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How Quantitative Trading Differs from Technical Analysis

Article Quant Q&A · Author: Marco Demaio

Summary

The discussion distinguishes quantitative trading from technical analysis by the rigor and breadth of the research process, rather than by how complicated an indicator is. A moving average or signal-processing filter can be used by either a discretionary technician or a quant; the calculation alone does not define the approach. The answers point to backtesting, statistical confidence measures, performance evaluation, optimization, and understanding the drivers of returns as features of quantitative work. They also note that technical signals can be one input among broader methods, including other indicators and position-sizing frameworks.

The document also separates quantitative finance into derivative valuation and statistical prediction or trading, while describing quant trading as a mix of systematic analysis and market-specific judgment. It offers no empirical comparison or operational definition that settles exactly when a person becomes a quant. One answer characterizes trading as a craft requiring knowledge beyond books, a view presented as opinion rather than established evidence. The practical takeaway is that mathematical complexity is insufficient: the research and decision process matter.

Key ideas

  • The sophistication of an indicator alone does not determine whether its user is a quant.
  • Quantitative trading commonly uses backtests, statistical measures, performance analysis, and optimization.
  • Technical indicators can be one component of a broader systematic strategy.
  • Quantitative finance includes both derivative valuation and statistical trading or prediction.
  • The answers offer viewpoints rather than a formal definition or empirical test of quant status.

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Full text
# At what point does someone using technical analysis become a Quant?


# At what point does someone using technical analysis become a Quant?












Sorry if the question sounds rough. It's not my intention to devaluate something I've not yet understood like Quantitative Finance.

So to keep it simple:

- is Quantitative Finance a science, like Math or Physics?

- Or is it something more similar to Technical Analysis, but with much more math into it?

I know Technical Analysis is not a science, but an attempt to apply math to past financial data in order to find a way to predict the future movement of the same financial data.

Obviously things can mix up and create confusion.

Formulas like a simple Moving Average are real math and they are still in the field of science. It's when people attempt to apply a moving average to predict the future that they trespass the border of science to enter the field of empirism (that unfortunately in worst cases might even lead to charlatanism).

It confuses me even more when I read on Wikipedia about "Algorithmic trading quant"

> Often the highest paid form of Quant, ATQs make use of methods taken from signal processing

Well A T3 (the so called Tillson's moving average) comes from signal processing (low pass filter/differentiators digital filter) and it's used in Technical Analysis.

So if someone uses a simple Moving Average is a Technical Analyst, but when he uses a T3 moving average is a Quant, because the latter one is more complicated to be calculated?

## Answer by Tal Fishman (score 11, accepted)

https://quant.stackexchange.com/a/2089

There is certainly much more to quantitative finance than technical analysis, and a previous question does a decent job of outlining the different areas, as does the wikipedia on "quantitative analyst".

Even for what wikipedia terms an "algorithmic trading quant" or what Mark Joshi terms a "statistical arbitrage quant", technical analysis is just one tool in a very broad tool chest. Some quantitative trading strategies will make absolutely zero use of what would commonly be referred to as technical indicators, while others will rely on them quite heavily. I would say that two things distinguish a quant who uses technicals from a technician:

- A rigorous approach, which includes backtesting, statistics (t-statistics, confidence intervals), performance measurement (information ratios and information coefficients), optimization, and a large heap of broader understanding of what is driving returns.

- A balanced use of technicals as well as other types of indicators and/or non-technical-analysis methods (e.g. mean-variance optimization for position sizing).

An example of technical analysis as it would be applied by a quant is Evidence-Based Technical Analysis by David Aronson. Most other technical analysis books are garbage.

## Answer by TheBridge (score 6)

https://quant.stackexchange.com/a/2088

Hi Quantitative Finance has in my opinion two main streams.

The first is about of valuation of some derivative contracts in a consistent way. This is a theory and once paradigms accepted it is coherent, it can considered as science at the same level as economy can pretend to this kind of terminology.

The second is about making (or trying to) prediction(s) over some time horizon about the behaviour of some underlying asset(s) in a statistical way, and ultimately trying to get advantage of your modelisation to generate some profit with "minimum risk taking" (this is purposely left ambiguous). This is more grounded (IMO)than the first branch as it is more dependent of microstructure of the paricular market you are studying, but can be as technical if not more than the pricing some exotic option.

The summum would be to reconcile both of course.

There is some kind of duality between those areas of QF just as there some kind of duality between probability and statistics.

Regards

## Answer by columbus (score 5)

https://quant.stackexchange.com/a/2095

Quant in trading creates system that can be backtested, has a certain risk valuation. It is more like playing chess when you need to calculate multistep strategy.

Let say certain instrument moves 1% a day. Our goal is to create strategy for one year (250 step strategy). If we use stock + options we get 50 or more entries a day into our system for analysis. 250*50 = 12500 a year to analyze. So, in order to create strategy, we simulate dynamics of 12500 entries.

Can quant trading be taught. I think it is not possible. Because you should know about the market something that is not in books and other don't know. So, it is more like a craft.

But other areas of quantitative analysis like risk management are more instructions friendly.

Is the TA used in quant strategies. The answer yes. For example, price clusterization or levels in TA.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.