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We should start from the premise that we operate from the point of view of self-preservation. This would be preservation of the immediate self, but also preservation of offspring and peers as a reflection, since they also represent a vehicle of the self into the future. Then, our existence is contingent on our ability to predict the future. The better the prediction, the better are the chances to stay alive and to project our own existence. "Will I be alive tomorrow if I stay into this cave ? Will I cripple myself if I walk barefoot on gravel ?"

Any prediction requires two elements:

1) Prior knowledge, the more the better.
2) Analytical tools to reliably derive an outcome from that prior knowledge.

To be efficient at this, we need to be able to process information in the most deterministic way possible. This means that the most valuable information is information that we can put through our analytical machinery (the brain, or any other sufficiently powerful calculator), and that can lead to a useful forecast of a given event.

The keyword here is "determinism", something that requires a level of rigidity that may be challenging for a human brain. This is actually where digital data storage, math and digital computers can help greatly.

The scientific method is also built on the concept of determinism. If you can consistently use prior knowledge to determine a future event, then your actions are useful and deserve more exposure. If instead a theory cannot predict the outcome, then the theory has no practical value. Of course the inability to prove something doesn't mean that a theory is necessarily invalid, but for all intents and purposes, one simply cannot rely on a formula that cannot forecast an outcome.

One could think of a deterministic structure as a web of points of determinism. A graph where each node is connected to other nodes. The more the connections, the more reliable is a certain fact established by that point of determinism. Nodes at the fringe of the web, with virtually no connections to others, must still exist, otherwise there would be no progress, but they are less reliable, because they have less support than the better interconnected points.

Image courtesy of Simon Cockell

The network structure is pervasive in nature, and it's how our brain is built. This structure is also what reality is to us: things are more or less real, depending on how well we understand them, meaning how well they relate to other pieces of data, with the goal of making useful predictions. The moment in which such structure comes less, it's also when reality dissipates. Reality is indeed a structure.

Going beyond definitions. Once we establish all this, it should be clear that to have any kind of success at any level, one is better served by leveraging determinism as much as possible (unless "success" is defined by self-destruction, but that's uninteresting and easily obtained).

In practice, establishing a robust level of determinism can be very difficult. The difficulty of establishing a clear logic connection between concepts can vary wildly. This depends on the amount of data at play and the process of analysis required to interpret those data. Most complex subjects are filtered through the lens of experts, which use their skills and experience to reduce complex subjects to a simplified form that can be easily digested by the non-expert. Experts however can often disagree on fundamental issues, hopefully in good faith, but sometimes in bad faith, too. On top of that, communication of the synthesized concepts usually goes through additional levels of simplification and bias. For larger issues, experts defer their communication to technical leaders, political leaders, public-relations, editors and finally journalists/writers.

Putting potential malice and communication issues aside, there's an inherent problem of complexity. Some fields necessarily rely on complicated statistical models to attempt to establish cause and effect while operating at a level of knowledge that is not very detailed.

Medical trials are a good example of an attempt to establish determinism from a very complex system (the human body) that in some cases one has to treat as a black box. A "black box" being a system that generates an output for some inputs, although the user doesn't completely understand the complex mechanics that make the box work. With medicine there may be a general understanding of the benefits of certain elements on the human body, but there is also hidden complexity of the system that forces researches to take a trial-and-error approach, usually starting from other, more expendable, living creatures.

The concept of "black box", stylized

Another problem with establishing determinism is that too much reality hurts. Suspension of disbelief is a necessary tool for survival. It's necessary against the nihilistic picture that naturally arises from thinking about existence. Imagination is essential both to cope with reality of existence, and to expand the vision of reality. At the same time, imagination can easily be abused to the point of becoming counterproductive.

In my opinion, while it's essential to keep a grasp on the better established aspects of reality, it's also important to let the mind run free, and to occasionally listen to "the crazies" (see "Adopt a conspiracy theorist"). This is a good mental exercise and also a reminder that reality is a dynamic concept. To push this to an extreme, in some ways, the person that cuts his arm looking for an alien microchip, may be closer to the universe than the person that wakes up at 8 in the morning to go to the office for 40 years. The schizophrenic has less ties to the common concept of reality, but our common concept of reality is also infinitesimally limited in the context of the greater universe.

A less extreme example of lateral thinking is that of religions. The modern educated man deride religions and the concept of a God, as some silly coping mechanism, however the fundamental questions that religions attempt to address never went away. One may decide to ignore those questions for a while, but they keep coming back. This is why nowadays theories about living in a simulation are so popular, it's just a modernized version of religions. It's a framing that has a better grounding with our map of reality, one that includes more advanced reasoning tools, but it's a framing that also validates the fundamental pursuit of ancient religions. In fact, the "simulation theory" could easily become the basis of new religions, where God is no longer an old man living in the clouds, but a game developer that clicks on you and checks your status from time to time.

"Little Computer People" on the C64

In conclusion, it's safe, efficient and productive to rely on the better established areas of the "reality network", but it's also important to keep in mind that there is a virtually infinite potential to explore and expand that structure, and that our point of view is extremely limited. Finding the right balance is the hard part, as with everything. Stay at the center and you're golden, but you're going to live a derivative life like any working bee, move too far to the edges, and life can become a mix of fantasy and paranoias. May the most balanced player win !

Below, a tribute to Terry A. Davis, a fellow programmer that was definitely living on the outer side of the network.

When I first became interested in algorithmic trading, I didn't have any kind of trading experience. I did however have some very limited experience with flight simulation and weapons systems as an evolution from working in game development.

Although I didn't know this at the time, simulation is just about the most important thing when it comes to developing trading strategies.

In weapon systems, simulation allows to estimate how reachable a target is. This can be used either to extrapolate fundamental formulas to be applied in real-time, or the simulation itself can be executed in real-time, if a weapons system has enough mobile computing power.

In the first case, simulation can help to build tables of parameters for quick retrieval when a weapon needs to be used. Let’s say that one has a cannon with a new kind of ammo. A well-established analytical solution can be adapted for the new ammo. But for more complex cases (i.e. different aerodynamical profile of the projectile) a computer simulation can find a more precise solution. A machine learning system can try millions of possible variations of parameters, such as elevation of the gun and amount of propellant, find the best possible one for given distances, and build a table that can then be consulted when the time comes to use the cannon to hit a target at a specific location.

Below is a ballistic table used in World War 2:

WW2 ballistic tables courtesy of tankarchives.ca

Here's an interesting explanation of bomb drops procedure in Vietnam using a F-4, which didn't have a computer for the task.

In the second case, a more advanced weapon system, let’s say one in a modern jet fighter or in a modern tank, could forgo with most precalculations and instead have the simulation running live. The benefit of this second solution is that it can adapt to more variables and it can improve with a software upgrade.

In practice, setting up a simulation that is accurate enough to replace most of the experimental work, is not a simple thing, unless one is already developing a simulation, such as a flight simulation game. When the time came to build a believable weapons system in my experimental flight sim, it was only natural to use the simulation logic already developed for the game to calculate the launch envelope for a bomb or a missile, or the homing guidance for a missile.

Why manually extract a formula, when you can simply use the already existing simulation engine to test thousands of trial-runs and find the best parameters for the optimal launch envelope ? This was my epiphany in regard to the power of building a simulation to solve problems in a more generic and simpler way. Once you have a simulation for something, then you can use raw computing power to search for the best variables, whether that’s to built a table to consult at a later time, or whether it’s to be used actively up to the point of launch of a projectile, or even during flight of a guided missile.

Practical application of simulation in the real world is probably something in between. Supercomputers can be used to analyze more complicated matters such as the aerodynamics of a particular kind of fins of a missile, while on-board computers can work on launch envelopes and homing guidance. For sure, once a problem is shifted into software, chances for improvement increase sensibly.

This does connect neatly to algorithmic trading and how fundamentally dependent it is (or it should be) on the concept of simulation. No sane person should ever attempt to trade without first having a computer model. Some may disagree, but I can’t imagine how having an analytical model would hurt success.

The only drawback would be the issue of the reliability of a computer model of something that is very stochastic in nature. A weapon has little room for error. Simulating a projectile may be difficult, but the outcome is immediate and straightforward. With trading, instead, success can only be found in odds with large numbers in an highly dynamic setting. This makes the process of optimization more difficult and often counterproductive, but this is a discussion for another post.

In 2022, war is now truly a live event. With cell phones, body cams and quad-copter drones, social media is filled with an abundance of the most disturbing footage that one can imagine.

This is certainly shocking from the perspective of societies that have lowered the bar for conflict to that of verbal micro-aggressions. At the same time, this is also very educative. It's a perspective into what humans are and can be (see also "The explosive 'boredom' problem of civilized societies").

I see interviews of people living underground and struggling simply to stay alive and find water and food, and I think of what I pictured from the WW2 stories from my grandparents.

Image courtesy of Alexander Turnbull Library

Everything checks… that's the war I've been hearing about, a war where human cost is obvious, one that feels close enough, because it's not happening to the third world. We're used to ignore the homeless in the streets, but if it's someone that looks like he has a job like us, then that's a different matter. Affinity with race also helps a lot to mobilize millions of voices on Twitter. As much as we can pretend that we don't care, we all instinctively feel more empathy towards living beings that look more like us. Our level of empathy and altruism varies in a continuous scale from two extremes, where most affinity is generated by our own children, and least affinity is probably some sort of alien insect coming from another galaxy.

Another major reality check from this war is how biological gender suddenly matters. Although some women are involved, they are very few and are usually relegated to being snipers, the kind of activity that requires less direct conflict. Most women are instead grouped with children and elders, while men are actually forced to go in combat, at least from the Ukrainian side. I think that we can safely assume that when shit truly hits the fan, the gender equity construct that has evolved in western societies goes straight into the pooper.

One could say that if there were no wars, then men and women could almost become interchangeable, but to expect a natural world without conflict is even more utopic than to expect a natural world without biological predispositions. Those that seek total equity for humanity have a better chance looking for it in the after-life, or in some fictional far future where any form of individualism is crushed together with all major human traits that make us what we are.

Meanwhile, in the real world, it would be wise to keep in touch with reality, because sooner or later the protective shield under which we are born and raised, will falter, and at that point understanding human nature will become a matter of survival.