The idea of “degrees of creative freedom” has bubbled up and started to percolate my consciousness recently. And, the concept is that the more degrees of creative freedom that a system enables then the greater the wealth that is possible to be created–where wealth is the expression of valuable ideas. And, system in this case doesn’t refer to simply trading systems but rather to all sorts of systems including computer systems.
Entrepreneurs who create businesses have virtually infinite degrees of creative freedom, and so the wealth potential is incredible. On the other hand, taking a job with a predefined set of requirements, i.e. working for another, has fewer degrees of creative freedom and reduced opportunity. On the other hand, the probability of return seems to be inversely correlated with creative freedom. The probability of return from working a job is very high while the probability of making money from a new business is low.
If we take the activity of trading as a system then we can analyze it in the same process. A trader who has fewer rules, fewer boundaries, and fewer restrictions has greater potential for discovering opportunity, and greater opportunity equates to greater potential for income. Yet, the lack of structure invites more opportunity for risk, as well. We can imagine trading as a spectrum, or number line, where at one end exists extremely creative and risky discretionary trading and at the other lies highly disciplined programmed systems, and everything in-between.
The question worth asking is how one can increase their degrees of creative freedom while still taking taking advantage of quantitative processes and benefits. Trading more markets is one simple way to increase access to opportunity. For the discretionary trader looking to refine form, the synthesis of discretionary analysis with quantitative analysis and systems trading, otherwise what we call graybox trading, may be an answer.
Curtis is passionate about markets. He has developed top ranked futures strategies. His core focus is (1) applying machine learning and developing systematic strategies, and (2) solving the toughest problems of discretionary trading by applying quantitative tools, machine learning, and performance discipline. You can contact him at firstname.lastname@example.org.
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