Why Do DeFi Projects Get Hacked? What Happens Between a Vulnerability and Funds Being Drained?

A DeFi project may have publicly available smart contracts, a polished interface, an active community, and even a security audit.

But none of these things means it is absolutely safe.

In the Web3 world, security incidents are often caused by more than one issue. Code flaws, permission design, price data, external dependencies, and human actions can all become points of entry for risk.

More importantly, when a local vulnerability interacts with the mechanisms that move funds, what initially seems

In crypto futures trading, 10x leverage may not sound particularly high, but many traders underestimate the risks behind it.

Suppose you have 1,000 USDT and use 10x leverage. This means you can open a notional position worth about 10,000 USDT (depending on the margin mode and trading fees).

If the market price moves 1% against you, your position will incur an unrealized loss of about 100 USDT, equivalent to 10% of your capital. If the price moves 5% in the opposite direction, the unrealized loss could theoretically reach 500 USDT.

This does not yet account for trading fees, funding rates, o

Why does higher trading frequency make profits easier to get eaten away?

Some traders believe that as long as they keep looking for opportunities, they can increase their probability of making a profit.

But the reality is that every trade may incur new costs. The more trades you make, the more easily these costs accumulate.

Even a strategy that is fairly good at predicting direction may ultimately fail to deliver ideal net returns because of trading too frequently.

I. Fees: Each one may seem small, but they can add up

Assume the combined cost of buying and selling on each trade is 0.10% o

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Why can a trading strategy perform excellently in historical backtests yet gradually fail in real markets?

A beautiful return curve does not necessarily mean a reliable trading strategy.

In the cryptocurrency market, many traders use historical data to test entry signals, take-profit and stop-loss levels, and position-sizing parameters. But once a strategy is deployed in the market, its win rate may fall, drawdowns may grow, or it may even lose money over the long term.

So where does the problem lie?

I. Historical data is not the same as future markets

Backtesting can only show how a stra

In the cryptocurrency market, many traders see BTC trading volume suddenly surge and assume prices are about to rise. But sometimes, volume increases noticeably while prices fail to rise and instead fall. Why does this happen?

First, it’s important to understand that trading volume represents market activity, not simply buying pressure. Every trade involves both a buyer and a seller, so rising volume does not necessarily mean prices will rise.

First, rising prices on increased volume. If prices continue to rise while trading volume increases, it means market participation is growing, and buy

How Much Should You Lose on a Single Trade? Manage Risk Scientifically to Achieve Consistent Long-Term Profits!

In crypto futures trading, many people spend every day studying when BTC will rise or fall, but rarely take the time to calculate one thing: if a trade goes wrong, how much of a loss can they actually afford?

In reality, correctly predicting market direction is only part of long-term trading. Risk management is what determines whether an account can survive over time.

First, set your risk per trade in advance. You can use 1% of your account balance as your risk budget for each tra

Support and resistance are the most fundamental and practical concepts in technical analysis. Many traders study candlesticks and indicators every day, yet overlook an important question: at which price levels are buying and selling forces likely to shift?

First, support is an area where buying pressure may increase as prices fall. When the price approaches this level, some buyers may start entering the market, slowing the decline. But support does not mean the price definitely won't break below it.

Second, resistance is an area where selling pressure may increase as prices rise. When the pr

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How can out-of-sample testing and walk-forward backtesting help determine whether a trading strategy is truly reliable?

Suppose you have spent months researching a trading strategy, constantly adjusting its parameters, and ultimately produced a beautiful historical return curve.

You might think you have found an effective approach.

But there is a problem: if you repeatedly use the same historical data to adjust the strategy, does this return curve prove that the strategy works, or merely that you found the parameters best suited to this particular historical data?

This is the problem overf

What signals indicate that BTC’s upward momentum is weakening as it rises?

In crypto trading, many people assume that the uptrend remains strong when they see BTC continually reach new highs. But rising prices do not necessarily mean that upward momentum is always strong. What really deserves attention is whether the market forces behind the price are changing.

There are four signals worth watching closely.

First, trading volume continues to contract. If prices keep rising while trading volume gradually declines, the buying pressure driving prices higher may be weakening.

Second, the RSI s

Many traders expect a pullback after BTC rises, hoping to get a better entry. But a retest is not always an opportunity; sometimes it can signal that a downtrend is resuming. The key is to determine whether support is holding and whether the broader market trend remains healthy.

First, assess the strength of the support level. If a price area has seen rebounds several times in the past, it may have strong buying demand. When the price returns there, watch closely to see whether buyers step back in.

Second, watch for changes in trading volume. If volume gradually declines as the price retests

Why Can a Strategy Perform Very Well in Backtests but Lose Money Continuously in Live Trading?

A trading strategy may perform excellently on historical data, with a high win rate, a beautiful equity curve, and a small maximum drawdown.

But once deployed in the real market, the results can be completely different: execution prices are unfavorable, trading costs keep rising, returns gradually shrink, and losses may even become persistent.

So where exactly does the problem lie?

Often, the issue is not that backtesting is worthless, but that we treat backtest results as a guarantee of live per

Chinese Long-Form | Why Does an Effective Trading Strategy Suddenly Stop Working?

Many traders run into the same problem:

A strategy delivers consecutive profits, and its backtest curve looks great, but a few months later, with the same parameters and signals, it starts losing frequently in live trading.

Is the problem really with the strategy itself?

Not necessarily. A strategy’s effectiveness often depends on the market environment it operates in, not on how much profit it has generated in the past.

There are at least four market conditions worth watching:

1. Trend structure changes

T

Why can higher trading frequency make it easier to underestimate the impact of costs on long-term returns?

Many traders have an intuition:

The more trading opportunities there are, the more chances there are to make money.

But in the cryptocurrency market, frequent trading also means more fees, more slippage, and more opportunities for execution errors.

The real question is not how many trades you can make in a day, but:

Is the expected return from each additional trade enough to cover all the costs it incurs?

I. Why can small per-trade costs have a large long-term impact?

Suppose a tra

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