QuantHustle.com | Algo Trading Blog
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📈 Algo Trader | 10 Yrs+ Building Quant System
⚠️ Not Financial Advice
🚀 Help You Build Winning Trading System
⚠️ Not Financial Advice
🚀 Help You Build Winning Trading System
Old strategy ≠ obsolete strategy.
The market’s not outsmarting this simple old school strategy 🤯🤯🤯
This research paper backs it up……🧵🪡
The market’s not outsmarting this simple old school strategy 🤯🤯🤯
This research paper backs it up……🧵🪡
February 5, 2026 at 11:00 AM
Old strategy ≠ obsolete strategy.
The market’s not outsmarting this simple old school strategy 🤯🤯🤯
This research paper backs it up……🧵🪡
The market’s not outsmarting this simple old school strategy 🤯🤯🤯
This research paper backs it up……🧵🪡
UC Berkeley Shows You The Most Popular Model in Algo Trading For FREE
Learn it step by step in 100 mins
In this course, you will learn
• Linear regression model
• Use case
• Model testing
• Python for linear regression
….course link in …🧵🪡
Learn it step by step in 100 mins
In this course, you will learn
• Linear regression model
• Use case
• Model testing
• Python for linear regression
….course link in …🧵🪡
February 5, 2026 at 12:00 AM
UC Berkeley Shows You The Most Popular Model in Algo Trading For FREE
Learn it step by step in 100 mins
In this course, you will learn
• Linear regression model
• Use case
• Model testing
• Python for linear regression
….course link in …🧵🪡
Learn it step by step in 100 mins
In this course, you will learn
• Linear regression model
• Use case
• Model testing
• Python for linear regression
….course link in …🧵🪡
Ways backtesting sharpens your edge:
- Exposes overfitting fast
- Shows true drawdown pain
- Reveals when edge dies
- Clarifies where to size up
- Turns “hope” into probabilities
The goal isn’t perfect prediction, just asymmetric bets.
- Exposes overfitting fast
- Shows true drawdown pain
- Reveals when edge dies
- Clarifies where to size up
- Turns “hope” into probabilities
The goal isn’t perfect prediction, just asymmetric bets.
February 4, 2026 at 8:02 PM
Ways backtesting sharpens your edge:
- Exposes overfitting fast
- Shows true drawdown pain
- Reveals when edge dies
- Clarifies where to size up
- Turns “hope” into probabilities
The goal isn’t perfect prediction, just asymmetric bets.
- Exposes overfitting fast
- Shows true drawdown pain
- Reveals when edge dies
- Clarifies where to size up
- Turns “hope” into probabilities
The goal isn’t perfect prediction, just asymmetric bets.
The true cost of launching your first quant trading system
• Scipy: FREE
• Python: FREE
• pandas: FREE
• VectorBT: FREE
• Statsmodel: FREE
• Scikit-learn: FREE
You can build strategies right from your laptop for FREE.
The only investment? Your time and effort.
• Scipy: FREE
• Python: FREE
• pandas: FREE
• VectorBT: FREE
• Statsmodel: FREE
• Scikit-learn: FREE
You can build strategies right from your laptop for FREE.
The only investment? Your time and effort.
February 4, 2026 at 11:00 AM
The true cost of launching your first quant trading system
• Scipy: FREE
• Python: FREE
• pandas: FREE
• VectorBT: FREE
• Statsmodel: FREE
• Scikit-learn: FREE
You can build strategies right from your laptop for FREE.
The only investment? Your time and effort.
• Scipy: FREE
• Python: FREE
• pandas: FREE
• VectorBT: FREE
• Statsmodel: FREE
• Scikit-learn: FREE
You can build strategies right from your laptop for FREE.
The only investment? Your time and effort.
The 4 steps you SHOULD know to develop a strategy:
1️⃣Research: Develop a trading hypothesis, define objectives
2️⃣Backtest: Backtest the strategy to evaluate performance & optimize
3️⃣Validate: Test on out-of-sample data to avoid overfitting.
4️⃣Paper Testing: Run strategy in simulated live environment
1️⃣Research: Develop a trading hypothesis, define objectives
2️⃣Backtest: Backtest the strategy to evaluate performance & optimize
3️⃣Validate: Test on out-of-sample data to avoid overfitting.
4️⃣Paper Testing: Run strategy in simulated live environment
February 4, 2026 at 12:00 AM
The 4 steps you SHOULD know to develop a strategy:
1️⃣Research: Develop a trading hypothesis, define objectives
2️⃣Backtest: Backtest the strategy to evaluate performance & optimize
3️⃣Validate: Test on out-of-sample data to avoid overfitting.
4️⃣Paper Testing: Run strategy in simulated live environment
1️⃣Research: Develop a trading hypothesis, define objectives
2️⃣Backtest: Backtest the strategy to evaluate performance & optimize
3️⃣Validate: Test on out-of-sample data to avoid overfitting.
4️⃣Paper Testing: Run strategy in simulated live environment
Most traders don’t lose from bad ideas. They lose from untested ideas. A robust backtest is how you turn “I think this works” into “I know the stats.” Edge = positive expectancy, stable drawdowns, and rules you actually trust.
February 3, 2026 at 8:02 PM
Most traders don’t lose from bad ideas. They lose from untested ideas. A robust backtest is how you turn “I think this works” into “I know the stats.” Edge = positive expectancy, stable drawdowns, and rules you actually trust.
Building a trading edge with backtests:
1) Define one clear hypothesis.
2) Code it rules-based.
3) Use out-of-sample data.
4) Track expectancy + max DD.
If you can’t measure it, you don’t have an edge.
1) Define one clear hypothesis.
2) Code it rules-based.
3) Use out-of-sample data.
4) Track expectancy + max DD.
If you can’t measure it, you don’t have an edge.
February 3, 2026 at 10:57 AM
Building a trading edge with backtests:
1) Define one clear hypothesis.
2) Code it rules-based.
3) Use out-of-sample data.
4) Track expectancy + max DD.
If you can’t measure it, you don’t have an edge.
1) Define one clear hypothesis.
2) Code it rules-based.
3) Use out-of-sample data.
4) Track expectancy + max DD.
If you can’t measure it, you don’t have an edge.
MIT FREE online video course on Maths in Finance
It covered everything you need to know for quant trading for FREE!
• Introduction, Financial Terms and Concepts
• Probability Theory
• Regression Analysis
• Volatility Modeling
• Time Series Analysis
link in …..🧵 🪡
It covered everything you need to know for quant trading for FREE!
• Introduction, Financial Terms and Concepts
• Probability Theory
• Regression Analysis
• Volatility Modeling
• Time Series Analysis
link in …..🧵 🪡
February 3, 2026 at 12:00 AM
MIT FREE online video course on Maths in Finance
It covered everything you need to know for quant trading for FREE!
• Introduction, Financial Terms and Concepts
• Probability Theory
• Regression Analysis
• Volatility Modeling
• Time Series Analysis
link in …..🧵 🪡
It covered everything you need to know for quant trading for FREE!
• Introduction, Financial Terms and Concepts
• Probability Theory
• Regression Analysis
• Volatility Modeling
• Time Series Analysis
link in …..🧵 🪡
How to know if your edge is real:
- Does it survive 2+ year backtest?
- Positive expectancy after all costs?
- Works across market regimes?
- Can you execute it 100 times?
If not, keep building. Edge isn't found, it's forged.
- Does it survive 2+ year backtest?
- Positive expectancy after all costs?
- Works across market regimes?
- Can you execute it 100 times?
If not, keep building. Edge isn't found, it's forged.
February 2, 2026 at 7:59 PM
How to know if your edge is real:
- Does it survive 2+ year backtest?
- Positive expectancy after all costs?
- Works across market regimes?
- Can you execute it 100 times?
If not, keep building. Edge isn't found, it's forged.
- Does it survive 2+ year backtest?
- Positive expectancy after all costs?
- Works across market regimes?
- Can you execute it 100 times?
If not, keep building. Edge isn't found, it's forged.
Losing traders:
- Chase the last hot setup
- Abandon systems after 3 losses
- Trade without testing edge
Winning traders:
- Build repeatable processes
- Trust 1000-trade sample sizes
- Measure expectancy constantly
Edge = math, not magic.
- Chase the last hot setup
- Abandon systems after 3 losses
- Trade without testing edge
Winning traders:
- Build repeatable processes
- Trust 1000-trade sample sizes
- Measure expectancy constantly
Edge = math, not magic.
February 1, 2026 at 7:57 PM
Losing traders:
- Chase the last hot setup
- Abandon systems after 3 losses
- Trade without testing edge
Winning traders:
- Build repeatable processes
- Trust 1000-trade sample sizes
- Measure expectancy constantly
Edge = math, not magic.
- Chase the last hot setup
- Abandon systems after 3 losses
- Trade without testing edge
Winning traders:
- Build repeatable processes
- Trust 1000-trade sample sizes
- Measure expectancy constantly
Edge = math, not magic.
Your edge dies the moment you stop evolving it.
- Backtest on 100+ scenarios, not 10
- Track edge decay in your journal
- Rebuild when win rate drops 15%
- Adapt to regime shifts weekly
Markets change. Your systems must too.
- Backtest on 100+ scenarios, not 10
- Track edge decay in your journal
- Rebuild when win rate drops 15%
- Adapt to regime shifts weekly
Markets change. Your systems must too.
January 30, 2026 at 7:59 PM
Your edge dies the moment you stop evolving it.
- Backtest on 100+ scenarios, not 10
- Track edge decay in your journal
- Rebuild when win rate drops 15%
- Adapt to regime shifts weekly
Markets change. Your systems must too.
- Backtest on 100+ scenarios, not 10
- Track edge decay in your journal
- Rebuild when win rate drops 15%
- Adapt to regime shifts weekly
Markets change. Your systems must too.
FREE Python training from JP Morgan
JP Morgan technologists and traders help you to understand complex quant topics without formal programming backgrounds in Python.
JP Morgan technologists and traders help you to understand complex quant topics without formal programming backgrounds in Python.
January 30, 2026 at 12:00 AM
FREE Python training from JP Morgan
JP Morgan technologists and traders help you to understand complex quant topics without formal programming backgrounds in Python.
JP Morgan technologists and traders help you to understand complex quant topics without formal programming backgrounds in Python.
Building edge is about stacking small advantages that compound.
• Test relentlessly.
• Execute consistently.
• Refine endlessly.
The market doesn't reward brilliance
It rewards discipline applied over thousands of trades.
• Test relentlessly.
• Execute consistently.
• Refine endlessly.
The market doesn't reward brilliance
It rewards discipline applied over thousands of trades.
January 29, 2026 at 8:02 PM
Building edge is about stacking small advantages that compound.
• Test relentlessly.
• Execute consistently.
• Refine endlessly.
The market doesn't reward brilliance
It rewards discipline applied over thousands of trades.
• Test relentlessly.
• Execute consistently.
• Refine endlessly.
The market doesn't reward brilliance
It rewards discipline applied over thousands of trades.
Top 9 quant trading strategies for retail quant trader…..🧵🪡
January 29, 2026 at 11:00 AM
Top 9 quant trading strategies for retail quant trader…..🧵🪡
Stanford Artificial Intelligence Free Course in YouTube is a gold mine!
Course highlights
• Linear Regression
• Linear Classification
• Feature Templates
• K-means
• Markov Network
• Bayesian Networks
• Reinforcement Learning
$0….course link in …🧵🪡
Course highlights
• Linear Regression
• Linear Classification
• Feature Templates
• K-means
• Markov Network
• Bayesian Networks
• Reinforcement Learning
$0….course link in …🧵🪡
January 29, 2026 at 12:00 AM
Stanford Artificial Intelligence Free Course in YouTube is a gold mine!
Course highlights
• Linear Regression
• Linear Classification
• Feature Templates
• K-means
• Markov Network
• Bayesian Networks
• Reinforcement Learning
$0….course link in …🧵🪡
Course highlights
• Linear Regression
• Linear Classification
• Feature Templates
• K-means
• Markov Network
• Bayesian Networks
• Reinforcement Learning
$0….course link in …🧵🪡
If your strategy’s alpha only works in certain regimes, naive sizing is timing risk in disguise. Trend CTAs, stat arb, vol strategies all cycle. Size up into regime exhaustion, size down into regime birth, and you can lose money with a profitable model.
January 28, 2026 at 8:00 PM
If your strategy’s alpha only works in certain regimes, naive sizing is timing risk in disguise. Trend CTAs, stat arb, vol strategies all cycle. Size up into regime exhaustion, size down into regime birth, and you can lose money with a profitable model.
😱😱😱 I can't believe the secret of Ray Dalio building billions of business unleashed to everyone in this paper!!
January 28, 2026 at 11:01 AM
😱😱😱 I can't believe the secret of Ray Dalio building billions of business unleashed to everyone in this paper!!
MUST WATCH - Market cycle is crystal clear after watching this video
www.youtube.com/watch?v=PHe...
www.youtube.com/watch?v=PHe...
How The Economic Machine Works by Ray Dalio
Economics 101 -- "How the Economic Machine Works."Created by Ray Dalio this simple but not simplistic and easy to follow 30 minute, animated video answers th...
www.youtube.com
January 27, 2026 at 7:56 PM
MUST WATCH - Market cycle is crystal clear after watching this video
www.youtube.com/watch?v=PHe...
www.youtube.com/watch?v=PHe...
4 edges that survive market cycles:
- Statistical mean reversion with volatility filters
- Volume-confirmed breakouts on liquid assets
- Microstructure patterns that beat slippage
- Execution speed that captures inefficiencies
Stack them. Compound wins.
- Statistical mean reversion with volatility filters
- Volume-confirmed breakouts on liquid assets
- Microstructure patterns that beat slippage
- Execution speed that captures inefficiencies
Stack them. Compound wins.
January 27, 2026 at 11:02 AM
4 edges that survive market cycles:
- Statistical mean reversion with volatility filters
- Volume-confirmed breakouts on liquid assets
- Microstructure patterns that beat slippage
- Execution speed that captures inefficiencies
Stack them. Compound wins.
- Statistical mean reversion with volatility filters
- Volume-confirmed breakouts on liquid assets
- Microstructure patterns that beat slippage
- Execution speed that captures inefficiencies
Stack them. Compound wins.
Software Developer Doesn’t Need To Write Any Code NOW!!
Stanford University New Course shows you how
Learn Stanford University New Era Of Software Developer Syllabus and FREE online material
Stanford University New Course shows you how
Learn Stanford University New Era Of Software Developer Syllabus and FREE online material
January 27, 2026 at 12:00 AM
Software Developer Doesn’t Need To Write Any Code NOW!!
Stanford University New Course shows you how
Learn Stanford University New Era Of Software Developer Syllabus and FREE online material
Stanford University New Course shows you how
Learn Stanford University New Era Of Software Developer Syllabus and FREE online material
VIX is not “the market.” It’s SPX. Tech? Look at VXN. Small caps? RVX. Dow? VXD. Different indices, different stress. 2020 taught a simple rule: if your risk is concentrated, your volatility gauge better match your actual exposure.
January 26, 2026 at 8:04 PM
VIX is not “the market.” It’s SPX. Tech? Look at VXN. Small caps? RVX. Dow? VXD. Different indices, different stress. 2020 taught a simple rule: if your risk is concentrated, your volatility gauge better match your actual exposure.
Capital management is not “more when it feels good, less when it hurts.”
It’s a framework:
• regime detection
• alpha diagnostics
• risk budgets
• slow capital ramps
The goal isn’t to juice lucky streaks, it’s to survive long enough for expectancy to matter.
It’s a framework:
• regime detection
• alpha diagnostics
• risk budgets
• slow capital ramps
The goal isn’t to juice lucky streaks, it’s to survive long enough for expectancy to matter.
January 24, 2026 at 8:00 PM
Capital management is not “more when it feels good, less when it hurts.”
It’s a framework:
• regime detection
• alpha diagnostics
• risk budgets
• slow capital ramps
The goal isn’t to juice lucky streaks, it’s to survive long enough for expectancy to matter.
It’s a framework:
• regime detection
• alpha diagnostics
• risk budgets
• slow capital ramps
The goal isn’t to juice lucky streaks, it’s to survive long enough for expectancy to matter.
🧐 Can you understand these lines of code?
If so, you are more than enough to code for your own algo trading system!
If so, you are more than enough to code for your own algo trading system!
January 23, 2026 at 8:00 PM
🧐 Can you understand these lines of code?
If so, you are more than enough to code for your own algo trading system!
If so, you are more than enough to code for your own algo trading system!
4 Major Types of Machine Learning that you should master
• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning
• Deep Learning
Quant trading use cases for all types of machine learning in …….🧵🪡
• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning
• Deep Learning
Quant trading use cases for all types of machine learning in …….🧵🪡
January 23, 2026 at 11:00 AM
4 Major Types of Machine Learning that you should master
• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning
• Deep Learning
Quant trading use cases for all types of machine learning in …….🧵🪡
• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning
• Deep Learning
Quant trading use cases for all types of machine learning in …….🧵🪡
FREE Artificial Intelligence with Python Course from Harvard University
• Reinforcement learning
• Machine learning
• Artificial intelligence principles
• How to design intelligent systems
• How to use AI in Python programs
$0….course link in …🧵🪡
• Reinforcement learning
• Machine learning
• Artificial intelligence principles
• How to design intelligent systems
• How to use AI in Python programs
$0….course link in …🧵🪡
January 23, 2026 at 12:02 AM
FREE Artificial Intelligence with Python Course from Harvard University
• Reinforcement learning
• Machine learning
• Artificial intelligence principles
• How to design intelligent systems
• How to use AI in Python programs
$0….course link in …🧵🪡
• Reinforcement learning
• Machine learning
• Artificial intelligence principles
• How to design intelligent systems
• How to use AI in Python programs
$0….course link in …🧵🪡