《BTC Falls Below the DCA Cost Basis:
This Isn’t a Crash—it’s “Long-Term Holders” Bleeding Together》
The chart shows BTC has fallen to $69,200,
while the Ahr999 indicator has dropped to 0.3569, nearing its historical “buy-the-dip zone.”
More importantly, the price has fallen below the 200-day DCA cost basis,
meaning people who dollar-cost averaged over the past 200 days are collectively underwater.
Does this look like a crash,
or like an inevitable step in coins changing hands from “true believers” to “patient capital”?
Army’s outlook:
When DCA investors start selling at a loss, that’s when lon

What Is Price-Volume Divergence? How Is It Different from a Normal Decline in Trading Volume?

In crypto markets, price and trading volume do not always move in sync. When prices continue to rise while trading volume gradually declines, or prices keep falling while trading volume continues to contract, traders may consider whether price-volume divergence is emerging. But price-volume divergence is only an analytical clue; it does not mean the market will necessarily reverse.

First, what is price-volume divergence?

Price-volume divergence refers to a mismatch between price movements and chang

nb: guys, this bot isn’t magic.
my strategy behind the rebalance, ratio, and allocation is strong.
but patience is still required.
#avax #sol #crypto #stocks

After finally grinding down for so long, the wick below 68 is the first time it has felt like a small-scale bottom. Market sentiment here is already in extreme fear. Continue holding spot and observe for a while longer. Generally speaking, after the first rebound in this kind of gradual decline, there will be another slight new low, perhaps 1–3 weeks later. It will only be safe once a head-and-shoulders bottom forms. Only then can we determine whether this is the major-stage bottom. We can't be too optimistic yet; not enough time has passed, and the moving-average pattern isn't there yet eithe

Bitcoin ETFs Continue to See Outflows—What Signal Is the Market Sending?

Recently, a trend in the Bitcoin market has raised concerns: U.S. spot Bitcoin ETFs are experiencing a significant wave of net outflows. This is not just about price fluctuations; it also reflects some investors reassessing risk.

According to public figures as of November 11, 2026, U.S. spot Bitcoin ETFs have seen cumulative net outflows of approximately $1.61 billion this month. On November 5, net outflows totaled approximately $430.2 million, followed by $411.9 million on November 6. Outflows narrowed over the followi

If all employees’ appeals succeed, Jensen Huang returns, and the stock makes a V-shaped reversal, anyone who bought the dip a few days ago will never have to worry about being poor again.
All NVIDIA employees, keep it up!

Must put knowledge into action—bought the dip #黄仁勋辞职

What Can Futures Premiums and Discounts Really Tell Us About the Market?

In the crypto market, when observing Bitcoin or Ethereum futures prices, you may notice that sometimes futures trade above spot and sometimes below it. This difference is known as a premium or discount, and is an important starting point for understanding the derivatives market.

But keep in mind: a premium does not necessarily mean bullishness, and a discount does not necessarily mean bearishness. What really matters is understanding why the spread forms and how it changes with market conditions.

First, what is a premi

$NBIS Down 16.48% in a single day, plunging straight from 164.58 to 119.10, with 517 million in trading volume—this isn’t a pullback; the meat grinder is switched on. Don’t touch it. I didn’t earn my reputation as Gate’s “stay-away” blogger for nothing. I’ve seen too many tokens like this: a 24-hour range approaching 40% means that whether you’re long or short, you’ll basically get liquidated if you use more than 3x leverage. Retail traders see the price at 126 and think, “It’s fallen a lot, maybe I can buy the dip.” But look closely: today’s low was 119, and the current price is 126, a reboun

Why can trading strategies that perform well in backtests fail in live markets?

A trading strategy may deliver strong returns and a high win rate in historical backtests, while keeping its maximum drawdown under control, yet produce very different results once deployed in the market. The problem may not necessarily lie in the strategy itself; it may also stem from the gap between backtesting and live trading.

First, historical data does not represent the future. Backtesting can only evaluate a strategy’s performance under specific historical market conditions. Market structure, volatility, a

$AKE This is really great, great, great, great

SOL shorts nailed the rhythm from start to finish! Trend-following shorts from elevated levels dominated across the board!
We had already identified 86 as resistance and a short opportunity. Yesterday, price made a slight test, rallying to 85.83 before touching resistance, stalling, and turning lower. Shorts played out as expected! A break below 80 was clearly expected, with 78 as the ultimate target!
The morning market lived up to the forecast, dropping straight to a low of 77 and exceeding the target! We locked in a solid 8-point profit on the full swing!
Resistance at the highs was pinpoint

🚨 NVIDIA chief Jensen Huang has resigned amid an alleged espionage scandal benefiting China, sending shockwaves through the U.S. artificial intelligence industry and financial markets.
The scandal erupted after his relationship with Alice Huang, a Chinese businesswoman whom U.S. intelligence officials suspect of transmitting strategic information to Beijing, was revealed.
A former executive at Megaspeed, she worked at a company specializing in AI infrastructure using NVIDIA chips.
The case is particularly concerning to Washington because NVIDIA supplies the processors that power many of the m

ethereum:native
H4 SFP in the works
Also re-longed bitcoin:native after being invalidated on the Daily close.
Looking for a move towards a 73k with a stop at 67k

How can out-of-sample testing help prevent mistaking accidental patterns in historical market data for a lasting edge?

A trading strategy performing well in historical backtests does not mean it can adapt to future markets. To reduce the risk of overfitting, out-of-sample testing is a crucial step in validating a strategy.

First, what is out-of-sample testing?

Simply put, it means dividing historical data into different periods: one part is used to develop the strategy and adjust parameters, while another is excluded from optimization and reserved specifically to test how the strategy perfo

Guys, I’ve opened an initial short position. In this market, every rebound is a chance to short. Just go all in and be bold, and money will flow like water. Once it moves up, I’ll add to my position

What Is the Break-Even Win Rate? How High Must a Trading Strategy’s Win Rate Be to Cover Trading Costs?

In cryptocurrency trading, many people know their win rate but not how high it needs to be to actually make a profit. If winning trades earn little while losing trades lose a lot, you can still end up losing money even if you make the right call more often. The break-even win rate helps traders understand the minimum performance their strategy needs to achieve.

First, what is the break-even win rate?

The break-even win rate is the minimum win rate required for long-term expected returns t

What Is the Sharpe Ratio? How Do You Measure Whether a Trading Strategy's Returns Are Worth the Risk?

In cryptocurrency trading, a high return does not necessarily mean a strategy is good. If a strategy can generate high returns but comes with sharp volatility and significant drawdowns, we need to assess further: are those returns worth taking on the corresponding risk? The Sharpe ratio is one tool that can help answer this question.

First, what is the Sharpe ratio?

The Sharpe ratio measures the excess return a portfolio or trading strategy earns per unit of volatility risk. In general, the