Lives, Lived, Will Live. Dies, Died, Will Die.

Introduction
I'm not sure where this thread is going to go, or where I plan on trying to take it. I really just wanted to talk about some ideas regarding 3 things to get some opinions on them and share some of my observations. New traders likely will have no idea what I am talking about. If this is you, please don't ask simple questions in this thread that can be answered with a search engine.

The 3 Main Ideas:
- Black-Scholes Model
- Geometric Brownian Motion
- Central Limit Theorem

I don't know everything about these 3 topics and I do not consider myself an expert on these subjects by any means.

The First Observation
Let's briefly talk about the Black-Scholes Model. The Black-Scholes Model is one of the most widely used models for stock price behavior. It is usually talked about when pricing European options. In this model, prices actually unfold or play out via Geometric Brownian Motion. This basically means that the model assumes all things are constant and that at any given time, the price of pair, is just as likely to move 1%, 2%, 5%, 10%, etc up as it is down.

It basically is the efficient market hypothesis in the sense that prices cannot be predicted. When choosing two points you think price may and may not go (SL and TP), the probability of going to each point is the same, assuming your RR is 1:1 (assuming no trading costs). This can be measured and proven many different ways and is always the case as long as your timeline for the trade to finish is infinite(you will wait till either SL or TP is hit). The one area where the Black-Scholes model fails is, it assumes the volatility of the market is constant, in this case, meaning that the time it takes to go from point to point is the same. This simply isn't true. This can easily be measured and even observed with your eyes.

So assuming the market is "efficient" and follows the Black-Scholes model, the only part of the market that isn't "efficient" is the volatility aspect. The time it takes to move from point to point. What does this mean to me? Time matters... a lot.

Lives, Lived, Will Live. Dies, Died, Will Die.

Thoughts?

With Time and Trading I think of Astrology and Gann

Nice topic Sys for a lazy weekend

These models are exceptional pieces of work despite their shortcomings as their successful application outside of periods of fat tails demonstrates that 'most of the time' we can adopt a position that the market actually is efficient.....and that predictive forecasts of direction are pointless.

It demonstrates to me at least that fundamentally there is very little 'actual' predictive certainty or 'alpha' in the market and this assumption, if correct, will ultimately cap long term returns (using the Law of Large numbers) to fairly low finite returns.....that can be expressed as an overall market return (Beta) plus or minus a small variation attributed to Alpha (market outperformance or market under-performance). Any extreme result above or below the market return will either be attributed to random chance or effects associated with leverage. Thus the majority of traders are actually being "fooled by randomness".

What biases an efficient market appears to be emergent market behaviours associated with repetitive participant behaviour and is contingent on whether the market is an open or closed system. If it was a closed system with no additional inputs or outputs, then modelling around an assumption of 'efficient markets' would rule. In any theoretical closed system, entropy dictates that system processes tend towards equilibrium. In a market context this simply ensures that an efficient market acts as a mechanism to re-distribute wealth. A real market however is open in that capital can be added, taken away, and the impacts of a sub-market such as Forex have a nested relationship with other sub-markets such as alternative financial assets which can top up or take capital from the Forex market in isolation. Of note is during periods of market stress where a market default in another asset segment can have a direct impact on the Forex market. Furthermore the participants in the Forex market are not perfectly constrained as participants in the Forex market can draw on resources external to the Forex system to keep a real market in a continuous state of flux avoiding the theoretical certainty of equilibrium that befalls a truly closed system. These external impacts lead to biases in an otherwise efficient market.

During the short term, emergent behaviors appear to be the overshoots and undershoots associated with collective participant behaviour that notably arise in periods of 'extreme'. What prevents these overshoots or undershoots from fully reverting back to equilibrium is the open nature of this market whereby participants enter and exit with or without capital and regulatory intervention injects or stifles economic stimulus in an attempt to reshape the short term impacts of market behaviour. What biases an efficient market over the long term appear to be the economic drivers that fundamentally drive participant behaviour and take a considerable period of time to play out and are a result of inputs/outputs from an 'open system'.

Aside from these broad postulates, and given that the market with it's open dynamic nature can never be quantitatively defined (non-stationery) we can never *actually* perfectly model how this market works and the best we can ever do is simply manage our risk and attempt to exploit these very broad assumptions while crossing our fingers. As with any complex 'open' system the actual outcomes over time are non-predictive emergent features associated with market dynamics and the complexity forged from the nested inter-relationships and 1 to many relationships that exist in any complex market.

IMO models help......but I recognise that their simplification assumptions are their undoing and ultimately it is the reality of the small variations to these broad underlying assumptions that will seal your fate and whether you live, lived, die or will die. The first thing we learn in physics is that conservation laws are only ever present and truly applicable for a closed system and are a result (or emergent feature) of system symmetries. As systems become progressively nested with other sub-systems these conservation laws then need to subsume the entire set of sub-systems to maintain their conservation properties. As a result broken symmetries arise in individual sub-systems that result in 'partial' or 'almost' conservation laws...well at least for sufficient variation in these conservation laws to actually lead to exploitable future opportunities :-)

Nice description, but it would be more attractive if you add relevant picture here! All the best.

IMO the main shortcoming of all these theories is that they try to explain the market in a purely mechanical way based on insufficient information.

Or in other words - these theories are incomplete! Why? Because they study only the end results and completely exclude the main component in the market - THE PEOPLE and their actions!

It's a bit like trying to judge (and to understand) a football game only by watching and analyzing the score.
Imagine this. You don't watch the actual game and the actions of the players. Only the score.
You can analyze the history of the scores and you can come up with all kinds of theories. But these theories cannot give you understanding.
In this case - what is a football game and how the score is formed.
To understand, you have to watch the real game. Or even better - take part in the game!

In the same way, analyzing ONLY the historical prices cannot give you true understanding about the mechanics of the market.

This principle of incomplete (or wrong) understanding because of insufficient information is explained perfectly in "Allegory of the Cave" by the Greek philosopher Plato. https://en.wikipedia.org/wiki/Allegory_of_the_Cave

IMO thinking in terms of efficient/inefficient or random/nonrandom market is counterproductive for the trader.

To understand the market, first you have to participate in the "game" and second you have to look behind and beyond the prices!
Deep into the underlying causes.

Reflexivity theory, feedback loops, game theory, general market (crowd) psychology.
This is where the truth is!

Once you begin to study these things, the price action and the patterns on your charts start to make sense! Then you realize that the whole debate about the randomness and the efficiency is pointless.

The academics clearly do not understand price behavior and the markets. Otherwise they wouldn't be working as teachers.

I'm not sure about your conclusion here - options are explicitly a way of trading volatility rather than assuming it's constant. In order to do so, the directional component is taken care of through delta hedging, and in FX the interest rates too, so options allow additional features of the market to be traded other than up or down.

In the real world, from the pricing of options we get implied volatility figures to see the market's best guess of volatility. Risk reversals give you best guess of direction.

I think the more important takeaway from this is given just how widespread FX options are, how does the model influence spot, rather than looking at the flaws of the model itself. Volatility now relates very tightly to bank's order book, which is why we get wild days of movement followed by glacial calm that unwinds right at the cut. No coincidence