Other than traders of metals, some of the most emotional and angry traders/investors I have seen in the “blog-o-sphere” are those who solely follow timing cycles. While there are many different cycles people follow, most seem to confound those who attempt to trade them.
While there may be certain segments of time that seem to work, they often leave people scratching their heads when the market changes cycles without warning. Well, markets don’t warn when they change their timing, do they? And, in fact, I have seen cycles analysts blow up many of their followers’ accounts.
Now, as I went through my own search of analysis methodologies early in my investment career, I always attempted to maintain an open mind and heavily contemplated any methodology which seemed to have a following. And, clearly, timing cycles have a strong following. But, intellectual honesty in the market is what will maintain your account on the correct side of the market, and anything that is unable to pass the test of intellectual honesty should be viewed quite skeptically.
Along those lines, when I contemplated these timing cycles, I had an open question which no timing cycles analyst was ever able to answer:
If markets are non-linear in nature, how can a finite, linear timing window accurately prognosticate the market more than 50% of the time?
You see, when you assume price and time are linear, you're overlooking the clear nonlinear nature of price movement. Traditional cycle analysis assumes linear and angular movement of price through time. But, if you understand that sentiment drives asset prices and is non-linear in nature, then does it make sense that the timing of sentiment is linear?
Do the ebbs and flows of human emotion track neatly like the hands of a clock? Of course not. Humans’ fears and greed are not set to sixty second and sixty minute increments any more so than rainstorms.
So, there must be a tool available that can see around linear corners of time. There must be a tool that quantifies human subjectivity as crisply as it analyzes data. I would argue such a tool has existed for over 100 years and is presently used in all areas of science and forecasting. That tool is Bayesian analysis and its specialty is decision making with nonlinear data in an uncertain world.
So how does the application of Bayesian analysis improve investment timing decisions? Bayesian is, at its best, working with nonlinear data and "learning" the underlying process of the variable of interest.
In the context of this discussion, Bayesian is learning the timing cycles of asset price movement by studying information found in option prices. Options contain many valuable pieces of information; however, the most valuable are the embedded sentiments and beliefs of price and time expectations of market participants. Thus, the Bayesian timing approach probabilistically quantifies turning points in time for security prices by using conditional information found in option prices. The end result is a powerful tool to help answer the question "When should I take a security position?" Combining this methodology with one that is able to track the sentiment affects upon price leads to potent 1-2 punch for traders.
To this end, for quite some time, I have been watching the work of Luke Miller. I met him when he became a member of my Trading Room at Elliottwavetrader.net
well over a year ago. I have been quite impressed with his work, as I am sure you will be as well, along with his impressive credentials.
Luke has been an active trader for over twenty years and got into swing trading to finance his undergraduate and masters degrees in industrial & systems engineering and a PhD in financial engineering. In 2003, Luke earned the Gilbreth Memorial Fellowship (top PhD student in the nation) and has since published over one dozen peer reviewed journal articles and a book in his area of expertise – investment timing decisions utilizing a novel technique he developed called Bayesian Learning Option Pricing (BLOP).
Luke’s Bayesian timing research has been presented all over the world and most recently won Best Presentation Award at the 18th International Conference on Business & Finance in Paris in 2016. Luke is presently a college professor and investment consultant to high net worth clients; using his Bayesian timing system to earn 30% per annum since 2007 by trading ETFs in indices, energy, and metals.
Luke will begin writing some articles with me about his Bayesian timing methodology, so I wanted to offer an introduction to his work this week. Be on the lookout for further articles explaining Luke’s groundbreaking work on timing.