Name: Banks Historical Stock Price
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Banks Historical Stock Price

Context

The main objective is to provide historical information on stock prices of certain banks. The goal is to make the information easily accessible in case it cannot be downloaded directly from yahoo finance. The idea is that different behaviors in stock prices can be analyzed over time to gain a better understanding of the banking industry. You can also see how different events affect prices, such as the 2007 subprime mortgage crisis, presidential elections, major political reforms, etc.

Content

The dataset contains 99 csv files. Each file has stock information from a specific bank or Financial Service company from Jan 1st, 2006 to Nov 1st, 2020.

For instance, you can find the following banks in this dataset:

Bank of America (BAC)
CitiGroup (C)
Goldman Sachs (GS)
JPMorgan Chase (JPM)
Morgan Stanley (MS)
Wells Fargo (WFC)

Acknowledgements

Yahoo Finance | Technology Sector
SEC EDGAR | Company Filings
NASDAQ | Historical Quotes

Inspiration

Many have tried, but most have failed, to predict the stock market's ups and downs. Can you do any better? Can you create visualizations that help investors make important decisions?

More Datasets

Tables

Ma

@kaggle.tomasmantero_banks_historical_stock_price.ma

190.44 kB
3,650 rows
7 columns

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

Mco

@kaggle.tomasmantero_banks_historical_stock_price.mco

185.98 kB
3,749 rows
7 columns

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

Met

@kaggle.tomasmantero_banks_historical_stock_price.met

175.23 kB
3,749 rows
7 columns

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

Met Pa

@kaggle.tomasmantero_banks_historical_stock_price.met_pa

76.79 kB
2,122 rows
7 columns

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

Met Pe

@kaggle.tomasmantero_banks_historical_stock_price.met_pe

29.65 kB
624 rows
7 columns

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

Mfc

@kaggle.tomasmantero_banks_historical_stock_price.mfc

145.03 kB
3,749 rows
7 columns

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

Mmc

@kaggle.tomasmantero_banks_historical_stock_price.mmc

172.22 kB
3,749 rows
7 columns

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

Ms

@kaggle.tomasmantero_banks_historical_stock_price.ms

175.55 kB
3,749 rows
7 columns

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

Msci

@kaggle.tomasmantero_banks_historical_stock_price.msci

155.52 kB
3,278 rows
7 columns

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

Ms Pa

@kaggle.tomasmantero_banks_historical_stock_price.ms_pa

79.51 kB
2,122 rows
7 columns

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

Ms Pe

@kaggle.tomasmantero_banks_historical_stock_price.ms_pe

65.5 kB
1,802 rows
7 columns

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

Ms Pf

@kaggle.tomasmantero_banks_historical_stock_price.ms_pf

63.05 kB
1,751 rows
7 columns

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

Ms Pi

@kaggle.tomasmantero_banks_historical_stock_price.ms_pi

57.08 kB
1,559 rows
7 columns

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

Ms Pk

@kaggle.tomasmantero_banks_historical_stock_price.ms_pk

38.38 kB
965 rows
7 columns

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

Pgr

@kaggle.tomasmantero_banks_historical_stock_price.pgr

162.75 kB
3,749 rows
7 columns

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

Pnc

@kaggle.tomasmantero_banks_historical_stock_price.pnc

181.23 kB
3,749 rows
7 columns

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

Puk

@kaggle.tomasmantero_banks_historical_stock_price.puk

161.74 kB
3,749 rows
7 columns

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

Pypl

@kaggle.tomasmantero_banks_historical_stock_price.pypl

71.54 kB
1,358 rows
7 columns

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

Rkt

@kaggle.tomasmantero_banks_historical_stock_price.rkt

9.1 kB
76 rows
7 columns

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

Ry

@kaggle.tomasmantero_banks_historical_stock_price.ry

168.56 kB
3,749 rows
7 columns

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

Ry Pt

@kaggle.tomasmantero_banks_historical_stock_price.ry_pt

42.32 kB
1,273 rows
7 columns

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

Schw

@kaggle.tomasmantero_banks_historical_stock_price.schw

165.3 kB
3,749 rows
7 columns

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

Schw Pc

@kaggle.tomasmantero_banks_historical_stock_price.schw_pc

50.13 kB
1,341 rows
7 columns

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

Schw Pd

@kaggle.tomasmantero_banks_historical_stock_price.schw_pd

44.38 kB
1,191 rows
7 columns

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

Smfg

@kaggle.tomasmantero_banks_historical_stock_price.smfg

116.6 kB
3,732 rows
7 columns

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