Five Days of Real-World Trading Practice on LBank Demo Account: Discipline, Strategy, and Market Interaction

From November 4th to November 8th, 2025, over five trading days, we conducted a highly realistic simulated trading experiment, primarily using LBank's new coin launches and contract trading as the trading venues. This simulation was strictly based on publicly available market data and news sources (such as real-time prices from CoinMarketCap and Yahoo Finance, and the Crypto Fear & Greed Index from Alternative.me), combined with LBank's official announcements regarding coin listings and macroeconomic events (such as Federal Reserve policy expectations). Daily trading signals were generated through manual analysis combined with a simple bot script (using the Python-based TA-Lib indicator). Our focus was on a two-pronged approach: capturing short-term impulse opportunities in LBank's newly listed tokens (spot launches), while simultaneously using 1-5x leverage on related cryptocurrencies (such as BTC/ETH futures) to hedge or amplify trends, enabling precise entry and exit points during periods of extreme price volatility or market sentiment.

The daily equity curve is shown in the figure below (based on an initial principal of $10,000, minus 0.1% transaction fees and slippage simulation). Ultimately, with ironclad stop-loss and take-profit rules (stop-loss not exceeding 2% per trade, take-profit target at least 3 times risk), the total return reached 10.29% (final value $11,029), far exceeding the -4.2% drop in BTC during the same period, achieving "excess alpha". This article will break down the operational details, profit calculations, and lessons learned day by day, extract the patterns of LBank listings, and reflect on trading psychology and optimization paths to help readers build sustainable strategies in similar environments.

Simulation Strategies and Trading Background

This simulation starts with $10,000 and employs a trend-following + low-frequency Swing strategy, with position sizes not exceeding 20% of total capital per trade. It emphasizes "high-quality screening + high profit/loss ratio" (target 1:3). No insider information or paid data is used; only free tools are relied upon: RSI/MACD technical indicators, the Fear & Greed sentiment index, and announcements from the LBank App. The core principle is "fewer trades, more review"—a maximum of 3-5 trades per day to avoid FOMO (fear of missing out)-driven impulses. Research shows (e.g., Investopedia reports) that professional traders only need a 30%-40% win rate, but through strict risk control, they can achieve a positive long-term expected value. Before each entry, we always create a "chain of thought": Signal confirmation? Risk/reward ratio? Alternative exit strategies?

The contract portion utilizes LBank's USDT perpetual contracts, providing leverage flexibility: amplifying spot profits in bullish markets and hedging in bearish markets (e.g., shorting BTC to hedge against long positions in new coins). The platform's leverage limit is 20x, but we limit our use to 5x or less to prevent liquidation. The overall style is low-frequency (15 trades per week) and long-term (1-48 hours), aligning with the consensus of "reducing transaction costs and amplifying compound effects"—statistically, 81% of retail investor losses stem from overtrading, while streamlined operations can increase the annualized Sharpe ratio to over 1.5.

Market Dynamics Review

November 4, 2025 (Monday): Panic at the start, conservative approach

Market pressure: BTC opened at $106,541 and closed at $101,504 (down 4.7%, Yahoo Finance data), hitting a low of $101,000; ETH also fell to $3,289 (-8.5%). The Fear & Greed Index plummeted to 21 (the extreme fear zone), and US stock futures dragged down the overall market capitalization of crypto, wiping out over $500 billion (CoinMarketCap).

Operation Details: Avoiding the bottomless signal in BTC, we shifted our focus to LBank's newly launched coin, $MMT. Entry: At the opening price of $0.05, we bought a $2,000 position (40% spot, with a 2x leveraged contract to hedge a $500 short position in ETH). Exit: The next morning, we closed the spot position at $0.065 (+30%), with a small loss of 0.5% in the contract (total hedging). Simultaneously, we opened a small short position in BTC ($1,000, 3x leverage) to capture the late-day decline, profiting 1.2%.

Profit Calculation: Spot +$60, Contract Short +$12, Net +$72 (Transaction Fee -$2). Total Daily Return +0.72%, Capital to $10,072. Win Rate 50% (1 Win, 1 Draw), Profit/Loss Ratio 1:2.5. Lesson Learned: New coins exhibit a significant "panic rally" pattern during periods of low sentiment, but position limits are necessary to guard against false breakouts.

November 5, 2025 (Tuesday): Deep pullback, contrarian hedging

Panic Continues: BTC bottomed out at $99,800 (-1.7%), ETH fell to $3,200 (-2.6%), and the index remained at 18. Capital outflows intensified, and stablecoin premiums rose to 1.5% (Investopedia).

Operation Details: Holding 30% cash, add to BTC futures short position to $1,500 (5x leverage, entry $100,200), target profit at $98,000. Buy ETH spot liquidity staking token $LST$ (LBank launched, position $1,000, entry $1.2). Exit: Close BTC short position before the next day's rebound (+2.1%), hold LST until $3,400 rebound (+8.3%, but take profit at 6%).

Profit Calculation: BTC short position +$31.5, LST spot +$60, net +$91.5 (fees -$1.5). Daily gain of 0.91%, capital to $10,163.5. Win rate 60% (2 wins, 1 small loss), drawdown <3%. Verification: "Combined short and long" hedging is effective during periods of panic; cash buffer protects against black swan events.

November 6, 2025 (Wednesday): Signs of recovery, offensive strategy.

A turnaround is emerging: BTC rebounded to $104,200 (+4.1%), ETH rose to $3,425 (+7.0%), and the index climbed to 28. Support at $100,353 held (CapitalStreetFX analysis), indicating a recovery in risk appetite.

Operation Details: Shifted to a long position. LBank launched $AIA (AI ecosystem token, position: $3,000 spot, entry price: $0.08; simultaneous BTC long position: $1,000, 3x leverage, entry price: $103,500). Exit: AIA position closed the next day at $0.144 (+80%), BTC long position held until $105,800 (+5.2%).

Profit Calculation: AIA +2,400 USD, BTC +52 USD, Net +2,452 USD (fees -4 USD). Daily gain of 24.3% (leveraged), capital reached $12,611.5 (Note: This day saw a significant profit, boosting the earnings curve). Win rate 80%, profit/loss ratio 1:4. Lessons Learned: On the first day of the recovery, new coin "theme premiums" surged; a trailing stop should be pre-set to lock in profits.

November 7, 2025 (Thursday): Market consolidation and shakeout, scattered trial and error.

Increased volatility: BTC briefly touched $101,500 (-2.6%), while ETH fluctuated around $3,312 (-3.3%). Focus shifted to storage/privacy coins, with FIL and ZEC showing significant gains.

Operation Details: Multiple positions in parallel (5 trades in total): FIL long position $1,000 (entered at $5.20, exited at +15%); ZEC long position $800 (entered at $28, +10%); AI pullback token short position $500 (+8%); LBank new coin $ASTER$ light position $500 (entered at $0.12, broke even). However, the diversification caused noise interference, resulting in two small losses (-1.5% each).

Profit Calculation: Profitable trade +$232, unprofitable trade -$30, net gain of $202 (fees -$3). Daily gain of 2.0% (actual unrealized loss recovered), capital reaches $12,866.5. Win rate 40%, profit/loss ratio 1:1.2. Lesson Learned: High-frequency, diversified trading during periods of volatility is prone to "wear and tear," should be limited to 3 trades per day to improve signal purity.

November 8, 2025 (Friday): Low-level end, optimize preparations.

As the weekend approached, the market returned to low volatility. Although Bitcoin dipped below $102,000 and Ethereum stabilized around $3,430 on November 8th, the overall market remained in a consolidation phase. There were no major new coin listings on LBank. We focused on a wait-and-see approach over the past two days, conducting a comprehensive review of our previous trades and optimizing our strategies. We also fine-tuned some stop-loss and take-profit rules to prepare for next week. While this period lacked significant volatility, it was an important time for learning and preparation. It's worth noting that, based on our research into the listing paths of major exchanges like Binance, we've summarized the expected trends for new coins: as Binance research indicates, coins listed through early-stage (Alpha/IDO) channels often quickly reach valuation highs (usually within the first 14 days), while those listed on platform spot exchanges tend to be more conservative in terms of short-term gains. Therefore, in future strategy development, we will pay more attention to selling on the first day and locking in profits as early as possible. Based on past experience, if a new coin's first-day gain is less than 40%, it's unlikely to continue its explosive growth like AIA.

To visually represent trading performance, a daily equity curve (hypothetical illustration) is shown below. The curve is adjusted at the end of each day to reflect the day's profit/loss, transaction fees, and leverage effect. Overall, our profit curve exhibits a pattern of "low-frequency, steady increases with occasional sharp rises," demonstrating greater consistency compared to manual trading. Although drawdowns occurred on individual days, the strategy's principle of "stop-loss first, then let profits run" remained consistently applied, resulting in a positive long-term trend. Notably, our maximum total drawdown did not exceed 30%, primarily due to our decisive shift to a wait-and-see approach during market weakness and our full capitalizing on opportunities during major market rebounds.

Trading strategies and learned experiences

Through the above 5 days of simulated trading, we have summarized several key insights:

• Low-frequency, high-quality trading is superior to blindly high-frequency trading. Our highly profitable trades are often based on in-depth review and entry after clear signals (such as the initial positioning on the first day of AIA), rather than frequent scalping. Numerous studies support this: reducing the number of trades lowers hidden costs and increases focus on each trade; focusing on a profit-to-loss ratio of 1:3 or higher allows for profitability even with a low win rate. Conversely, high-frequency trading like that on Thursday easily leads to "wear and tear," ultimately resulting in losses. This reveals the greed and anxiety inherent in human nature: consecutive small profits tempt traders to enter the market frequently, but research shows that most retail investors lose money precisely because of excessive chasing of high prices.
• Strict discipline leads to sustainable returns. We consistently set stop-loss points and "avoid cutting losses to prevent significant losses." Even during periods of high volatility, as long as the rules are clearly defined and strictly enforced, losses can be kept within manageable limits. If the market reverses, we do not hesitate to close losing positions. This approach of "small losses, small wins, and big wins" aligns with classic trading maxims. Conversely, risky trades often result in catastrophic drawdowns due to hesitation or excessive risk-taking—such as excessive leverage and blindly holding onto losing positions.
• Multidimensional analysis and a robust thought process influence the rigor of decision-making. In simulated trading, we strive to mimic the "AI thought chain" approach, continuously reviewing each decision. Before placing an order, we comprehensively analyze market indicators (such as moving averages and RSI), market sentiment, and individual currency news to ensure no important factors are overlooked. Research also shows that trading decisions based on systematic review and forward-looking thinking are more successful. Hasty, impulsive trading ideas often correspond to short decision-making chains and weak reasoning, as illustrated by Thursday's loss example. Moving forward, we will continue to strengthen our trading log, reflecting on the trading process at least once a week, and implementing self-discipline in every trade.
• Identifying LBank's Listing Patterns is Key. Based on this simulation and industry reports, we've summarized the listing patterns for new coins on LBank and other exchanges: Generally, new coins tend to experience significant volatility on their first day of listing, attracting speculators. According to Binance research, early listings through channels like Alpha/IDO can lead to an average return of around 177% (14 days), but also extremely high volatility. While LBank doesn't have entirely equivalent Alpha/IDO classifications, experience suggests that it's advisable to sell in batches on the initial listing day to lock in profits. Our strategy capitalized on this: recognizing the "short-term main upward wave" characteristics of AIA and MMT, we immediately closed our positions for profit. Positions that weren't closed in time, even with short-term gains exceeding 100%, often experienced rapid subsequent pullbacks. Strategically, if there's no stronger fundamental support after a day's surge, selling is often wiser than holding. We found that if a project gains more than 40% in the first week after its launch following a previous round of pre-launch hype (such as private placements or IDOs), it can be basically concluded that it is highly popular and is likely to have a second chance; otherwise, profits should be realized quickly.

In conclusion, discipline and strategic rigor determine the success of the demo account. Although we only used publicly available technical data and news information, through calm analysis and execution, we achieved significantly better results than most retail investors. As the research indicates, data-driven trading systems (whether AI-based or strictly rule-based) often maintain an advantage during bull and bear market transitions. Our simulation results echo this: even with the same information channels, as long as trading habits are scientific and orderly, above-average returns can be achieved.

Summarize

This LBank demo trading experience taught us a profound lesson: profitability depends not on luck, but on strategy and discipline. High-probability, aggressive trading (such as high-leverage all-or-nothing gambles) may bring fleeting pleasure, but without risk management, the risks are enormous. Sustained profits, on the other hand, come from low-frequency trading that strictly adheres to risk-reward ratios and consistently uses stop-loss orders. Our review revealed that every profit stemmed from letting profits run after a stop-loss order was placed, while every loss arose from violating established rules or overconfidence. Moving forward, when trading on LBank and other platforms, we will continue to follow these lessons: utilize platform contract tools appropriately, remain sensitive to market trends but never blindly follow the crowd; and, based on data patterns similar to those found in Binance's listing research, buy at opportune times and sell in batches.

Finally, it's important to emphasize that our current success in the demo account largely stems from the element of luck in following the market trend. Whether our previous strategies will remain sound should the market environment change remains to be seen. Regardless, the lessons and insights gained from this live trading simulation will bring us closer to the mindset of a mature trader. While this "Open Class on Trends, Discipline, and Greed" has concluded, the trading principles we learned will continue to be tested and refined in future live trading.