Losing Retail Traders Keep Trading, Winning Retail Traders Know When to Rest

深潮Опубліковано о 2025-12-09Востаннє оновлено о 2025-12-09

Анотація

Stop Losing Money in Crypto: Why Day Trading is a Structural "Scam" for Retail Investors The author, drawing from personal trading experience since adolescence, argues that day trading is fundamentally rigged against ordinary investors. Retail traders lack critical advantages like real order flow data, liquidity maps, or execution speed. While infrequent trading might be survivable, high-frequency trading almost guarantees eventual ruin due to mathematical inevitability, even with strong discipline and risk management. The key insight isn't about winning—it's about keeping the money. Major losses often follow big wins when traders don't step back. The author transformed his results by becoming a low-frequency swing trader who pauses after profitable trades. The piece warns that the current social media-driven day trading culture misleads young people (e.g., on TikTok or Discord) into believing it's a learnable skill, not gambling. This false sense of control is dangerous—it prevents them from quitting. Unlike a casino, which is openly a gamble, day trading is disguised as a legitimate "system," making it harder to recognize the risk. In reality, most profitable retail traders are simply lucky, catching a trend and having enough discipline to stop temporarily. True success lies not in making money, but in preserving it.

Author:Pickle Cat

Compiled by: Deep Tide TechFlow

Want to stop losing money in the cryptocurrency market? First, stop your day trading!

Because for the average investor, day trading is structurally a "scam."

This article is long, but if you're willing to spend 120 seconds reading it, I guarantee you'll thank yourself years from now.

I started trading when I was a teenager.

I've had wins that made me feel like "Batman," and I've had painful failures that shattered me inside—wounds I'm still healing from today.

I've tried every trading strategy an average investor can find.

There was even a whole year when I was obsessed with day trading, thinking it would finally turn things around for me, but I failed so miserably that it still stings every time I look back.

My profit and loss (PNL) was so bad that my grandma's automated Bitcoin buying plan made more money than I did.

Later, I transformed into a low-frequency swing trader, rarely adjusting my positions. After making a profit, I would decisively exit and then take a break from trading for a while.

It was only then that my life started to improve, and everything began to make sense.

I'm no saint. I'm writing this to save my younger, foolish, naive, and impulsive self.

First, as an average day trader, you're engaging in high-frequency trading with no informational edge (no order flow data, no clear liquidity maps, no market maker position insights, no execution advantages, nothing).

If you only trade a few times per quarter, you might survive.

But what if you trade more than 10 times a week?

Even if you have the strongest "discipline" and "risk management" skills in the world, the math will eventually make you lose everything.

The reason average investors fail isn't that they never win; it's that they never stop. The only outcome of high-frequency trading is one: ruin.

That's why I set up a "penalty system" for myself—if I exceed my quarterly trading limit, I face consequences.

Every major loss I've experienced came after a big win, when I kept trading instead of stepping away.

And all my big wins (the ones where I actually held onto the money for a long time) happened because I caught a major trend and then chose to rest and cool off.

The pattern is so obvious it hurts.

"Winning" isn't just about making a lot of money suddenly; real "winning" is being able to keep that money instead of losing it all the next year.

Now I see 14-year-olds on TikTok calling themselves day traders, drawing a few lines on TradingView, thinking that buying some "guru's" course or joining a Discord group means they've mastered some daily executable trading system.

It makes me sick. If they knew they were gambling, I wouldn't mind—at least they'd know they're playing a game.

But the current day trading craze is even bigger than the "drop-shipping hype" of 2016 and 2017. And we all know how that ended.

People underestimate the difficulty of trading and severely overestimate their own abilities.

The problem isn't just mathematical. Yes, the more you trade and the less you stop, the harder it is to sustain profits.

The real issue is that young retail traders genuinely believe that with "discipline" and "risk management," they're not gambling at all. They think day trading is a "skill" that can be executed like a daily habit.

This doesn't just apply to cryptocurrency day trading; it's the same for the U.S. stock market and almost every other market.

High-frequency trading is only for institutions.

Take the U.S. stock market, for example.

Do you know what institutional traders don't even look at? Candlestick charts and TradingView.

They use Bloomberg terminals, which contain data retail investors will never see.

Sure, you might already know this. But 14- to 18-year-olds don't. They think their indicators are the tools everyone uses.

That's the real danger.

If you know you're gambling, at least part of you will know when to stop.

But once you believe it's a "system," you'll never quit.

You'll keep clicking until the market empties you out.

Day Trading: A Casino Disguised as a Café

It really is like a casino in plain sight.

When you walk into Las Vegas or Macau, you know what kind of place you're entering. You see the lights, the tables, the dealers, the noise. Your brain immediately recognizes: this is gambling.

But day trading today is like a casino disguised as a coffee shop.

New traders walk in thinking they're there to "learn a skill," unaware that they've already sat down at a table designed to slowly drain them.

So they don't stop.

That's the essence of the tragedy, not the losses themselves.

The truly sad part is that they truly believe they're not gambling, and it's that belief that keeps them going until they lose everything.

As for those retail traders who seem to be "making money" (like I once was)... honestly, most of them just caught a wave.

They had good luck at the right time, combined with a little discipline learned from previous losses, and finally learned to stop after winning.

Even so, such lucky ones make up less than one percent of all retail traders.

Making money in trading isn't actually that hard; what's truly difficult is keeping it.

Пов'язані питання

QWhy does the author believe that day trading is structurally a 'scam' for retail investors?

AThe author argues that retail day traders operate without any informational advantages (such as real order flow, liquidity maps, or market maker positioning), execution edge, or other institutional tools, making consistent profits mathematically improbable and leading to inevitable ruin through frequent trading.

QWhat key realization helped the author start improving their trading results?

AThe author improved their results by transitioning to low-frequency swing trading, taking profits decisively after wins, and then pausing trading for extended periods, which allowed them retain gains and avoid subsequent losses.

QAccording to the author, what is the true danger for young retail traders engaged in day trading?

AThe true danger is that young traders genuinely believe day trading is a skill-based system reliant on discipline and risk management, not gambling. This false belief prevents them from stopping even as losses accumulate, unlike in a casino where the gambling nature is obvious.

QHow does the author describe the environment of modern day trading for newcomers?

AThe author compares modern day trading to a casino disguised as a café—newcomers think they are learning a skill but are actually at a table designed to slowly drain their funds, unaware they are gambling.

QWhat does the author identify as the hardest part about making money in markets?

AThe hardest part is not making money, but keeping it. True winning is defined by the ability to retain profits over time, rather than giving them back in subsequent trades.

Пов'язані матеріали

After the Passage of the GENIUS Act and the CLARITY Act, What Is the Correct Architecture for On-Chain Yield?

The article discusses the evolution of on-chain credit, distinguishing three markets: overcollateralized crypto lending, unsecured lending (largely unsuccessful), and asset-backed credit (ABC). ABC, backed by identifiable real-world collateral with legal recourse, is identified as the fastest-growing category and the only one credibly addressing adverse selection—the core problem in credit where the riskiest borrowers self-select. Current growth in on-chain Real World Assets (RWAs), particularly tokenized private credit funds (e.g., Maple Finance, Centrifuge), is substantial but often merely "wraps" existing fund structures, inheriting their risks rather than solving adverse selection at the protocol level. The regulatory landscape is a key driver, with the US GENIUS Act (prohibiting stablecoin issuers from paying yield) and the proposed CLARITY Act (closing loopholes on indirect yield) set to redefine permissible yield-bearing products. This makes vaults (like ERC-4626) the critical architecture—they become the primary compliant vehicle for delivering yield, functioning as issuance, disclosure, distribution, and recovery mechanisms. The author's thesis is that the correct post-GENIUS/CLARITY architecture involves building ABC solutions where credit assessment, structure, and recovery are encoded directly into the smart contract vault layer, moving beyond mere tokenized fund wrappers to solve adverse selection fundamentally and ensure regulatory compliance.

Foresight News25 хв тому

After the Passage of the GENIUS Act and the CLARITY Act, What Is the Correct Architecture for On-Chain Yield?

Foresight News25 хв тому

TechFlow Intelligence Bureau: Anthropic's New Model Fable Sparks Controversy by Restricting Biosafety Research, US CPI Soars to 4.2%, a Three-Year High

**Summary of TechFlow Intelligence Report:** The newsletter covers several key tech and finance developments. In AI, Anthropic's new Fable model faced backlash for secretly limiting biomedical research capabilities and enforcing a 30-day data retention policy, prompting the company to promise more transparent adjustments. In a related story, Anthropic's founder revealed his departure from OpenAI was due to dishonesty from Sam Altman, not safety concerns. Meanwhile, OpenAI is considering significant price cuts to compete with Anthropic, potentially sparking a price war. In crypto/Web3, BlackRock filed a new amendment for a yield-generating Bitcoin ETF, while Bank of America's CEO warned that stablecoin yields could drain trillions from traditional banks. U.S. Senator Cynthia Lummis advocated for the U.S. to officially accumulate Bitcoin reserves. In hardware, Nvidia released the DiffusionGemma-2-6B image model optimized for efficient inference, and AMD promoted its unified memory architecture to challenge Nvidia's dominance. TSMC's CFO hinted at possible price increases due to soaring AI chip demand. A major legal ruling in Germany held Google legally responsible for inaccurate information generated by its AI Overviews feature. Google Chrome also moved to fully block ad-blocker workarounds like uBlock Origin. Macroeconomic headlines included U.S. CPI rising to 4.2% (a 3-year high) and Iran's complete closure of the Strait of Hormuz, raising oil price and inflation fears. South Korean markets saw continued volatility with massive foreign capital outflow. Other notable stories: Microsoft expanded its Copilot AI assistant "Mico" globally; a study found r/wallstreetbets users' stock picks outperformed Wall Street; a fully autonomous drone killed a human soldier for the first time, raising AI ethics concerns; and a Chinese hospital used brain-computer interface technology to help a blind person "see." The overarching theme connects debates over AI boundaries and responsibility (Anthropic's restrictions, Google's liability, lethal autonomous drones) with real-world economic and geopolitical turmoil (inflation, Strait of Hormuz closure, market instability), highlighting the tense interplay between technological advancement and global chaos.

marsbit38 хв тому

TechFlow Intelligence Bureau: Anthropic's New Model Fable Sparks Controversy by Restricting Biosafety Research, US CPI Soars to 4.2%, a Three-Year High

marsbit38 хв тому

Alibaba's Yet Another New Business Division: What Signal Does It Send?

Alibaba has established a new "Token Foundry" business unit, merging its Tongyi large model division and Future Life Lab. Led directly by Group CEO Wu Yongming, this marks the company's third significant AI organizational reshuffle in 2026, following the creation of the Alibaba Token Hub (ATH) and a Group Technology Committee. The move signals a strategic shift from consolidating AI resources to accelerating productization and commercialization. The "Token Foundry" name reflects Alibaba's ambition to become a foundational supplier in the AI era, focusing on model development and commercial application. Key teams, including those behind the high-performing HappyHorse video generation model, have been integrated into the new unit. Concurrently, Zhou Jingren, architect of the Qwen model series, has been appointed Group Chief Scientist to lead a new AI Future Research Institute, focusing on long-term technological breakthroughs like Agent capabilities. This restructuring creates a clear four-layer AI architecture within Alibaba: the research institute for frontier exploration, Token Foundry for core models and commercialization, MaaS for platform services, and business units like Qianwen (C端) and Wukong (B端) for end-user applications. The adjustments align with a global trend among tech giants like Google and Microsoft to centralize AI leadership under the CEO and deeply integrate research with business units. The urgency is driven by a narrowing competitive window. Alibaba has announced its AI business is now entering a commercialization phase, with AI-related revenue seeing triple-digit growth for eleven consecutive quarters. The company faces intense competition in the MaaS (Model-as-a-Service) sector from rivals like ByteDance and Tencent. The Token Foundry initiative represents Alibaba's effort to streamline execution and enhance competitiveness in this critical, fast-evolving landscape.

marsbit1 год тому

Alibaba's Yet Another New Business Division: What Signal Does It Send?

marsbit1 год тому

From Return to Resignation: Chen Hang's 437 Days at DingTalk

The 437-Day Return and Departure of Chen Hang at DingTalk This article chronicles the 437-day period from March 31, 2025, to June 11, 2026, when Chen Hang (also known as "No Move") returned as CEO of DingTalk, the enterprise communication platform he originally founded, only to later step down. Chen Hang, the creator of DingTalk in 2015, was brought back by Alibaba in 2025 after the company acquired his subsequent startup, HHO. His return was driven by Alibaba's renewed focus on AI and DingTalk's strategic role as its key to-B AI application. However, his aggressive management style, marked by strict work policies like mandatory clock-ins and extended hours, quickly caused internal friction and was criticized as being at odds with Alibaba's culture. Despite the internal turmoil, Chen Hang drove significant product launches. In August 2025, he unveiled "AI DingTalk 1.0," featuring new products like the AI-native entry point "DingTalk ONE." By March 2026, he announced "Wukong," touted as the world's first enterprise-grade AI-native work platform, representing a fundamental rebuild of DingTalk's architecture. The turning point came in early June 2026. A detailed internal post criticizing DingTalk's work culture went viral, followed by a public critique from a former executive. This prompted an unprecedented public rebuke from the Alibaba Partners Committee, which stated such management was not aligned with company values. One day later, on June 11, Alibaba announced Chen Hang's departure. He was succeeded by Chen Yusen, a 32-year-old technical expert known for founding cybersecurity firm Changting Technology. While Chen Hang's tenure laid the technical foundation for DingTalk's AI transformation with "Wukong," his leadership style ultimately led to his replacement as the company seeks a new direction under younger leadership.

marsbit1 год тому

From Return to Resignation: Chen Hang's 437 Days at DingTalk

marsbit1 год тому

Торгівля

Спот
Ф'ючерси

Популярні статті

Як купити T

Ласкаво просимо до HTX.com! Ми зробили покупку Threshold Network Token (T) простою та зручною. Дотримуйтесь нашої покрокової інструкції, щоб розпочати свою криптовалютну подорож.Крок 1: Створіть обліковий запис на HTXВикористовуйте свою електронну пошту або номер телефону, щоб зареєструвати обліковий запис на HTX безплатно. Пройдіть безпроблемну реєстрацію й отримайте доступ до всіх функцій.ЗареєструватисьКрок 2: Перейдіть до розділу Купити крипту і виберіть спосіб оплатиКредитна/дебетова картка: використовуйте вашу картку Visa або Mastercard, щоб миттєво купити Threshold Network Token (T).Баланс: використовуйте кошти з балансу вашого рахунку HTX для безперешкодної торгівлі.Треті особи: ми додали популярні способи оплати, такі як Google Pay та Apple Pay, щоб підвищити зручність.P2P: Торгуйте безпосередньо з іншими користувачами на HTX.Позабіржова торгівля (OTC): ми пропонуємо індивідуальні послуги та конкурентні обмінні курси для трейдерів.Крок 3: Зберігайте свої Threshold Network Token (T)Після придбання Threshold Network Token (T) збережіть його у своєму обліковому записі на HTX. Крім того, ви можете відправити його в інше місце за допомогою блокчейн-переказу або використовувати його для торгівлі іншими криптовалютами.Крок 4: Торгівля Threshold Network Token (T)Легко торгуйте Threshold Network Token (T) на спотовому ринку HTX. Просто увійдіть до свого облікового запису, виберіть торгову пару, укладайте угоди та спостерігайте за ними в режимі реального часу. Ми пропонуємо зручний досвід як для початківців, так і для досвідчених трейдерів.

452 переглядів усьогоОпубліковано 2024.12.10Оновлено 2026.06.02

Як купити T

Обговорення

Ласкаво просимо до спільноти HTX. Тут ви можете бути в курсі останніх подій розвитку платформи та отримати доступ до професійної ринкової інформації. Нижче представлені думки користувачів щодо ціни T (T).

活动图片