ChartSense AI
The First Quantitative Intelligence Suite for Crypto Traders
4 followers
The First Quantitative Intelligence Suite for Crypto Traders
4 followers
Retail sees candles; Institutions see Math. ChartSense AI is the first Quantitative OS visualizing hidden forces: Market Entropy, Hurst Exponent &10,000 Risk Simulations. Plus, an AI Psychologist to fix your emotional leaks. Stop trading naked charts.
"Hi Hunters! 👋
I'm the founder of ChartSense AI.
I built this platform because I realized retail traders are fighting a losing battle. We look at 'Support and Resistance' lines while Institutions look at Math and Probability.
ChartSense AI bridges that gap. We built a Quantitative Intelligence OS that runs the same logic as the big desks, but visualizes it for you instantly:
⚛️ Quant Engine: We calculate Market Entropy and the Hurst Exponent to tell you if a trend is real or just noise.
🚨 Risk of Ruin: Our engine runs 10,000 Monte Carlo Simulations for every scan to calculate your exact drawdown probability.
🐳 Order Flow: See Liquidity Walls & Taker Aggression in real-time.
🧠 Psychologist: An AI that audits your trade history to fix emotional leaks.
🎁 Launch Special: We just released our Free 'Wake Up' Sensor for TradingView (linked on the site), and you can try the full Quant Dashboard today for just $1 (5 Credits included).
I'll be hanging out here all day. Ask me anything about the math behind the market! 📉
Hey, this is super interesting especially the whole idea of visualizing entropy and trend validity.
Quick question though: when the Quant Engine detects a “real” trend vs noise, is there a specific threshold it uses? Like does the Hurst/entropy combo have to hit a certain level before it flags it as legit?
Just trying to understand how the system decides what’s actually signal.
@olajiggy321 Glad you found the entropy concept interesting! You are spot on—it isn’t a guessing game. The engine uses hard mathematical floors that the data must clear to be classified as a "real" signal rather than noise.
To answer your question, yes, we use specific thresholds for the Hurst/Entropy combo to filter out false positives. Here are the exact cutoffs the system uses:
Hurst Exponent (Trend Memory): A value of 0.5 is a random walk. The system requires a Hurst > 0.55 to classify the move as "Strong Trend Persistence" (meaning breakouts are statistically likely to work). Anything between 0.45 and 0.55 is filtered out as random noise.
Shannon Entropy (System Chaos): We verify if the signal is "clean" by calculating an entropy ratio. We look for a Ratio < 0.65 to deem the market "Structured" and tradeable. If the ratio drops below 0.40, it is flagged as "Crystalline," which is our highest conviction trend signal.
Fractal Dimension (Complexity): As a final check, we look for a Fractal Dimension Index (FDI) < 1.3. This confirms the trend is "smooth" rather than jagged or complex.
Basically, even if the price is skyrocketing, if the Hurst is only 0.51 or the Entropy is above 0.65, the system flags it as "Chaotic Noise" and invalidates the setup.
Hope that helps clarify how we separate the signal from the noise!
@chartsense_ai
Wow, that’s actually super clear appreciate you breaking it down like that.
What I find interesting is how strict the system is with those cutoffs, especially the entropy ratio. Most tools just call everything a trend if the chart is pointing up 😅
Quick follow-up though:
When one of these indicators disqualifies a setup (like entropy popping above 0.65), does the UI explain why it got invalidated?
Or does it just show the final verdict?
I’m asking because traders love seeing why a signal didn’t pass it builds more trust in the logic.
You are spot on: visibility into the machine's decision-making process is the only way to build trust in quantitative logic.
Our answer is: We do not just show the final verdict; we explain the exact reason for invalidation. We've recently upgraded the system to align with institutional audit standards, ensuring transparency for the two most critical reasons a setup might be disqualified:
1. If the Math Fails (Risk Disqualification): If the calculated Reward:Risk (R:R) ratio is below our institutional threshold of 1.5:1, the setup is immediately killed. * The Report Now States: "Analysis invalidated: The mathematical Reward:Risk ratio is too low. Potential reward does not justify the risk."
2. If the Market Fails (Chaos Disqualification): If the market's structure is too unstable, we prevent pattern-based trades. * The Entropy Rule: When the system's System Entropy metric (which quantifies market disorder) pops above 0.85, it indicates chaos. * The Report Now States: "Analysis invalidated: System Entropy is too high (Chaos detected). Visual patterns and structures are unreliable."
In short, your analysis will now clearly report which guardrail—Math Lock or Chaos Filter—prevented the trade, turning a confusing "No" into an educational, trust-building explanation. Let me know if you have any other questions about the system's performance.