Dead Cat Bounce to $118K? 5 Things to Know in Bitcoin This Week

Bitcoin started the week rebounding from last week’s violent sell-off, with bulls attempting to defend key levels and shorts eyeing a retest of the infamous $102,000 wick on Binance. The question on everyone’s mind: is this just a dead cat bounce or the start of a push back toward $118K? Below are five factors to watch, with sources so you can separate signal from noise.

1) What a “dead cat bounce” really means

A dead cat bounce is a brief price recovery during a broader downtrend that soon reverses lower. In other words, price pops, traps late buyers and then resumes falling. Traders watch the context (trend, volume, positioning) to judge whether a rebound is sustainable or just a pause before another leg down.

Why it matters now:

After the Oct. 10–11 liquidation cascade the largest in crypto history by some estimates. Bitcoin’s rebound must prove it’s more than reflex. Reuters reported $19B in forced liquidations during that crash, which leaves markets fragile and headline-sensitive. If the bounce lacks breadth (weak flows, soft volume, overheated funding), downside risk increases.

2) The “$102K wick” and the path to $118K

Market structure still revolves around two reference points:

$102K Binance wick remains unfilled. Cointelegraph highlighted that the Oct. 10 meltdown printed a deep wick near $102,000 on Binance levels that bears would love to revisit; bulls want to keep price well above it.
$118K overhead magnet. If dip-buyers retain control and macro winds ease (see #4), technicians will look for a reclaim of prior supply zones toward $118K. That target is discussed across trader notes as the next “clean” range high if bids keep absorbing sell pressure and spot flows stabilize. (Inference based on the same weekly outlook and prevailing range discussions.)

Bottom line: Holding above $110K and building higher lows reduces the probability of revisiting $102K; losing $110K with momentum invites that wick test.

3) ETF and fund flow pulse: from outflows to stabilization?

Flows into and out of U.S. spot Bitcoin ETFs have become a primary driver of week-to-week direction:

Significant outflows last week: U.S. spot BTC ETFs saw ~$536M net redemptions on Oct. 17, the largest daily outflow since August, reflecting risk-off sentiment after the crash.
Daily tape still choppy: Aggregators tracking each issuer show back-to-back negative prints around Oct. 14–17, consistent with cautious risk appetite. Use daily dashboards (Farside) to gauge whether outflows are abating or inflecting back positive.
ETP flows outside the U.S.: CoinShares’ weekly note shows US$513M outflows at the product level after the liquidity shock, but with Germany/Switzerland/Canada recording inflows evidence of dip-buying abroad even as U.S. investors de-risk.

How to read it: Sustained net inflows typically support price; persistent outflows make rebounds fragile. This week, watch if U.S. outflows slow and whether non-U.S. inflows continue.

4) Macro wildcard: the Fed, data vacuum, and inflation narrative

Macro remains the backdrop. Reuters reports the Fed is poised to cut rates by 25 bps at its Oct. 28–29 meeting, but a U.S. government shutdown has created a data vacuum, complicating policy signals. Lower policy rates generally ease financial conditions often supportive for risk assets like BTC yet uncertainty can amplify volatility.

For context, the August 2025 CPI ran hotter on the month even as the year-over-year trend moderated, keeping the inflation debate alive. Crypto-native and mainstream coverage continue to frame Bitcoin as a potential inflation hedge over the long run even if short-term correlations wobble. See BLS for CPI specifics and Forbes explainers for the inflation-hedge thesis.

What to watch this week: Any surprise Fed commentary or macro headlines that shift rate-cut odds can whipsaw BTC. A benign macro tone plus stabilizing flows favors the bull case toward $118K.

5) Derivatives positioning: funding, open interest, and the squeeze factor

In perpetual futures, funding rates show who’s paying whom: positive funding means longs pay shorts (bullish bias); negative means shorts pay longs (bearish bias). After large liquidations, funding often flips and open interest shrinks—creating room for either a short squeeze (if price grinds up) or renewed deleveraging (if it slips). Coinbase’s primer is a good quick refresher on how funding works.

Actionable read: If you see funding normalize near flat while price builds higher lows, it suggests a healthier spot-led advance rather than a leverage-driven pop. Conversely, funding spiking positive into resistance implies fragility—classic dead-cat bounce conditions.

Bonus: Sentiment & on-chain hints

Sentiment check: Investopedia’s guides on market sentiment and technical analysis help decode “mood” indicators (moving averages, breadth, volatility) you’ll see cited in crypto Twitter and trader notes.
Accumulation footprints: Market coverage late last week noted BTC hovering near $107K with accumulation hints consistent with the idea that some investors bought the dip even as ETFs saw outflows. Treat these as tactical, not guarantees.

How to Use This (Simple Framework)

Start with flows: Are ETF/ETP flows net positive or negative today?
Overlay macro: Is their any Fed or CPI surprise that changes rate-cut odds?
Check derivatives health: Funding near flat + rebuilding open interest = healthier uptrend odds.
Map levels: Above $110K and building higher lows supports a drive to $118K; lose $110K and the $102K wick risk rises.
Validate with sentiment/TA: Use simple moving averages and momentum to confirm or fade the bounce.

Further Reading

Trend & sentiment basics: Check more trend analysis and market sentiment here

Final Word (Not Financial Advice)

This week’s rebound will be judged by flows, macro, and the quality of demand. If U.S. ETF outflows subside, macro stays calm into the Fed meeting, and derivatives avoid overheating, $118K is achievable. If not, expect choppy range-trading and keep $102K on the risk map. Manage position size, use stop-losses, and let data not emotions drive decisions.