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.

Abstract of associated article: This paper analyzes the effects of the Commodity Futures Trading Commission's (CFTC) announcements on the stock returns of oil and gas companies around the financial crisis of 2008. Using event study methodology and regression analyses, we examine a set of 122 oil and gas related stocks listed in the New York Stock Exchange (NYSE) for 35 announcements. Our results indicate that CFTC announcements, depending on their content, can affect the stock returns of oil and gas companies. In particular, this is found to hold true during the period of high-volatility in oil prices, i.e., the period following Lehman Brothers failure. During this period, oil and gas related stock returns respond positively to most regulatory announcements, showing that the CFTC's regulatory interventions are perceived positively by the stock market.

Formaat: MP4Omvang: 47,2 Mb27 February 2008Online beschikbaar: [01-12-2014]Standard Youtube LicenseUploaded on Jun 11, 2008Video summary of the ALDE workshop "The International Financial Crisis: Its causes and what to do about it?"Event date: 27/02/08 14:00 to 18:00Location: Room ASP 5G2, European Parliament, BrusselsThis workshop will bring together Members of the European Parliament, economists, academics and journalists as well as representatives of the European Commission to discuss the lessons that have to be drawn from the recent financial crisis caused by the US sub-prime mortgage market.With the view of the informal ECOFIN meeting in April which will look at the financial sector supervision and crisis management mechanisms, this workshop aims at debating a wide range of topics including:- how to improve the existing supervisory framework,- how to combat the opacity of financial markets and improve transparency requirements,- how to address the rating agencies' performance and conflict of interest,- what regulatory lessons are to be learnt in order to avoid a repetition of the sub-prime and the resulting credit crunch.PROGRAMME14:00 - 14:10 Opening remarks: Graham Watson, leader of the of the ALDE Group14:10 - 14:25 Keynote speech by Charlie McCreevy, Commissioner for the Internal Market and Services, European Commission14:25 - 14:40 Presentation by Daniel Daianu, MEP (ALDE) of his background paper14:40 - 15:30 Panel I: Current features of the financial systems and the main causes of the current international crisis.-John Purvis, MEP EPP-Eric De Keuleneer, Solvay Business School, Free University of Brussels-Nigel Phipps, Head of European Regulatory Affairs Moody's-Wolfgang Munchau, journalist Financial Times-Robert Priester, European Banking Federation (EBF), Head of Department Banking Supervision and Financial Markets-Ray Kinsella, Director of the Centre for Insurance Studies University College Dublin-Servaas Deroose, Director ECFIN.C, Macroeconomy of the euro area and the EU, European Commission-Leke Van den Burg, MEP PSE-David Smith, Visiting Professor at Derby Business School

Graph and download economic data for Dates of U.S. recessions as inferred by GDP-based recession indicator (JHDUSRGDPBR) from Q4 1967 to Q4 2024 about recession indicators, GDP, and USA.

This dataset accompanies the article: Hoyer, K., Zeisberger, S., Breugelmans, S. M., & Zeelenberg, M. (2021). Greed and individual trading behavior in experimental asset markets. Decision, 8(2), 80. Article abstract: Greed has been shown to be an important economic motive. Both the popular press as well as scientific articles have mentioned questionable practices by greedy bankers and investors as one of the root causes of the 2008 global financial crisis. In spite of these suggestions, there is as of yet no substantive empirical evidence for a contribution of greed to individual trading behavior. This article presents the result of 15 experimental asset markets in which we test the influence of greed on trading behavior. We do not find empirical support for the idea that greedier investors trade fundamentally differently from their less greedy counterparts in markets. These findings shed light on the role of greed in trading and the emergence of asset market bubbles in specific, and of the financial crisis in general. Directions for future research are discussed.

Abstract The objective of this study was to document the relationship between the two mechanisms of state action (credit earmarking and corporate control of banks) and the granting of bank credit in Brazil during the 2008 global financial crisis. There is an intense debate in the literature about the effectiveness of the State’s role in the financial system and its effects on the economy. One aspect of this issue is identifying whether the state presence contributes to stabilizing the granting of credit and softening financial crises’ economic impact. The studies carried out to date have not considered the differences between free and earmarked credits at the bank level, nor their possible interaction with the type of bank property. The study’s subject is relevant because it can help guide counter-cyclical public policies to face crises, including the use of changes in credit earmarking or state-owned banks’ performance. The analyses carried out can inform the debate about the pros and cons of the state’s presence in the credit market. The study analyses data from 2005 to 2012 from financial institutions that capture deposits from the public. Inferences are based on linear regression models, including a wide range of control variables. This study documents a significant reduction in credit granted by private banks in Brazil and state-owned banks’ expansion during the 2008 crisis. This evidence is not only due to differences in the funding rate during the period or to economic fundamentals, suggesting that the effect of corporate control is possibly related to the counter-cyclical performance of state-owned banks. The results show that the credit earmarking mechanisms were not particularly relevant in smoothing the contraction resulting from the financial crisis.