float, shares outstanding, market cap in order to classify them into a category. Then, I will place an order based on the expectancy derived from previous data.
After noticing that some household items went up in prices, I did some research to figure out how much exactly. Then, I will find out how much 1% of inflation is going to affect the stock prices. Also, before placing the trade, I need to compare the earnings report of the company with previous quarters to see if the company is consistently growing.
Limitations of a qualitative process
1. Single-case analysis
The biggest difference between a qualitative process and a quantitative process is considering historical samples. In other words, a qualitative process is also commonly regarded as a "single-case analysis".
By isolating a case, it comes with its own set of limitations and setbacks, the predominant one being methodological rigour.
Being methodological rigour means that the analysis process has been tested a number of times and it has been proven to provide the researcher with a wholistic conclusion. Qualitative analysis, however, is quite the opposite, in theory.
2. Vulnerable to biases
When the analysis process is not fixed or it "depends on the scenario", the biggest enemy will then be biases.
Survivorship bias, confirmation bias, sunk-cost bias, are only a few that are commonly found in traders. And we won't know if we're making them until it's complete or if a third-person tells us. Even then, it will fall into the category of hindsight bias.
Not just that, because there are no rules that prevent poor decisions, it is much easier for the trader to keep rationalising their position.
For instance: "It's going down, and the price keeps getting cheaper, I'm just going to buy more." But at what point does the trader stop and say "I think it's time for me to sell this loss." Well, technically, a qualitative trader can choose to never say that.
Limitations of a quantitative process
1. Context is ignored
A quantitative trading process is all about numbers and statistics. Most of the time, the answer from this process is binary; yes or no. Because of that, you'll never understand the context behind the event.
Why did the stock go up? Why did the stock gap down?
This then leads to the paradox of curve-fitting. If you notice something being a strong buy signal, do you include that into your existing strategy? If you did, it will affect the expectancy of your strategy and become another strategy altogether.
2. You don't know what you don't know
There are a number of "unfortunate situations" you can get into when you automate.
Sometimes, even the smallest mistakes in code (for example, having a parenthesis in the wrong place) can lead you down a slippery slope with huge losses.
You might think that you've protected yourself by implementing stop losses, but there are other factors that can influence your stop losses. Every cause has an effect, and we humans simply can't prepare for the things we don't know.
The computer doesn't know how to protect you from this. Maybe AI can, but even then, the human fight-or-flight intuition is still the best way to protect ourselves.
Types of quantitative trading strategies
Many people think that quantitative trading is only about using robots to combat human emotions. But, it's actually more than that.
There are different ways to use quantitative information to help boost a trader's decision. With that, here are 3 ways quantitative data can help you:
Alternative data analysis
There are more types of data than just the traditional data about a stock or a currency pair. It's the measurements that are outside of the charts (volume, price, market cap, net income, etc.) that also impact the company's performance.
Satellite images of the number of cars at a Walmart parking lot.
The number of trucks leaving an Ikea factory.
The number of "check-ins" a month at McDonald's.
As traditional trading strategies generate gets more and more well-known, traders are eager to be one step ahead of their competitors. Hence these are some of the creative ways that they've come up with to get that tiny edge in the market.
These are the quantitative data that other traders don't have access to and have high barriers to entry.
High-frequency trading (HFT)
High-frequency trading is the type of trading that is executed at speeds human cannot. That's the edge.
It's the type of trading that results in a large number of trades and pivots on low profit per trade. Because of this, the infrastructure that is needed to achieve this is also comparatively expensive.
Breaking it down even more, there are 2 main types of high-frequency strategies:
1. Arbitrage
Arbitrage is the idea of buying the cheaper asset while shorting the pricier asset when it is priced differently on two exchanges.
2. News releases
Being the first in an extremely competitive market pays off. Especially during the release of major news.
The downside of being in the high-frequency trading field is that it is extremely competitive. Once the intricacies of a certain strategy are out in the public, the edge quickly disappears. That's why most HFT firms are extremely secretive about what they do.
Machine learning
Machine learning techniques enable computers to perform certain tasks without being explicitly given the instructions. It's when the computer organises the data and extracts the important information to form its own thesis.
The advantage really lies in being able to analyse large quantities of data which would have taken qualitative traders a tremendous amount of time to do so.
Conclusion
Not everything that can be counted counts, and not everything that counts can be counted. - Albert Einstein
In this day and age, there are more than just a few hybrid strategies that you can adopt. In fact, most trading strategies are a mixture of both qualitative and quantitative values.
However, the demand for quantitative strategies has gone up significantly because of the progression of technology.
To sum up everything, it really depends on the trader you are to know which type of trading can benefit you the most. Both qualitative and quantitative analysis has their pros and cons.
The question you have to answer is that how much qualitative and quantitative research are you going to emphasize on?
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