Price formation is the ultimate puzzle for economists, traders, and market analysts alike. Each approaches the puzzle with different skill sets, toolboxes, and priorities. As a trader with a quantitative background, I was unsatisfied with the contextually blind (but quantitatively rigorous) approaches of technical analysis, and I was equally unsatisfied by the contextually rich (but quantitatively vague) approaches of fundamental analysis. Further, there were other areas of relevance that did not neatly fit into either of the two “competing” approaches to the markets such as sentiment, flows, and market structure. Convinced of the merits of all of the aforementioned, I set out to prepare easily digestible, actionable market analytics that incorporate all of the information and data that drive the market and feed the underlying forces of price formation.
Information is only as useful as our ability to digest and fully comprehend it. I am a strong proponent of what I term the reduction principle. As humans, and even more so as traders, we are constantly inundated with a vast amount and wide variety of information. To best comprehend and retain this information, I believe it is imperative that we have a method to both reduce it down to a few critical factors and interpret it through a familiar, well-understood framework. Once we have an appropriate method in place that covers these two critical bases, we are able to free our minds from the overwhelming burden of endlessly sorting through, processing, and remembering all of the incoming information. This freedom grants us the opportunity to engage in deeper analyses and progress our understanding to a level of detail well beyond that of which we were previously capable.
As traders, the value of the reduction principle is most apparent. There is an endless flood of market data, economic data, news reports, analyses, research, and so on flowing into our brains. It is simply not possible to maintain a mental database of all of these inputs without some measure of reduction, be it a spreadsheet to summarize, technical analysis chart or indicator, or simply mental heuristics we subconsciously tap into. Even with a well-tuned process, it is quite difficult to stay on top of all of the moving parts and their impacts on each market under study.
With these difficulties and mental limitations in mind, I created a robust package of analytics to not only decompose and reduce each market into easily digestible factors and analytic approaches, but to do so in a manner that is visually efficient and comprehensible and presents a common framework that can be applied to markets of all sectors. All of the fundamental model indicators are reduced to a simple, 0-10 scale with familiar red/green, dynamic coloring to indicate bearishness/bullishness. Common technical indicators are logically modified to provide comparable signals across markets. Color schemes are designed and standardized to help the analyst associate and quickly scan to connected features of the report. This effort is extended across sectors, so that logical connections can be made between the analysis of a currency rate and that of an agricultural market, bolstering the analyst’s understanding of and ability to interpret a common framework consistent with the reduction principle.