Numbers, facts, analysis — this is how I am trained to evaluate and decide.  This approach works well in the world of engineering and physical science.  However, I’ve found that in the domain of investing, quantitative methods sometimes function best as a means keeping grounded and objective; subjective approaches can be extremely effective and profitable.

The  cognitive process of investing can roughly subdivided into 3 categories:

  1. Intuitive (‘I’).  This portion is essentially driven by emotion, feelings, hunches.   Thoughts and choices are arrived at, not by inductive nor deductive reasoning, but by other means.  Cognitive science suggests that this process is achieved by the brains massive neural nets weighing massive stores of perceived information and arriving at conclusions based on past experience and training.
  2. Quasi-objective reasoning (‘Q’) mixes intuitive thinking with top-down reasoning  — idea first.  It also encompasses bottom-up reasoning (guided by intuition) — data first.  This approach blends analytical and intuitive thinking.
  3. Numerical/analytical (‘N’).  This approach focuses on quantitative empirical data.  Numbers are crunched and conclusions are obvious.  The difficult part is in ensuring both the inputs to the “number crunching” and the mechanisms of the “number crunching” are accurate.

I’ll use the shorthand I,Q,N to denote the processes enumerated above.   In my experiences, most well-examined financial decisions follow the basic pattern I→Q→N→Q→I or I→Q→I.  In other words, most financial decisions begin and end with intuitive (A.K.A. gut-level) thinking.  If a “disciplined investing approach” is strictly employed, a truncated →Q (or →Q→N→Q)  is added to the end of the process, where pre-determined “rules” are used to vet investment elections against predetermined suitability criteria.

So far my highest-return investment decisions have been I1→Q1→I2Q2→N1→Q3 decisions.  The first red part is the time-consuming part (in aggregate) because many ideas are discarded during the Q1 and I2 steps.  The quicker green part is the sanity and scale check. Q2 frames the decision, N1 crunches the numbers, and Q3 evaluates the outcome.  If the investment is deemed sound it is then scaled appropriately based on risk and value-at-risk ratios, otherwise it is discarded, or in some cases revised and re-evaluated.

Sigma1 Financial software can play an important role in the Q and N steps of the investment decision process.  The Q process can be either data-first or idea-first.  Sigma1 Financial also excels in the N process, imposing objectivity and performing the numerical heavy lifting.  What Sigma1 Financial software cannot nor is ever likely to do is participate directly in the I steps.  ‘I’ steps remain solidly aligned with the human element of the investment decision process.

The choice of letters ‘I’ and ‘Q’ is deliberate.  The investment IQ of investors is one important component to successful investing.  Higher investment IQs tend to result in superior investment returns.  Similarly, Qi is also critical to long-term investing success.  ‘N’ is used because it is neutral and disconnected.  Numerical and disciplined analytical methods provide ballast against the classic investing emotions of fear and greed (as well as unbridled enthusiasm and despair).

Investing IQ and Qi are brought to the table by financial professionals, while financial software provides powerful enhancements to Q, N, and especially QN and NQ, the areas separate from IQ and Qi.

The IQN domain is continuous, not discrete.  ‘I’ defines one edge which begins to blend into ‘Q’.   ‘N’ defines the opposite edge which blends with the other side of ‘Q’.  Q resides in the middle, merging aspects of I and N.

When investors understand IQN concepts, it helps to remove emotion from investment decisions, while acknowledging the importance of intuition.  IQN concepts also help demonstrate where and how financial software and analysis tools integrate with the investing process.

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