New York Stock Exchange
S&P 500 companies historical prices with fundamental data
@kaggle.dgawlik_nyse
S&P 500 companies historical prices with fundamental data
@kaggle.dgawlik_nyse
This dataset is a playground for fundamental and technical analysis. It is said that 30% of traffic on stocks is already generated by machines, can trading be fully automated? If not, there is still a lot to learn from historical data.
Dataset consists of following files:
Prices were fetched from Yahoo Finance, fundamentals are from Nasdaq Financials, extended by some fields from EDGAR SEC databases.
Here is couple of things one could try out with this data:
Which company has biggest chance of being bankrupt? Which one is undervalued (how prices behaved afterwards), what is Return on Investment?
CREATE TABLE fundamentals (
"unnamed_0" BIGINT -- Unnamed: 0,
"ticker_symbol" VARCHAR,
"period_ending" TIMESTAMP,
"accounts_payable" DOUBLE,
"accounts_receivable" DOUBLE,
"add_l_income_expense_items" DOUBLE -- Add\u0027l Income/expense Items,
"after_tax_roe" DOUBLE,
"capital_expenditures" DOUBLE,
"capital_surplus" DOUBLE,
"cash_ratio" DOUBLE,
"cash_and_cash_equivalents" DOUBLE,
"changes_in_inventories" DOUBLE,
"common_stocks" DOUBLE,
"cost_of_revenue" DOUBLE,
"current_ratio" DOUBLE,
"deferred_asset_charges" DOUBLE,
"deferred_liability_charges" DOUBLE,
"depreciation" DOUBLE,
"earnings_before_interest_and_tax" DOUBLE,
"earnings_before_tax" DOUBLE,
"effect_of_exchange_rate" DOUBLE,
"equity_earnings_loss_unconsolidated_subsidiary" DOUBLE,
"fixed_assets" DOUBLE,
"goodwill" DOUBLE,
"gross_margin" DOUBLE,
"gross_profit" DOUBLE,
"income_tax" DOUBLE,
"intangible_assets" DOUBLE,
"interest_expense" DOUBLE,
"inventory" DOUBLE,
"investments" DOUBLE,
"liabilities" DOUBLE,
"long_term_debt" DOUBLE,
"long_term_investments" DOUBLE,
"minority_interest" DOUBLE,
"misc_stocks" DOUBLE -- Misc. Stocks,
"net_borrowings" DOUBLE,
"net_cash_flow" DOUBLE,
"net_cash_flow_operating" DOUBLE,
"net_cash_flows_financing" DOUBLE,
"net_cash_flows_investing" DOUBLE,
"net_income" DOUBLE,
"net_income_adjustments" DOUBLE,
"net_income_applicable_to_common_shareholders" DOUBLE,
"net_income_cont_operations" DOUBLE -- Net Income-Cont. Operations,
"net_receivables" DOUBLE,
"non_recurring_items" DOUBLE,
"operating_income" DOUBLE,
"operating_margin" DOUBLE,
"other_assets" DOUBLE,
"other_current_assets" DOUBLE,
"other_current_liabilities" DOUBLE,
"other_equity" DOUBLE,
"other_financing_activities" DOUBLE,
"other_investing_activities" DOUBLE,
"other_liabilities" DOUBLE,
"other_operating_activities" DOUBLE,
"other_operating_items" DOUBLE,
"pre_tax_margin" DOUBLE,
"pre_tax_roe" DOUBLE,
"profit_margin" DOUBLE,
"quick_ratio" DOUBLE,
"research_and_development" DOUBLE,
"retained_earnings" DOUBLE,
"sale_and_purchase_of_stock" DOUBLE,
"sales_general_and_admin" DOUBLE -- Sales, General And Admin.,
"short_term_debt_current_portion_of_long_term_debt" DOUBLE -- Short-Term Debt / Current Portion Of Long-Term Debt,
"short_term_investments" DOUBLE,
"total_assets" DOUBLE,
"total_current_assets" DOUBLE,
"total_current_liabilities" DOUBLE,
"total_equity" DOUBLE,
"total_liabilities" DOUBLE,
"total_liabilities_equity" DOUBLE -- Total Liabilities \u0026 Equity,
"total_revenue" DOUBLE,
"treasury_stock" DOUBLE,
"for_year" DOUBLE,
"earnings_per_share" DOUBLE,
"estimated_shares_outstanding" DOUBLE
);
CREATE TABLE prices (
"date" VARCHAR,
"symbol" VARCHAR,
"open" DOUBLE,
"close" DOUBLE,
"low" DOUBLE,
"high" DOUBLE,
"volume" DOUBLE
);
CREATE TABLE prices_split_adjusted (
"date" TIMESTAMP,
"symbol" VARCHAR,
"open" DOUBLE,
"close" DOUBLE,
"low" DOUBLE,
"high" DOUBLE,
"volume" DOUBLE
);
CREATE TABLE securities (
"ticker_symbol" VARCHAR,
"security" VARCHAR,
"sec_filings" VARCHAR,
"gics_sector" VARCHAR,
"gics_sub_industry" VARCHAR,
"address_of_headquarters" VARCHAR,
"date_first_added" TIMESTAMP,
"cik" BIGINT
);
Anyone who has the link will be able to view this.