The company’s shares rose 5% in extended trading after gaining about 41% in 2020 as COVID-19 shifted computing to areas where the software maker has bet big. It also saw a surprise recovery in sales on the LinkedIn professional social network and navigated a chip shortage that had threaten to hold back its Xbox business.

The shift to work from home due to the COVID-19 pandemic has accelerated enterprises’ switch to cloud-based computing, benefiting Microsoft and rivals such as Amazon.com Inc’s cloud unit and Alphabet Inc’s Google Cloud.

On a conference call with investors, Microsoft executives said they expect a midpoint of $14.83 billion in revenue from the company’s “Intelligent Cloud” segment for the fiscal third quarter, compared with Wall Street expectations of $14.12 billion, according to Refinitiv data. For the company’s productivity segment and its personal computing segment, sales are expected to have a respective midpoint of $13.48 billion and $12.50 billion, compared with estimates of $12.90 billion and $11.60 billion, according to Refinitiv data.

Microsoft said GamePass, the company’s $10 monthly gaming subscription, has 18 million users, up from 15 million disclosed in September. The Xbox Live online gaming service has more than 100 million monthly active users. Microsoft did not give an update on the 115 million Teams daily users it disclosed in October but did say that the mobile version is used by 60 million daily users.

Microsoft said revenue in its “Intelligent Cloud” segment rose 23% to $14.6 billion, with 50% growth in Azure. Analysts had expected a 41.4% growth in Azure, according to consensus data from Visible Alpha. The previous quarter Azure grew 48%.
This was really driven by continued customer demand, with stronger-than-expected consumption as customers have increased their focus on digital transformation,” Microsoft Chief Financial Officer Amy Hood told Reuters in an interview.

Atlantic Equities analyst James Cordwell said that last year, “economic weakness and delays in implementation had masked the extent to which Azure was benefiting from the accelerated shift to the cloud caused by the pandemic. But with these results that benefit is now plain to see.”
LinkedIn revenue growth, which dipped as the pandemic shut down businesses, reached 23%, near its pre-pandemic rate of 24% a year earlier. Hood said advertisements on LinkedIn drove the increase.

“We continue to see advertising market recovery,” she said.

Microsoft bundles several sets of software and services such as Office and Azure into a “commercial cloud” metric that investors watch closely to gauge the company’s progress in selling to large businesses.

Commercial cloud gross margins – a measure of the profitability of its sales to large businesses – were 71% in the quarter, compared with 67% a year earlier.

Revenue from its personal computing division, which includes Windows software and Xbox gaming consoles, rose 14% to $15.1 billion, driven by strong Xbox content and services growth, beating analysts’ estimates of $13.5 billion, according to IBES data from Refinitiv.

Microsoft in November released two new Xbox consoles, its most visible non-work and non-school brand, but the hardware proved difficult to find as a global semiconductor shortage contributed to tight stocks as many retailers. Xbox hardware sales were up 86% despite the shortages, and Hood said growth is likely to continue, with older models also contributing to sales.
“Demand still outpaces supply, and we do expect that to continue,” Hood said. “The team did a nice job of getting consoles, both of this newest generation as well as continuing to sell the older generation, which provides a great value for gamers.”

Microsoft’s gaming business topped $5 billion in quarterly sales for the first time ever and was propelled by gaming subscriptions and sales as well as new consoles. Microsoft said Xbox content and services revenue grew 40% in the quarter.

The software giant’s overall revenue rose to $43.08 billion in the second quarter ended Dec. 31, from $36.91 billion a year earlier, beating analysts’ estimates of $40.18 billion, according to IBES data from Refinitiv.

Datadog, Inc. (NASDAQ:DDOG) has a beta value of 0 and has seen 2,949,512 shares traded in the last trading session. The company, currently valued at $30.96 Billion, closed the last trade at $102.08 per share which meant it gained $3.14 on the day or 3.17% during that session. The DDOG stock price is -15.72% off its 52-week high price of $118.13 and 71.71% above the 52-week low of $28.88. If we look at the company’s 10-day average daily trading volume, we find that it stood at 3.35 Million shares traded. The 3-month trading volume is 5.01 Million shares.

The consensus among analysts is that Datadog, Inc. (DDOG) is an Overweight stock at the moment, with a recommendation rating of 2.4. None of the analysts rate the stock as a Sell, while none rate it as Overweight. 10 out of 19 have rated it as a Hold, with 9 advising it as a Buy. None have rated the stock as Underweight. The expected earnings per share for the stock is $0.01.

Datadog, Inc. (NASDAQ:DDOG) trade information
Sporting 3.17% in the green today, the stock has traded in the green over the last five days, with the highest price hit on Monday, Oct 19 when the DDOG stock price touched $113.75 or saw a rise of 10.26%. Year-to-date, Datadog, Inc. shares have moved 170.2%, while the 5-day performance has seen it change -9.15%. Over the past 30 days, the shares of Datadog, Inc. (NASDAQ:DDOG) have changed 12.05%. Short interest in the company has seen 19.56 Million shares shorted with days to cover at 3.9.

Wall Street analysts have a consensus price target for the stock at $101.6, which means that the shares’ value could jump -0.47% from current levels. The projected low price target is $80 while the price target rests at a high of $140. In that case, then, we find that the current price level is +37.15% off the targeted high while a plunge would see the stock lose -21.63% from current levels.

Datadog, Inc. (DDOG) estimates and forecasts
17 analysts offering their estimates for the company have set an average revenue estimate of $144.31 Million for the current quarter. 17 have an estimated revenue figure of $155.23 Million for the next quarter concluding in December 01, 2020. Year-ago sales stood $95.86 Million and $113.64 Million respectively for this quarter and the next, and analysts expect sales will grow by 50.5% for the current quarter and 36.6% for the next.

Datadog, Inc. (NASDAQ:DDOG)’s Major holders
Insiders own 1.59% of the company shares, while shares held by institutions stand at 50.31% with a share float percentage of 51.12%. Investors are also buoyed by the number of investors in a company, with Datadog, Inc. having a total of 238 institutions that hold shares in the company. The top two institutional holders are Price (T.Rowe) Associates Inc with over 23.14 Million shares worth more than $2.01 Billion. As of June 29, 2020, Price (T.Rowe) Associates Inc held 12.19% of shares outstanding.

The other major institutional holder is Vanguard Group, Inc. (The), with the holding of over 11.24 Million shares as of June 29, 2020. The firm’s total holdings are worth over $976.99 Million and represent 5.92% of shares outstanding.

Also the top two Mutual Funds that are holding company’s shares are Price (T.Rowe) New Horizons Fund and Vanguard Total Stock Market Index Fund. As of June 29, 2020, the former fund manager holds about 4.44% shares in the company for having 8431832 shares of worth $733.15 Million while later fund manager owns 4.02 Million shares of worth $349.28 Million as of June 29, 2020, which makes it owner of about 2.12% of company’s outstanding stock.

DDOG Share Price Performance

Shares of Datadog, Inc. (NASDAQ: DDOG) were trading at $38.79 per share on the reported date, up from a previous closing price of $35.73 — representing an 8.56% single-session gain. Over the same reporting period, the stock recorded a year-to-date (YTD) rise of approximately 3.30%, with a 52-week trading range between $27.55 and $44.09. The stock’s simple moving average over the prior 200 days reflected a gain of approximately 9.42%, suggesting moderate medium-term upward momentum.

Analyst Ratings and Price Targets

Multiple equity research firms weighed in on DDOG shares during Q4 2019:

• Oppenheimer changed its rating to “Perform” in a report dated November 21, 2019.
• Needham reiterated a “Buy” rating in a report dated November 13, 2019.
• Credit Suisse assigned a “Neutral” rating with a price target of $40, published November 6, 2019.
• Stifel initiated coverage with a “Buy” rating in a report dated October 14, 2019.
• RBC Capital Markets gave DDOG a “Sector Perform” rating with a price target of $39, also dated October 14, 2019.
• Raymond James assigned a “Market Perform” rating.

At the time of reporting, the consensus long-term analyst price target stood at approximately $42.78, suggesting upside potential from the then-current trading price of $38.79.

Key Financial Metrics

Investors evaluating DDOG at this stage would have considered several core financial indicators:

• Dividend yield: 0% — Datadog does not pay a dividend, which is typical for high-growth SaaS companies reinvesting capital into expansion.
• Quarter-over-quarter revenue growth: 87.70%, reflecting strong and accelerating demand for its cloud monitoring platform.
• Quick ratio: 4.90, indicating solid short-term liquidity and a strong ability to cover near-term liabilities.
• Average daily trading volume: approximately 2.43 million shares.
• Monthly price volatility: 6.02%
• Weekly price volatility: 6.45%, with an 8.02% gain over the prior seven days.
• EPS growth (year-over-year): -318.60%, consistent with a pre-profitability growth company investing heavily in sales, marketing, and R&D.
• P/E ratio: Reported as -0.08, reflecting negative earnings at the time.

What to Consider When Analyzing DDOG

Datadog operates in the technology sector, specifically providing cloud-scale monitoring, security, and analytics for development and operations teams. When benchmarking DDOG against peers in the software infrastructure and DevOps tooling space, investors typically examine:

• Revenue growth rate — particularly important for pre-profitability SaaS companies where top-line growth signals future earnings potential.
• Price-to-Sales (P/S) ratio — often more meaningful than P/E for companies with negative earnings.
• Net Revenue Retention (NRR) — a critical SaaS metric measuring how much existing customers expand their usage over time.
• Gross margin — high gross margins (typically 70%+ for SaaS) indicate strong unit economics.
• Insider ownership — at the time of reporting, insider ownership stood at approximately 0.20% of shares outstanding, which is relatively low and may signal reduced executive skin-in-the-game for some investors.
• Institutional ownership — reported at 98.60%, a high level of institutional interest that can indicate conviction from sophisticated investors but also potential for large block selling.

Institutional Investor Activity

Several major institutional investors and hedge funds were reported to have increased their positions in DDOG during the period covered:

• Iconiq Capital LLC held approximately 30.67 million shares valued at roughly $1.25 billion, after adding 30.67 million shares during the most recent quarter.
• T. Rowe Price Associates, Inc. increased its stake by 272.50%, bringing its holdings to approximately 5.04 million shares valued at around $205.43 million, after acquiring an additional 3.69 million shares.
• Whale Rock Capital Management LLC established a new position valued at approximately $76.58 million.
• Morgan Stanley & Co. LLC increased its position by 208.06%, now holding approximately 1.21 million shares valued at around $72.84 million, after acquiring an additional 1.79 million shares.
• The Vanguard Group, Inc. increased its position, now holding approximately 1.72 million shares valued at around $70.18 million, after purchasing an additional 1.72 million shares.

In aggregate, institutional investors controlled approximately 98.60% of DDOG’s outstanding shares at the time of reporting — a notably high figure that reflects strong institutional confidence in Datadog’s long-term growth prospects in the cloud observability market.

Context: Datadog’s Market Position in Late 2019

Datadog went public in September 2019, pricing its IPO at $27 per share. By December 2019, the stock had already traded well above that level, supported by strong revenue growth and increasing adoption of its unified monitoring and analytics platform across infrastructure, application performance, and log management. The metrics reported here reflect the company’s early post-IPO period, when growth metrics were prioritized over profitability — a common pattern for high-growth SaaS businesses in their early public life.

Original source data attributed to uspostnews.com. Financial figures are historical and sourced from the original publication dated December 2019.

Technical vs. Fundamental Analysis: A Quick Distinction

Strictly technical traders focus on price history, chart patterns, and mathematical indicators rather than factors such as earnings, competitive positioning, or management quality. The goal is to identify trends and short-term price fluctuations that can be acted on quickly. Because these traders often hold positions for short periods, they pay close attention to support and resistance levels—price points where a stock has historically bounced or reversed.

Ichimoku Cloud: Span A vs. Span B

The Ichimoku Kinko Hyo (often shortened to Ichimoku Cloud) is a comprehensive indicator that plots several lines on a price chart. Two of the most watched are Span A and Span B, which together form the “cloud” (also called the Kumo).

• Span A is the midpoint of the Conversion Line and the Base Line, plotted 26 periods ahead.
• Span B is the midpoint of the highest high and lowest low over the past 52 periods, also plotted 26 periods ahead.

When Span A is above Span B, the cloud is colored green, which many traders interpret as a bullish signal—suggesting that upward momentum may be building. When Span B is above Span A, the cloud turns red, indicating a potentially bearish environment. Price trading above the cloud is generally considered bullish; price below the cloud is considered bearish.

Commodity Channel Index (CCI)

The Commodity Channel Index was originally developed by Donald Lambert for commodity markets but has since become a popular equity indicator. The CCI measures the difference between an asset’s current price and its historical average price, normalized by mean deviation.

Key interpretation guidelines:

• The indicator oscillates above and below a zero line.
• Readings typically stay within a range of -100 to +100 during normal market conditions.
• A reading above +100 may signal overbought conditions.
• A reading below -100 may indicate oversold territory.
• Readings between -100 and +100 are generally considered neutral.

Traders often combine CCI readings with trend direction to decide whether an extreme reading represents a reversal opportunity or simply a continuation of a strong trend.

Relative Strength Index (RSI)

The RSI is a momentum oscillator created by J. Welles Wilder, first introduced in his 1978 book New Concepts in Technical Trading Systems. It measures the speed and magnitude of recent price changes to evaluate whether an asset is overbought or oversold.

RSI ranges from 0 to 100:

• Readings above 70 are commonly interpreted as overbought.
• Readings below 30 are commonly interpreted as oversold.
• A reading near 50 suggests roughly balanced momentum.

The 14-period RSI is the most widely used setting, but traders also monitor shorter periods such as 3-day and 7-day RSI for near-term momentum shifts. Shorter RSI periods are more sensitive to recent price changes and will signal overbought or oversold conditions more frequently, while longer periods smooth out the data and generate fewer signals.

The RSI is calculated based on the average gain versus average loss over the chosen period, using closing prices. It is displayed as a line chart beneath the main price chart, making it easy to spot divergences—situations where the RSI moves in the opposite direction of price, which can sometimes foreshadow a reversal.

Moving Averages: 50-Day and 200-Day

Moving averages smooth price data to reveal the underlying trend direction. Two of the most commonly watched are the 50-day moving average (MA) and the 200-day MA.

• The 200-day MA is used to assess the long-term trend. Price consistently above the 200-day MA is generally considered a bullish sign.
• The 50-day MA provides a medium-term view and is often used alongside the 200-day to identify crossover signals.
• A Golden Cross—when the 50-day MA crosses above the 200-day MA—is widely considered a bullish signal.
• A Death Cross—when the 50-day MA crosses below the 200-day MA—is generally interpreted as bearish.

Traders may also watch the 20-day MA for shorter-term trend insights, particularly in fast-moving markets.

Average Directional Index (ADX)

Also developed by J. Welles Wilder, the ADX measures the strength of a trend—not its direction. It is plotted as a single line ranging from 0 to 100.

• Below 20: Suggests no discernible trend; the market may be ranging.
• 20–25: A borderline zone; the trend signal is not yet clear.
• Above 25: Generally indicates a strong trend is in place.
• Above 40–50: Indicates a very strong or extreme trend.

A rising ADX line means the existing trend—whether up or down—is gaining strength. A falling ADX line suggests the trend is weakening. The ADX itself does not indicate whether the trend is bullish or bearish; it must be read alongside directional indicators (the +DI and -DI lines) for that information.

Williams %R

Developed by Larry Williams, Williams %R is a momentum indicator that compares a closing price to the high-low range over a specified period (commonly 14 days). It is designed to identify when a security may be approaching an overbought or oversold extreme and could be due for a reversal.

Williams %R oscillates between 0 and -100:

• Readings between 0 and -20 are generally considered overbought.
• Readings below -80 are generally considered oversold.
• The further the reading is from the center, the more extreme the condition—and potentially the more likely a reversal could occur.

Like all oscillators, Williams %R works best in ranging markets. In strongly trending markets, overbought and oversold readings can persist for extended periods without producing a reversal, so traders typically use it in combination with a trend indicator such as ADX.

Combining Indicators: A Practical Approach

No single indicator tells the complete story. Experienced technical traders typically combine multiple signals to improve the reliability of their entries and exits:

• Use ADX to confirm whether a trend is strong enough to trade directionally.
• Use moving averages to determine overall trend direction.
• Use RSI or CCI to identify momentum and potential turning points within the trend.
• Use Williams %R to spot short-term overbought or oversold extremes.
• Use Ichimoku Span A/B for a multi-dimensional view of support, resistance, and trend bias.

Beginners are generally advised to master two or three indicators before adding more. A crowded chart with conflicting signals can create more confusion than clarity. Starting with a trend indicator and a momentum oscillator is a common and practical approach.

Final Thoughts

Technical indicators are tools, not guarantees. Each of the indicators covered here—Ichimoku Spans, CCI, RSI, ADX, and Williams %R—offers a different perspective on price behavior. Understanding the theory behind each indicator, including its strengths and limitations, helps traders apply them more effectively and avoid over-relying on any single signal. As with any trading methodology, risk management and position sizing remain critical regardless of how compelling the technical setup appears.