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UBER Uber Technologies, Inc.

Technology

65.25 Close 10/30
Since 2024-12-02 -10.7%
Open
65.61
High
65.80
Low
64.67
Prev close
65.74
Volume
17.1M
Amplitude
1.72%
P/E
14.3
P/B
4.9
Revenue YoY (TTM)
+16.7%
52W 64.04 100.35

Is Uber Technologies, Inc. a buy? Fundamentals and valuation first

As of 2026-10-30

Valuation: Fair, Quality: Good, Risk / liquidity: Strong.

Valuation Fair Free-cash-flow yield is Good, but Price / book is Expensive.
TTM P/E 14.34 39th percentile Fair
Price / book 4.88 82th percentile Expensive
Free-cash-flow yield (%) 7.59 76th percentile Good
US Stock Backtest in Python: Price-to-Book Ratio StrategyQuality Factor Investing: A US Quality Value Backtest
Quality Good ROE, TTM is Top; Operating margin, TTM is Good.
ROE, TTM (%) 35.07 89th percentile Top
Operating margin, TTM (%) 12.47 60th percentile Good
FCF margin, TTM (%) 18.32 74th percentile Good
Quality Factor Investing: A US Quality Value Backtest
Growth Neutral Revenue growth, TTM YoY is Good, but Diluted EPS growth, TTM YoY is Average.
Revenue growth, TTM YoY (%) 16.68 71th percentile Good
Diluted EPS growth, TTM YoY (%) -22.49 45th percentile Average
Momentum Neutral All 2 indicators are Average.
60-day return (%) -7.41 48th percentile Average
240-day return (%) -28.78 27th percentile Average
Momentum Trading Strategy: A 12-1 Momentum Backtest
Risk / liquidity Strong 20-day dollar volume is Top; 60-day annualized volatility is Good.
20-day dollar volume 1,092,033,122 99th percentile Top
60-day annualized volatility (%) 31.77 36th percentile Good
FinLab Studio

From Uber Technologies, Inc. to every stock like it

AI finds several complementary traits of Uber Technologies, Inc. across different dimensions, combines them into a multifactor strategy, and backtests it against the market.

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Uber Technologies, Inc. (UBER) peers and tracking

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Uber Technologies, Inc. (UBER) quant signal backtests

Market-wide momentum baseline

Across 99,493 liquid US common-stock samples, top-quintile 6-month momentum was followed by an average 60-trading-day return of +6.42%, a 58.4% positive-return rate, and +3.08 percentage points of average excess return versus the S&P 500.

Baseline: weekly samples since 2016 where a liquid US common stock ranked in the top quintile by 126-trading-day momentum. Forward return is 60 trading days; excess return is versus S&P 500 (^GSPC).

More history: Signals not active now

Signals not active now

Inactive signals still show the stock-specific historical forward-return distribution for context.

52-week adjusted-price high

Pending

Adjusted close first reaches a 252-trading-day high; repeated hits within 20 days count once.

10 times historically; 60-day forward avg +8.94%, win rate 70%, beating the market by +0.89 pts on average.

Top-quintile 6-month momentum

Pending

The stock ranks in the top 20% of the liquid US common-stock universe by 126-day adjusted return.

13 times historically; 60-day forward avg +8.61%, win rate 76.9%, beating the market by +1.18 pts on average.

Filed revenue acceleration

Pending

TTM revenue growth is at least 10% and improved versus the prior filed quarter; event date is the SEC filing date.

12 times historically; 60-day forward avg -2.22%, win rate 50%, beating the market by -3.35 pts on average.

EPS surprise beat

Pending

Reported EPS beat consensus estimate by at least 5%; event date is the earnings-surprise timestamp.

15 times historically; 60-day forward avg +0.52%, win rate 53.3%, beating the market by -1.9 pts on average.

Method and limits

  • Returns use us_price:adj_close, adjusted for splits and dividends where available.
  • Excess returns use world_index:^GSPC as the S&P 500 benchmark proxy.
  • Quarterly fundamentals are aligned to SEC filing dates before daily valuation studies.
  • The promoted universe starts from active NYSE/NASDAQ common stocks, then applies price and dollar-volume gates.
  • Snapshot-only tables such as analyst consensus, DCF, us_ratios, and us_key_metrics are intentionally excluded from historical evidence.
  • Overlapping event windows are descriptive distributions, not independent samples.

This page is for historical data analysis and education only. It is not investment advice. Backtests and historical return distributions do not predict future performance; evaluate risk independently before trading.