Many of the big winners included in the S&P 500 index from 2020 are companies firmly rooted in the technology sector. The obvious big winner is Tesla, whose share price increased by *** times for a variety of reasons. While the increase in Tesla stocks (arguably) does not have a direct connection to the global coronavirus (COVID-19) pandemic, a look at many of the other companies in this list indicates a clear link. Online retailers such as Amazon and Etsy saw large increases in their stock price, along with companies who provide crucial parts of infrastructure necessary for online shopping such as PayPal and FedEx. Given the closure of brick and mortar stores in many parts of the world due to the pandemic, the causation here is evident. Similarly, computer chip manufactures NVIDIA and AMD saw returns of 100 percent or more, likely due both to the shift to remote working necessitated by the pandemic, as well as the global increase in playing video games resulting from the unavailability of many other activities.

Everyone has looked at the stock market so I wasn't expecting to get excited about looking for patterns. But it's a good practice set to develop skills and learn new models. After working through a deep learning model, trying to predict the best-performing stocks of the next day, my most sophisticated model regressed toward the mean. I mean the exact mean. I was working with 446 stocks, training a model on the prior 30 days, and making a prediction on the next day. My model returned what it thought would be the best performing ten stocks, that I would then compare against the actual best performers. I ran the train/predict over 200 days, using six dense layers of 1,000 nodes on 100 epochs with EarlyStopping. When I calculated the mean of the predicted best 10's actual score, it was 223.04. I learned from this exercise that the yahoo data isn't predictive at the day-to-day scale and my best model was just flipping a coin. The Random Walk Hypothesis is the best explanation.

That's when I turned to another technique to try and make sense of the data. I had an intuitive hunch that when a stock starts to dive, there is an emotionally charged reaction, an irrational over-reaction, which will lead to a predictable rebound. Because my Keras model failed to produce results, I decided to spend some time answering the question: Is there a rebound after a dive? This isn't a complicated modeling technique. Instead of using data to predict an event, we choose an identifiable event and follow its performance forward. I chose the day's worst dive, but you could look for stocks that have consecutive days of growth, the day's best performer, stocks that lose 20% of their value over a 5 trading-day period, etc. Pick an event that you can define and describe and then look for it in the historical data. Look at your subset's performance against the rest of the market (ideally over the exact time window) and see if you can beat my 10X market growth!

I called my subset Unicorns because there were only 45 out of 1.3M records. They don't happen that often and nearly half lost value. But as a group, they showed a dependable rebound 10 and 20 days after the event. The most recent Unicorn was flagged on 4/14/21. Discovery (DISCA) was wrapped up in the Archegos bubble where this guy lost $20B in two days. Because it lost over half its value in the bubble, its relatively mild decline three weeks later put it in the Unicorn group. I'm not advocating a risky investment in a particular stock. Certainly, this one is unique because of its participation in an acute bubble. But the historical peers of this stock make it worth watching and doing some follow-up.

I have to give a shout-out to Bryan B. who continued to press at each dead end. The rebound isn't significant among all stocks, and he prompted the interest in comparing relative volatility. Special thanks to Ludo A. for playing mentor while I learned to code in Python. Happy pattern hunting!

As of November 14, 2021, all S&P 500 sector indices had recovered to levels above those of January 2020, prior to full economic effects of the global coronavirus (COVID-19) pandemic taking hold. However, different sectors recovered at different rates to sit at widely different levels above their pre-pandemic levels. This suggests that the effect of the coronavirus on financial markets in the United States is directly affected by how the virus has impacted various parts of the underlying economy. Which industry performed the best during the coronavirus pandemic? Companies operating in the information technology (IT) sector have been the clear winners from the pandemic, with the IT S&P 500 sector index sitting at almost ** percent above early 2020 levels as of November 2021. This is perhaps not surprising given this industry includes some of the companies who benefitted the most from the pandemic such as ************** and *******. The reason for these companies’ success is clear – as shops were shuttered and social gatherings heavily restricted due to the pandemic, online services such shopping and video streaming were in high demand. The success of the IT sector is also reflected in the performance of global share markets during the coronavirus pandemic, with tech-heavy NASDAQ being the best performing major market worldwide. Which industry performed the worst during the pandemic? Conversely, energy companies fared the worst during the pandemic, with the S&P 500 sector index value sitting below its early 2020 value as late as July 2021. Since then it has somewhat recovered, and was around ** percent above January 2020 levels as of October 2021. This reflects the fact that many oil companies were among the share prices suffering the largest declines over 2020. A primary driver for this was falling demand for fuel in line with the reduction in tourism and commuting caused by lockdowns all over the world. However, as increasing COVID-19 vaccination rates throughout 2021 led to lockdowns being lifted and global tourism reopening, demand has again risen - reflected by the recent increase in the S&P 500 energy index.

Comprehensive daily stock market data for 21 major S&P 500 companies across diverse sectors from 2020 to 2024.

This dataset contains daily stock data for 21 prominent companies in the S&P 500 index from January 1, 2020, to December 31, 2024. Covering a range of sectors including Technology, Healthcare, Energy, Financials, Consumer, Industrials, and Cloud/Software, this dataset offers a diverse view of market trends and performance over a five-year period.

Features Include:

Date: The trading day. Open: Opening price of the stock. High: Highest price during the trading day. Low: Lowest price during the trading day. Close: Closing price of the stock. Volume: Number of shares traded. Ticker: Stock symbol representing the company.

Sectors Covered:

Technology & AI: Apple (AAPL), Microsoft (MSFT), Alphabet (GOOGL), Amazon (AMZN), NVIDIA (NVDA), Taiwan Semiconductor (TSM). Healthcare: Johnson & Johnson (JNJ), UnitedHealth Group (UNH), Eli Lilly (LLY). Energy: ExxonMobil (XOM), NextEra Energy (NEE). Financial: JPMorgan Chase (JPM), Visa (V), BlackRock (BLK). Consumer: Walmart (WMT), Costco (COST), Procter & Gamble (PG). Industrial: Caterpillar (CAT), Honeywell (HON). Software/Cloud: Salesforce (CRM), ASML Holding (ASML).

This dataset is ideal for financial analysts, data scientists, and machine learning enthusiasts interested in exploring stock market trends, building predictive models, or conducting sector-based analysis over a significant time span.

Data Source: Retrieved using Yahoo Finance API, ensuring accuracy and reliability.

Usage: This dataset can be used for time-series analysis, machine learning predictions, financial modeling, and comparative studies across different sectors.

Feel free to download and explore the data, and share your findings with the community!

The value of the DJIA index amounted to ****** at the end of June 2025, up from ********* at the end of March 2020. Global panic about the coronavirus epidemic caused the drop in March 2020, which was the worst drop since the collapse of Lehman Brothers in 2008. Dow Jones Industrial Average index – additional information The Dow Jones Industrial Average index is a price-weighted average of 30 of the largest American publicly traded companies on New York Stock Exchange and NASDAQ, and includes companies like Goldman Sachs, IBM and Walt Disney. This index is considered to be a barometer of the state of the American economy. DJIA index was created in 1986 by Charles Dow. Along with the NASDAQ 100 and S&P 500 indices, it is amongst the most well-known and used stock indexes in the world. The year that the 2018 financial crisis unfolded was one of the worst years of the Dow. It was also in 2008 that some of the largest ever recorded losses of the Dow Jones Index based on single-day points were registered. On September 29, 2008, for instance, the Dow had a loss of ****** points, one of the largest single-day losses of all times. The best years in the history of the index still are 1915, when the index value increased by ***** percent in one year, and 1933, year when the index registered a growth of ***** percent.

This is not going to be an article or Op-Ed about Michael Jordan. Since 2009 we've been in the longest bull-market in history, that's 11 years and counting. However a few metrics like the stock market P/E, the call to put ratio and of course the Shiller P/E suggest a great crash is coming in-between the levels of 1929 and the dot.com bubble. Mean reversion historically is inevitable and the Fed's printing money experiment could end in disaster for the stock market in late 2021 or 2022. You can read Jeremy Grantham's Last Dance article here. You are likely well aware of Michael Burry's predicament as well. It's easier for you just to skim through two related videos on this topic of a stock market crash. Michael Burry's Warning see this YouTube. Jeremy Grantham's Warning See this YouTube. Typically when there is a major event in the world, there is a crash and then a bear market and a recovery that takes many many months. In March, 2020 that's not what we saw since the Fed did some astonishing things that means a liquidity sloth and the risk of a major inflation event. The pandemic represented the quickest decline of at least 30% in the history of the benchmark S&P 500, but the recovery was not correlated to anything but Fed intervention. Since the pandemic clearly isn't disappearing and many sectors such as travel, business travel, tourism and supply chain disruptions appear significantly disrupted - the so-called economic recovery isn't so great. And there's this little problem at the heart of global capitalism today, the stock market just keeps going up. Crashes and corrections typically occur frequently in a normal market. But the Fed liquidity and irresponsible printing of money is creating a scenario where normal behavior isn't occurring on the markets. According to data provided by market analytics firm Yardeni Research, the benchmark index has undergone 38 declines of at least 10% since the beginning of 1950. Since March, 2020 we've barely seen a down month. September, 2020 was flat-ish. The S&P 500 has more than doubled since those lows. Look at the angle of the curve: The S&P 500 was 735 at the low in 2009, so in this bull market alone it has gone up 6x in valuation. That's not a normal cycle and it could mean we are due for an epic correction. I have to agree with the analysts who claim that the long, long bull market since 2009 has finally matured into a fully-fledged epic bubble. There is a complacency, buy-the dip frenzy and general meme environment to what BigTech can do in such an environment. The weight of Apple, Amazon, Alphabet, Microsoft, Facebook, Nvidia and Tesla together in the S&P and Nasdaq is approach a ridiculous weighting. When these stocks are seen both as growth, value and companies with unbeatable moats the entire dynamics of the stock market begin to break down. Check out FANG during the pandemic. BigTech is Seen as Bullet-Proof me valuations and a hysterical speculative behavior leads to even higher highs, even as 2020 offered many younger people an on-ramp into investing for the first time. Some analysts at JP Morgan are even saying that until retail investors stop charging into stocks, markets probably don’t have too much to worry about. Hedge funds with payment for order flows can predict exactly how these retail investors are behaving and monetize them. PFOF might even have to be banned by the SEC. The risk-on market theoretically just keeps going up until the Fed raises interest rates, which could be in 2023! For some context, we're more than 1.4 years removed from the bear-market bottom of the coronavirus crash and haven't had even a 5% correction in nine months. This is the most over-priced the market has likely ever been. At the night of the dot-com bubble the S&P 500 was only 1,400. Today it is 4,500, not so many years after. Clearly something is not quite right if you look at history and the P/E ratios. A market pumped with liquidity produces higher earnings with historically low interest rates, it's an environment where dangerous things can occur. In late 1997, as the S&P 500 passed its previous 1929 peak of 21x earnings, that seemed like a lot, but nothing compared to today. For some context, the S&P 500 Shiller P/E closed last week at 38.58, which is nearly a two-decade high. It's also well over double the average Shiller P/E of 16.84, dating back 151 years. So the stock market is likely around 2x over-valued. Try to think rationally about what this means for valuations today and your favorite stock prices, what should they be in historical terms? The S&P 500 is up 31% in the past year. It will likely hit 5,000 before a correction given the amount of added liquidity to the system and the QE the Fed is using that's like a huge abuse of MMT, or Modern Monetary Theory. This has also lent to bubbles in the housing market, crypto and even commodities like Gold with long-term global GDP meeting many headwinds in the years ahead due to a demographic shift of an ageing population and significant technological automation. So if you think that stocks or equities or ETFs are the best place to put your money in 2022, you might want to think again. The crash of the OTC and small-cap market since February 2021 has been quite an indication of what a correction looks like. According to the Motley Fool what happens after major downturns in the market historically speaking? In each of the previous four instances that the S&P 500's Shiller P/E shot above and sustained 30, the index lost anywhere from 20% to 89% of its value. So what's what we too are due for, reversion to the mean will be realistically brutal after the Fed's hyper-extreme intervention has run its course. Of course what the Fed stimulus has really done is simply allowed the 1% to get a whole lot richer to the point of wealth inequality spiraling out of control in the decades ahead leading us likely to a dystopia in an unfair and unequal version of BigTech capitalism. This has also led to a trend of short squeeze to these tech stocks, as shown in recent years' data. Of course the Fed has to say that's its done all of these things for the people, employment numbers and the labor market. Women in the workplace have been set behind likely 15 years in social progress due to the pandemic and the Fed's response. While the 89% lost during the Great Depression would be virtually impossible today thanks to ongoing intervention from the Federal Reserve and Capitol Hill, a correction of 20% to 50% would be pretty fair and simply return the curve back to a normal trajectory as interest rates going back up eventually in the 2023 to 2025 period. It's very unlikely the market has taken Fed tapering into account (priced-in), since the euphoria of a can't miss market just keeps pushing the markets higher. But all good things must come to an end. Earlier this month, the U.S. Bureau of Labor Statistics released inflation data from July. This report showed that the Consumer Price Index for All Urban Consumers rose 5.2% over the past 12 months. While the Fed and economists promise us this inflation is temporary, others are not so certain. As you print so much money, the money you have is worth less and certain goods cost more. Wage gains in some industries cannot be taken back, they are permanent - in the service sector like restaurants, hospitality and travel that have been among the hardest hit. The pandemic has led to a paradigm shift in the future of work, and that too is not temporary. The Great Resignation means white collar jobs with be more WFM than ever before, with a new software revolution, different transport and energy behaviors and so forth. Climate change alone could slow down global GDP in the 21st century. How can inflation be temporary when so many trends don't appear to be temporary? Sure the price of lumber or used-cars could be temporary, but a global chip shortage is exasperating the automobile sector. The stock market isn't even behaving like it cares about anything other than the Fed, and its $billions of dollars of buying bonds each month. Some central banks will start to taper about December, 2021 (like the European). However Delta could further mutate into a variant that makes the first generation of vaccines less effective. Such a macro event could be enough to trigger the correction we've been speaking about. So stay safe, and keep your money safe. The Last Dance of the 2009 bull market could feel especially more painful because we've been spoiled for so long in the markets. We can barely remember what March, 2020 felt like. Some people sold their life savings simply due to scare tactics by the likes of Bill Ackman. His scare tactics on CNBC won him likely hundreds of millions as the stock market tanked. Hedge funds further gamed the Reddit and Gamestop movement, orchestrating them and leading the new retail investors into meme speculation and a whole bunch of other unsavory things like options trading at such scale we've never seen before. It's not just inflation and higher interest rates, it's how absurdly high valuations have become. Still correlation does not imply causation. Just because inflation has picked up, it doesn't guarantee that stocks will head lower. Nevertheless, weaker buying power associated with higher inflation can't be overlooked as a potential negative for the U.S. economy and equities. The current S&P500 10-year P/E Ratio is 38.7. This is 97% above the modern-era market average of 19.6, putting the current P/E 2.5 standard deviations above the modern-era average. This is just math, folks. History is saying the stock market is 2x its true value. So why and who would be full on the market or an asset class like crypto that is mostly speculative in nature to begin with? Study the following on a historical basis, and due your own due diligence as to the health of the markets: Debt-to-GDP ratio Call to put ratio

Nvidia Corporation is a multinational technology company headquartered in Santa Clara, California, United States. It was incorporated in Delaware,**United States in 1993**. Nvidia Corporation went public on January 22, 1999, and its shares began trading on NASDAQ Stock Market under the ticker symbol of NVDA. NVDA shares are also included as a component on several stock market indices, namely S&P 500, S&P 100 and NASDAQ-100. On November 6, 2020, NVDA stocks reached an all-time highest stock closing price of $582.48.

In 2002, Fortune magazine recognised Nvidia Corporation as the fastest-growing company in the US. NVDA entered in another acquisition in 2003 and bought-off MediaQ Inc. in a transaction of $70 million. Stanford Graduate School of Business Alumni Association named Nvidia Corporation as the Entrepreneurial Company of the Year in 2003. Nvidia GPUs powered all Academy Award Nominees in the category of Best Visual Effects 2010, which included Star Trek and Avatar.

In 2010, it also powered the world's fastest supercomputer at the time - China's Tianhe- 1A. The company made an acquisition in 2020 and purchased Mellanox Technologies, Ltd., a leading producer of networking products at the time, for a purchase price of $7 billion. As of 2021, the company has over 50 offices worldwide, including countries like Sweden, Denmark, Israel, Czech Republic, Poland, Russia, United Arab Emirates, Germany, France, Ukraine, Finland, Switzerland, and the United Kingdom, among others.

NVDA ranked 292nd on the list of Fortune 500 companies. It ranked 489th on Forbes' list of Global 2000 2020 companies. Forbes also included Nvidia Corporation in its 2020 rankings of World's Best Employers, America's Best Employers By State, and Best Employers for Diversity.

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Stocks of video game retailer GameStop exploded in January 2021, effectively doubling in value on a daily basis. At the close of trading on January 27, GameStop Corporation's stock price reaching 86.88 U.S. dollars per share - or +134 percent compared to the day before. On December 30, 2020, the price was valued at 4.82 U.S. dollars per share. The cause of this dramatic increase is a concerted effort via social media to raise the value of the company's stock, intended to negatively affect professional investors planning to ‘short sell’ GameStop shares. As professional investors started moving away from GameStop the stock price began to fall, stabilizing at around 11-13 U.S. dollars in mid-February. However, stock prices unexpectedly doubled again on February 24, and continued to rise, reaching 66.25 U.S. dollars at the close of trade on March 10. The reasons for this second increase are not fully clear. At the close of trade on January 29, 2025, GameStop shares were trading at nearly 27.5 U.S. dollars. Who are GameStop? GameStop are a retailer of video games and associated merchandise headquartered in a suburbs of Dallas, Texas, but with stores throughout North America, Europe, Australia and New Zealand. As of February 2020 the group maintained just over 5,500 stores, variously under the GameStop, EB Games, ThinkGeek, and Micromania-Zing brands. The company's main revenue source in 2020 was hardware and accessories - a change from 2019, when software sales were the main source of revenue. While the company saw success in the decade up to 2016 (owing to the constant growth of the video game industry), GameStop experienced declining sales since because consumers increasingly purchased video games digitally. It is this continual decline, combined with the effect of the global coronavirus pandemic on traditional retail outlets, that led many institutional investors to see GameStop as a good opportunity for short selling. What is short selling? Short selling is where an investor effectively bets on a the price of a financial asset falling. To do this, an investor borrows shares (or some other asset) via an agreement that the same number of shares be returned at a future date. They can then sell the borrowed shares, and purchase the same number back once the price has fallen to make a profit. Obviously, this strategy only works when the share price does fall – otherwise the borrowed stocks need to be repurchased at a higher price, causing a loss. In the case of GameStop, a deliberate campaign was arranged via social media (particularly Reddit) for individuals to purchase GameStop shares, thus driving the price higher. As a result, some estimates place the loss to institutional investors in January 2021 alone at around 20 billion U.S. dollars. However, once many of these investors had 'closed out' their position by returning the shares they borrowed, demand for GameStop stock fell, leading to the price reduction seen early in early February. A similar dynamic was seen at the same time with the share price of U.S. cinema operator AMC.

Some of the most sought-after stocks come with a hefty price tag and many of us equate value with price. The higher the price, the more valuable and, therefore, the more desirable a company becomes. The average investor may not be able to afford a single share of the highest prices stocks from the following companies.

But remember, a high stock price in and of itself does not equal a company's total market value - that is determined by the market capitalization or the number of shares outstanding multiplied by the share price. A company's stock price is not useful without knowing how many shares there are. For instance, a company with ten shares at $1 million each would certainly have a high share price, giving a total value of $10 million. Another company may have ten million shares at just $200 a piece, but it would be worth $2 billion.

Retail investors need to know which stocks may be difficult to trade because of their high per-share price. It's also worth noting that not all brokers offer their clients the option to purchase fractional shares, making even these high-flyers accessible.

Here's a list of the top five highest-priced stocks that trade in the US, in the last decade, excluding those sold only on over-the-counter (OTC) markets.

View monthly updates and historical trends for S&P 500 Monthly Return. from United States. Source: Standard and Poor's. Track economic data with YCharts a…

In just *** week in March 2020, investors with a short position on Tesla stock were able to generate profits of over *** billion U.S. dollars. From around mid-February 2020, the global coronavirus (COVID-19) pandemic sent global stock markets into a tailspin as entire countries closed down their economy in order to slow the spread of the virus. While the effect on financial markets was catastrophic for many most investors, once class of investor was able to profit handsomely off the disaster - short sellers. Short selling is a process whereby investors effectively borrow a certain number of shares for a period of time, with the aim of selling them when the price is high, then repurchasing at a lower price in order to return them.

Context

This dataset is helpful for those interested in daily market share values changes of Amazon, Apple, Google, Microsoft, and Tesla from mid-2010 to mid-2020.

Content

This dataset contains daily OPEN, CLOSE, VOLUME, HIGH, and LOW values of Amazon, Apple, Google, Microsoft, and Tesla companies as tagged by dates.

Acknowledgements

Values are fetched from the official NASDAQ website.

Photo by Maxim Hopman on Unsplash.

Introduction

According to Economatica, a company specializing in the Latin American stock market, the Brazilian stock exchange market, governed by Brasil, Bolsa, Balcão (B3), exchanged BRL ~25.9 billion per day in the first half of 2020, during the coronavirus epidemic. Furthermore, it is estimated that in this same period there was an 18% growth in the number of Brazilian investors, totaling ~2.6 million active investors. Therefore, the financial market moves a large amount of values and, consequently, produces a vast amount of information and data daily; These data represent the movements of shares, their respective prices, dollar exchange values, and so on. This dataset contains daily stock values and information about their companies.

Inspiration

• Data Analysis - Spark
• Price Prediction - Regression task
• Best Group of Stocks - Association Rules task

This dataset provides an environment (Data Warehouse-like) for analysis and visualization of financial business for users of decision support systems. Specifically, the data allow compare different assets (i.e. stocks) listed on B3, according to the sectors of the economy in which these assets operate. For example, with this Data Warehouse, the user will be able to answer questions similar to this one: What are the most profitable sectors for investment in a given period of time? In this way, the user can identify which are the sectors that are standing out, as well as which are the most profitable companies in the sector.

Dataset

https://i.imgur.com/28Mf0sN.png" alt="Data Warehouse">

This dataset is split into five files: - dimCoin.csv - Dimension table with information about the coins. - dimCompany.csv - Dimension table with information about the companies. - dimTime.csv - Dimension table with information about the datetime. - factCoins.csv - Fact table with coin value over time. - factStocks.csv - Fact table with stock prices over time.

Source

The data were available by B3. You can access in https://www.b3.com.br/en_us/market-data-and-indices/ .I just structure and model the data as Data Warehouse tables. You can access my code in https://github.com/leomaurodesenv/b3-stock-indexes

FAANG

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• FAANG is an acronym referring to the stocks of the five most popular and best-performing American technology companies: Meta (formerly known as Facebook), Amazon, Apple, Netflix, and Alphabet (formerly known as Google).

• In addition to being widely known among consumers, the five FAANG stocks are among the largest companies in the world, with a combined market capitalization of nearly $7.1 trillion as of Aug. 19, 2021.

• Some have raised concerns that the FAANG stocks may be in the midst of a bubble, whereas others argue that their growth is justified by the stellar financial and operational performance they have shown in recent years.

Each of the FAANG stocks trades on the Nasdaq exchange and is included in the S&P 500 Index. Since the S&P 500 is a broad representation of the market, the movement of the market mirrors the index's movement. As of August 2021, the FAANGs make up about 19% of the S&P 500—a staggering figure considering the S&P 500 is generally viewed as a proxy for the United States economy as a whole.

This large influence over the index means that volatility in the stock price of the FAANG stocks can have a substantial effect on the performance of the S&P 500 in general. In August 2018, for example, FAANG stocks were responsible for nearly 40% of the index’s gain from the lows reached in February 2018.

What Makes FAANG Stocks So Popular?

• The five stocks that make up the “FAANG” acronym - Meta (FB), Amazon (AMZN), Apple (AAPL), Netflix (NFLX), and Alphabet (GOOG) are all well-known brands among consumers. But they are also famous for their remarkable growth in recent years, with market capitalizations ranging from $240 billion (in the case of Netflix)3 to $2.4 trillion (in the case of Apple), as of August 2021.

• From an investment perspective, these five stocks are generally praised for their stellar historical track records and clear leadership positions within their industries.

Datset Information

The dataset consists of the historical stock prices of the FAANG companies. The dataset has been cleaned and uploaded for easy use and analysis.

• Google Class A(GOOGL) consists of 4340 data records of stock prices starting from 20/08/2004 to date(11/11/2021)
• Google Class C(GOOG) consists of 1924 records of GOOG stocks starting from 28/03/2004 to date.
• Apple (AAPL) consists of 10319 records starting from 12/12/1980 to date
• Amazon(AMZN) consists of 6167 records starting from 15/5/1997 to date
• Meta(FB) consists of 2389 records from 18/05/2012 records to date
• Netflix(NFLX) consists of 4904 records from 24/05/2002 to date

Note:

You might find two different types of google stocks GOOGL and GOOG in the dataset.

• GOOGL

  • GOOGL shares are categorized as Class A shares. Class A shares are known as common shares. They give investors an ownership stake and, typically, voting rights. They are the most common type of shares.

• GOOG

  • GOOG shares are the company's Class C shares. Class C shares give stockholders an ownership stake in the company, just like Class A shares, but unlike common shares, they do not confer voting rights to shareholders.

Class A: Held by a regular investor with regular voting rights (GOOGL) Class B: Held by the founders with 10 times the voting power compared to Class A Class C: No voting rights, normally held by employees and some Class A stockholders (GOOG)

Inspiration

• Annual growth rate of FAANG companies
• Forecast the growth rate of FAANG companies in the next ten years
• Exploratory data analysis

Context

According to Investopedia:

FAANG is an acronym referring to the stocks of the five most popular and best-performing American technology companies: Facebook, Amazon, Apple, Netflix and Alphabet (formerly known as Google). In addition to being widely known among consumers, the five FAANG stocks are among the largest companies in the world, with a combined market capitalization of over $4.1 trillion as of January 2020. Some have raised concerns that the FAANG stocks may be in the midst of a bubble, whereas others argue that their growth is justified by the stellar financial and operational performance they have shown in recent years.

Regardless of the myriad of accolades, comments, and even controversies surrounding the FAANG stocks, they are nevertheless a data science/mining treasure and the bellwether of the NASDAQ index, if not the entire US technology sector.

This Kaggle dataset contains over 20 years of daily historical data for the five FAANG constituents, as retrieved from this free stock API. It is a public-domain dataset that gives the data science practitioners (a.k.a., you!) the full flexibility to derive second-order insights and investment heuristics from it.

Content

Over 20 years of daily historical data (2000-01-01 to 2020-10-01) for the five FAANG stocks: Facebook, Amazon, Apple, Netflix, and Alphabet/Google. For completeness, both raw and adjusted prices are included, along with historical split events and dividend payouts (check out here for how stock market API providers perform price adjustments).

Acknowledgements

Data source: https://www.alphavantage.co/

China's main stock market index, the SHANGHAI, fell to 3898 points on December 2, 2025, losing 0.42% from the previous session. Over the past month, the index has declined 1.98%, though it remains 15.36% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from China. China Shanghai Composite Stock Market Index - values, historical data, forecasts and news - updated on December of 2025.

Context

If you are satisfied in data and code, please upvote :)👍 The investing is necessary for everyone's future. I think that just knowing the meaning of the variables without interpreting this dataset is enough to study. This data is google trends of stock (Dow, S&P500 index, Nasdaq index to update later) from pytrends (It is not official). Contains value of trend's result normalized as date of about 1 year (2020-06-14, 2021-06-06).

The data format is received as json and can be used as a data frame. The script used can be checked at Github repository and if you want longer time scale data or up-to-date data, please run the script from the link. And also, if you want to compare stock's recent price, you should check this data set and refer to the Notebook.

If you interest this data and code, Pleases see notebooks of strategy :)

I'm still learning Python, so if you find messy code execution or have a better way of doing it, let me know!! and Please contact me :) I think it will be a good study.

Content

• In Trend_sp500.json It is presented that trend of google to be normalized by index of S&P500

• In Trend_dow.json. It is presented that trend of google to be normalized by index of Dow

All data is presented recently. If you want the statements before, Pleases check and fix below code.

Acknowledgements

I'm studying physics and writing code of python and c++. However I'm not used to it yet and also English :(. Let you know if it is not correctly for code and English :🙏

Inspiration

It is funning model comparing trend of google if it has correlation or not.

This data is highly likely to be used for various analyzes, and it is considered to be basic data for understanding the stock's market. Let's study together and find the best model!

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Egypt: Stock market capitalization w/o top 10 firms, percent of total market cap: The latest value from 2020 is 55 percent, an increase from 33 percent in 2019. In comparison, the world average is 47.89 percent, based on data from 28 countries. Historically, the average for Egypt from 2004 to 2020 is 51.51 percent. The minimum value, 33 percent, was reached in 2019 while the maximum of 60.58 percent was recorded in 2009.

While the global coronavirus (COVID-19) pandemic caused all major stock market indices to fall sharply in March 2020, both the extent of the decline at this time, and the shape of the subsequent recovery, have varied greatly. For example, on March 15, 2020, major European markets and traditional stocks in the United States had shed around ** percent of their value compared to January *, 2020. However, Asian markets and the NASDAQ Composite Index only shed around ** to ** percent of their value. A similar story can be seen with the post-coronavirus recovery. As of November 14, 2021 the NASDAQ composite index value was around ** percent higher than in January 2020, while most other markets were only between ** and ** percent higher. Why did the NASDAQ recover the quickest? Based in New York City, the NASDAQ is famously considered a proxy for the technology industry as many of the world’s largest technology industries choose to list there. And it just so happens that technology was the sector to perform the best during the coronavirus pandemic. Accordingly, many of the largest companies who benefitted the most from the pandemic such as Amazon, PayPal and Netflix, are listed on the NADSAQ, helping it to recover the fastest of the major stock exchanges worldwide. Which markets suffered the most? The energy sector was the worst hit by the global COVID-19 pandemic. In particular, oil companies share prices suffered large declines over 2020 as demand for oil plummeted while workers found themselves no longer needing to commute, and the tourism industry ground to a halt. In addition, overall share prices in two major stock exchanges – the London Stock Exchange (as represented by the FTSE 100 index) and Hong Kong (as represented by the Hang Seng index) – have notably recovered slower than other major exchanges. However, in both these, the underlying issue behind the slower recovery likely has more to do with political events unrelated to the coronavirus than it does with the pandemic – namely Brexit and general political unrest, respectively.

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Mastercard Inc. (stylized as MasterCard from 1979 to 2016 and MasterCard since 2016) is an American multinational financial services corporation headquartered in the Mastercard International Global Headquarters in Purchase, New York. The Global Operations Headquarters is located in O'Fallon, Missouri, a municipality of St. Charles County, Missouri. Throughout the world, its principal business is to process payments between the banks of merchants and the card-issuing banks or credit unions of the purchasers who use the "Mastercard" brand debit, credit, and prepaid cards to make purchases. Mastercard Worldwide has been a publicly traded company since 2006. Prior to its initial public offering, Mastercard Worldwide was a cooperative owned by the more than 25,000 financial institutions that issue its branded cards.

Mastercard, originally known as Interbank from 1966 to 1969 and Master Charge from 1969 to 1979, was created by an alliance of several regional bank card associations in response to the BankAmericard issued by Bank of America, which later became the Visa credit card issued by Visa Inc.

Mastercard is one of the best performing stocks of the decade of 2011-2020