OpenAI gives veterans one year of free ChatGPT Plus; more than 20,000 have claimed it
OpenAI said in a post on November 11, 2026, that more than 20,000 veterans and active-duty service members transitioning out of the military have claimed a year of free ChatGPT Plus over the past year. The program was driven by veterans within the company, with identity verification assisted by . One easily overlooked point: the free memberships have already been distributed, but most recipients have not attended training. Those who have put it to use have focused on practical steps like job searches, résumé

Fed’s Michelle Bowman warns: Stocks could face a sharp correction if AI investments fail to deliver expected returns. Big spending. Bigger expectations. Little room for disappointment.

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

In BTC trading, many people see a candlestick with a long lower wick and assume buyers are starting to fight back and the price is about to rebound, so they rush in to buy the dip. But in reality, a long lower wick does not necessarily mean a trend reversal; it may simply be a brief rebound during a decline.

So, how should you tell?

First, look at where it appears. If a long lower wick forms near an important support level from earlier, it suggests that strong buying may have absorbed selling pressure after the price fell to that area, making the rebound relatively more significant. But if i

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Yesterday, the monthly CPI came in hotter than expected.
Headline rose 0.4% on the month against the 0.3% the market expected, and core came in at 0.3% against 0.2%.
I believe the market reaction is also muted, considering the yearly data wasn’t released due to the 2025 government shutdown.
So it could’ve been much worse, considering the last PPI spiked to a 4-year high.
The odds of a hike at the December meeting have now jumped to around 87%.
In fact, the debate is no longer hike or hold, but hike once or more, as there’s a 12% chance of a 50 bps hike.
Not looking good for $BTC , as higher rat

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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we better squeeze the fk out btc 🐻 or else next more srs bid area is 67-68

#晒出我的持仓收益 -24%! $ONE Plunged from an intraday high of 0.00207 to 0.00157, down 11.7% in 24 hours. $ONE Bearish on the contract: My post this afternoon was still bullish, but the 0.00163 stop-loss has been breached. I was wrong, so I’m admitting it and flipping short. Current price: 0.00157; take profit: 0.00137; stop-loss: 0.00163—if it gets back above 0.00163, I’ll admit I’m wrong and exit immediately; if it can’t hold, I’m looking toward 0.00137. #ONE:

$ARIA Definitely getting cut in half today, everyone start selling

$OPEN Buyers Eye a Potential Breakout Toward Higher Levels
OPEN is approaching an important price zone where buyers could attempt to regain momentum. Holding above the $0.0900 area would help maintain the short-term bullish structure, while increased buying pressure could support another upward move.

Key figures

$0.0900–$0.0920 — Important price zone to monitor.

$0.0890 — Key support and bullish structure invalidation.

$0.0935 — First upside resistance.

$0.0945 — Next resistance level.

$0.0960 — Potential continuation target.

$0.0980 — Higher resistance if bullish momentum strengthens.

#ETH Current price: 2068. Price action remains highly correlated with BTC, reflecting a weak, high-beta market that is largely following BTC. Independent buying momentum is extremely scarce, and the rebound is clearly weaker than BTC’s. Near-term resistance is concentrated in the 2110-2130 range. Only a high-volume move above and sustained hold in this area would briefly ease the downside pressure and allow a further test of resistance near 2180. The key support below is the psychological 2000 level, a major target for bears in recent weeks. A decisive break below it would open up further down

BTC has been trading sideways for three days, with the price fluctuating within a range. Many traders are starting to feel anxious: should they go long or short?

In fact, one of the easiest mistakes to make in a sideways market is trying to predict the direction of a breakout in advance.

To assess a breakout, focus on three signals.

First, trading volume. When the price approaches the upper end of the range, a sustained increase in volume indicates rising market participation. But higher volume alone does not necessarily mean the price will rise; you also need to watch whether the price can

$BTC The price is currently around 73,900, and the 73,000 level has held for now. Short-term momentum looks weak, with multiple timeframes trending downward; 72k-73k is the support zone, and if it fails, the next level to watch is 70k, while 75k-76k is the resistance band. Looking further ahead, institutional sentiment is optimistic, with a 2027 target range of 100k-150k+, and more aggressive forecasts even calling for 200k; cycle models also point upward. ETFs have seen outflows recently, and macro volatility remains elevated. The next move depends on whether 75k can be reclaimed. If the pri

Why can a strategy perform very well in backtests yet continuously lose money in live trading?

A trading strategy performs excellently on historical data, with a high win rate, a beautiful return curve, and a very small maximum drawdown.

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

Where exactly does the problem lie?

Often, it is not that backtesting is worthless, but that we treat backtest results as a guarantee of live performance.

Some parents are really something else.