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1 year
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The best algorithmic developers aren't just programmers - they're traders who code.
I develop and code custom trading strategies, automation tools and custom software across multiple platforms and languages, including TradingView (Pine Script), MetaTrader 5 (MQL5), Python and other modern development frameworks.
Looking for a quantitative developer role.
I can turn trading strategies into fully functional systems.
Extensive experience with Linux (Gentoo, Debian) and Unix systems (FreeBSD, OpenBSD)
I’m available for projects.You can ask for me directly in the Freelance section.
How Observation Changes Outcomes :
In quantum mechanics, when light (or electrons) passes through two slits, it creates an interference pattern on the screen behind them.
Each particle seems to go through both slits at once, existing in a super position of all possible paths and the resulting pattern reflects the probabilities of where the particle could land.
If you try to measure which slit the particle goes through, the interference pattern disappears.
Observing the particle forces it into a definite state - it goes through one slit or the other.
The act of measurement collapses the wave function and fundamentally changes the outcome.
Before you check a trade, it’s in super position.
From a statistical perspective, your trade has a probability of winning or losing based on your system but you don’t yet know the outcome.
The trade is evolving naturally, just like a quantum system.
The moment you look at it, your observation collapses the “trade wave function” into a definite state - good or bad, winning or losing.
That observation triggers an emotional reaction — stress, fear, or overconfidence—which can cause you to break your plan, over-leverage, or revenge trade.
Just like in quantum mechanics, the act of measurement affects the system.
If you hadn’t looked, the system would have continued evolving naturally and you would have followed your plan without emotional interference.
This analogy mirrors the quantum concept perfectly - observation changes the outcome, not because the market changed, but because your interaction with it changed your behavior.
In other words, checking too often destroys the natural probabilistic outcome of your system, just like measuring the slit destroys the interference pattern.
The trade itself hasn’t changed; your observation changed how you interact with it, which changes the outcome.
Final Thoughts:
Traders, you know what I’m talking about — in a demo, you can leave your strategy untouched for days, weeks, even months.
The moment it goes live, you start checking too often, micromanaging your trades, and suddenly your observation is affecting the outcome.
I develop and code custom trading strategies, automation tools and custom software across multiple platforms and languages, including TradingView (Pine Script), MetaTrader 5 (MQL5), Python and other modern development frameworks.
Looking for a quantitative developer role.
I can turn trading strategies into fully functional systems.
Extensive experience with Linux (Gentoo, Debian) and Unix systems (FreeBSD, OpenBSD)
I’m available for projects.You can ask for me directly in the Freelance section.
How Observation Changes Outcomes :
In quantum mechanics, when light (or electrons) passes through two slits, it creates an interference pattern on the screen behind them.
Each particle seems to go through both slits at once, existing in a super position of all possible paths and the resulting pattern reflects the probabilities of where the particle could land.
If you try to measure which slit the particle goes through, the interference pattern disappears.
Observing the particle forces it into a definite state - it goes through one slit or the other.
The act of measurement collapses the wave function and fundamentally changes the outcome.
Before you check a trade, it’s in super position.
From a statistical perspective, your trade has a probability of winning or losing based on your system but you don’t yet know the outcome.
The trade is evolving naturally, just like a quantum system.
The moment you look at it, your observation collapses the “trade wave function” into a definite state - good or bad, winning or losing.
That observation triggers an emotional reaction — stress, fear, or overconfidence—which can cause you to break your plan, over-leverage, or revenge trade.
Just like in quantum mechanics, the act of measurement affects the system.
If you hadn’t looked, the system would have continued evolving naturally and you would have followed your plan without emotional interference.
This analogy mirrors the quantum concept perfectly - observation changes the outcome, not because the market changed, but because your interaction with it changed your behavior.
In other words, checking too often destroys the natural probabilistic outcome of your system, just like measuring the slit destroys the interference pattern.
The trade itself hasn’t changed; your observation changed how you interact with it, which changes the outcome.
Final Thoughts:
Traders, you know what I’m talking about — in a demo, you can leave your strategy untouched for days, weeks, even months.
The moment it goes live, you start checking too often, micromanaging your trades, and suddenly your observation is affecting the outcome.
Jason Smith
Hidden Markov Model (HMM)
Retraining Canary
This Allocator runs a 5-model pipeline where:
Production is the live trading model (100% allocation) that generates your primary signal
Champion is the best historical performer used for validation (25% allocation)
Canary acts as an early warning system—a deliberately poor model used as a contrarian indicator (if it agrees with PRODUCTION, that's a red flag)
Archived stores retired models that are kept for reference but no longer used in live decisions
Shadow runs in parallel without affecting trades, allowing you to test new models or strategies in real-time without risking capital
Together, PRODUCTION drives your trades, CHAMPION validates the signal, CANARY warns of danger, while ARCHIVED and SHADOW handle historical tracking and experimental testing respectively.
Retraining Canary
This Allocator runs a 5-model pipeline where:
Production is the live trading model (100% allocation) that generates your primary signal
Champion is the best historical performer used for validation (25% allocation)
Canary acts as an early warning system—a deliberately poor model used as a contrarian indicator (if it agrees with PRODUCTION, that's a red flag)
Archived stores retired models that are kept for reference but no longer used in live decisions
Shadow runs in parallel without affecting trades, allowing you to test new models or strategies in real-time without risking capital
Together, PRODUCTION drives your trades, CHAMPION validates the signal, CANARY warns of danger, while ARCHIVED and SHADOW handle historical tracking and experimental testing respectively.
Jason Smith
HMM dashboard -
Even though the dashboard runs inside a Python shell, it can be accessed through a browser thanks to ngrok tunneling, which provides a secure login.
Alternatively, you can interact with it directly via the shell itself.
However, the browser option offers the added benefit of remote access with authentication.
Even though the dashboard runs inside a Python shell, it can be accessed through a browser thanks to ngrok tunneling, which provides a secure login.
Alternatively, you can interact with it directly via the shell itself.
However, the browser option offers the added benefit of remote access with authentication.
Jason Smith
HMM (Hidden Markov Model) Python Back-end.
Despite a STRONG_UPTREND market regime with 100% alignment, the system is holding off on new allocations due to elevated risk and recent model degradation (production model replaced).
Position sizing is reduced to 50% as a defensive measure.
Bullish trend but risk-off stance – system holds due to elevated risk and recent model under performance, protecting capital until conditions improve.
Despite a STRONG_UPTREND market regime with 100% alignment, the system is holding off on new allocations due to elevated risk and recent model degradation (production model replaced).
Position sizing is reduced to 50% as a defensive measure.
Bullish trend but risk-off stance – system holds due to elevated risk and recent model under performance, protecting capital until conditions improve.
Jason Smith
Thought of the day: Hope you didn't dump your Bitcoin holdings.
There's been a lot of fear talk lately — some of it might be justified, but it could also have been a way to buy coins on the cheap.
MicroStrategy might have been in on it too, possibly buying coins through another business entity and averaging down across multiple accounts.
Plenty of youtubers anouncing they are closing their bc holdings in big losses, seem a bit suspicious to me. Time will tell.
Was 57 k the real bottom?
There's been a lot of fear talk lately — some of it might be justified, but it could also have been a way to buy coins on the cheap.
MicroStrategy might have been in on it too, possibly buying coins through another business entity and averaging down across multiple accounts.
Plenty of youtubers anouncing they are closing their bc holdings in big losses, seem a bit suspicious to me. Time will tell.
Was 57 k the real bottom?
Jason Smith
The HMM Allocator is a sophisticated trading system that uses Hidden Markov Models to detect market regimes and make allocation decisions.
It analyzes multiple timeframes simultaneously to determine the most likely market state and execute optimal trades.
It analyzes multiple timeframes simultaneously to determine the most likely market state and execute optimal trades.
Jason Smith
Thought of the day:
Socratic Irony -The speaker pretends to be ignorant or less intelligent than they really are.
They ask seemingly naive questions to expose the flaws in the other person's logic.
Classic example:
Socrates would say, I am such a fool, I don't understand justice at all.
Please, wise friend, explain it to me.
Then, through questioning, he'd expose that the "wise" friend actually had no idea what they were talking about.
The classic MQL5 forum example:
A user with minimal trading history posts, Forgive my inexperience, but can someone explain why this EA's backtest shows 90% win rate when the forward test is bleeding?
I'm sure I'm missing something obvious." Through a series of carefully worded follow-ups, they proceed to dismantle the EA's logic, expose over fitting, and question the developer's understanding of risk management — all while maintaining the pose of a humble novice.
Then get banned for it
Socratic Irony -The speaker pretends to be ignorant or less intelligent than they really are.
They ask seemingly naive questions to expose the flaws in the other person's logic.
Classic example:
Socrates would say, I am such a fool, I don't understand justice at all.
Please, wise friend, explain it to me.
Then, through questioning, he'd expose that the "wise" friend actually had no idea what they were talking about.
The classic MQL5 forum example:
A user with minimal trading history posts, Forgive my inexperience, but can someone explain why this EA's backtest shows 90% win rate when the forward test is bleeding?
I'm sure I'm missing something obvious." Through a series of carefully worded follow-ups, they proceed to dismantle the EA's logic, expose over fitting, and question the developer's understanding of risk management — all while maintaining the pose of a humble novice.
Then get banned for it
Jason Smith
Treat your men as you would your own beloved sons, and they will follow you into the deepest valley.— Sun Tzu
Every step forward could trigger hidden dangers — you walk carefully because betrayal is everywhere.
Recognize manipulation and treachery before it reaches the battlefield — sometimes the best defense is awareness.
In fact I think we'd be fooling ourselves.
If we had an audience this large and didn't realize that there were some enemies present
Every step forward could trigger hidden dangers — you walk carefully because betrayal is everywhere.
Recognize manipulation and treachery before it reaches the battlefield — sometimes the best defense is awareness.
In fact I think we'd be fooling ourselves.
If we had an audience this large and didn't realize that there were some enemies present
Jason Smith
Wednesday
If you wait by the river long enough, the bodies of your enemies will float by — Sun Tzu
Jason Smith
The system handles multiple assets by running a separate Hidden Markov Model instance for each individual symbol.
You have full control to build your own custom watchlist, giving you the flexibility to track any combination of assets that matter to you.
Whether you want to monitor major indices like the S&P 500 and FTSE, energy commodities such as WTI and Brent crude, or precious metals including gold and silver, the system lets you add or remove symbols effortlessly.
You have full control to build your own custom watchlist, giving you the flexibility to track any combination of assets that matter to you.
Whether you want to monitor major indices like the S&P 500 and FTSE, energy commodities such as WTI and Brent crude, or precious metals including gold and silver, the system lets you add or remove symbols effortlessly.
Jason Smith
Markov Bot default setting -
Markov.py --symbol AUDCAD --fixed-lots 0.2 --journal audcad.db --magic 1 --auto-reconnect --mt5-timeout 60 --mt5-retries 5 --mt5-path \"C:\Program Files\MetaTrader 8 IC Markets Global\terminal64.exe\" --max-positions 1 --quiet --signal-max-age 7000 --zero-on-hold
Full Trading System Available for Purchase -
The suite includes:
A Hidden Markov Model-based allocator that detects market regimes and manages portfolio allocation.
An interactive dashboard for monitoring system performance and signals.
A Python trading bot that executes trades based on HMM outputs.
An MT5 bot — currently undergoing a rewrite to improve compatibility and performance with the HMM
Markov.py --symbol AUDCAD --fixed-lots 0.2 --journal audcad.db --magic 1 --auto-reconnect --mt5-timeout 60 --mt5-retries 5 --mt5-path \"C:\Program Files\MetaTrader 8 IC Markets Global\terminal64.exe\" --max-positions 1 --quiet --signal-max-age 7000 --zero-on-hold
Full Trading System Available for Purchase -
The suite includes:
A Hidden Markov Model-based allocator that detects market regimes and manages portfolio allocation.
An interactive dashboard for monitoring system performance and signals.
A Python trading bot that executes trades based on HMM outputs.
An MT5 bot — currently undergoing a rewrite to improve compatibility and performance with the HMM
