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Wir haben diesen TRADER 12 Mon begleitet - Tipps, Strategien, Erfahrungen 📈

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Winko, a 26-year-old car-dealership employee who says he has traded for about 10 years, describes moving from leveraged, unstructured trading to a rules-based approach. His story emphasizes risk control, patience, testing strategies, and avoiding pressure to make regular monthly profits.

Trading history and lessons

  • He first became interested in stocks through his grandfather and began following markets at around age 13. At 17, he opened an account through his mother with €100.
  • In 2019, he says he made about €2,000 in two weeks trading an index, then lost the account after holding an unprotected, leveraged position over a weekend. He says he had no strategy or stop-loss and used the RSI without a clear plan.
  • During the COVID-era market volatility, he later received €10,000 from his grandfather after making gains on a demo account. He says he lost the money within four weeks in leveraged trading.
  • He then stepped away from CFDs and traded individual stocks and ETFs, reading company accounts and looking for undervalued companies. He describes selling Palantir at about $11 before its subsequent rise to around $140. His account of a GameStop trade includes figures that appear garbled in the subtitles (“$100,” “$4.50,” and later “$400–$500”), so the exact entry and exit prices are unclear.
  • After further experimentation with CFDs, he sought formal trading education through TradingFreaks, completing its video course quickly and working with a coach.

Strategies and trading process

  • Start with one setup: Winko initially focused on a rejection/reversal setup rather than trying to learn all the strategies offered. The host says the program provides about 10 strategies.
  • Look for confluence: The rejection setup seeks significant liquidity areas, support or resistance, and other technical factors that may support a potential reversal. One example combines an S&P 500 support area near a former all-time high, a trend line, and a Fibonacci level.
  • Use defined rules: Winko recommends clear criteria for when to enter, when not to trade, and how to manage a position—rules precise enough, in principle, to be handed to a trading bot.
  • Test before going live: He demo-traded an additional, higher-frequency U.S. stock strategy for roughly January to May before returning to live trading in June. He says that strategy required practice identifying momentum and liquidity.
  • Use limit orders when appropriate: He describes identifying a potential zone after work, placing a limit order, and deleting it if the setup no longer applies. This lets him avoid watching the market continuously.
  • Check the news as a filter: He monitors general news and market coverage, including NTV and Investing.com/Investing Live (caption wording is uncertain), and may avoid technical trades around major geopolitical or monetary-policy events. He cites oil-market developments and U.S.–Iran tensions as a reason he avoided a potential long.
  • Review performance over a meaningful sample: The speakers caution against judging a strategy after only four or 10 trades. They suggest reviewing after roughly 100 trades or at quarter-end, since losing streaks can occur even with a strategy that has a positive win rate.

Risk management and performance

  • On a $360,000 prop-trading account, Winko says he initially risked 0.25% per trade, following his account manager’s recommendation, and maintained that level for about four to five months. He reports a profitable start and payouts, but gives no independently verifiable return figures.
  • After roughly six months, he says he increased risk to 1%, having built a buffer. The subtitles are unclear about the precise size of that buffer and the conditions for reducing risk again.
  • He reports a losing month in August after several losing swing trades and struggling with overtrading. During a live attempt at the higher-frequency strategy, he also says eight of 10 trades lost, including a streak of six losses. He responded by reducing trade frequency and reconsidering whether that strategy suited him.
  • A separate strategy is said to have had a 70%–75% backtested win rate, attributed to Pascal. The subtitles do not provide the test period, sample size, or other performance statistics.
  • The speakers advise against trying to force a positive result by month-end or targeting a fixed monthly return such as 4%. They suggest treating trading gains as a less frequent bonus, such as quarterly or annual income, rather than a monthly salary.
  • They also caution against trading under financial pressure—for example, trying to replace lost employment income or fund personal expenses through trading.

Assets, markets, and instruments mentioned

  • Equities: Deutsche Telekom, Palantir, GameStop, NIO, Virgin Galactic, Dropbox, Stellantis, and U.S. stocks generally.
  • Indices: DAX, S&P 500, and Nasdaq (the exact Nasdaq index is not specified).
  • Markets and instruments: CFDs, leveraged products, index futures, ETFs, individual stocks, Forex/currency pairs, and oil.
  • Technical tools and concepts: RSI, support and resistance, liquidity zones, trend lines, Fibonacci levels, stop-losses, limit orders, and take-profit orders.

Cautions and disclosures

  • The interview is educational and includes promotion of TradingFreaks’ coaching and links below the video. No explicit “not financial advice” disclaimer appears in the subtitles.
  • The guest’s trading outcomes are personal anecdotes; the interview does not provide audited performance records or enough information to assess the prop account’s rules, fees, drawdowns, or payout conditions.
  • Several figures and strategy names are distorted in the auto-generated subtitles. Unclear numbers have been identified as such rather than treated as confirmed results.

Presenters and sources

  • Winko: Interview guest and trader.
  • TradingFreaks host: Name is unclear in the subtitles.
  • Lukas: Identified as Winko’s coach.
  • Pascal: Mentioned in connection with the backtested strategy result.

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