In their book The Systems View of Life, authors Capra and Luisi distinguish between analytical thinking – which involves taking something apart to understand it  – and systems thinking – which means putting it into the context of a larger whole.  They note that,

“the tension between mechanism and holism has been a recurring theme throughout the history of Western Science.”

The tension is not so overt in investment analysis but is there nonetheless.   Portfolio managers tend to focus on the systemic wood whilst stock analysts get lost in the mechanical trees.  Strategists adopt top down systemic models in contrast to analysts bottom up forecasts.   Traders focus on the behaviour of the market system; analysts focus on mechanical understanding of the company.

Whilst both methods of thinking are important and necessary at different times, a proper Investment Framework needs to be built upon a Systems Solution.  In this post we distinguish between the two approaches.

The Analytical (Mechanichal) vs Systemic (Holistic) Approach

According to Capra and Luisi, the systems way of thinking involves “thinking in terms of connectedness, relationships, patterns and context.”   These systemic properties belong to the whole of the system and so cannot be understood by looking purely at the individual objects.  They distinguish the two approaches as follows:

Mechanical View

Systems View



Inherently multidisciplinary

Systems are everywhere and share common properties that apply across disciplines.



Systems nest hierarchically within other systems. What we call a part is merely a pattern in “an inseparable web of relationships”.  The analytical view sees this as a collection of objects.  The systems view sees the objects as nested in relationships.



We can measure parts, but need to map relationships. These relationship configurations occur repeatedly in certain patterns.



Mapping relationships is more qualitative than quantifying objects.  Systems complexity is an analysis of visual patterns.



Mechanistic view starts with structures interacting to give process. Systems view says structure is a result of process.



In mechanistic thinking there is objective truth. In systems thinking, truth is a function of the method of questioning. We are part of the system.

Ultimate/Systemic Cause

Proximate Cause

In a mechanistic world, local cause creates local effect. In a systemic world, behaviour is caused by non-local connections to the whole.


Approximate knowledge

If everything is interconnected then in order to explain something, we must know everything. Therefore, we must accept the concept of approximate knowledge. These models can nevertheless be effective.

Reductionist Equity Analysis vs Systems Equity Analysis

These general principles of analysis apply as much to investment analysis as they do to other physical and social sciences.  A common example would be the distinction between the analytical approach of valuation and the more systemic approach of value.

In valuation, the analyst uses bottom up analysis of cash flows, returns and discount rates to develop “accurate” valuations.  In contrast, the idea of value understands the difficulty of knowing these numbers exactly.  Nevertheless, it is possible to develop an approximate understanding of how the company and share price “systems” might behave over time.  This approximate knowledge helps to evaluate risk and reward.  We discussed this idea in more detail in The Intrinsic Value Myth. 

There are numerous other examples of how we can apply a systems view to expand our investment framework beyond simple analysis:

Reductionist Equity Analysis

Systems Equity Analysis


Analysts become expert in one industry field and aim to know everything in that field.

They search for specific, in depth knowledge that can be used to understand outcomes.


Investors become expert in the generic models that are applicable across many different investments.

They search for underlying financial patterns in behaviours at company/industry/market levels.


Focus on bottom up knowledge:

Company strategy


Cash Flow

Balance Sheet


Focus on top down relationships:

Industry Structure (relationships between company strategies)

Returns – relationship between earnings and capital

Earnings Quality – Relationship between earnings and cash flow



Financial Ratios

Tabulated Data


Relationship between earnings and share prices

Financial Trends








Cash In vs Cash Out



Prices determine profits based on cost curve.


Profits determine prices by altering the cost curve.


Ask question, receive answer.

Evaluate as true or false.


Does the nature of the question I ask, or the manner of my asking, impact the answer?

Contextualise answer.

Proximate Cause

Earnings fell because competitor x launched a product

Ultimate/Systemic Cause

Earnings fell because returns were unsustainable.




Risk/Reward Assessment


Systems thinking is critical in building a succesful investment framework.   Not only does it help understand the market better, but it does so in a way that increases our awareness of our lack of knowledge.  This in turn avoids overconfidence and helps manage risk.

The best way to conlclude is with a quote from the wonderful book, The Dao of Capital by Mark Spitznagel:

“Anyone can see the pinecones in the tree.  None can see the trees, none can foresee the forest in the pinecone.”