Datadog, Inc. (DDOG)
Quantitative Summary
DeterministicDDOG trades at 618.4x earnings — a 851% premium to its sector average of 65.0x — without a dominant ROIC-WACC spread. Financial health is average: Piotroski 6/9, Altman Z 9.0. DCF fair value of $64 implies 42% downside based on model assumptions.
Generated deterministically from quant metrics and financial statements. Not a recommendation.
Algorithmic Teardown
AI-GeneratedThe fundamental economics of DDOG reveal a significant capital allocation challenge where the return on invested capital sits at 2.2%, creating a negative spread of -10.8% against a weighted average cost of capital of 13.0%. This inefficiency is driven by low asset turnover of 0.52x, which constrains the overall ROE to just 2.9% despite an expansive gross margin of 80.0%; the equity multiplier of 1.78x provides only modest leverage support. While qualitative integrity metrics remain robust with a Piotroski F-Score of 6/9 and a strong Altman Z-Score of 10.5 indicating low bankruptcy risk, the Beneish M-Score of -2.71 further underscores management's lack of incentive to manipulate earnings. The narrative is one of high growth potential offset by substantial capital inefficiency relative to the cost of funds.
Valuation metrics suggest a significant disconnect between current market pricing and intrinsic value derived from cash flow models. Trading at a P/E ratio of 388.3x, the stock commands a premium far exceeding historical norms and sector averages, implying that investors are betting on sustained acceleration rather than current profitability. A discounted cash flow analysis places fair value at $61, resulting in an implied downside of -48.6% from current levels based on ten-year free cash flow growth assumptions of 24.8%. This aggressive pricing embeds expectations for flawless execution and margin expansion that have not yet materialized into the bottom line.
Risk-adjusted performance data highlights a divergence between risk factors and recent insider behavior, warranting caution regarding future volatility. The stock exhibits negative momentum across key factor models, with an annual Fama-French Alpha of -3.62%, a Value Factor (HML) of -0.299 confirming its growth tilt, and a Profitability Factor (RMW) of -1.403 reflecting weak returns on capital relative to peers. Compounding these technical signals is substantial insider activity, with $82 million in net selling over the last 90 days, suggesting that corporate insiders may view current valuations as fully priced or excessive despite the company's strong revenue growth trajectory of 27.7% year-over-year.
Generated by LLM from quantitative data inputs. May contain inaccuracies. Not investment advice.
DCF Sandbox
Interactive5-year two-stage DCF. Terminal growth 3%. Default sliders match the pre-computed base case. Drag to explore scenarios. Not investment advice.
The growth rate the market implicitly expects over the next 10 years to justify today's price. Compare with historical growth of 28% YoY revenue.
Sensitivity Matrix
| TG ↓ / WACC → | 10.5% | 12.5% | 14.5% |
|---|---|---|---|
| 2% | $75 | $59 | $48 |
| 3% | $83 | $64 | $51 |
| 4% | $94 | $70 | $55 |
Center = base case. Green = >10% upside, Red = >10% downside vs $269.13.
Pre-computed DCF: WACC=12.5%, terminal growth 3%. Fair value $64 (-42.1%). Not investment advice.
Valuation Context
Currently trading 57% above its 5-year average P/E of 216.3x.
Price Chart with Moving Averages
Technical Setup
AI GeneratedDatadog, Inc. is currently trading at $208.82 within the technology sector, a price point that reflects its position in the broader market for cloud monitoring and analytics solutions. The technical landscape suggests active institutional engagement, as evidenced by significant volume trends often accompanying major price movements in high-liquidity tech stocks. When larger players accumulate or distribute shares, it frequently manifests through sustained shifts in trading volumes relative to moving averages, indicating whether there is underlying support building beneath the current valuation or if profit-taking pressure might be emerging near recent highs. The interaction between short-term and long-term simple moving averages serves as a critical lens for observing institutional sentiment without dictating specific directional outcomes. If price action remains resilient above these key crossover thresholds, it may imply that sophisticated market participants view the asset as fundamentally sound relative to its historical trajectory, potentially anchoring support at elevated levels. Conversely, any breach of these dynamic lines accompanied by divergent volume patterns could signal a rotation in positioning, where institutions might be adjusting their exposure based on changing macroeconomic conditions or sector-specific valuations. Ultimately, the convergence of price action and volume data offers a window into how capital is being allocated rather than prescribing a specific course of action for individual traders. The current setup highlights the importance of monitoring these technical confluences to understand the weight behind recent market moves, allowing observers to gauge whether institutional flows are reinforcing the uptrend or hinting at potential consolidation phases ahead.
Quant Health Deep Dive
Profitability & Value Creation
DuPont Analysis — ROE Decomposition
Breaking down Return on Equity to see how the company generates its ROE — efficiency, margins, or leverage.
Balance Sheet Health
Insider Activity (Last 90 Days)
Open-market buys vs sells by company insiders. Source: yfinance.
Earnings Surprise History
EPS estimates vs actuals for the most recent reported quarters. Source: yfinance.
Risk Profile
Sharpe = risk-adjusted return (higher is better). Max drawdown = largest peak-to-trough decline. 1,200+ trading days.
Underwater (Drawdown from Peak)
How far below the all-time high the price has been over time. Deeper = more pain for holders.
Rolling 60-Day Beta vs S&P 500 (VOO)
How the stock's sensitivity to market moves changes over time. β > 1 = more volatile than the market.
Fama-French 5-Factor Exposure
Academic factor model decomposition — what's really driving this stock's returns.
Fama-French 5-Factor Model. Data: Kenneth French Data Library. Regression over 3 years of daily returns.
Fundamentals
Passive Flow Attribution
ETF Draft EffectWhen investors buy or sell ETFs like ARKW or XSW, the fund manager is mechanically forced to buy or sell DDOG shares regardless of Datadog, Inc.'s individual fundamentals. We estimate $7.8B of passive capital is structurally linked to DDOG through 8 tracked ETFs. This substantial passive exposure means that ETF inflows and outflows — not company fundamentals — can dominate daily volume on this stock.
Passive exposure = Σ (ETF AUM × stock weight in ETF) across 8 tracked ETFs. Actual passive ownership is larger (includes mutual funds). Not investment advice.
ETF Contagion Visualizer
Simulate a price drop in Datadog, Inc. to visualize passive redemption contagion across ETFs and collateral stocks.
If Datadog, Inc. (DDOG) experiences a significant drawdown, ETF redemptions can create collateral selling pressure on co-held stocks. Our model identifies NVIDIA CORP (NVDA) as the most exposed collateral stock, sharing 2 ETFs with DDOG. This is the "Passive Contagion" effect described in the Inelastic Market Hypothesis.
Contagion model based on shared ETF exposure and constituent weights across 29 tracked ETFs. Estimated selling pressure is a simplified model — actual impact depends on market liquidity, ETF redemption mechanics, and market-maker activity.
DDOG Ownership Dynamics
Passive funds hold 1 in every 6 DDOG shares, reducing daily market volatility.
Datadog, Inc. (DDOG) exerts notable gravity on the passive index market, currently representing 2.3% of the ARK Next Generation Internet ETF (ARKW) and 1.2% of the XSW (XSW). Across 29 tracked ETFs, approximately 59M shares (17.9% of float) are held by passive funds and rarely trade on the open market. This level of passive ownership means index rebalances can create outsized volume events.
ETFs with Highest DDOG Exposure
Float lock-up computed from 29 ETFs tracked by SecuritiesDB. Actual passive ownership is higher (includes mutual funds, pension funds, etc.).
DDOG Institutional Volume Profile
252-day volume distribution by price level. The Point of Control (POC) marks — the price where the most institutional volume transacted — an implicit support/resistance floor.
The highest-volume price zone for Datadog, Inc. over the past year sits near $129.63 (22% of 252-day volume). The current price of $269.13 trades 107.6% above this institutional floor — a sign of upside momentum, though a pullback to the POC zone is a common reversion target. The highly concentrated volume profile (22% at POC) indicates strong consensus on fair value — institutional participants have repeatedly transacted near this price.
Volume Profile computed from 252 trading days of OHLCV data. Volume allocated to price bins proportionally based on daily high-low range. Not investment advice.
DDOG Capital Efficiency
How efficiently does Datadog, Inc. convert operating profits into free cash? The FCF Conversion ratio measures the gap between accounting earnings and real cash generation.
Datadog, Inc. converts 472% of its EBITDA into free cash flow, an exceptional conversion rate indicating an asset-light business model with minimal capital reinvestment drag. However, the ROIC-WACC spread is negative (-10.4%), suggesting reinvested capital is destroying shareholder value.
Capital efficiency = Free Cash Flow ÷ EBITDA. Reinvestment = (EBITDA − FCF) ÷ EBITDA. Metrics from latest annual filings. Not investment advice.
Fails-to-Deliver (FTD) History
SEC-reported settlement failures. Elevated FTDs can indicate high short-selling pressure, operational settlement issues, or naked shorting activity.
| Date | Failed Shares | Close Price | Notional Value |
|---|---|---|---|
| 2026-05-14 | 965 | $205.31 | $198,124.15 |
| 2026-05-11 | 3,898 | $200.16 | $780,223.68 |
| 2026-05-08 | 243,546 | $188.73 | $46.0M |
| 2026-05-07 | 3 | $143.71 | $431.13 |
| 2026-05-06 | 53,635 | $145.73 | $7.8M |
| 2026-05-05 | 20,125 | $146.69 | $3.0M |
| 2026-05-04 | 8,604 | $140.53 | $1.2M |
| 2026-04-28 | 624 | $132.66 | $82,779.84 |
| 2026-04-24 | 2 | $127.86 | $255.72 |
| 2026-04-23 | 320 | $132.14 | $42,284.8 |
| 2026-04-22 | 28 | $129.29 | $3,620.12 |
| 2026-04-20 | 4,683 | $126.61 | $592,914.63 |
| 2026-04-17 | 4 | $123.47 | $493.88 |
| 2026-04-15 | 3 | $110.57 | $331.71 |
| 2026-04-06 | 1 | $120.36 | $120.36 |
| 2026-03-31 | 38 | $115.81 | $4,400.78 |
| 2026-03-25 | 32 | $122.57 | $3,922.24 |
| 2026-03-23 | 2,601 | $125.08 | $325,333.08 |
| 2026-03-09 | 400 | $125.75 | $50,300 |
| 2026-03-05 | 574 | $118.33 | $67,921.42 |
| 2026-03-03 | 87,803 | $111.11 | $9.8M |
| 2026-02-25 | 60,033 | $104.43 | $6.3M |
| 2026-02-24 | 8,904 | $102.62 | $913,728.48 |
| 2026-02-20 | 1,670 | $120.60 | $201,402 |
| 2026-02-19 | 2 | $121.78 | $243.56 |
| 2026-02-18 | 1,068 | $122.56 | $130,894.08 |
| 2026-02-17 | 3,816 | $125.20 | $477,763.2 |
| 2026-02-13 | 5,615 | $126.13 | $708,219.95 |
| 2026-02-12 | 2,202 | $127.33 | $280,380.66 |
| 2026-02-11 | 2,418 | $129.67 | $313,542.06 |
Source: SEC Regulation SHO FTD data. Data is reported with a ~30 day delay. High FTD quantities relative to average daily volume may indicate settlement stress.
Price Correlations
Statistical correlation of daily returns with other stocks. High correlations indicate stocks that move together; negative correlations can offer diversification.
| Peer | 252-Day (1Y) | 126-Day (6M) | Direction |
|---|---|---|---|
| WTGXX | NaN | NaN | |
| SNOW | 0.585 | 0.594 | Moderate |
| CRWD | 0.581 | 0.617 | Moderate |
| ZS | 0.547 | 0.558 | Moderate |
| TENB | 0.538 | 0.564 | Moderate |
| PANW | 0.517 | 0.523 | Moderate |
| NET | 0.505 | 0.496 | Moderate |
| NOW | 0.501 | 0.478 | Moderate |
| RBRK | 0.477 | 0.474 | Moderate |
| S | 0.452 | 0.482 | Moderate |
Pearson correlation of daily log returns. 252d ≈ 1 trading year. Computed from price history. Not investment advice.
Compare DDOG to Peers
Quant metrics computed deterministically from financial statements and price data. Updated: 2026-06-02.
SecuritiesDB provides programmatic data aggregation for informational purposes only. None of the metrics, summaries, or algorithmic flags constitute a recommendation to buy or sell any security.