Top 10 Fast Food Giants: Stock Price Dataset(2024) by Kaggle | Finance and Economics

About this Dataset

Top 10 Fast Food Giants: Stock Price Dataset(2024)

Dataset Description: This dataset consists of historical stock price data for 10 of the largest fast food companies, collected from Yahoo Finance. Each company’s stock data is stored in a separate Excel file, containing key financial metrics that are typically tracked for market analysis, such as open, high, low, close, adjusted close prices, and trading volume over a specified time period.

Files Descriptions: Each Excel file corresponds to a different fast food company’s stock, identified by its ticker symbol:

BRK-A - Berkshire Hathaway Inc. (A financial conglomerate that has major stakes in fast food and other industries)
DNUT- Krispy Kreme, Inc.
DPZ - Domino’s Pizza, Inc.
LKNCY - Luckin Coffee Inc.
MCD - McDonald's Corporation
PZZA - Papa John's International, Inc.
QSR - Restaurant Brands International Inc. (Parent of Burger King, Tim Hortons, and Popeyes)
SBUX - Starbucks Corporation
WEN - The Wendy’s Company
YUM - Yum! Brands, Inc. (Parent of KFC, Taco Bell, and Pizza Hut)

Column Descriptions: Each file likely contains the following columns (standard in Yahoo Finance datasets):

Date: The trading date.
Open: The price at which the stock opened on a given day.
High: The highest price of the stock during the trading session.
Low: The lowest price of the stock during the trading session.
Close: The price of the stock at market close.
Adj Close: The closing price adjusted for dividends and stock splits.
Volume: The number of shares traded during the day.

Purpose: This dataset can be used to:

Analyze stock trends and volatility in the fast food sector.
Compare the performance of different fast food companies over time.
Explore correlations between companies and broader economic or market conditions.
Test financial models or strategies, such as momentum trading or moving average crossovers.

Tables

Brk A

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.brk_a

344.3 KB
11222 rows
7 columns


CREATE TABLE brk_a (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Dnut

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.dnut

36.96 KB
810 rows
7 columns


CREATE TABLE dnut (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Dpz

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.dpz

238.85 KB
5083 rows
7 columns


CREATE TABLE dpz (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Lkncy

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.lkncy

63.37 KB
1345 rows
7 columns


CREATE TABLE lkncy (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Mcd

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.mcd

540.19 KB
14652 rows
7 columns


CREATE TABLE mcd (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Pzza

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.pzza

315.05 KB
7878 rows
7 columns


CREATE TABLE pzza (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Qsr

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.qsr

113.13 KB
2459 rows
7 columns


CREATE TABLE qsr (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Sbux

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.sbux

349.27 KB
8117 rows
7 columns


CREATE TABLE sbux (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Wen

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.wen

299.14 KB
11187 rows
7 columns


CREATE TABLE wen (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Yum

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.yum

313.12 KB
6796 rows
7 columns


CREATE TABLE yum (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);