Netflix reported 57.06 in PE Price to Earnings for its fiscal quarter ending in June of 2025. Data for Netflix | NFLX - PE Price to Earnings including historical, tables and charts were last updated by Trading Economics this last August in 2025.

This dataset offers a comprehensive historical record of Netflix’s stock price movements, capturing the company’s financial journey from its early days to its position as a global streaming giant.

From its IPO in May 2002, Netflix (Ticker: NFLX) has transformed from a DVD rental service to a powerhouse in on-demand digital content. With its disruptive innovation, strategic shifts, and global expansion, Netflix has seen dramatic shifts in stock prices, reflecting not just market trends but also cultural impact. This dataset provides a window into that evolution.

What’s Included?

Each row in this dataset represents daily trading activity on the stock market and includes the following columns:

• Date – The trading day (from 2002 onward)
• Open – Stock price when the market opened
• High – Highest trading price of the day
• Low – Lowest trading price of the day
• Close – Final price at market close
• Adj Close – Closing price adjusted for splits and dividends
• Volume – Number of shares traded that day

The data is structured in CSV format and is clean, easy to use, and ready for immediate analysis.

Why Use This Dataset?

Whether you're learning data science, building a financial model, or exploring machine learning in the real world, this dataset is a goldmine of insights. Netflix's market history includes:

• Periods of explosive growth during digital transformation
• Volatility during market crashes and global events (e.g., 2008, COVID-19)
• Strategic pivots such as the shift to original content
• Market reactions to earnings, acquisitions, and subscriber milestones

This makes the dataset ideal for:

• Time-series forecasting (ARIMA, Prophet, LSTM)
• Technical and trend analysis (moving averages, RSI, Bollinger Bands)
• Predictive modeling with machine learning
• Investment simulation projects
• Stock market visualization and storytelling
• Financial dashboards (Tableau, Power BI, Streamlit, etc.)

Who Can Use It?

This dataset is designed for:

• Aspiring data scientists practicing EDA and modeling
• Financial analysts and traders exploring trends
• AI researchers working on time-series models
• Students building ML projects
• Developers creating stock visualization tools
• Kaggle competitors seeking real-world datasets

Data Source & Credits

The dataset is derived from publicly available historical stock price data, such as Yahoo Finance, and has been cleaned and organized for educational and research purposes. It is continuously maintained to ensure accuracy.

Start Exploring

Netflix’s rise is more than just a business story — it’s a data-driven journey. With this dataset, you can analyze the company’s stock behavior, train models to predict future trends, or simply visualize how tech reshapes the market.

Netflix reported $5.33B in Cost of Sales for its fiscal quarter ending in June of 2025. Data for Netflix | NFLX - Cost Of Sales including historical, tables and charts were last updated by Trading Economics this last August in 2025.

Access a detailed Netflix stock price dataset with historical records on opening, highest, lowest, closing prices, adjusted closing prices, and trading volumes.

This is a Historical Stock Price dataset of the NETFLIX (Ticker: NFLX) stock in NASDAQ. The dataset contains data for the past 10 years. The dataset contains, opening price, closing price, day's high and each traded date.

Netflix stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Netflix reported $3.85B in EBITDA for its fiscal quarter ending in June of 2025. Data for Netflix | NFLX - Ebitda including historical, tables and charts were last updated by Trading Economics this last August in 2025.

Netflix's global subscriber base has reached an impressive milestone, surpassing *** million paid subscribers worldwide in the fourth quarter of 2024. This marks a significant increase of nearly ** million subscribers compared to the previous quarter, solidifying Netflix's position as a dominant force in the streaming industry. Adapting to customer losses Netflix's growth has not always been consistent. During the first half of 2022, the streaming giant lost over *** million customers. In response to these losses, Netflix introduced an ad-supported tier in November of that same year. This strategic move has paid off, with the lower-cost plan attracting ** million monthly active users globally by November 2024, demonstrating Netflix's ability to adapt to changing market conditions and consumer preferences. Global expansion Netflix continues to focus on international markets, with a forecast suggesting that the Asia Pacific region is expected to see the most substantial growth in the upcoming years, potentially reaching around **** million subscribers by 2029. To correspond to the needs of the non-American target group, the company has heavily invested in international content in recent years, with Korean, Spanish, and Japanese being the most watched non-English content languages on the platform.

Context

The art of forecasting stock prices has been a difficult task for many of the researchers and analysts. In fact, investors are highly interested in the research area of stock price prediction. For a good and successful investment, many investors are keen on knowing the future situation of the stock market. Good and effective prediction systems for the stock market help traders, investors, and analyst by providing supportive information like the future direction of the stock market. In this work, we present a recurrent neural network (RNN) and Long Short-Term Memory (LSTM) approach to predict stock market indices.

Content

Data from yahoo.com/finance Netflix historical price 12/16/2015 ~ 12/16/2019 daily price and volume. There are 7 columns; Date, open, high, low, close, volume, adj close (2001, 7) each of stock

Acknowledgements

I want to find relationship between volume and price.

Inspiration

Here is couple of things one could try out with this data:

One day ahead prediction: Rolling Linear Regression, ARIMA, Neural Networks, LSTM
Momentum/Mean-Reversion Strategies
Security clustering, portfolio construction/hedging

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

Netflix reported $11.08B in Sales Revenues for its fiscal quarter ending in June of 2025. Data for Netflix | NFLX - Sales Revenues including historical, tables and charts were last updated by Trading Economics this last August in 2025.

As of February 2025, Netflix users in the Philippines pay approximately **** U.S. dollars for a basic subscription monthly. Meanwhile, those with a premium subscription pay around **** U.S. dollars per month.

Netflix reported $522.3B in Market Capitalization this July of 2025, considering the latest stock price and the number of outstanding shares.Data for Netflix | NFLX - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last July in 2025.

These are the top 10 countries for Netflix in terms of penetration rate.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Is There a Netflix Effect on Unemployment? A Statistical Exploration

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Netflix had the most expensive subscription plan among video streaming services in the U.S., with its ad-free premium tier costing just under 23 U.S. dollars per month as of October 2024. By contrast, the streaming giant’s most basic plan supported with ads costs subscribers nearly seven U.S. dollars on a monthly basis. Peacock and Paramount+ were priced lower than the larger, more established SVOD providers like Netflix, Max, and Disney+, with the latter recently increased their fees. Consumer behavior after price hikes Video streaming services regularly increase their subscription costs. However, in light of recent economic developments, it is particularly taxing for consumers who must decide whether they can still afford the luxury of having multiple streaming subscriptions. According to a 2024 survey, the main reasons for consumers to stop the use of streaming offers were cost-related, and they are increasingly looking for alternative monetization models and bundling options. DTC business under pressure In order to keep their customers engaged and boost income, streaming providers needed to take action. Disney, for example, not only increased subscription fees, but also announced several cost-cutting measures to become profitable in the direct-to-consumer business in the upcoming years. These included laying off thousands of employees and reducing content spending by removing TV shows and movies from their services.

Netflix reported $1.45B in Trade Debtors for its fiscal quarter ending in March of 2025. Data for Netflix | NFLX - Trade Debtors including historical, tables and charts were last updated by Trading Economics this last August in 2025.

Netflix reported **** million paid streaming subscribers across the United States and Canada in the fourth quarter of 2024. This marked a growth of over **** million compared with the same quarter of the previous year. Why is Netflix losing subscribers? The EMEA (Europe, the Middle East, and Africa) region is Netflix's top-performing market in terms of subscribers, surpassing North America in the third quarter of 2022 for the first time. The company reported losing an estimated *** million users worldwide in the second quarter of 2022, with the number of Netflix users standing at approximately *** million that quarter. But why have audiences canceled their subscriptions? One reason for the unprecedented drop in account holders is Netflix's monthly fee, which has been increasing rapidly over the past few years. On top of that, viewers have also voiced criticism over Netflix's cancellation of popular shows and its lack of big movie franchises. What are audiences watching? Netflix's vast content library offers anything from reality TV to Hollywood blockbusters, with shows and movies delivered in many languages. As of mid-2024, European countries such as Slovakia, Bulgaria, and Slovenia boasted the largest content catalogs on Netflix. In the U.S., where audiences could choose from approximately ***** titles, “NCIS” and “Suits” ranked among the most popular streaming series on Netflix in 2023. As of that year, fan favorites “Stranger Things” and “3 Body Problem” were the most expensive Netflix original series, with production costs of ** and ** million U.S. dollars per episode, respectively.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

NFLX Netflix Inc. Common Stock

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Subscription Video on Demand Market Global Trend and Opportunity Analysis in Energy with a focus on upcoming trends and growth opportunities...

Netflix is distinctly more popular with younger consumers in the United States than with older generations. According to the findings of a recent survey, around ** percent of respondents aged 18 to 34 subscribed to Netflix as of mid-2021, compared to just ** percent of those aged 65 or above. Netflix predicts further subscriber loss Netflix is the most popular subscription video-on-demand (SVOD) service worldwide. Millions of viewers from various demographics access the platform each day, but despite its availability in over *** countries and its ever-expanding content catalog, Netflix reported a subscriber loss of around *** thousand in the first quarter of 2022. It was the first time in over a decade that the streamer experienced a drop in user numbers, but according to the company, this downward trend might very well continue in the second quarter of the year. According to company reports, Netflix expects to lose an additional * million subscribers by mid-2022. Cracking down on password sharing Credential sharing has become an essential part of the video-on-demand (VOD) experience. Companies can stand out in today’s crowded streaming space by offering viewers to create multiple profiles and split subscription costs with other people in their household – which might be particularly appealing to younger audiences. Netflix is one of the first services to have provided multiple subscription options at various price tiers, but even so, the company has also acknowledged that millions of people share their login data without paying for additional accounts. In 2021, Netflix was estimated to have lost over **** billion U.S. dollars in revenue due to password sharing. In 2022, the company reacted by announcing to charge additional sub-account fees for people streaming content outside the primary account holder’s household.