Regardless of the midterm election outcome, the market has already priced in a Democratic sweep of both chambers. Since prices have already dropped significantly, the actual result might just cause a brief spike down before the bad news is fully absorbed. Then I’m betting again—this is my one shot 😅 If anything else happens, it’s all good news, and there’s bound to be a strong rebound. The Nasdaq 100 has strong support around 28,000, and BTC similarly has solid support at 76,000. Even if the midterm results come in and cause a brief spike down, I’m confident there’ll be a rebound—and I’m all in 😄

Why does open interest surge, yet we still can’t tell if “the big players are about to pump or dump”? The most common mistake in crypto data analysis is equating “someone is entering” directly with “someone is bullish.” OI, or open interest, represents the total number of outstanding contracts. Every open contract has both a long and a short side. An increase of 10,000 contracts means 10,000 matched long-short positions have been established—just looking at this number alone won’t reveal who’s more informed. Experienced traders often misinterpret this: when price falls but OI rises, they assume large capital is accumulating at the bottom, thinking “someone’s willing to buy,” so they wait longer. But new longs could simply be catching falling knives, while new shorts are continuously pushing prices down. Someone buying doesn’t mean they can hold—there’s a whole account’s worth of difference between “taking the trade” and “holding through the drop.” Another easily overlooked detail: USD-denominated OI is affected by price movements. Even if the number of contracts doesn’t increase, rising coin prices can inflate the reported value of open interest. Always check the unit before comparing figures. To assess position sentiment, you must combine OI with price action, aggressive trading volume, funding rates, and basis. A spot buy paired with a futures short could simply be a hedge. Even when piecing together multiple indicators, you can only form an educated guess—you still can’t read the full script of any “whale.” Remember: OI tells you how many chips are on the table, not who will win. Don’t mistake increased leverage for a confirmed directional signal.

Why do you see everyone else making money, but whenever you jump in, you keep paying tuition? Because the people who lose everything rarely post daily profit screenshots. Scroll through your feed: someone hits a 100x coin, someone turns a small stake into a fortune, someone perfectly exits at the top. After seeing enough of this, it’s easy to believe that making money is the norm—and that you’re just the one who doesn’t get it. But what you’re seeing is only the subset of people who are willing to showcase their wins—and who get pushed to the forefront by the platform. Those who got liquidated and deleted their accounts, those who went silent after losses, those who created new accounts to tell fresh stories—these are rarely part of your sample. This is survivorship bias. Imagine ten thousand people all heavily invested in different small-cap coins. Someone will inevitably hit a massive rally. When you hear their post-mortem, every step—from the story to the entry point—sounds perfectly logical. But if you only look at the winners, you can’t tell whether it was a sound strategy, or simply that among so many taking risks, a few were bound to get lucky. Even more insidious: the winners’ strategies aren’t necessarily replicable. They might have had low-cost positions or other assets backing them up. You, however, are using your living expenses—and blindly copying their riskiest trade. So when you see a get-rich story, don’t immediately ask, “What did they buy?” Ask instead: How many people tried a similar approach? Where did the losers go? What was the maximum drawdown on this return—and how many times could you realistically repeat it? Remember: Someone profiting from a method only proves it worked once. Only when you account for the failures do you truly understand how hard the path really is.

Why does studying a coin longer make it harder to cut your losses? The most dangerous kind of research is when you uncover more and more problems with the project, yet find more and more reasons to stay. Before buying, you analyze the team, revenue, vesting schedules, and valuation. After being trapped, you rationalize: the team selling tokens is “improving liquidity,” declining users are “a market downturn,” and breaking support levels is “a washout by big players.” You’ve applied all your research skills—except to ask whether you made a wrong purchase. Hidden in this is a psychological ledger: so much time spent, so much information reviewed—selling now would make it all feel wasted. So beyond your entry cost, you’ve added another layer of emotional attachment to your investment. But the market doesn’t pay you for the hours you studied. Understanding a project doesn’t mean its token is worth holding: business growth doesn’t automatically create token demand, and funds raised by the project won’t automatically flow to token holders. A practical self-check: if you were currently holding zero, and faced with the same information and same price today, would you still buy? If the answer is no, it’s time to reevaluate your position—don’t let “I’ve held it this long” make your decision for you. Remember: research should clarify your exit conditions. If, in the end, you’re only accumulating more reasons to hold, you may have unintentionally become the project’s free public relations agent.

Why, when the pullback you’ve been waiting for in your plan finally arrives, do you dare not buy? When the market is rising, I often tell myself: “If it drops another 10%, I’ll definitely get in.” But when the price actually falls, the news turns negative, and the group chat fills with bearish sentiment, the “low price” I once anticipated suddenly feels like it might still crash by another 50%. Later, I realized: what we truly want isn’t just cheap—it’s cheap and certain. Yet the market rarely offers both at the same time. When prices rise, we think they’re expensive. We predefine a pullback zone, and when the price finally reaches our planned level, a single large red candle scares us. We wait for signs of stabilization—confirmation of a bottom, a rebound, clarification of negative news, restored market sentiment. By the time we finally feel comfortable buying, the price has already climbed well above our original target. Of course, this doesn’t mean you should buy at every drop. The purpose of a plan is to clearly define: at what price should I initiate a trial position? What underlying logic still holds? And at what level must I admit I’m wrong? Use position sizing to manage uncertainty. If your plan simply says “buy when it drops,” without defining failure conditions, it’s not a plan—it’s just wishful thinking during an uptrend. Low prices always come with bad news; high prices are often accompanied by compelling stories. By the time all risks disappear, the bargain usually disappears too. Remember: the real buying opportunity won’t feel absolutely safe. Trading doesn’t require waiting for fear to vanish—it requires the courage to execute your prewritten plan when risks are manageable.

Why does a logic that everyone agrees on suddenly seem unreliable? When I first started trading, I loved chasing “certainty”: policy support, institutional entry, explosive sectors—ideally with unanimous consensus online. If everyone was bullish, it felt like I was on the right side. Later, I realized that trading profits don’t come from being right about the logic—they come from price not yet fully reflecting that logic. I once chased a hot sector. The logic was solid: user growth, strong funding, compelling ecosystem narrative—all clearly laid out in research reports. But by the time I bought in, early money had already made multiples, funding rates were sky-high, and open interest was overcrowded. Every new piece of good news only triggered a brief spike. The project didn’t suddenly get worse—but the price started falling. Why? Because the market didn’t lack reasons—it lacked buyers who were even later, willing to pay even higher prices. Consensus itself isn’t the risk; overpricing is. To judge an opportunity, don’t just ask: “Is the logic sound?” Ask: “How many people already believe it? How much capital has already entered? And if the利好 materializes—who’s left to buy?” The best opportunities aren’t those with zero consensus—they’re those where fundamentals are improving, but prices still carry doubt. Once everyone can recite the same story fluently, trading has shifted from discovering value to fighting over the last chair. Remember: A good logic doesn’t mean a good price. When the right answer is known by everyone, what truly matters is calculating how much buying power remains unfilled.

Why is the true bottom of a bear market often not the moment of greatest panic, but rather when everyone has stopped talking about it? Right after a sharp crash, the market is still very lively. Some are buying the dip, others are shouting “zero,”群里 debating the next candlestick, with high trading volume and open interest—everything looks dire, but everyone is still watching the price, which means hope hasn’t truly vanished. I used to enter the market right after the first big drop, thinking panic had peaked—only to see prices rebound for a few days, then begin a long, slow decline. There’s no waterfall, no headlines—just a little drop every day—until no one in the group chats talks about crypto anymore, rebounds go ignored, and project announcements generate no volume. Only then did I realize: what makes a bear market truly grueling isn’t the sharp drop, but time. Sharp drops crush leverage; slow declines crush confidence. The former causes liquidations; the latter drives people to walk away voluntarily. The true bottom only emerges when trapped holders stop averaging down, short-term traders lose interest, and long-term holders begin to doubt—only then do holdings gradually shift from those with no patience to those willing to wait. Of course, quiet doesn’t mean the bottom is here yet. You also need to see whether selling pressure is exhausting, whether bad news can still hit new lows, and whether reaction lows after bounces are gradually rising. Remember: tops form when everyone fears missing out; bottoms mature when most have already stopped caring. The market’s most complete surrender isn’t screaming—it’s silence.

Why do small positions always make money, but losses start the moment I increase my position? What’s most painful isn’t being wrong—it’s making a few bucks on a small test trade, then losing half a year’s salary when I go all in. I used to think it was just bad luck: the market cooperated with my small trades, but turned against me the moment I placed bigger bets. Later, when I reviewed my trading history, I realized it wasn’t just my position size that increased—my entire trading approach had quietly changed. With a small position, I could wait out pullbacks and exit if the signal faded. But once I increased my position, every down candle felt like it was deducting from my rent money. I went from analyzing the 4-hour trend to fixating on 1-minute fluctuations. I’d panic-sell during normal retracements, then chase the price back up after it rebounded. The market direction hadn’t changed—but I’d worn myself out chasing it and lost money in the process. Even more insidiously, after a few successful test trades, I’d often miss the most comfortable entry point. By the time I finally “confirmed” the trend and added to my position, the price had already moved far from its original setup. The same quantity of coins now carried a completely different level of risk. Making money on small positions only proves those individual trades worked—it doesn’t prove you can stick to the same rules when scaling up tenfold. What truly needs gradual testing is whether larger price swings will force you to abandon your plan. Remember: Position size isn’t a dial that simply amplifies your profits. When your position grows large enough to change how you act, you’re no longer executing the same trade.

Why do the profits made in a bull market often get doubled back in a bear market? After spending years in crypto, I’ve noticed a harsh reality: many people aren’t inexperienced—they’ve made money, but then mistakenly believe they’ve mastered the market. In a bull market, BTC rises, altcoins rotate, and simply buying a few coins can turn a profit. When prices surge and holdings grow, traders convince themselves they’ve understood the narratives, sensed the capital flows, and cracked the cycle. They increase their positions, ramp up leverage, and even reinvest all prior profits into the next gamble. I used to do this too. The most common mistake? Mistaking market luck for skill. When you profit in a bull market, you start seeing pullbacks as opportunities—unafraid of drops because your profits act as a cushion. Then, when the market truly turns bearish—liquidity dries up, altcoins keep sliding—you realize those earlier gains weren’t a shield; they were merely an excuse to take on greater risk. Even more ironic: when your account shifts from profit to loss, people often refuse to accept reality. Because what’s lost isn’t just money—it’s confidence in your own judgment. So you chase losses, hoping to break even, and end up losing your principal too. After going through several cycles, I’ve grown increasingly convinced: the true dividing line in trading isn’t how much you made in the bull market—it’s whether you can still recognize, during the peak of the rally, how much of your profit came from luck. Remember: the bull market determines how much you can earn; risk management determines how much you ultimately keep. Don’t treat profits handed to you by the cycle as proof that you’re always right.

Why was the first time you held onto a losing position and turned it into a profit possibly the most expensive victory of your trading career? When I first started trading futures, I had a long position that dropped below my stop-loss level, but I couldn’t bring myself to exit. Instead of cutting my loss, I kept adding to the position—until the market suddenly reversed, and somehow, I turned a loss into a profit. That win taught me not reverence, but侥幸 (false hope). From then on, whenever I made a wrong trade, I’d recall that reversal: “Just wait a little longer—the market will come back.” I refused to accept small losses, added more during big losses, and treated stop-losses as numbers I could adjust anytime. The first few times, I managed to pull through again—I even convinced myself I’d discovered the pattern of “major players washing out retail traders.” Then came a true one-sided move—the price never returned. All the money I’d侥幸 earned from the previous ten wins was wiped out in one go. The most dangerous thing about the market is that it occasionally rewards mistakes. Profiting from holding a losing position doesn’t mean your decision was right—it only means the cost of that error wasn’t immediate. Conversely, a price rebound after a strict stop-loss doesn’t prove discipline is useless. Reviewing your trades shouldn’t just ask: “Did I make money?” It must also ask: “If I repeated this exact action 100 times, would my account survive?” Remember: Errors that cost you money are easy to fix; errors that make you money are the hardest to quit. When the market lets you off the hook, it’s not endorsing your strategy—it’s just waiting for you to increase your position size.