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Innovating the Future of Trading with Precision and Strategy
Welcome to my MQL5 profile! I’m TraderSmith, a passionate and results-driven trader committed to developing Expert Advisors (EAs) that transform complex market data into simple, actionable trading decisions.
Through developing trading bots, I aim to eliminate the emotional biases that often lead to impulsive decisions.
Every strategy I design is rooted in robust market analysis, precise risk management, and an understanding of market dynamics, ensuring that each trade has a solid foundation.
I focus on creating tools that are adaptable to a wide range of trading styles and risk profiles.
From high-frequency scalping to trend-following strategies, my EAs are built to execute trades with speed, accuracy, and discipline—freeing you from emotional reactions and enabling you to trade with confidence.
Every Expert Advisor I develop is designed with a clear trading philosophy.
I avoid random, “black-box” approaches and instead focus on precise, rule-based systems that are backtested, validated, and optimized to adapt to current market conditions.
Whether you’re executing strategies with pending orders, focusing on ATR-based risk management, or leveraging complex thresholds, my EAs are built to excel in dynamic market environments.
Comprehensive Support and Education
Trading is a journey, and I’m here to support you along the way.
Not only do I provide customer support to help you with any setup or technical questions, but I also offer educational resources and guidance on how to fully leverage the bots in various market conditions.
My goal is to ensure you not only use the tools effectively but also understand the underlying strategies that drive them.
My Commitment to You
As an active trader, I am constantly analyzing market trends and refining my tools to keep up with the latest advancements in algorithmic trading.
My mission is to give you the edge you need—whether you’re managing a prop account, building a portfolio, or just getting started.
I’m committed to creating robust, high-performance solutions that allow you to trade smarter, not harder.
I believe in building long-term relationships with my clients, so your feedback and success are always important to me.
If you have any questions, need advice, or simply want to discuss strategies, don’t hesitate to reach out. I’m here to ensure your trading journey is as successful as possible.
Thank you for considering my tools for your trading endeavors. I look forward to helping you achieve your trading goals!
Through algorithmic trading, you will develop discipline and patience—core traits for consistent performance. These bots will enforce rule-based execution, removing emotional bias and promoting data-driven decision-making. Over time, you'll learn that edge comes from systematic testing, risk management, and long-term consistency. Each trade, whether a win or a loss, becomes part of a feedback loop that sharpens both your strategy and your mindset. Once you’ve set up the bot, let it work.
Avoid the urge to micromanage every trade. Trust in the strategy and parameters you’ve defined.
Welcome to my MQL5 profile! I’m TraderSmith, a passionate and results-driven trader committed to developing Expert Advisors (EAs) that transform complex market data into simple, actionable trading decisions.
Through developing trading bots, I aim to eliminate the emotional biases that often lead to impulsive decisions.
Every strategy I design is rooted in robust market analysis, precise risk management, and an understanding of market dynamics, ensuring that each trade has a solid foundation.
I focus on creating tools that are adaptable to a wide range of trading styles and risk profiles.
From high-frequency scalping to trend-following strategies, my EAs are built to execute trades with speed, accuracy, and discipline—freeing you from emotional reactions and enabling you to trade with confidence.
Every Expert Advisor I develop is designed with a clear trading philosophy.
I avoid random, “black-box” approaches and instead focus on precise, rule-based systems that are backtested, validated, and optimized to adapt to current market conditions.
Whether you’re executing strategies with pending orders, focusing on ATR-based risk management, or leveraging complex thresholds, my EAs are built to excel in dynamic market environments.
Comprehensive Support and Education
Trading is a journey, and I’m here to support you along the way.
Not only do I provide customer support to help you with any setup or technical questions, but I also offer educational resources and guidance on how to fully leverage the bots in various market conditions.
My goal is to ensure you not only use the tools effectively but also understand the underlying strategies that drive them.
My Commitment to You
As an active trader, I am constantly analyzing market trends and refining my tools to keep up with the latest advancements in algorithmic trading.
My mission is to give you the edge you need—whether you’re managing a prop account, building a portfolio, or just getting started.
I’m committed to creating robust, high-performance solutions that allow you to trade smarter, not harder.
I believe in building long-term relationships with my clients, so your feedback and success are always important to me.
If you have any questions, need advice, or simply want to discuss strategies, don’t hesitate to reach out. I’m here to ensure your trading journey is as successful as possible.
Thank you for considering my tools for your trading endeavors. I look forward to helping you achieve your trading goals!
Through algorithmic trading, you will develop discipline and patience—core traits for consistent performance. These bots will enforce rule-based execution, removing emotional bias and promoting data-driven decision-making. Over time, you'll learn that edge comes from systematic testing, risk management, and long-term consistency. Each trade, whether a win or a loss, becomes part of a feedback loop that sharpens both your strategy and your mindset. Once you’ve set up the bot, let it work.
Avoid the urge to micromanage every trade. Trust in the strategy and parameters you’ve defined.
Jason Smith
Thought of the day - Happiness in your life depends upon the quality of your thoughts.
You have power over your mind — not outside events.
Realize this, and you will find strength.
Marcus Aurelius.
You have power over your mind — not outside events.
Realize this, and you will find strength.
Marcus Aurelius.
Jason Smith
Markov Matrix –
The strategy has experienced some losing trades this week, but overall it remains 90 dollars ahead on balance.
In addition, there is currently a healthy unrealized profit, leaving the system in a strong position.
The strategy has experienced some losing trades this week, but overall it remains 90 dollars ahead on balance.
In addition, there is currently a healthy unrealized profit, leaving the system in a strong position.
Jason Smith
New features - Markov Matrix
The Markov model generates three core signals : buy, sell, and hold – plus a flip signal for directional changes.
When the system is currently in a buy or sell position and a hold signal comes in.
NOTE the image below.
The close on hold is very useful feature for risk managment.
The flip signal is the most aggressive – it tells the system to completely reverse direction, exiting the current position and entering the opposite side.
Full training and 100% support are included every step of the way.
I will guide you through the complete installation process and share everything I know about the system, backed by an in-depth PDF guide covering its features, setup, and operation.
I built this system from the ground up, know every part of the code, and understand all of its capabilities.
Even a complete beginner should be able to have it installed and running within 24 hours.
Over time, you will become as familiar with the system as I am.
It is designed not only to provide a powerful tool but also to help you learn, develop your understanding
The Markov model generates three core signals : buy, sell, and hold – plus a flip signal for directional changes.
When the system is currently in a buy or sell position and a hold signal comes in.
NOTE the image below.
The close on hold is very useful feature for risk managment.
The flip signal is the most aggressive – it tells the system to completely reverse direction, exiting the current position and entering the opposite side.
Full training and 100% support are included every step of the way.
I will guide you through the complete installation process and share everything I know about the system, backed by an in-depth PDF guide covering its features, setup, and operation.
I built this system from the ground up, know every part of the code, and understand all of its capabilities.
Even a complete beginner should be able to have it installed and running within 24 hours.
Over time, you will become as familiar with the system as I am.
It is designed not only to provide a powerful tool but also to help you learn, develop your understanding
Jason Smith
HMM (Hidden Markov Model) Gold -
The system ran its full multi-timeframe consensus across H4, D1, W1, M15, M30, H1, and M5.H4 came back as a strong downtrend, while most other timeframes showed neutral, weak uptrend, or high volatility.
Eleven features were calculated without issue.
A new challenger model was trained but rejected with a Sharpe ratio of -0.53 – well below the acceptance threshold.
The overall regime was confirmed as a strong downtrend, now entering its third cycle.
Alignment hit 100%, with zero up signals, two down signals, and five neutral readings.
Risk was assessed as elevated, so the system took a HOLD action – no new positions were opened.
A drift adjustment was applied, cutting the position from 0.05 micro down to 0.02 – a 50% reduction.
With the final multiplier applied, total exposure landed at just 25%.
Bottom line: XAUUSD is in a strong downtrend with elevated risk, the system held off opening a sell trade, and exposure was slashed by 75% from baseline.
Baseline is 1 mini lot, the drift adjustment and other factors applied a 75% reduction, bringing exposure down to just 0.02 micro lots.
The system ran its full multi-timeframe consensus across H4, D1, W1, M15, M30, H1, and M5.H4 came back as a strong downtrend, while most other timeframes showed neutral, weak uptrend, or high volatility.
Eleven features were calculated without issue.
A new challenger model was trained but rejected with a Sharpe ratio of -0.53 – well below the acceptance threshold.
The overall regime was confirmed as a strong downtrend, now entering its third cycle.
Alignment hit 100%, with zero up signals, two down signals, and five neutral readings.
Risk was assessed as elevated, so the system took a HOLD action – no new positions were opened.
A drift adjustment was applied, cutting the position from 0.05 micro down to 0.02 – a 50% reduction.
With the final multiplier applied, total exposure landed at just 25%.
Bottom line: XAUUSD is in a strong downtrend with elevated risk, the system held off opening a sell trade, and exposure was slashed by 75% from baseline.
Baseline is 1 mini lot, the drift adjustment and other factors applied a 75% reduction, bringing exposure down to just 0.02 micro lots.
Jason Smith
Up, up, and away—Bitcoin to the skies. Slush fund or not, today's news has the bulls charging.
The $100K+ target is back in the conversation.
Whether it happens next few months or later in the cycle, the momentum and narrative are building.
As always, price will have the final say.
#Bitcoin #BTC #Crypto #BullMarket
The $100K+ target is back in the conversation.
Whether it happens next few months or later in the cycle, the momentum and narrative are building.
As always, price will have the final say.
#Bitcoin #BTC #Crypto #BullMarket
Jason Smith
This is my new website, though I’ve recently lost some motivation.
It can be difficult to stay motivated when your work isn’t getting the attention it deserves.
I’m open to collaborating with someone who can help take this to the next level, potentially offering up to a 50% share.
If you have experience in marketing and think you can help grow this product, feel free to get in touch.
One of the standout features of this system is its dynamic position sizing.
It doesn't just give you a simple buy, sell or hold signal – it actively adjusts how much you risk based on real-time market conditions.
In the AUDNZD cycle, it applied a 60% multiplier with elevated risk – willing to take a decent position but leaving room for caution.
In contrast, the earlier AUS200 cycle saw a canary alert trigger a 50% position cut, reducing exposure all the way down to just 10%.
Scaling up when confidence is high.
Slashing when danger is detected.
That's what separates this system from the rigid, one-size-fits-all strategies out there.
It can be difficult to stay motivated when your work isn’t getting the attention it deserves.
I’m open to collaborating with someone who can help take this to the next level, potentially offering up to a 50% share.
If you have experience in marketing and think you can help grow this product, feel free to get in touch.
One of the standout features of this system is its dynamic position sizing.
It doesn't just give you a simple buy, sell or hold signal – it actively adjusts how much you risk based on real-time market conditions.
In the AUDNZD cycle, it applied a 60% multiplier with elevated risk – willing to take a decent position but leaving room for caution.
In contrast, the earlier AUS200 cycle saw a canary alert trigger a 50% position cut, reducing exposure all the way down to just 10%.
Scaling up when confidence is high.
Slashing when danger is detected.
That's what separates this system from the rigid, one-size-fits-all strategies out there.
Jason Smith
Pazartesi
The base position size is 2 mini lots, but this is fully configurable. The system will never trade above the defined maximum size.
Jason Smith
model d2213356 successfully graduated from shadow to canary after 10 cycles of observation, meaning it's now ready for limited live deployment.
AUDNZD is showing a strong uptrend that's been running for 2 cycles now, with perfect 100% alignment across all timeframes.
Risk is assessed as elevated, but the system is still taking a buy signal with a 60% position multiplier, keeping some room for caution.
System is confident, promoted a new model, and is taking a measured buy position.
AUDNZD is showing a strong uptrend that's been running for 2 cycles now, with perfect 100% alignment across all timeframes.
Risk is assessed as elevated, but the system is still taking a buy signal with a 60% position multiplier, keeping some room for caution.
System is confident, promoted a new model, and is taking a measured buy position.
Jason Smith
Pazartesi
This system is for sale -
A rare, original strategy built from the ground up with a refined, elite-level design. Created for traders who want a real edge.
A rare, original strategy built from the ground up with a refined, elite-level design. Created for traders who want a real edge.
Jason Smith
Pazartesi
This operates in just three clicks, using batch files to launch the Markov (The Allocator), the dashboard, and the Python bot.
Jason Smith
The trading system is running its 10th analysis cycle for the Australian stock index (AUS200), and it's basically doing a multi‑timeframe health check before deciding what to do.
It looks at several timeframes (from daily down to 5‑minute charts) to get a consensus, and most are neutral, though the 15‑minute shows a weak downtrend and the 5‑minute a weak uptrend—so nothing decisive.
The system then builds and tests a new "challenger" trading model, which performs well enough to be accepted, but it's put into a 10‑cycle "shadow mode" to be observed rather than used immediately.
The real action is a CANARY alert: the system detects a drift (statistical change) in the data for AUS200, with a high divergence (100% disagreement) and a KL score of 14.4, which is a red flag.
As a defensive measure, it cuts the position size by 50%—so the allocation drops from 0.16 to 0.084, and after an additional 10% multiplier, the final exposure is only 10% of normal.
Despite the drift, the overall risk is judged as "NORMAL" and the action is "HOLD" (no new trades), meaning the system is staying put but with much smaller stakes until it gets more confidence that the market behaviour has stabilised.
In short: the system spotted something unusual in the data, got cautious, slashed its position, and is now watching and waiting.
The AI models have been learning continuously refining their performance and adapting to market conditions.
It looks at several timeframes (from daily down to 5‑minute charts) to get a consensus, and most are neutral, though the 15‑minute shows a weak downtrend and the 5‑minute a weak uptrend—so nothing decisive.
The system then builds and tests a new "challenger" trading model, which performs well enough to be accepted, but it's put into a 10‑cycle "shadow mode" to be observed rather than used immediately.
The real action is a CANARY alert: the system detects a drift (statistical change) in the data for AUS200, with a high divergence (100% disagreement) and a KL score of 14.4, which is a red flag.
As a defensive measure, it cuts the position size by 50%—so the allocation drops from 0.16 to 0.084, and after an additional 10% multiplier, the final exposure is only 10% of normal.
Despite the drift, the overall risk is judged as "NORMAL" and the action is "HOLD" (no new trades), meaning the system is staying put but with much smaller stakes until it gets more confidence that the market behaviour has stabilised.
In short: the system spotted something unusual in the data, got cautious, slashed its position, and is now watching and waiting.
The AI models have been learning continuously refining their performance and adapting to market conditions.
Jason Smith
HMM (Hidden Markov Model)Markov went live at 2:00 AM GMT (demo account) for the start of the new trading week.
These are the results so far.
The models have been learning for approximately four months.
These are the results so far.
The models have been learning for approximately four months.
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