The price of Meta (former Facebook) shares traded on the Nasdaq stock exchange fluctuated significantly but increased overall during the period from May 2012 to January 2025. After peaking at ****** U.S. dollars per share in August 2021, the price of Meta shares started to fluctuate and exceeded its previous peak in 2025. The share price stood at ****** U.S. dollars as of the end of January 2025. Substantial fluctuations in the last few years Meta's stock prices have fluctuated particularly after the rebranding announcement in late 2021. Following the announcement and through 2022, Meta's revenue remained rather stagnant, and its net income decreased considerably. Moreover, the tech giant announced one of the industry's largest layoffs in late 2022. As a result, the share price hit a low of ***** U.S. dollars in October 2022, the lowest value observed since 2016. However, Meta's share price has been steadily recovering since then. Shift in strategy for the world’s first social network Meta has shifted its focus to the metaverse, virtual reality (VR), and augmented reality (AR), with the rebranding in late 2021. As a result, Reality Labs was established as a dedicated business and research unit to focus on developing metaverse and AR/VR technologies. However, as of early 2023, Meta still relies mainly on advertising and its Family of Apps to generate most of its revenue, despite having made significant investments in virtual reality. Reality Labs generated *** billion U.S. dollars in revenue in 2024 and has been consistently incurring operating losses since 2019.

This dataset contains the historical stock data for Meta Platforms Inc. (META), formerly known as Facebook Inc., sourced from Yahoo Finance, spanning from its initial public offering (IPO) on May 18, 2012 through to December 2024. The data includes daily stock prices and provides essential details such as:

Date: The specific trading date for each record. Open: The opening price of Meta’s stock for that day. High: The highest price reached by Meta’s stock on that day. Low: The lowest price of Meta’s stock on that day. Close: The closing price for Meta’s stock on that day. Adj Close: The adjusted closing price, accounting for stock splits, dividends, and other corporate actions. Volume: The number of shares traded on that particular day. This dataset is ideal for those interested in analyzing the financial journey of Meta Platforms, from its early days as a social media giant to its transformation into a broader technology company focused on virtual reality, artificial intelligence, and the "Metaverse." It can be used for time series analysis, stock price prediction, and financial modeling.

Source: The data has been sourced from Yahoo Finance, a trusted platform for obtaining accurate and reliable historical financial data.

Data Usage:

Time Series Analysis: Analyze Meta’s stock price trends and market behavior over time. Stock Price Prediction: Build predictive models to forecast Meta’s future stock price movements based on historical data. Financial Analysis: Perform detailed analysis of Meta’s stock performance, volatility, and market impact as it evolved from a social network to a global tech leader.

Context

Facebook is a company that literally every kid is aware of. Its a household name. People from various age groups are there on this social media website. It has helped many in connecting with different people and also has helped some of the investors by earning them a good amount of money. This data set contains the details of the stock of Facebook Inc.

Content

This data set has 7 columns with all the necessary values such as opening price of the stock, the closing price of it, its highest in the day and much more. It has date wise data of the stock starting from 2012 to 2020(August).

Context

Time series modelling for the prediction of stocks prices is a challenging task. Political events, market expectations and economic factors are just a few known factors that can impact financial market behaviour. The financial market is a complex, noisy, evolutionary and chaotic field of study that attracts many enthusiasts and researches — the first, usually driven by the economic benefit of it, the latter, inspired by the challenge of handling such complex data.

This project aims to predict Facebook (FB) next day stock price direction with machine learning algorithms. Technical indicators and global market indexes are used, and their influence on the forecast accuracy is analysed.

Content

Daily values were retrieved (volume, open, close, low and high prices) from Yahoo! Finance website. For Facebook (FB), July 2012 was the earliest data available. The date range is July 2012 to November 2018.

The closing price of current day C(t) and closing price from the previous day C(t-1) are compared to build the initial dataset. The objective is to define if the price trend is going up or down by analysing these two values. For each instance, a comparison was made and recorded. If the price is going up, C(t) > C(t-1), class “1” is assigned. Class “0” is assigned for the opposite case.

• ID: Sample ID
• Close: Closing value of previous day
• Low: Lowest value of previous day
• High: Highest value of previous day
• Volume: Volume value of previous day

Research was initiated to understand which features could help the model to forecast the stock direction. Three main routes were found: Lag features, Technical Indicators and Global Market Indexes. Below is an explanation of each group of features.

Lag features are features that contain the closing price and direction of previous days and it is a common strategy for Time Series models. The following features were added:

• C(t-5): Closing price of 5 days before
• C(t-4): Closing price of 4 days before
• C(t-3): Closing price of 3 days before
• C(t-2): Closing price of 2 days before
• C_up_4: Output 1 if closing price went up 4 days ago
• C_up_3: Output 1 if closing price went up 3 days ago
• C_up_2: Output 1 if closing price went up 2 days ago
• C_up_1: Output 1 if closing price went up 1 day ago

Technical indicators are used by researches and financial market analysts to support stock market trend forecasting. Common indicators retrieved from the literature were selected and calculated for Facebook stock. Techical Indicators added:

• MA-10: Moving Average considering previous 10 days
• MA-5: Moving Average considering previous 5 days
• WMA-10: Weighted Moving Average considering previous 10 days
• SO: Stochastic Oscillator
• M: Momentum as the difference in closing price in a 10 days interval
• SSO: Slow Stochastic Oscillator
• EMA: Exponential Moving Average for a 10 day period
• MACD_Sline_9: MACD Signal Line for a 9 day period
• RSI: Relative Strength Index
• CCI: Commodity Channel Index
• ADO: Accumulation Distribution Oscillator

Technical indicators provide a suggestion of the stock price movement. Additional features were created for each technical indicator by analysing its daily value and assigning a class according to their meaning. Class “1” is given if the indicator numerical value suggests upper trend, class “0” for a downtrend. In other words, financial market analysis is performed at a simplistic level, in the attempt to translate what the continuous value means.

• MA-10>C: If MA-10 is higher than Closing price output 1
• MA-5>C: If MA-5 is higher than Closing price output 1
• WMA-10>C: If WMA-10 is higher than Closing price output 1
• SO>SOt-1: Output is 1 if SO current value is higher than previous day
• M>0: A positive momentum outputs 1
• SSO>SSOt-1: SSO current value is higher than previous day
• EMA>C: If EMA is higher than Closing price output 1
• MACD>MACDt-1: If MACD current value is higher than previous day output 1
• RSI70-30: If RSI is above 70, output 0. Values below 30 output is one. For values within this range it compares to previous day and outputs 1 if value has increased
• CCI200-200: Similar to RSI, but if threshold set for 200 and -200.
• ADO>ADOt-1: Output is 1 if ADO current value is higher than previous day

For a given country or region, the stock market index characterises the performance of its financial market and the overall local economy. For this reason, the same day performance of these markets could contribute to the machine learning model predictions. Six global indexes were added as features, with their closing direction as up or down, class “1” or “0”, respectively. Data for these indexes (Nikkei, Hang Seng, All Ordinaries, Euronext 100, SSE and DAX) were also retrieved from Yahoo! Finance.

Iran Consumer Price Index (CPI): Urban: FB: Fats and Oils data was reported at 568.500 Apr2004-Mar2005=100 in Dec 2012. This records an increase from the previous number of 560.000 Apr2004-Mar2005=100 for Nov 2012. Iran Consumer Price Index (CPI): Urban: FB: Fats and Oils data is updated monthly, averaging 199.100 Apr2004-Mar2005=100 from Apr 2007 (Median) to Dec 2012, with 69 observations. The data reached an all-time high of 568.500 Apr2004-Mar2005=100 in Dec 2012 and a record low of 129.600 Apr2004-Mar2005=100 in Apr 2007. Iran Consumer Price Index (CPI): Urban: FB: Fats and Oils data remains active status in CEIC and is reported by Central Bank of the Islamic Republic of Iran. The data is categorized under Global Database’s Iran – Table IR.I005: Consumer Price Index: April 04-March 05=100: Urban.

ABSTRACT Increasing globalization has meant the internet becoming ever more part of the routine of people around the world. With the evolution of the internet, social networks have emerged in order to facilitate communication between people, communities and even between corporations. Social networks offer companies a way of instantly releasing information, allowing those who use this information greater flexibility when searching for news about the companies in which they have invested or wish to invest. In this context, the objective of this study was to analyze how social networks (Facebook, Twitter and Youtube) affect levels of information asymmetry and the pricing of shares for Brazilian and U.S. public companies during 2012. To achieve the proposed goal, the conceptual framework of the Ohlson model (1995) was used to verify whether the information posted on social networks affects the pricing of shares, and share price volatility was used as a proxy for information asymmetry. The sample included 170 Brazilian companies listed on the BM&FBOVESPA and 100 companies listed on the U.S. stock market in 2012. The results show that social networks can affect levels of information asymmetry in these markets, but only "unofficial" Facebook affects the pricing of shares for companies in the Brazilian stock market, although sensitivity analysis indicated that the groups that use and those that do not use Facebook do not exhibit different average returns. Thus, investors should not use this information to devise strategies to generate better returns.

Stock Market Analysis of Meta Platforms, Inc. (META) from it's Founding / Listing Years which is 2012 to 2022

Data Dictionary

About Meta Platforms, Inc. (META)

Meta Platforms, Inc., doing business as Meta and formerly named Facebook, Inc., and TheFacebook, Inc., is an American multinational technology conglomerate based in Menlo Park, California. The company owns Facebook, Instagram, and WhatsApp, among other products and services. Meta is one of the world's most valuable companies. It is considered one of the Big Five American information technology companies, alongside Alphabet, Amazon, Apple, and Microsoft.

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Iran Consumer Price Index (CPI): Urban: FB: Fruit and Nut data was reported at 422.600 Apr2004-Mar2005=100 in Dec 2012. This records an increase from the previous number of 398.200 Apr2004-Mar2005=100 for Nov 2012. Iran Consumer Price Index (CPI): Urban: FB: Fruit and Nut data is updated monthly, averaging 249.200 Apr2004-Mar2005=100 from Apr 2007 (Median) to Dec 2012, with 69 observations. The data reached an all-time high of 492.900 Apr2004-Mar2005=100 in Jun 2012 and a record low of 149.200 Apr2004-Mar2005=100 in Sep 2007. Iran Consumer Price Index (CPI): Urban: FB: Fruit and Nut data remains active status in CEIC and is reported by Central Bank of the Islamic Republic of Iran. The data is categorized under Global Database’s Iran – Table IR.I005: Consumer Price Index: April 04-March 05=100: Urban.

Iran Consumer Price Index (CPI): Urban: FB: Dairy Products and Eggs data was reported at 455.600 Apr2004-Mar2005=100 in Dec 2012. This records a decrease from the previous number of 463.600 Apr2004-Mar2005=100 for Nov 2012. Iran Consumer Price Index (CPI): Urban: FB: Dairy Products and Eggs data is updated monthly, averaging 192.500 Apr2004-Mar2005=100 from Apr 2007 (Median) to Dec 2012, with 69 observations. The data reached an all-time high of 463.600 Apr2004-Mar2005=100 in Nov 2012 and a record low of 129.500 Apr2004-Mar2005=100 in Jun 2007. Iran Consumer Price Index (CPI): Urban: FB: Dairy Products and Eggs data remains active status in CEIC and is reported by Central Bank of the Islamic Republic of Iran. The data is categorized under Global Database’s Iran – Table IR.I005: Consumer Price Index: April 04-March 05=100: Urban.

Each company has it's own story behind their success. Here I just want to introduce when they came in the market for the time and issue first IPO.

IPO Term:- An initial public offering (IPO) refers to the process of offering shares of a private corporation to the public in a new stock issuance for the first time. An IPO allows a company to raise equity capital from public investors.

Meta:- Facebook (FB), now Meta Platforms, Inc. (META), went public with its initial public offering (IPO) on May 18, 2012. The popular social networking company had one of the largest and most anticipated IPOs in history. On that day, FB shares closed at $38.23, slightly above the $**38.00** IPO price.

Amazon:- Amazon went public on May 15, 1997, and the IPO price was $18.00, or $0.075 adjusted for the stocks splits that occurred on June 2, 1998 (2-for-1 split), January 5, 1999 (3-for-1 split), and September 1, 1999 (2-for-1 split), and June 3, 2022 (20-for-1 split).

Apple:- Apple went public on **December 12, 1980 at $22.00 **per share. The stock has split five times since the IPO, so on a split-adjusted basis the IPO share price was $.10. The stock split on a 4-for-1 basis on August 28, 2020, a 7-for-1 basis on June 9, 2014, and split on a 2-for-1 basis on February 28, 2005, June 21, 2000, and June 16, 1987.

Netflix:- Since its initial public offering (IPO) in May 23, 2002, NFLX's stock price has skyrocketed. Consider this: Netflix currently has a market capitalization of $101 billion, compared to $3 billion in January 2010.

Google:- Google, now known as Alphabet Inc. Finally held its highly anticipated IPO in 2004, six years after it was founded. The company had already become a search juggernaut by that time, and IPO shares were priced at $85 per share for a valuation of $23 billion.

Column Description Of Each File

• Date: Trading Date
• Open: Opening Price
• High: It shows that maximum price during the day
• Low: It shows that minimum price during the day
• Close: close price adjust for calls
• Close : close price adjusted for splits
• Adj Close : adjusted close price adjusted for both dividends and splits.
• Volume : the number of shares that changed hands during a given day

India Consumer Price Index (CPI): 2012=100: Urban: FB: Spices data was reported at 141.000 2012=100 in Oct 2018. This records a decrease from the previous number of 141.200 2012=100 for Sep 2018. India Consumer Price Index (CPI): 2012=100: Urban: FB: Spices data is updated monthly, averaging 125.000 2012=100 from Jan 2011 (Median) to Oct 2018, with 94 observations. The data reached an all-time high of 145.500 2012=100 in Dec 2016 and a record low of 98.400 2012=100 in Jul 2012. India Consumer Price Index (CPI): 2012=100: Urban: FB: Spices data remains active status in CEIC and is reported by Central Statistics Office. The data is categorized under Global Database’s India – Table IN.IA005: Consumer Price Index: 2012=100: Urban.

Iran Consumer Price Index (CPI): Urban: Food and Beverages (FB) data was reported at 476.400 Apr2004-Mar2005=100 in Dec 2012. This records an increase from the previous number of 465.300 Apr2004-Mar2005=100 for Nov 2012. Iran Consumer Price Index (CPI): Urban: Food and Beverages (FB) data is updated monthly, averaging 222.600 Apr2004-Mar2005=100 from Apr 2007 (Median) to Dec 2012, with 69 observations. The data reached an all-time high of 476.400 Apr2004-Mar2005=100 in Dec 2012 and a record low of 144.300 Apr2004-Mar2005=100 in Aug 2007. Iran Consumer Price Index (CPI): Urban: Food and Beverages (FB) data remains active status in CEIC and is reported by Central Bank of the Islamic Republic of Iran. The data is categorized under Global Database’s Iran – Table IR.I005: Consumer Price Index: April 04-March 05=100: Urban. Rebased from 2004-05=100 to 2011-12=100 Replacement series ID: 286591704

India Consumer Price Index (CPI): 2012=100: Urban: FB: Cereals and Products data was reported at 137.500 2012=100 in Oct 2018. This records an increase from the previous number of 137.000 2012=100 for Sep 2018. India Consumer Price Index (CPI): 2012=100: Urban: FB: Cereals and Products data is updated monthly, averaging 123.700 2012=100 from Jan 2011 (Median) to Oct 2018, with 94 observations. The data reached an all-time high of 137.500 2012=100 in Oct 2018 and a record low of 93.200 2012=100 in Jun 2011. India Consumer Price Index (CPI): 2012=100: Urban: FB: Cereals and Products data remains active status in CEIC and is reported by Central Statistics Office. The data is categorized under Global Database’s India – Table IN.IA005: Consumer Price Index: 2012=100: Urban.

India Consumer Price Index (CPI): 2012=100: Urban: FB: Egg data was reported at 137.800 2012=100 in Nov 2018. This records an increase from the previous number of 133.500 2012=100 for Oct 2018. India Consumer Price Index (CPI): 2012=100: Urban: FB: Egg data is updated monthly, averaging 119.500 2012=100 from Jan 2011 (Median) to Nov 2018, with 95 observations. The data reached an all-time high of 146.700 2012=100 in Nov 2017 and a record low of 82.300 2012=100 in May 2011. India Consumer Price Index (CPI): 2012=100: Urban: FB: Egg data remains active status in CEIC and is reported by Central Statistics Office. The data is categorized under Global Database’s India – Table IN.IA005: Consumer Price Index: 2012=100: Urban.

India Consumer Price Index (CPI): 2012=100: Urban: FB: Pulses and Products data was reported at 113.300 2012=100 in Oct 2018. This records a decrease from the previous number of 113.500 2012=100 for Sep 2018. India Consumer Price Index (CPI): 2012=100: Urban: FB: Pulses and Products data is updated monthly, averaging 113.400 2012=100 from Jan 2011 (Median) to Oct 2018, with 94 observations. The data reached an all-time high of 191.600 2012=100 in Nov 2015 and a record low of 89.700 2012=100 in Jan 2011. India Consumer Price Index (CPI): 2012=100: Urban: FB: Pulses and Products data remains active status in CEIC and is reported by Central Statistics Office. The data is categorized under Global Database’s India – Table IN.IA005: Consumer Price Index: 2012=100: Urban.

India Consumer Price Index (CPI): 2012=100: Urban: Food and Beverages (FB) data was reported at 139.400 2012=100 in Oct 2018. This records an increase from the previous number of 138.900 2012=100 for Sep 2018. India Consumer Price Index (CPI): 2012=100: Urban: Food and Beverages (FB) data is updated monthly, averaging 125.000 2012=100 from Jan 2011 (Median) to Oct 2018, with 94 observations. The data reached an all-time high of 141.500 2012=100 in Nov 2017 and a record low of 89.200 2012=100 in Mar 2011. India Consumer Price Index (CPI): 2012=100: Urban: Food and Beverages (FB) data remains active status in CEIC and is reported by Central Statistics Office. The data is categorized under Global Database’s India – Table IN.IA005: Consumer Price Index: 2012=100: Urban.

India Consumer Price Index (CPI): 2012=100: Urban: FB: Milk and Milk Product data was reported at 141.500 2012=100 in Oct 2018. This stayed constant from the previous number of 141.500 2012=100 for Sep 2018. India Consumer Price Index (CPI): 2012=100: Urban: FB: Milk and Milk Product data is updated monthly, averaging 124.750 2012=100 from Jan 2011 (Median) to Oct 2018, with 94 observations. The data reached an all-time high of 141.500 2012=100 in Oct 2018 and a record low of 83.400 2012=100 in Jan 2011. India Consumer Price Index (CPI): 2012=100: Urban: FB: Milk and Milk Product data remains active status in CEIC and is reported by Central Statistics Office. The data is categorized under Global Database’s India – Table IN.IA005: Consumer Price Index: 2012=100: Urban.

India Consumer Price Index (CPI): 2012=100: Rural: FB: Fruits data was reported at 143.500 2012=100 in Nov 2018. This records a decrease from the previous number of 144.500 2012=100 for Oct 2018. India Consumer Price Index (CPI): 2012=100: Rural: FB: Fruits data is updated monthly, averaging 129.700 2012=100 from Jan 2011 (Median) to Nov 2018, with 95 observations. The data reached an all-time high of 157.500 2012=100 in May 2018 and a record low of 84.100 2012=100 in Jan 2011. India Consumer Price Index (CPI): 2012=100: Rural: FB: Fruits data remains active status in CEIC and is reported by Central Statistics Office. The data is categorized under Global Database’s India – Table IN.IA003: Consumer Price Index: 2012=100: Rural.

Mexico PPI: Weights: TA: FB: Self-Service Restaurants, Takeaways & Others data was reported at 0.469 % in 2018. This stayed constant from the previous number of 0.469 % for 2017. Mexico PPI: Weights: TA: FB: Self-Service Restaurants, Takeaways & Others data is updated yearly, averaging 0.469 % from Dec 2012 (Median) to 2018, with 7 observations. The data reached an all-time high of 0.469 % in 2018 and a record low of 0.469 % in 2018. Mexico PPI: Weights: TA: FB: Self-Service Restaurants, Takeaways & Others data remains active status in CEIC and is reported by National Institute of Statistics and Geography. The data is categorized under Global Database’s Mexico – Table MX.I043: Producer Price Index: Jun2012=100: Weights.

India Consumer Price Index (CPI): 2012=100: Rural: FB: Spices data was reported at 140.800 2012=100 in Nov 2018. This records an increase from the previous number of 139.500 2012=100 for Oct 2018. India Consumer Price Index (CPI): 2012=100: Rural: FB: Spices data is updated monthly, averaging 116.000 2012=100 from Jan 2011 (Median) to Nov 2018, with 95 observations. The data reached an all-time high of 140.800 2012=100 in Nov 2018 and a record low of 91.300 2012=100 in Jan 2011. India Consumer Price Index (CPI): 2012=100: Rural: FB: Spices data remains active status in CEIC and is reported by Central Statistics Office. The data is categorized under Global Database’s India – Table IN.IA003: Consumer Price Index: 2012=100: Rural.