The End of Chart Staring:
How Alert Driven Trading Is Replacing the 12-Hour Screen Grind
The smartest move in crypto trading is learning to look away from the charts - and letting the charts come to you. Alert Driven Trading replaces hours of manual scanning with automated pattern detection, preserving your decision-making energy for the trades that actually matter.
Somewhere right now, a retail crypto trader is four hours into a session. They've cycled through the same 15 charts twice. Nothing has set up. They're bored, tired, and running out of patience. In about 20 minutes, they'll force a trade on a pattern that isn't quite there - just to feel like the time wasn't wasted. By tomorrow, they'll have a smaller account and no idea what went wrong.
I know this because I was that trader. For years. I've been in crypto since 2013 - four bull markets, four bear markets, and more blown trades than I'd like to admit. And if there's one thing those years taught me, it's that the biggest threat to a trader's account isn't a bad strategy. It's a bad workflow.
That realization is why I built ChartScout. But before I explain what it does, I want to explain the problem it solves - because the data behind it is far worse than most traders realize. This article covers the research on decision fatigue, overtrading, and why Alert Driven Trading is likely the only sustainable workflow for retail traders in 2026.
The Numbers Behind the Burnout
The data on retail trading is devastating, and it points to a problem that has nothing to do with strategy. These numbers haven't improved despite better tools, better education, and better market access. If anything, the proliferation of complex charting platforms has made the problem worse.
72% End the Year With Losses
According to QuantifiedStrategies.com (citing FINRA data), nearly three-quarters of day traders lose money annually. Only about 1% maintain profitability over five years, though the exact figure lacks a clear primary source. [1]
97% Lose Over 300 Days
A Brazilian study tracking equity futures traders found that 97% of those who persisted for 300+ days lost money. [3]
74-89% Lost in Every Major Event
Industry data from PiP World (using proprietary Exinity platform data) tracking 8 million traders over 27 years found losses across all platforms, education levels, and regulatory environments. Note: this is proprietary industry data, not peer-reviewed academic research. [2]
40% Quit in Month One
According to industry estimates, nearly half of all day traders quit within the first month. Only 13% remain after three years. [4]
More indicators, more timeframes, more pairs to monitor - the cognitive load has exploded while the human brain's processing capacity has stayed exactly the same. The root cause isn't lack of knowledge. It's decision fatigue.
Decision Fatigue: The Silent Account Killer
Decision fatigue is a well-documented cognitive phenomenon: the quality of decisions deteriorates after a prolonged period of making them.
“In a widely cited study, Israeli parole judges granted freedom 65% of the time at the start of the day but nearly 0% by late afternoon - not because the cases changed, but because their brains were exhausted.”
- Danziger, Levav & Avnaim-Pesso, Proceedings of the National Academy of Sciences [5]Note: This study has been contested. Glöckner (2016) suggested the effect could be partly explained by case-ordering artifacts, and Weinshall-Margel & Shapard (2011) argued case order was not random. The core concept of decision fatigue remains well-supported by other research, but the specific judicial finding is debated.
Think of your decision-making ability as a battery. It starts the day fully charged. Every time you look at a chart and decide “No, not yet,” you drain it slightly. Every micro-decision - Is this worth watching? Should I enter? Where's my stop? Is that volume confirming or diverging? - pulls a little more charge. Multiply that across 10 charts, five timeframes, and an 8-hour session, and you've made thousands of judgment calls before lunch.
By the time a genuinely good setup appears at 4 PM, your battery is at 20%. You might hesitate and miss the move. Or you might rush and get a terrible entry. Either way, you've spent your best mental energy on the 99 charts that didn't matter, and you have nothing left for the one that did.
The Progression of Fatigue
Early in the session, you're patient and disciplined. By hour four, you're overtrading. By hour six, you're revenge trading. By hour eight, you've abandoned your rules entirely. “Decision fatigue does not announce itself as exhaustion - it manifests as justified exceptions to previously sound rules.” [6]
The crypto market makes this exponentially worse. Unlike stocks, which at least offer the mercy of a closing bell, crypto trades 24 hours a day, 7 days a week. There is no natural stopping point. The charts are always moving. The fear of missing out never sleeps. And the psychological strain of constant access pushes traders toward the exact impulsive behavior that destroys accounts [7].
A Personal Wake-Up Call
At my worst, I was spending up to 18 hours a day staring at screens. Many nights I would wake up twice just to check the markets. When I received my Binance annual report for 2021, the number staring back at me was roughly 36,000 trades in a single year. Most were breakout entries with tight stop losses - jumping on every formation, getting stopped out over and over, racking up fees each time. I wasn't trading a strategy. I was feeding an addiction to activity.
Research on stress and decision-making has confirmed what I experienced firsthand: high stress biases people toward riskier, short-term rewards [8]. A meta-analysis found that stress promotes increased risk-taking and reward-seeking even when this leads to disadvantageous outcomes [8]. A separate review confirmed these findings across valuation, learning, and risk-taking contexts [9]. That's not a description of a bad trader. That's a description of every trader after enough screen time.
The Paradigm Shift: From Hunter to Trapper
There is a name for the solution I eventually arrived at: Alert Driven Trading. But to understand why it works, think about two survival strategies.
🏹 The Hunter
Puts on gear and runs through the forest for 8 hours, scanning the horizon for a deer.
- By hour six, exhausted
- Might shoot at a shadow out of desperation
- High energy, high time, high emotional risk
- Inconsistent results
🪤 The Trapper
Spends one hour analyzing the forest. Sets 50 snares at exact spots. Goes home and lives their life.
- Only returns when they hear a snap
- Arrives fresh, focused, and ready
- Low energy, almost zero time after setup
- Consistent, repeatable results
This is not about laziness. It`'s about leverage - specifically, the concept of asymmetric effort. In the old model, active charting might produce 10 hours of screen time for one potential trade. That`'s low leverage. In the Alert Driven model, one hour of setup produces notifications for potentially dozens of valid setups over the coming weeks. That`'s high leverage.
The insight is that humans are terrible at monitoring but excellent at deciding. A human staring at a chart for hours will get tired, emotional, and eventually force a trade. A machine watching 1,000 charts for 24 hours will never get bored, never force a trade, and never check a chart “just one more time” at 3 AM.
The result: you spend zero energy searching and 100% of your energy executing. This also addresses what may be the single biggest account killer in retail trading - overtrading [10]. If your workflow depends on a notification system, you physically cannot trade until a setup exists. If your phone doesn't buzz, you don't trade. The system effectively automates patience, which is the one virtue every trading book preaches but no charting platform enforces.
JOMO: The Joy of Missing Out
The active trader lives in FOMO. They stare at charts because they`'re terrified a candle will move without them. The Alert Driven trader lives in JOMO. If your phone doesn`'t ring, you know for a fact that nothing matches your criteria. You`'re free. You can go to the gym, spend time with your family, or sleep through the night without anxiety - trusting that your digital sentries are standing guard.
The Execution Gap: Why This Actually Works
There`'s a massive difference between identifying a pattern and trading it successfully. The Alert Driven model works because it separates these two distinct tasks and assigns each to whoever does it best.
Task A: Scanning
Mathematically rigid. Is the price forming a converging triangle? Is the wedge rising with declining volume? Yes or no.
- Humans are terrible at this at scale
- We “force” trendlines to fit our bias
- Software is perfect at this - raw data, no emotion, 24/7
Task B: Contextualizing
Is Bitcoin crashing? Did the SEC just announce something? Is this a low-liquidity session where fakeout rates spike?
- Software is terrible at this
- It doesn't read news or feel market panic
- Humans are excellent at this
The perfect workflow lets the software handle Task A - the grunt work of scanning. When the notification hits, you step in for Task B - the contextual decision that actually determines profit or loss. You're no longer a “chart watcher.” You're a risk manager. And you arrive at that decision with your battery at 100%, because you haven't wasted it on the 999 charts that didn't matter.
Why I Built ChartScout
I wanted this tool since 2017. In 2024, I finally decided to build it. Before starting, I bought access to every competing tool I could find. Some were too complex - powerful features buried under steep learning curves that required hours of setup. Other tools looked promising but didn't give me any actual edge in practice.
I couldn't find a tool that did what I needed: detect patterns early, across many pairs, with alerts fast enough to actually trade on. So I decided to build it myself.
“What sets ChartScout apart isn`'t more features. It`'s a fundamentally different philosophy. Most platforms hand you a cockpit with 150+ pattern types and endless customization. ChartScout just calls you an Uber. Most traders don`'t need a cockpit - they need to get to the destination.”
- Stjepan Ivanović, Founder of ChartScoutHow It Works: The Watcher Model
ChartScout's architecture is built around simplicity. You create “watchers” - each one monitors a single combination of trading pair + timeframe + pattern. One watcher might be BTC/USDT on the 15-minute chart watching for rising wedges. Another might be ETH/USDT on the 4-hour chart watching for ascending triangles.
The system scans 1,000+ pairs across four major exchanges - Binance, Bybit, KuCoin, and MEXC - on both spot and futures markets. When a pattern forms that matches your criteria, you get an alert in under 20 seconds.
| Tier | Price | Watchers | Min. Timeframe | Patterns |
|---|---|---|---|---|
| Free | $0 | 5 | 30min | 3 bullish |
| Basic | $49/mo | 50 | 15min | 12 core |
| Pro | $129/mo | 150 | 5min | All 19 |
| Enterprise | $299/mo | 350 | 1min | All 19 |
What's Under the Hood: Why ML Failed and Manual Logic Won
Perhaps the thing I'm most honest about with ChartScout is what didn't work. We spent months trying machine learning approaches to pattern detection. The models that looked excellent in backtesting fell apart on live data - too many false signals, too slow to adapt.
So we went a different direction. The pattern detection uses manual logic combined with algorithms like RANSAC Regressor, while ML models (SVM, Isolation Forest, LOF) handle the filtering and data cleaning. Every pattern script goes through thousands of test results and hundreds of manual parameter tweaks before reaching users.
Development Timeline
The first pattern detection script alone took six months - from October 2024 to March 2025 - to work reliably on live markets. We're now over 15 months into development and still in beta. We currently support 19 patterns, with each new script undergoing months of testing before being offered to users.
The Black Box Philosophy: Why You Can't Tweak the Detection
One thing people notice quickly about ChartScout is that you can't adjust the internal detection parameters. There's no “sensitivity slider.” No “reliability score threshold” to loosen. You pick the pattern, the pair, and the timeframe. The detection logic is locked.
This is deliberate. By locking the parameters, we're taking responsibility for the signal. We're saying: “We've done the testing. We've spent months tuning what a valid bull flag looks like mathematically. We're not going to let you break that by loosening the rules just to get more alerts.”
Why Customization Can Be Dangerous
On platforms where customization is the selling point, if you miss a trade, the instinct is: “Maybe I should tweak my settings.” This leads to endless tinkering and curve fitting - changing rules to match past data - which is one of the most reliable ways to lose money in the future. With ChartScout's locked parameters, you accept that it didn't meet the criteria and wait for the next alert.
When you use ChartScout, you're not just paying for software - you're paying for curated intelligence. You're paying us to say: “No, that wasn't a head and shoulders. It looked like one, but our algorithm rejected it because the right shoulder volume was too high. Trust us, it would have failed.”
Radical Transparency: Prove It Before Charging for It
Most trading software operates on a “Paywall First, Value Later” model. The established platforms say: “Sign up for a free trial - credit card required - and maybe we'll show you what we can do.” Most crypto signal services are even worse: they sell you access to a “secret” edge that usually doesn't exist. I decided to do the opposite.
ChartScout has multiple public channels where anyone can observe real pattern detections without creating an account, without entering a credit card, without signing up for anything.
- The landing page widget at chartscout.io features a live feed that filters the best detections from actual users across the platform.
- The X/Twitter bot (@ChartScout_bot) posts top detections to social media in real time.
- The ChartScout Discord server includes a detection feed accessible to anyone who joins - no paid subscription needed.
Why Public Channels Change the Game
By broadcasting live detections to public channels without a login wall, ChartScout does something risky: it creates a public audit trail.
- Proof of work: Anyone can scroll back through months of alerts in our Discord channel and see exactly every detection that was fired. You can verify the accuracy yourself.
- Anti-scam: Scammers hide their history. They delete bad calls. A public feed is immutable. If the bot called a bull flag on Bitcoin and Bitcoin crashed, the evidence is there forever.
- The freemium flip: We give you the full outcome (the actual alerts, in real time, publicly) but restrict the convenience. You know exactly what you're buying before you spend a dollar.
Why Competitors Don't Do This
There are two reasons. The first is fear of exposure - if established platforms streamed every single “strong buy” signal into a public chat, users might realize how many false positives there are. The second is that they simply don't need to. They have millions in revenue, massive user bases, and years of brand recognition.
Our Position
ChartScout is a startup. We have no revenue track record. No millions of users. When you're starting from zero, you can't just say “trust us” - you have to show the work. Radical transparency isn't just a philosophy for us. It's the only credible option.
Education First: Chart Patterns Are Not Enough
This might sound strange coming from someone who built a pattern detection tool, but I'll say it plainly: chart patterns alone are not enough.
The scenario is simple: two traders spot the same ascending triangle on ETH/USDT. One profits. The other gets stopped out on a false move. Same pattern, same pair, different outcomes. The difference is volume.
📚 Related Guides
Drawing on Thomas Bulkowski's Encyclopedia of Chart Patterns, we published comprehensive guides that teach you to question the very alerts you're paying for:
Honest Disclosure
According to Bulkowski's Encyclopedia of Chart Patterns, breakout failure rates can range from under 20% to over 80% depending on the pattern type, market conditions, and how “failure” is defined [14]. Crypto's structural characteristics - 24/7 trading, thin liquidity on altcoins, exchange fragmentation, whale manipulation - likely push failure rates toward the higher end [15]. Yes, I'm telling you that the patterns my own tool detects will fail most of the time without additional context.
The Hidden Trap: Context Blindness
No honest discussion of Alert Driven Trading can avoid its central limitation. A notification tool sees mathematics, not market conditions.
The entire idea isn`'t just “good” - it`'s likely the only way for a retail trader to compete in 2026. Institutions have algorithms running 24/7. If you`'re trying to beat them by staring at a screen with your naked eyes, you lose. By using Alert Driven detection, you`'re essentially hiring an algorithmic assistant to level the playing field, freeing you to focus on the one thing the algorithm can`'t do: understand the bigger picture.
This is what experienced traders call “context blindness,” and it's inherent to any pattern-only alert system - not a flaw specific to ChartScout. This is exactly why the Execution Gap matters. ChartScout handles Task A - scanning. You handle Task B - contextualizing.
✅ The Right Way
- Phone buzzes → Open chart
- Check Bitcoin's trend
- Check the news
- Evaluate volume
- Execute (or don't)
❌ The Wrong Way
- Phone buzzes → Buy immediately
Treating alerts as buy signals instead of investigation triggers is the fastest way to lose money with any alert tool.
⏱️ The 30-Second Rule
When a notification arrives, if you can't see a clear reason to take the trade within 30 seconds of opening the chart, close it and move on. This prevents you from sitting there for 10 minutes trying to justify a bad alert. If the setup isn't obvious at a glance, it's not obvious enough.
The Broader Risk Picture
Beyond context blindness, crypto pattern trading carries risks that no software can eliminate. I want to be completely transparent about these.
Critical Warning
No tool guarantees profitability. ChartScout won't make you a better trader. It won't guarantee profits. It won't tell you when to buy or sell. Markets are unpredictable, and no software changes that. What it does is save you time.
- The base rate is brutal: An estimated 72% of day traders lose money annually (per industry surveys citing FINRA data) [1]. Among those who persist for 300+ days, 97% lose money [3]. According to proprietary industry data (not peer-reviewed), 85% of failed accounts follow a predictable four-phase spiral: cautious success, overconfidence, catastrophic loss, terminal decline [2].
- Crypto amplifies every risk: The 24/7 market eliminates rest periods. Thin liquidity produces frequent false breakouts. Whale manipulation and liquidation cascades can invalidate textbook formations instantly.
- Lower timeframes are dramatically less reliable: Patterns on 1-minute or 5-minute charts produce far more false signals than 4-hour or daily formations [14].
- A single event can override any pattern: A tweet or regulatory announcement can invalidate any technical formation instantly.
How to Implement Alert-Driven Trading
If you want to adopt this workflow - whether you use ChartScout or any other tool - here's the blueprint:
- Define your edge. You need to know what you're trapping. Don't configure alerts for “everything.” Be specific: “I only want Bull Flags on the 4H timeframe on the top 20 coins by volume.” The more precise your criteria, the fewer false leads you'll waste energy on.
- Set your sentries. Configure your watchers to scan for that specific edge. This is the one-time setup that replaces hours of daily screen time.
- Apply the 30-second rule. When a notification arrives, open the chart. If you can't see a clear reason to take the trade within 30 seconds, close it. No justifying, no forcing, no “well, maybe if I switch to the 5-minute...” If it's not obvious, it's not a trade.
- Run your checklist. If the setup passes the 30-second test: check Bitcoin's trend, check the news, evaluate volume against the pattern, and confirm the context supports the trade. This is Task B - the part humans do better than any algorithm.
- Execute or walk away. Place the trade or close the chart. Either way, you've spent two minutes instead of two hours, and your decision battery is intact for the next alert.
The entire idea isn't just “good” - it's likely the only way for a retail trader to compete in 2026. Institutions have algorithms running 24/7. If you're trying to beat them by staring at a screen with your naked eyes, you lose. By using alert-driven detection, you're essentially hiring an algorithmic assistant to level the playing field, freeing you to focus on the one thing the algorithm can't do: understand the bigger picture.
The Verdict: Alert Driven Trading Is the Right Direction
The shift from active chart monitoring to passive alert-based workflows represents a genuine evolution in how retail traders can approach markets. The evidence is clear that decision fatigue, overtrading, and emotional exhaustion are primary drivers of retail losses [6][10] - and these are problems of workflow, not strategy.
ChartScout is still in beta. Our pattern library is still growing. But everything about how we've built this - the months of testing per pattern, the ML approaches abandoned when they didn't hold up on live data, the free public detection channels, the educational content that teaches you to question the very alerts you're paying for - comes from a simple belief: the tool should earn your trust before it earns your money.
Key Takeaways
- Decision fatigue is the real enemy - not bad strategy. Every chart you scan drains your decision battery.
- Be the trapper, not the hunter - set your alert criteria once, then only engage when a valid setup appears.
- Alerts are not buy signals - they're investigation triggers. Always apply the 30-second rule and run your context checklist.
- No tool guarantees profits - but the right workflow protects your mental capital and eliminates overtrading.
- Demand transparency - any tool asking for your money should let you audit its results publicly first.
Stop being the hunter. Become the trapper. Set your snares, protect your decision battery, and show up fresh when something actually matters. ChartScout watches 1,000 charts so you don't have to. What you do when it taps your shoulder - that's still entirely up to you.
Frequently Asked Questions
What is Alert Driven Trading?
Alert Driven Trading is a workflow where you configure automated scanners to monitor charts for specific patterns or conditions, then only open a chart when a notification arrives. Instead of spending hours manually scanning, you let software handle the monitoring and preserve your mental energy for the actual trading decision.
How does decision fatigue affect trading performance?
Decision fatigue causes the quality of decisions to deteriorate after prolonged decision-making. In trading, every chart scan and micro-decision drains your mental battery. A widely cited (though debated) study found that favorable judicial rulings dropped from 65% to nearly 0% within each decision session [5]. The same effect causes traders to overtrade, force entries, and abandon their rules after hours of screen time.
What percentage of day traders lose money?
According to QuantifiedStrategies.com (citing FINRA data), 72% of day traders end the year with losses. A Brazilian study found 97% of persistent traders lost money [3]. Only about 1% maintain profitability over five years [1], and an estimated 40% quit within the first month [4].
What is the hunter vs trapper analogy in trading?
The hunter spends 8+ hours scanning charts, getting tired and eventually forcing trades. The trapper spends one hour configuring alerts, then goes about their life - only returning when a notification signals a valid setup. The trapper model leverages asymmetric effort for maximum coverage with minimal time investment.
How does ChartScout work?
You create “watchers” - each monitors a specific trading pair + timeframe + pattern. The system scans 1,000+ pairs across Binance, Bybit, KuCoin, and MEXC on spot and futures markets. When a pattern matches your criteria, you get an alert in under 20 seconds via platform notification, Discord, email, or Telegram.
Why can't you customize ChartScout's detection parameters?
Each pattern script goes through thousands of test results and hundreds of manual parameter tweaks. Locking the parameters prevents users from loosening rules (increasing false positives), eliminates analysis paralysis from endless tinkering, and ensures standardized, high-confidence patterns for all users.
What is the 30-second rule?
When a notification arrives, if you can't see a clear reason to take the trade within 30 seconds of opening the chart, close it and move on. This prevents sitting for 10 minutes trying to justify a bad alert. If the setup isn't obvious at a glance, it's not obvious enough.
Can chart pattern alerts guarantee profitable trades?
No. According to Bulkowski's data, breakout failure rates can range from under 20% to over 80% depending on pattern type, market conditions, and how failure is defined [14]. Crypto likely pushes those rates toward the higher end [15]. An alert tells you a pattern exists; you must still evaluate volume, market context, news, and liquidity conditions before deciding whether to trade.
Ready to Stop Staring at Charts?
ChartScout watches 1,000+ pairs across 4 exchanges so you don't have to. Set your watchers, protect your decision battery, and only trade when it matters.
Sources & References
Retail Trading Statistics
Industry research on trader performance and behavior:
- QuantifiedStrategies.com. “Day Trading Statistics 2025: The Hard Truth.” Reports 72% of day traders end the year with losses (citing FINRA data) and estimates only 1% succeed over five years. Note: These figures are from a secondary source; the specific 72% and 1% numbers have not been independently verified in primary FINRA publications.
Available at: quantifiedstrategies.com - PiP World / ZeroHedge. “Retail Traders Lost 74-89% During Every Major Volatility Event” (November 2025). Proprietary industry analysis by PiP World using Exinity retail trading platform data, covering 8 million traders and 295 million trades across 27 years (1998-2025). Note: This is proprietary industry data published on ZeroHedge, not independent peer-reviewed academic research. PiP World is a commercial entity promoting its AI trading product.
Available at: zerohedge.com - Chague, F., De-Losso, R., & Giovannetti, B. (2020). “Day Trading for a Living?” University of São Paulo, Department of Economics Working Paper. 97% of persistent traders lost money.
Available at: SSRN - ForTraders.com. “Is Day Trading Still Profitable in 2025?” Reports 40% of day traders quit within one month; only 13% remain after three years. Note: ForTraders.com is a blog/aggregator; the underlying primary data source for this specific figure is not clearly identified.
Available at: fortraders.com
Psychology & Decision Science Research
Academic sources on decision fatigue and stress in decision-making:
- Danziger, S., Levav, J., & Avnaim-Pesso, L. (2011). “Extraneous Factors in Judicial Decisions.” Proceedings of the National Academy of Sciences, 108(17), 6889-6892. Note: This widely cited study has been contested. Glöckner (2016) proposed that the observed pattern could be explained by favorable rulings taking longer, and Weinshall-Margel & Shapard (2011) argued case ordering was not random. The broader concept of decision fatigue is supported by other research.
Available at: pnas.org - FXStreet. “Managing Decision Fatigue: Why Fewer Choices Lead to Better Trading Performance” (December 2025).
Available at: fxstreet.com - DayTrading.com. “Cognitive Load & Decision Fatigue in Trading” (September 2025). Review of continuous market monitoring and cognitive overload.
Available at: daytrading.com - Starcke, K. & Brand, M. (2016). “Effects of Stress on Decisions Under Uncertainty: A Meta-Analysis.” Psychological Bulletin. Stress promotes increased risk-taking and reward-seeking.
Meta-analysis of stress and decision-making under uncertainty. - Porcelli, A.J. & Delgado, M.R. (2017). “Stress and Decision Making: Effects on Valuation, Learning, and Risk-taking.” Current Opinion in Behavioral Sciences, 14, 33-39.
Available at: PubMed Central - Vetted Prop Firms. “Day Trading Statistics 2026: The Numbers Most Traders Ignore” (November 2025). Identifies overtrading and emotional decision-making as top mistakes.
Available at: vettedpropfirms.com
Technical Analysis & Market Research
Pattern analysis and trading literature:
- ChartScout. “How to Combine Chart Patterns with Volume Analysis.” Comprehensive guide covering volume signatures for 8 major pattern types.
Available at: chartscout.io/chart-patterns-and-volume-analysis - Bulkowski, Thomas N. Encyclopedia of Chart Patterns, 3rd Edition. John Wiley & Sons. Industry-standard reference for chart pattern statistics and breakout failure rates.
- ChartScout. “How to Spot Fake Breakouts in Crypto Trading [2026 Guide].” Discussion of breakout failure rates in traditional markets, which Bulkowski's data shows can range from under 20% to over 80% depending on pattern type, market conditions, and failure definition.
Available at: chartscout.io/how-to-spot-fake-breakouts-crypto
Additional Academic References
- Barber, B.M. & Odean, T. (2000). “Trading is Hazardous to Your Wealth.” The Journal of Finance, 55(2), 773-806.
- Barber, B.M., Lee, Y.T., Liu, Y.J., & Odean, T. (2014). “The Cross-Section of Speculator Skill: Evidence from Day Trading.” Journal of Financial Markets, 18, 1-24.
- Mather, M. & Lighthall, N.R. (2012). “Both Risk and Reward are Processed Differently in Decisions Made Under Stress.” Current Directions in Psychological Science, 21(2), 36-41.
- Tharp, Van K. (2006). Trade Your Way to Financial Freedom, 2nd Edition. McGraw-Hill. Chapter 4: Risk management psychology.
Stjepan Ivanović
Founder of ChartScout · Crypto Trader Since 2013
Trading crypto since 2013 with his first Bitcoin bought at ~$200. Four complete bull/bear market cycles, traded on early exchanges like Mt.Gox and BTC-e, on-chain trading on IDEX and EtherDelta, and ~70 crypto project investments. Built ChartScout after 15 months of development to automate what no trader can do manually - watch hundreds of charts 24/7.