Why Can a Strategy Perform Well in Backtests but Keep Losing in Live Trading?

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

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

So where does the problem lie?

Often, it’s not that backtesting has no value, but that we treat backtest results as a guarantee of live performance.

I. Backtests Test Histor

Old Huang cheats,
what’s that got to do with my Ethereum?
I’m getting caught in the crossfire just lying here.
If I cheat tomorrow,
does that mean U.S. stocks have to wobble too?

Why Does Higher Trading Frequency Make Profits Easier to Erode?

Some traders believe that constantly looking for opportunities can increase their chances of making a profit.

But in reality, every trade can incur new costs. The more trades you make, the more easily these costs accumulate.

Even a strategy that is fairly good at predicting market direction may ultimately fail to deliver the desired net returns if it trades too frequently.

I. Fees: Small Each Time, But They Can Add Up

Suppose the combined cost of buying and selling each time is 0.10% of the trade's notional value.

If the not

My mom doesn’t care about this. She only cares about her mahjong. If she said that, I’d even go to Thailand for surgery just to make her wish come true.

#StakeOnLaunchpoolToShare450KVLX
450,000 $VLX is not just a reward pool; it is a strategic allocation signal for the next cycle of decentralized infrastructure.

The launch of the Stake On Launchpool campaign featuring 450,000 $VLX represents more than a standard yield farming opportunity. It is a market-tested mechanism for distributing governance tokens to engaged users while simultaneously securing network participation. For serious participants, this event serves as a real-time indicator of project viability, community strength, and long-term tokenomics sustainability. Understanding the m

$SILVER Hits $53! 🚀

11.9$BTC Analysis
It quietly plunged in the early hours. The current decline is not the result of a single event, but a concentrated eruption of macro, regulatory, institutional, and endogenous risks. News assessment: This is not a single bearish catalyst, but a compound pullback driven by “tighter regulatory expectations, institutional retreat, and leveraged liquidations.” In the short term, bulls lack a fresh narrative to latch onto, and any rebound is likely to encounter holders looking to break even and new short sellers entering. MACD bearish crossover: DIF (-574.1) and DEA (-551.5) are

Some sweet moments that were captured❤️

#Gate股票畅聊季 #SHIB #WCTCS9
#SHIBMarketAnalysis | Shiba Inu: Can SHIB Recover From Its Recent Weakness?

Current Reference Price: $0.000004421

Shiba Inu (SHIB) is approaching an important decision zone. At the current reference price of $0.000004421, traders need to watch whether buyers can defend the lower support area or sellers will push the market toward another decline.

My view is that SHIB has recovery potential, but confirmation is still needed. Buying simply because the price looks cheap can be risky. Volume, market sentiment, Bitcoin's direction and the strength of buying pressure w

Why might a trading strategy’s returns come from just a few trades?

A strategy has high cumulative returns and a decent win rate.

But if you remove the few most profitable trades and the entire strategy goes from profitable to losing, would you still consider it to have a stable trading edge?

This question is more worth exploring than simply looking at returns.

I. First, look at where the returns actually come from

Suppose a strategy completes 100 trades and ends up with a net profit of $1,000.

On the surface, the strategy is profitable.

But a closer breakdown reveals:

* The first 5 pr

People who have never truly loved a car, or even felt for one the way they would for a pet, won’t understand.

Repost: I didn’t expect Jensen to actually collapse. Roughly speaking, the worst-case scenario is that Jensen’s wife gets half the shares and sells them all for cash. She would hold $75.7 billion worth of NVDA, equivalent to about 3.5 days of trading volume, with an approximately 10% impact on the market.
But California divorces have a T+6-month timeline, and the money is held in a trust. So if they divorce next year, the company’s $235 billion in buybacks in 2028 would be enough to absorb the shares.
Tech stocks, already facing considerable uncertainty, will most likely price this in early. N

Are institutional investors getting nervous? What NVDA fears most isn’t a 2.2% drop, but these three follow-up signals!

Nvidia fell as much as 2.2% after hours, which doesn’t seem particularly alarming. But for institutional investors, the real cause for concern may not be those few percentage points, but the three signals that follow.
First signal: Progress of the board investigation.
If the investigation concludes quickly and confirms there was no leak of company secrets or material governance issue, the market may gradually lower its risk premium. But if new issues keep emerging, uncertain

75,600 held for three days, but still broke. Overnight, BTC plunged to 73,510 on a single wick, liquidating $715 million in long positions in one hour. It’s back to 75,148 this morning—the first day after the breakdown, the key thing to watch isn’t how high the rebound goes, but whether 73,500, the wick’s low, holds. #70%山寨币跌破200日均线
First, the numbers (around 09:00 on November 9, 2026, sources: Finnhub / CoinGecko): BTC at $75,148, down 0.83% in 24 hours, trading in a range of 73,510–76,200; Friday’s close was 75,773, which means the 75,600 level held for three days over the weekend before gi

After Compute Dominance, the Next Pricing Power Is On-Chain!
A Sequoia partner called Jensen Huang one of the greatest entrepreneurs of our time and indispensable to America’s AI leadership.
But the more concentrated compute becomes, the more it needs a decentralized settlement layer: idle capacity in GPU clusters is being tokenized, inference tasks are starting to be verified on-chain, and AI agents naturally make payments in stablecoins.
The next question is who can turn NVIDIA’s chips into a global public network that anyone can access, price, and share revenue through—that’s what it means

Just after 8 a.m.
I was still thinking over the market action
when prediction markets started trending again

After the Democrats’ midterm landslide
Politico said they plan to step up regulation of prediction markets

Kalshi and Polymarket were singled out
Senator Jeff Merkley
Representative Maxine Waters
both criticized them
Bets can even be placed on
sensitive events like elections, wars, and assassinations
Legislative action is also in the works

Trading volume for election-related contracts this cycle
exceeded roughly $3 billion
Kalshi alone accounted for around $2.5 billion or more

Kalsh