In the following post, I will define the concepts of determinism and stochasticism to clarify and refine the approach. I will also explain what 'probability' actually means from a mathematical perspective, as an introduction to the fundamentals of risk management.
Determinism means that the final output of a process is causally inevitable. It implies that a process is entirely driven by causality, and the outcome depends solely on the variables involved. There is no randomness, and thus the system will always produce the same output from a given starting condition or initial state.
For example, imagine a computer running a well-defined algorithm. It will always produce the same output for the same inputs, calculated deterministically. Our classical physical laws have also been viewed as deterministic because they are based on differential equations and function algorithmically.
However, in the real world, no system is truly deterministic—not even a computer. Using deterministic models is a simplification we often employ when analyzing processes at a macro level. This simplification works because it is easier and "good enough" to describe certain systems this way (e.g., the path of a thrown rock).
Why is it "good enough"? Simply because complex systems tend to exhibit properties that their individual parts do not possess. When these parts interact with one another, they create a larger unit or system that produces well-observed, repeating patterns, unified behaviors, or properties that can be described deterministically. This phenomenon is known as emergence.
Take the example of a thrown rock: beyond the macro level, countless variables and forces (wind, temperature, air pressure, momentum of small particles, molecules, etc.) influence its path. However, on a macro scale, the rock follows a clear trajectory that can be described reasonably well using deterministic models. If you throw it again with the same force, the path will be almost identical.
Similarly, society is composed of thousands of individuals, each with their unique inner world. Yet, as a collective, society exhibits regular behavioral patterns.
(This additive effect of random processes is a primary subject of chaos theory.)
On the other hand, when we discuss random processes, we refer to stochasticism. Stochastic systems are entirely random, meaning there is a 50-50% probability for various outcomes, as discussed in my previous article on volatility.