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AEHR Aehr Test Systems

Technology

51.47 -3.42 -6.23% Close 11/2
Since 2024-12-02 +332.2%
Open
55.66
High
57.29
Low
50.52
Prev close
54.89
Volume
4M
Amplitude
12.33%
P/B
8.2
Revenue YoY (TTM)
-13.7%
52W 18.70 147.40

Is Aehr Test Systems a buy? Fundamentals and valuation first

As of 2026-10-30

Valuation: Pricey.

Valuation Pricey Free-cash-flow yield is Average; Price / book is Expensive.
TTM P/E -238.65 N/A
Price / book 8.16 90th percentile Expensive
Free-cash-flow yield (%) -0.3 45th percentile Average
US Stock Backtest in Python: Price-to-Book Ratio StrategyQuality Factor Investing: A US Quality Value Backtest
Quality Neutral All 3 indicators are Average.
ROE, TTM (%) -3.25 35th percentile Average
Operating margin, TTM (%) -27.8 21th percentile Average
FCF margin, TTM (%) -10.56 28th percentile Average
Quality Factor Investing: A US Quality Value Backtest
Growth Neutral Diluted EPS growth, TTM YoY is Top, but Revenue growth, TTM YoY is Lagging.
Revenue growth, TTM YoY (%) -13.65 19th percentile Lagging
Diluted EPS growth, TTM YoY (%) 75.3 81th percentile Top
Momentum Neutral 240-day return is Top, but 60-day return is Lagging.
60-day return (%) -44.97 9th percentile Lagging
240-day return (%) 169.86 98th percentile Top
Momentum Trading Strategy: A 12-1 Momentum Backtest
Risk / liquidity Neutral 20-day dollar volume is Top, but 60-day annualized volatility is Lagging.
20-day dollar volume 188,716,854 92th percentile Top
60-day annualized volatility (%) 105.04 84th percentile Lagging
FinLab Studio

From Aehr Test Systems to every stock like it

AI finds several complementary traits of Aehr Test Systems across different dimensions, combines them into a multifactor strategy, and backtests it against the market.

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Aehr Test Systems (AEHR) peers and tracking

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Aehr Test Systems (AEHR) 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.

17 times historically; 60-day forward avg +55.71%, win rate 56.2%, beating the market by +52.68 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.

25 times historically; 60-day forward avg +55.52%, win rate 60%, beating the market by +51.02 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.

8 times historically; 60-day forward avg -7.39%, win rate 37.5%, beating the market by -7.97 pts on average.

EPS surprise beat

Pending

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

18 times historically; 60-day forward avg +52.17%, win rate 61.1%, beating the market by +47.9 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.