Miniseries: A Journey Through Systems, Boundaries, and Entropy: Part 2
This miniseries expands on the concepts introduced in our prior 5 part miniseries “The Power of Process” by delving deeper into the mechanics of Complex Adaptive Systems (CAS). It uncovers the intricate processes behind system evolution, exploring core principles like boundaries, symmetry breaking, iterative rules, and entropy. The series reveals how these forces shape the complexity observed in everything from natural ecosystems to financial markets. By emphasizing the interconnectedness and structured nature of systems, it provides a comprehensive view of how the universe evolves, offering profound insights into growth, adaptation, and eventual decline.
Part 2/5: Unveiling the Power of Process
The way we traditionally think about systems is often focused on the static, tangible components—the things we can observe and measure. Whether it’s a financial market, an economy, or even a biological ecosystem, we tend to look at the things: prices, organisms, or numbers. But what if this perspective is only scratching the surface? What if, beneath these seemingly isolated elements, there exists a vast, interconnected web of processes within processes that are continuously shaping the world around us?
In this post, we embark on a journey to reconsider the very nature of things, not as isolated objects but as products of dynamic, adaptive processes. By lifting the blinkers of traditional thinking, we’ll see that systems—especially Complex Adaptive Systems (CAS)—are not driven by static components, but by continuous interactions, feedback loops, and emergent patterns.
A Shift in Perspective: From Things to Processes
At first glance, financial markets might seem to be made up of “things” like stock prices, commodities, and assets. But to a trend follower, the focus is not on the price at any given moment, but on the movement of that price over time. The market is not a static entity but a constantly evolving process, shaped by countless interactions and forces that work together to form trends.
What can we learn from this? It invites us to shift our attention from the things themselves to the processes that give rise to these things. Every market trend, every price movement, and every trade is part of a larger system—a process inside a process—where interactions between market participants, economic forces, and global events continuously reshape the landscape.
In this light, markets are living, breathing systems, where what matters is not the individual “thing” (such as a stock or bond) but the interplay of forces that drive its behaviour.
Peeling Back the Layers: Processes Within Processes
Let’s start with a simple example from nature: an ecosystem. At first glance, we see animals, plants, water, and land—distinct “things” that we can point to and name. But if we look closer, it becomes apparent that none of these “things” exist in isolation. Every plant is growing, every animal is moving, and the water is constantly flowing. These aren’t static entities—they are processes unfolding over time.
Zoom in even further, and you’ll see that a tree, for example, isn’t just a tree; it’s a collection of interacting processes—photosynthesis, nutrient absorption, growth, and decay. The same goes for every element in the ecosystem. Even the soil is a dynamic process, full of life, as microorganisms break down organic matter. In reality, every so-called “thing” in the ecosystem is an ongoing process interwoven with other processes, contributing to the overall dynamics of the system.
Taking this one step further: the tree, the river, or the predator and prey aren’t things in the traditional sense; they are processes that unfold over time, interacting and influencing each other in feedback loops that sustain the ecosystem. When we view ecosystems this way, they become Complex Adaptive Systems (CAS)—dynamic, evolving networks of processes within processes.
Autonomy Versus Embedded Dependency
However, this view brings us to a deeper realization: the idea of an autonomous system—something that exists independently—dissolves when we examine the world as a collection of interdependent processes. What might seem like autonomous systems are, in reality, deeply embedded in larger systems that they depend on for survival.
Consider a human being. At first glance, we perceive ourselves as autonomous, self-contained entities, capable of acting independently in the world. But this perception is an illusion when examined through the lens of processes within processes. Our survival depends on the larger systems in which we are embedded. We rely on the oxygen-rich atmosphere to breathe, the biosphere to provide food and water, and the planet’s gravitational field to keep us grounded. Remove any one of these systems, and what we consider “autonomy” quickly vanishes.
Take, for example, the scenario of a human being in deep space. On Earth, we might feel entirely independent, but the moment we leave the planet’s oxygen-rich atmosphere and gravitational field, our fragile dependency on life support systems—like oxygen tanks and pressure suits—becomes starkly evident. What seems like autonomy is, in fact, a product of a deeply co-evolved relationship between human biology and Earth’s environmental systems.
Scale Invariance and Boundaries in Nature
Before diving into scale invariance, it’s essential to recognize that not all processes are uniform across scales. In fact, understanding how a process adapts as it grows or shrinks is fundamental to grasping the true nature of Complex Adaptive Systems. Scale invariance plays a key role in identifying where self-similar patterns hold and where new adaptations are necessary. Processes that might seem simple and consistent at one scale can manifest complex and even contradictory behaviors at another. Recognizing these shifts allows us to understand both the potential and the limitations of systems that evolve through embedded processes.
In nature, scale invariance is evident when similar patterns repeat across different sizes or scales. A classic example is the branching structure of trees and rivers, where smaller branches resemble larger ones in shape and form. This self-similarity, or fractal nature, can be found in many natural systems, from the branching of blood vessels in organisms to the distribution of tributaries in river networks. In these systems, simple, recursive growth rules generate complex patterns that look similar whether viewed up close or from afar.
However, this scale invariance has limitations because physical boundaries change how systems function at different scales. For example, ants can carry objects many times their weight, showcasing high relative strength due to their small size. However, if an ant were scaled to human size, it would collapse under its own weight because its muscles and exoskeleton could not support the larger mass—a constraint imposed by the square-cube law. This law illustrates that as size increases, volume (and therefore weight) grows faster than surface area, setting a boundary where strength no longer scales in a simple, self-similar manner.
In biological systems, metabolic rates also exhibit non-linear scaling. Smaller animals, like mice, have fast metabolisms to sustain their bodies, while larger animals, like elephants, have much slower metabolisms relative to their size. This boundary in metabolic scaling shows that efficiency and energy usage change with size, preventing large organisms from functioning identically to small ones. Thus, while fractal structures in nature demonstrate self-similarity at different scales, physical and biological boundaries impose constraints that alter behavior and efficiency as systems grow larger.
These examples illustrate that scale invariance operates within boundaries that define when self-similar patterns can persist and where different structures or adaptations are required. Boundaries, whether physical laws or metabolic constraints, ensure that systems adjust to their scale, often limiting how far scale invariance can apply.
Co-Evolution and Systemic Dependencies
This concept of embedded dependency extends to all living systems. Every organism is part of a vast, interconnected web of life that has co-evolved over millennia. Our survival, for instance, is not just a result of individual strength or adaptation but is deeply tied to a network of relationships that span across various systems. From the oxygen we breathe to the microorganisms in the soil that support plant life, every living organism depends on the systems in which it is embedded.
This interdependence stretches beyond the biosphere to include the atmosphere, oceans, and even the Sun, whose energy powers the entire system of life on Earth. In this light, the human body itself is a prime example of processes within processes. Each bodily system—respiratory, circulatory, nervous, and digestive—relies on external inputs from the environment, like air, water, and food, to function. But these inputs are themselves products of other interconnected systems: oxygen is created by plants and algae through photosynthesis, water is distributed through the hydrological cycle, and food emerges from ecosystems.
However, co-evolution isn’t limited to natural systems. Technological systems, too, are embedded in larger networks and have co-evolved with other systems over time. Consider the internet—what started as a network for sharing academic research has co-evolved with global economies, communication systems, and social networks. Today, industries, governments, and even personal relationships are shaped by the capabilities of the internet, and in turn, the internet has adapted and evolved with these systems. The rise of artificial intelligence (AI) and machine learning also illustrates this dynamic. As AI systems have grown in sophistication, they’ve altered industries, economics, and even our understanding of human potential, creating a feedback loop where technological advancements spur societal changes, and societal needs drive further technological development.
A Planetary Web of Life
In this sense, Earth’s biosphere is deeply interconnected with the atmosphere, which regulates climate and weather, and the energy from the Sun, which powers photosynthesis and drives the global energy cycle. These layers of systems, all nested within one another, have co-evolved over time to create the conditions that allow life to thrive. The relationships and dependencies between these systems are not coincidental but rather the result of millions of years of mutual adaptation. The oxygen we breathe today, for instance, is a product of billions of years of photosynthesis by early life forms, shaping the atmosphere to support increasingly complex organisms.
We can apply this thinking to all systems. For example, the life of a predator depends on the prey it hunts, the prey depends on the plants it consumes, and the plants rely on sunlight and soil nutrients to grow. Every level of the ecological system is a process embedded in another process, each layer depending on the others for survival. The planet itself is similarly embedded in broader cosmic systems—the Sun’s energy, the gravitational pull of the moon, and the stability of the solar system all help maintain the conditions necessary for life on Earth.
Complexity Through Interdependence
When we peel back the layers of these processes, we begin to see that complexity arises not from the isolated existence of individual elements but from the interconnections between them. Every subsystem, from a human being to a planetary ecosystem, is part of a larger web of interactions that sustains the whole. The boundary between what we perceive as an autonomous system and its environment blurs, as the system cannot exist without the external processes on which it depends.
For example, consider the global economy, another CAS. At first glance, individual markets, corporations, and financial institutions may seem to function as independent units, but they are all deeply embedded in a network of trade relationships, regulations, and technological infrastructures. A single disruption, such as a financial crisis or a major technological innovation, sends ripple effects throughout the system, influencing the behavior of participants at every level. This systemic dependency ensures that each part of the economy is connected to, and influenced by, the larger system, just as humans depend on the ecosystems they inhabit.
A Co-Evolved System of Systems
In conclusion, all systems, whether natural or human-made, are part of a co-evolved system of systems, where each subsystem plays a crucial role in sustaining the whole. This web of interconnected processes allows complexity to emerge and systems to adapt and evolve. As one system changes, others must adjust, creating a continuous process of co-evolution. This principle applies not only to living organisms and ecosystems but also to human systems like economies, technological networks, and societal structures.
Viewing the world not as a collection of isolated things but as a dynamic interplay of processes within processes reveals that autonomy is an illusion. Everything is connected, and the survival of each part depends on the health and functioning of the larger system in which it is embedded. This process-driven understanding of Complex Adaptive Systems illuminates the deep connections that underpin both natural and human-made worlds.
One to Many and Many to One: Power Laws and the Sum of Its Parts
In addition to these nested processes, ecosystems—and financial markets—also reveal another powerful dynamic: One to Many and Many to One relationships. These relationships illustrate how the actions of a single element can have widespread consequences, or how many small actions can collectively influence a single outcome. These non-linear relationships often follow what are known as power laws.
Power laws describe situations where a small change in one part of the system can lead to disproportionately large effects elsewhere. Unlike in linear systems, where cause and effect are directly proportional, power law systems exhibit non-linearity—small inputs can produce massive, unpredictable outcomes, and vice versa. In simpler terms, power laws explain why “the rich get richer” or how a minor tremor can sometimes lead to a massive earthquake. The frequency and magnitude of events are not evenly distributed but follow a pattern where a few large events dominate over many smaller ones.
Let’s first look at a natural example. Consider the role of a single canopy tree in a rainforest. While it may seem like just one element in the ecosystem, this tree supports countless other processes. It provides shelter for a multitude of species, serves as a conduit for nutrient exchange, captures water, and regulates temperature. From insects living in its bark to birds nesting in its branches, this single tree influences many parts of the ecosystem, demonstrating a One to Many relationship. The tree’s presence disproportionately impacts the environment around it.
On the flip side, the health of the tree itself depends on countless smaller factors—a Many to One relationship. It relies on microorganisms in the soil for nutrient processing, other plants for symbiotic relationships, and animals for seed dispersal. Numerous small, seemingly insignificant processes come together to maintain the well-being of the tree itself.
Together, these relationships create the conditions for a power law dynamic, where the sum of these interactions results in a system far more complex and resilient than the sum of its parts. The tree, as both an influencer and a dependent, exemplifies the non-linear power laws at play: the actions of one can influence many, and many small actions can determine the outcome for one.
The Pareto Principle in Complex Adaptive Systems: Amplifying One-to-Many Dynamics
Building on the One-to-Many and Many-to-One dynamics, the Pareto Principle (80/20 rule) illustrates how, in Complex Adaptive Systems (CAS), a small fraction of elements often drives a majority of the outcomes. This pattern emerges from feedback loops and network effects, where certain agents accumulate influence through positive reinforcement, elevating their significance within the system.
In natural ecosystems, keystone species embody this principle by exerting disproportionate influence on their environment. These species create ripple effects throughout their ecosystem, impacting many other organisms and ecological balances. In financial markets, a small subset of assets or investors frequently dominates value fluctuations, with top stocks, for example, accounting for most of the index movements. In both scenarios, a few key players embody the Pareto effect, reinforcing One-to-Many dynamics on a broader scale.
Within CAS, the Pareto distribution highlights the formation of powerful “hubs” through preferential attachment—where new entities are naturally drawn to already dominant nodes. This creates a self-reinforcing cycle, where prominent nodes grow in influence, leading to concentrated impact. While these hubs improve efficiency and specialization, they also introduce system vulnerabilities, as an over-reliance on a few components makes the system sensitive to disruptions.
This concentration of influence reflects a CAS’s tendency toward dynamic equilibrium, where few components balance complex interactions across the whole. In systems from biological to technological networks, the Pareto Principle illustrates how interconnectedness naturally breeds a landscape where a minority holds significant power, driving adaptability yet introducing unique risks inherent to CAS structure.
Financial Markets: A Nested System of Relationships
This dynamic is also present in financial markets, which operate as a nested system of relationships, much like ecosystems. At first glance, individual markets, corporations, and financial institutions might appear to function as independent units. But when viewed through the lens of power laws, it becomes clear that financial markets are deeply interconnected systems, where small events can have massive impacts.
For example, consider the 2008 global financial crisis. It began with an increase in subprime mortgage defaults—a seemingly localized problem. However, this small disturbance set off a chain reaction, revealing deep interconnectedness within the financial system. Mortgage-backed securities held by banks worldwide collapsed in value, triggering a liquidity crisis that reverberated across markets. This is a classic example of a One to Many relationship, where a single disturbance in the housing market led to a global financial meltdown, highlighting the disproportionate impact small events can have in a power law system.
Conversely, the collective behavior of millions of market participants—banks, hedge funds, traders—can have an equally profound effect on the stability of the entire financial system. This Many to One relationship was evident in the aftermath of the crisis, when central banks worldwide coordinated efforts to stabilize markets through quantitative easing. The decisions of millions of individual actors fed into the broader response, showing how small actions, in aggregate, shape the overall market.
In both ecosystems and financial markets, power laws arise because of these One to Many and Many to One relationships. The interconnectedness of components in a system means that small actions can lead to outsized consequences, while large inputs sometimes have surprisingly limited effects. This is why power laws are a defining feature of Complex Adaptive Systems: they explain how the whole system’s behavior is shaped by the dynamic interplay between its parts, often in unpredictable and non-linear ways.
Financial Markets: Not Just Things, But Dynamic Systems
Financial markets provide a powerful illustration of this shift in thinking from static “things” to dynamic, adaptive processes. As a trend follower, you are trained to view the market as a series of evolving trends, rather than a mere collection of isolated prices. These trends emerge from the complex interplay of countless factors—traders’ actions, institutional strategies, macroeconomic shifts, and changing market sentiment.
By focusing on the process of price evolution, rather than just the price at any given moment, you start to uncover how trends form. Trends are not the outcome of a single event, but rather the accumulation of countless small actions interacting over time. Every trade, decision, and external event is woven into a larger process that is itself embedded within even larger economic, social, and political systems.
In this way, a market trend is not a “thing” in isolation but a dynamic process—an emergent behavior that reflects the continuous adaptation of market participants to ever-changing forces. The real insight for the trend follower lies in understanding how these myriad forces interact, respond to feedback, and, together, create the patterns we observe in the markets.
Beyond Averages: Capturing Market Complexity
When exploring financial markets through the lens of Complex Adaptive Systems, it becomes clear that the patterns we observe arise not from isolated events but from a web of interdependent processes, where nonlinearity and power laws shape behavior. Markets don’t respond linearly to individual actions; instead, they reflect the amplified effects of feedback loops and collective actions, which power laws describe. In these systems, small decisions can have outsized impacts, while many large trades may balance out, highlighting a fundamental aspect of complexity: outcomes are rarely proportional to inputs.
In analyzing financial markets, simplified metrics like averages or per capita measures are often used to provide a general sense of trends or behavior. While these figures offer a convenient overview, they overlook the deeper network effects and interdependencies that truly define market dynamics. Financial markets are not merely aggregates of individual decisions; they are complex, adaptive systems shaped by interactions that ripple through the market.
For instance, averages tend to smooth out individual extremes, obscuring volatility, contagion, and the influence of large trades or unique participants. During market crashes, averages may indicate a steady decline, yet they hide the scale and intensity of specific sell-offs and the feedback loops that amplify downturns. These averages give an impression of linearity that does not capture the reality of sudden cascades in price.
Similarly, per capita metrics can be misleading in financial contexts, as they assume uniform participation or influence across all market participants. In reality, a small group of institutional traders often holds significant sway over market direction, and their large-scale trades can lead to rapid shifts in prices. When per capita figures are used, they imply a simplistic, “one person, one influence” approach, obscuring the disproportionate impact that key players or major trades have on the market.
By focusing on averages and per capita measures, we risk oversimplifying the forces at play and ignoring patterns such as herding behavior and market contagion. Herding behavior arises when traders mimic each other’s moves, often driven by sentiment or fear, leading to rapid changes that an average simply cannot capture. Similarly, market contagion spreads quickly across interconnected sectors, often turning a localized issue into a widespread crisis. These are precisely the dynamics that averaged metrics cannot reveal.
To gain a true understanding of financial market behavior, it is essential to look beyond per capita and average figures. A systems-based approach captures the scale-dependent behaviors and feedback loops, offering a view of the market as a network of agents whose actions drive emergent phenomena. Through this lens, market dynamics become clearer, revealing insights that are otherwise hidden within oversimplified, aggregate metrics.
Conclusion: Seeing Beyond Things, Embracing Processes
At the beginning of our exploration, we challenged the traditional mindset of viewing the world in terms of static, isolated “things.” Whether we’re talking about financial markets, ecosystems, or technological systems, the common tendency is to focus on the tangible, measurable components—the stock prices, the plants, the algorithms. But as we’ve journeyed through the intricacies of Complex Adaptive Systems (CAS), it becomes clear that this view only scratches the surface.
The reality is far more dynamic. What we perceive as fixed elements are merely snapshots of ongoing, evolving processes—processes that are deeply interconnected and adaptive, continuously shaping and reshaping one another. From the way a tree grows and interacts with its environment, to the way market trends emerge and dissipate, everything operates as part of a larger, intricate web of interactions and feedback loops.
By shifting our perspective from “things” to “processes,” we unlock a deeper understanding of how complexity arises in the systems around us. We see that markets aren’t driven solely by individual trades but by the complex interplay of millions of decisions, economic forces, and global events. Similarly, ecosystems aren’t just collections of organisms—they are networks of life processes that sustain one another through co-evolution and adaptation.
This new lens transforms how we approach both natural and human-made systems. It reveals the hidden forces at work—feedback loops, power laws, emergent behaviors—that shape the behavior of systems over time. And it underscores a fundamental truth: nothing exists in isolation. Every market trend, every technological innovation, every living organism is part of a larger process, embedded within other processes, co-evolving and adapting.
By embracing this process-driven understanding, we move from a world of static objects to a world of dynamic interactions. We can better navigate the complexity of the systems we depend on—whether predicting market trends, managing ecosystems, or adapting to technological change. The blinkers of traditional thinking are lifted, revealing a richer, more interconnected reality where everything is in motion, constantly influenced by the processes that govern its behavior.
As we continue our journey into the study of CAS, this shift in perspective will help us see the world for what it truly is—not a collection of isolated things, but a living, breathing system of processes within processes, where complexity, adaptation, and co-evolution shape the world around us.