Monday, January 13, 2020

Knowledge and Understanding in Trading

I've been teaching myself new approaches to trading and have learned many valuable lessons in the process.

One of the most significant changes I've made is trading from a place of understanding rather than a place of knowledge.  

As the quote suggests, knowing something and understanding it are quite different things.  I know a number of people, but I would not be so presumptuous as to pretend that I understand all of them.  Similarly, I might know a Bible passage or a poem, but that doesn't necessarily mean I understand them.

Much of what is taught in trader education is knowledge.  It might be knowledge about fundamental factors that influence the stock market, such as interest rates.  It might be knowledge about chart patterns, trends, and indicators.  It might be knowledge about potential catalyst events, such as shifts in monetary or fiscal policies.  From their knowledge, traders typically attempt to make predictions, such as whether the market will go up or down.  Sometimes the predictions made from the pieces of knowledge are quantified through backtests.  This is common among many of the services that I recently highlighted.

This knowledge-prediction paradigm of trading is what I have found to be limited.  "X is occurring; therefore the market should do Y" does not necessarily reflect any understanding of why that relationship might hold.  When we look for X-Y patterns in markets, it becomes easy to reach for so many patterns that the relationships we trade are spurious and not meaningful.  That is how overfitting occurs in backtests, for example.  We test so many combinations of variables that eventually we find the 1 in 20 that is significant at the p<.05 level!

In science, we first observe nature and develop theories about what is occurring and why.  Theory building is the hallmark of understanding:  a theory represents causal thinking, not just correlational thought.  "The market is going higher because we've formed a certain candlestick pattern on a chart" does not capture anything of a causal nature.  Conversely, if we look at the expansion of the Federal Reserve's balance sheet and their stance on rates and hypothesize that excess funds in a low rate environment will spur speculative activity, that could represent part of  understanding of why we're in a bull market.  Or if I break down volume that is transacted at market bid and offer prices and notice that institutions are predominantly lifting offers across different time frames, this could represent an understanding of market participant behavior and a theory of why we're seeing a market trend.

To be sure, once the scientist has a promising theory, it's important to put the ideas to the test--and that is where prediction comes in.  Ideally, a trade is a test of a market hypothesis derived from a trader's understanding.  When well-constructed trades are working out, they add confidence to our theory.  When they don't work out, they may lead us to revise our theory.  Ideally, our trading is our way of testing our understanding of the market.

Too often, however, traders assemble knowledge and immediately want to create trades out of what they have learned.  Bypassing the process of understanding leads to a shallow perspective on market behavior--one that does not merit true conviction.  Genuine conviction comes from deep understanding, not simple correlations and patterns.  "There is nothing so practical as a good theory," psychologist Kurt Lewin observed.  What traders need are frameworks for understanding how markets behave and why, not mere "setups" for the next trade.

Further Reading: