Embracing Heuristics
The prisoners can't see anything behind them as they've been chained, looking at the wall their entire life. They believe the cast shadows are real entities — it's all they've ever known.
As the allegory concludes, Plato poses what would happen if the prisoners were forced to leave. How would they react to the real world? Would they return to safety and relish in the ignorance of the cave?
It's such a versatile analogy that it's often applied to several real-life phenomena: human ignorance, scientific endeavors, and cognitive biases, among many more.
Further, there's a nuanced argument when applying this story to trading.
Our personal experiences and relationships with the world shape how we perceive reality. In this sense, our subjective view of life and the universe is highly dependent on our abilities to think, our senses, and our perceptions, as opposed to objective standards governing the world.
This is self evidently true.
It's why as human beings, we're incredibly susceptible to cognitive biases that can creep into our decision-making process. This is the backbone of the scientific method, maintaining a rigorous skepticism of observations given how our cognitive biases can distort the interpretation of the observation in question.
Though there's some level of irony in the assumption that this process eliminates all the mental shortcomings Plato noted in his cave analogy when applied to trading.
The empirical approach now dominant in quantitative technical analysis — finding the perfect moving average system, the countless number of oscillator systems, or any infinite number of data-fitted indicators — is largely a waste of time.
The overwhelming majority of trading systems are useless when applied in a real-world context beyond trial data.
It's ironic given the level of faith placed in empirical models when all they've done is empirically fail investors.
The over-scrutinization of data often does more harm than good to the regular trader. The real issue is that making money in past data tells you very little about your actual abilities.
And what's worse about the whole mess is that even a system built off an objective standard like machine learning fails to sustainably model risk factors because patterns are constantly in flux.
In the context of Plato's allegory, the data-science approach may seem like a conscious unshackling of the falsehoods of the cave. But, in doing so, we risk subconsciously falling back into the mental pitfalls of the prisoners.
The problem is not with heuristics per se but instead with a lack of self-awareness to differentiate emotion from visceral intelligence. Humans are wired for pattern recognition; intuition is merely unconscious pattern recognition.
In having the privilege to work with a team of world-class technical analysts all day, I feel as if those with experience develop a feeling of what is "right" or what's going to happen.
And this intuition is perfectly fine to lean on.
Sometimes it helps to have many variables and measures, but sometimes you only need to know one big thing.
Call me a contrarian, but perhaps an over-emphasis on the objective data science approach in quantitative technical analysis leads us to a merely subjective and fallacious idea of the world. Meanwhile, heuristics may be the daylight illuminating the cave of ignorance.
Under this seemingly paradoxical framework, it would reinforce the power of simplicity to a trader.
I must say, this is just a fun thought experiment from a naïve 20-year-old technical analyst.
But from what I can ascertain, we shouldn't be scared to lean into visceral thinking in an industry that often gets stuck in analysis paralysis. Not knowing how to recognize visceral intelligence because it's confused with emotions doesn't invalidate its value.
Chasing perfection in your trading systems may yield results, but we ought to remain mindful that not all lights in the darkness are natural daylight leading to the exits from Plato’s cave.
Thanks for reading, and please let us know if you have any questions.