screener

Screen for companies meeting various criteria.

These criteria include market cap, price, beta, volume, and dividend yield.

Parameters

• standard
• finviz
• fmp
• nasdaq
• yfinance

metric: Literal['overview', 'valuation', 'financial', 'ownership', 'performance', 'technical']

The data group to return, default is 'overview'.

• Default: overview

• Optional: True

---

exchange: Literal['all', 'amex', 'nasdaq', 'nyse']

Filter by exchange.

• Default: all

• Optional: True

---

index: Literal['all', 'dow', 'nasdaq', 'sp500', 'russell']

Filter by index.

• Default: all

• Optional: True

---

sector: Literal['all', 'energy', 'materials', 'industrials', 'consumer_cyclical', 'consumer_defensive', 'financial', 'healthcare', 'technology', 'communication_services', 'utilities', 'real_estate']

Filter by sector.

• Default: all

• Optional: True

---

industry: str

Filter by industry.

Choices

• all
• stocks_only
• etf
• advertising_agencies
• aerospace_defense
• agricultural_inputs
• airlines
• airports_airservices
• aluminum
• apparel_manufacturing
• apparel_retail
• asset_management
• auto_manufacturers
• auto_parts
• auto_dealerships
• banks_diversified
• banks_regional
• beverages_brewers
• beverages_nonalcoholic
• beverages_wineries_distilleries
• biotechnology
• broadcasting
• building_materials
• building_products_equipment
• business_equipment_supplies
• capital_markets
• chemicals
• closed_end_fund_debt
• closed_end_fund_equity
• closed_end_fund_foreign
• coking_coal
• communication_equipment
• computer_hardware
• confectioners
• conglomerates
• consulting_services
• consumer_electronics
• copper
• credit_services
• department_stores
• diagnostics_research
• discount_stores
• drug_manufacturers_general
• drug_manufacturers_specialty_generic
• education_training_services
• electrical_equipment_parts
• electronic_components
• electronic_gaming_multimedia
• electronics_computer_distribution
• engineering_construction
• entertainment
• farm_heavy_construction_machinery
• farm_products
• financial_conglomerates
• financial_data_stock_exchanges
• food_distribution
• footwear_accessories
• furnishings_fixtures_appliances
• gambling
• gold
• grocery_stores
• health_care_plans
• health_information_services
• home_improvement_retail
• household_personal_products
• industrial_distribution
• information_technology_services
• infrastructure_operations
• insurance_brokers
• insurance_diversified
• insurance_life
• insurance_property_casualty
• insurance_reinsurance
• insurance_specialty
• integrated_freight_logistics
• internet_content_information
• internet_retail
• leisure
• lodging
• lumber_wood_production
• luxury_goods
• marine_shipping
• medical_care_facilities
• medical_devices
• medical_distribution
• medical_instruments_supplies
• metal_fabrication
• mortgage_finance
• oil_gas_drilling
• oil_gas_ep
• oil_gas_equipment_services
• oil_gas_integrated
• oil_gas_midstream
• oil_gas_refining_marketing
• other_industrial_metals_mining
• other_precious_metals_mining
• packaged_foods
• packaging_containers
• paper_paper_products
• personal_services
• pharmaceutical_retailers
• pollution_treatment_controls
• publishing
• railroads
• real_estate_development
• real_estate_diversified
• real_estate_services
• recreational_vehicles
• reit_diversified
• reit_health_care_facilities
• reit_hotel_motel
• reit_industrial
• reit_mortgage
• reit_office
• reit_residential
• reit_retail
• reit_specialty
• rental_leasing_services
• residential_construction
• resorts_casinos
• restaurants
• scientific_technical_instruments
• security_protection_services
• semiconductor_equipment_materials
• semiconductors
• shell_companies
• silver
• software_application
• software_infrastructure
• solar
• specialty_business_services
• specialty_chemicals
• specialty_industrial_machinery
• specialty_retail
• staffing_employment_services
• steel
• telecom_services
• textile_manufacturing
• thermal_coal
• tobacco
• tools_accessories
• travel_services
• trucking
• uranium
• utilities_diversified
• utilities_independent_power_producers
• utilities_regulated_electric
• utilities_regulated_gas
• utilities_regulated_water
• utilities_renewable
• waste_management

• Default: all

• Optional: True

---

mktcap: Literal['all', 'mega', 'large', 'large_over', 'large_under', 'mid', 'mid_over', 'mid_under', 'small', 'small_over', 'small_under', 'micro', 'micro_over', 'micro_under', 'nano']

Description

Filter by market cap.
Mega - > 200B
Large - 10B - 200B
Mid - 2B - 10B
Small - 300M - 2B
Micro - 50M - 300M
Nano - < 50M

• Default: all

• Optional: True

---

recommendation: Literal['all', 'strong_buy', 'buy+', 'buy', 'hold+', 'hold', 'hold-', 'sell', 'sell-', 'strong_sell']

Filter by analyst recommendation.

• Default: all

• Optional: True

---

signal: str

Description

The Finviz screener signal to use. When no parameters are provided, the screener defaults to 'top_gainers'. Available signals are:
channel: both support and resistance trendlines are horizontal
channel_down: both support and resistance trendlines slope downward
channel_up: both support and resistance trendlines slope upward
double_bottom: stock with 'W' shape that indicates a bullish reversal in trend
double_top: stock with 'M' shape that indicates a bearish reversal in trend
downgrades: stocks downgraded by analysts today
earnings_after: companies reporting earnings today, after market close
earnings_before: companies reporting earnings today, before market open
head_shoulders: chart formation that predicts a bullish-to-bearish trend reversal
head_shoulders_inverse: chart formation that predicts a bearish-to-bullish trend reversal
horizontal_sr: horizontal channel of price range between support and resistance trendlines
major_news: stocks with the highest news coverage today
most_active: stocks with the highest trading volume today
most_volatile: stocks with the highest widest high/low trading range today
multiple_bottom: same as double_bottom hitting more lows
multiple_top: same as double_top hitting more highs
new_high: stocks making 52-week high today
new_low: stocks making 52-week low today
overbought: stock is becoming overvalued and may experience a pullback.
oversold: oversold stocks may represent a buying opportunity for investors
recent_insider_buying: stocks with recent insider buying activity
recent_insider_selling: stocks with recent insider selling activity
tl_resistance: once a rising trendline is broken
tl_support: once a falling trendline is broken
top_gainers: stocks with the highest price gain percent today
top_losers: stocks with the highest price percent loss today
triangle_ascending: upward trendline support and horizontal trendline resistance
triangle_descending: horizontal trendline support and downward trendline resistance
unusual_volume: stocks with unusually high volume today - the highest relative volume ratio
upgrades: stocks upgraded by analysts today
wedge: upward trendline support, downward trendline resistance (contiunation)
wedge_down: downward trendline support and downward trendline resistance (reversal)
wedge_up: upward trendline support and upward trendline resistance (reversal)

Choices

• channel
• channel_down
• channel_up
• double_bottom
• double_top
• downgrades
• earnings_after
• earnings_before
• head_shoulders
• head_shoulders_inverse
• horizontal_sr
• major_news
• most_active
• most_volatile
• multiple_bottom
• multiple_top
• new_high
• new_low
• overbought
• oversold
• recent_insider_buying
• recent_insider_selling
• tl_resistance
• tl_support
• top_gainers
• top_losers
• triangle_ascending
• triangle_descending
• unusual_volume
• upgrades
• wedge
• wedge_down
• wedge_up

• Optional: True

---

preset: str

Description

A configured preset file to use for the query. This overrides all other query parameters except 'metric', and 'limit'. Presets (.ini text files) can be created and modified in the '~/OpenBBUserData/finviz/presets' directory. If the path does not exist, it will be created and populated with the default presets on the first run. Refer to the file, 'screener_template.ini', for the format and options.

Note: Syntax of parameters in preset files must follow the template file exactly - i.e, Analyst Recom. = Strong Buy (1)

• Optional: True

---

filters_dict: Union[Dict, str]

A formatted dictionary, or serialized JSON string, of additional filters to apply to the query. This parameter can be used as an alternative to preset files, and is ignored when a preset is supplied. Invalid entries will raise an error. Syntax should follow the 'screener_template.ini' file.

• Optional: True

---

limit: int

The number of data entries to return.

• Optional: True

mktcap_min: int

Filter by market cap greater than this value.

• Optional: True

---

mktcap_max: int

Filter by market cap less than this value.

• Optional: True

---

price_min: float

Filter by price greater than this value.

• Optional: True

---

price_max: float

Filter by price less than this value.

• Optional: True

---

beta_min: float

Filter by a beta greater than this value.

• Optional: True

---

beta_max: float

Filter by a beta less than this value.

• Optional: True

---

volume_min: int

Filter by volume greater than this value.

• Optional: True

---

volume_max: int

Filter by volume less than this value.

• Optional: True

---

dividend_min: float

Filter by dividend amount greater than this value.

• Optional: True

---

dividend_max: float

Filter by dividend amount less than this value.

• Optional: True

---

is_etf: bool

If true, returns only ETFs.

• Default: False

• Optional: True

---

is_active: bool

If false, returns only inactive tickers.

• Default: True

• Optional: True

---

sector: Literal['consumer_cyclical', 'energy', 'technology', 'industrials', 'financial_services', 'basic_materials', 'communication_services', 'consumer_defensive', 'healthcare', 'real_estate', 'utilities', 'industrial_goods', 'financial', 'services']

Filter by sector.

• Optional: True

---

industry: str

Filter by industry.

• Optional: True

---

country: str

Filter by country, as a two-letter country code.

• Optional: True

---

exchange: Literal['amex', 'ams', 'ase', 'asx', 'ath', 'bme', 'bru', 'bud', 'bue', 'cai', 'cnq', 'cph', 'dfm', 'doh', 'etf', 'euronext', 'hel', 'hkse', 'ice', 'iob', 'ist', 'jkt', 'jnb', 'jpx', 'kls', 'koe', 'ksc', 'kuw', 'lse', 'mex', 'mutual_fund', 'nasdaq', 'neo', 'nse', 'nyse', 'nze', 'osl', 'otc', 'pnk', 'pra', 'ris', 'sao', 'sau', 'set', 'sgo', 'shh', 'shz', 'six', 'sto', 'tai', 'tlv', 'tsx', 'two', 'vie', 'wse', 'xetra']

Filter by exchange.

• Optional: True

---

limit: int

Limit the number of results to return.

• Default: 50000

• Optional: True

exchange: Union[Union[Literal['all', 'nasdaq', 'nyse', 'amex'], str], list[Union[Literal['all', 'nasdaq', 'nyse', 'amex'], str]]]

Filter by exchange. Multiple items allowed for provider(s): nasdaq.

• Default: all

• Optional: True

---

exsubcategory: Union[Union[Literal['all', 'ngs', 'ngm', 'ncm', 'adr'], str], list[Union[Literal['all', 'ngs', 'ngm', 'ncm', 'adr'], str]]]

Description

Filter by exchange subcategory.
NGS - Nasdaq Global Select Market
NGM - Nasdaq Global Market
NCM - Nasdaq Capital Market
ADR - American Depository Receipt Multiple items allowed for provider(s): nasdaq.

• Default: all

• Optional: True

---

mktcap: Union[Union[Literal['all', 'mega', 'large', 'mid', 'small', 'micro'], str], list[Union[Literal['all', 'mega', 'large', 'mid', 'small', 'micro'], str]]]

Description

Filter by market cap.
Mega - > 200B
Large - 10B - 200B
Mid - 2B - 10B
Small - 300M - 2B
Micro - 50M - 300M Multiple items allowed for provider(s): nasdaq.

• Default: all

• Optional: True

---

recommendation: Union[Union[Literal['all', 'strong_buy', 'buy', 'hold', 'sell', 'strong_sell'], str], list[Union[Literal['all', 'strong_buy', 'buy', 'hold', 'sell', 'strong_sell'], str]]]

Filter by consensus analyst action. Multiple items allowed for provider(s): nasdaq.

• Default: all

• Optional: True

---

sector: Union[Union[Literal['all', 'energy', 'basic_materials', 'industrials', 'consumer_staples', 'consumer_discretionary', 'health_care', 'financial_services', 'technology', 'communication_services', 'utilities', 'real_estate'], str], list[Union[Literal['all', 'energy', 'basic_materials', 'industrials', 'consumer_staples', 'consumer_discretionary', 'health_care', 'financial_services', 'technology', 'communication_services', 'utilities', 'real_estate'], str]]]

Filter by sector. Multiple items allowed for provider(s): nasdaq.

• Default: all

• Optional: True

---

region: Union[Union[Literal['all', 'africa', 'asia', 'australia_and_south_pacific', 'caribbean', 'europe', 'middle_east', 'north_america', 'south_america'], str], list[Union[Literal['all', 'africa', 'asia', 'australia_and_south_pacific', 'caribbean', 'europe', 'middle_east', 'north_america', 'south_america'], str]]]

Filter by region. Multiple items allowed for provider(s): nasdaq.

• Default: all

• Optional: True

---

country: Union[Union[Literal['all', 'argentina', 'armenia', 'australia', 'austria', 'belgium', 'bermuda', 'brazil', 'canada', 'cayman_islands', 'chile', 'colombia', 'costa_rica', 'curacao', 'cyprus', 'denmark', 'finland', 'france', 'germany', 'greece', 'guernsey', 'hong_kong', 'india', 'indonesia', 'ireland', 'isle_of_man', 'israel', 'italy', 'japan', 'jersey', 'luxembourg', 'macau', 'mexico', 'monaco', 'netherlands', 'norway', 'panama', 'peru', 'philippines', 'puerto_rico', 'russia', 'singapore', 'south_africa', 'south_korea', 'spain', 'sweden', 'switzerland', 'taiwan', 'turkey', 'united_kingdom', 'united_states', 'usa'], str], list[Union[Literal['all', 'argentina', 'armenia', 'australia', 'austria', 'belgium', 'bermuda', 'brazil', 'canada', 'cayman_islands', 'chile', 'colombia', 'costa_rica', 'curacao', 'cyprus', 'denmark', 'finland', 'france', 'germany', 'greece', 'guernsey', 'hong_kong', 'india', 'indonesia', 'ireland', 'isle_of_man', 'israel', 'italy', 'japan', 'jersey', 'luxembourg', 'macau', 'mexico', 'monaco', 'netherlands', 'norway', 'panama', 'peru', 'philippines', 'puerto_rico', 'russia', 'singapore', 'south_africa', 'south_korea', 'spain', 'sweden', 'switzerland', 'taiwan', 'turkey', 'united_kingdom', 'united_states', 'usa'], str]]]

Filter by country. Multiple items allowed for provider(s): nasdaq.

• Default: all

• Optional: True

---

limit: int

Limit the number of results to return.

• Optional: True

country: str

Filter by country, as a two-letter country code. Default is, 'us'. Use, 'all', for all countries.

Choices

• all
• ar
• at
• au
• be
• br
• ca
• ch
• cl
• cn
• cz
• de
• dk
• ee
• eg
• es
• fi
• fr
• gb
• gr
• hk
• hu
• id
• ie
• il
• in
• is
• it
• jp
• kr
• kw
• lk
• lt
• lv
• mx
• my
• nl
• no
• nz
• pe
• ph
• pk
• pl
• pt
• qa
• ro
• ru
• sa
• se
• sg
• sr
• th
• tr
• tw
• us
• ve
• vn
• za

• Default: us

• Optional: True

---

exchange: Literal['ams', 'aqs', 'ase', 'asx', 'ath', 'ber', 'bru', 'bse', 'bts', 'bud', 'bue', 'bvb', 'bvc', 'ccs', 'cnq', 'cph', 'cxe', 'dfm', 'doh', 'dus', 'ebs', 'fka', 'fra', 'ger', 'ham', 'han', 'hel', 'hkg', 'ice', 'iob', 'ise', 'ist', 'jkt', 'jnb', 'jpx', 'kls', 'kuw', 'lis', 'lit', 'lse', 'mce', 'mex', 'mil', 'mun', 'ncm', 'neo', 'ngm', 'nms', 'nsi', 'nyq', 'nze', 'oem', 'oqb', 'oqx', 'osl', 'par', 'pnk', 'pra', 'ris', 'sau', 'ses', 'set', 'sgo', 'shh', 'shz', 'sto', 'stu', 'tai', 'tal', 'tlv', 'tor', 'two', 'van', 'vie', 'vse', 'wse']

Filter by exchange.

• Optional: True

---

sector: Literal['basic_materials', 'communication_services', 'consumer_cyclical', 'consumer_defensive', 'energy', 'financial_services', 'healthcare', 'industrials', 'real_estate', 'technology', 'utilities']

Filter by sector.

• Optional: True

---

industry: str

Filter by industry.

Choices

• advertising_agencies
• aerospace_defense
• agricultural_inputs
• airlines
• airports_air_services
• aluminum
• apparel_manufacturing
• apparel_retail
• asset_management
• auto_components
• auto_manufacturers
• auto_parts
• auto_truck_dealerships
• automobiles
• banks
• biotechnology
• broadcasting
• building_materials
• building_products
• building_products_equipment
• business_equipment_supplies
• capital_markets
• chemicals
• coking_coal
• commercial_services
• communication_equipment
• computer_hardware
• confectioners
• construction_engineering
• construction_materials
• consulting_services
• consumer_durables
• consumer_electronics
• consumer_services
• copper
• credit_services
• department_stores
• diagnostics_research
• discount_stores
• diversified_financials
• education_training_services
• electrical_equipment
• electrical_equipment_parts
• electronic_components
• electronic_gaming_multimedia
• electronics_computer_distribution
• energy_services
• engineering_construction
• entertainment
• farm_heavy_construction_machinery
• farm_products
• financial_conglomerates
• financial_data_stock_exchanges
• food_distribution
• footwear_accessories
• furnishings_fixtures_appliances
• gambling
• gold
• grocery_stores
• health_information_services
• healthcare_plans
• home_builders
• home_improvement_retail
• household_products
• household_personal_products
• industrial_conglomerates
• industrial_distribution
• information_technology_services
• infrastructure_operations
• insurance
• integrated_freight_logistics
• internet_content_information
• internet_retail
• leisure
• lodging
• lumber_wood_production
• luxury_goods
• machinery
• marine_shipping
• media
• medical_care_facilities
• medical_devices
• medical_distribution
• medical_instruments_supplies
• metal_fabrication
• mortgage_finance
• oil_gas_drilling
• oil_gas_e_p
• oil_gas_equipment_services
• oil_gas_integrated
• oil_gas_midstream
• oil_gas_producers
• oil_gas_refining_marketing
• other_industrial_metals_mining
• other_precious_metals_mining
• packaged_foods
• packaging_containers
• paper_forestry
• paper_paper_products
• personal_services
• pharmaceuticals
• pharmaceutical_retailers
• pollution_treatment_controls
• precious_metals
• publishing
• railroads
• real_estate
• recreational_vehicles
• refiners_pipelines
• rental_leasing_services
• residential_construction
• resorts_casinos
• restaurants
• retailing
• scientific_technical_instruments
• security_protection_services
• semiconductor_equipment_materials
• semiconductors
• shell_companies
• silver
• software_and_services
• solar
• specialty_business_services
• specialty_chemicals
• specialty_industrial_machinery
• specialty_retail
• staffing_employment_services
• steel
• technology_hardware
• telecom_services
• textiles_apparel
• textile_manufacturing
• thermal_coal
• tobacco
• tools_accessories
• traders_distributors
• transportation
• transportation_infrastructure
• travel_services
• trucking
• uranium
• utilities
• waste_management

• Optional: True

---

mktcap_min: int

Filter by market cap greater than this value. Default is 500M.

• Default: 500000000

• Optional: True

---

mktcap_max: int

Filter by market cap less than this value.

• Optional: True

---

price_min: float

Filter by price greater than this value. Default is, 5

• Default: 5

• Optional: True

---

price_max: float

Filter by price less than this value.

• Optional: True

---

volume_min: int

Filter by volume greater than this value. Default is, 10K

• Default: 10000

• Optional: True

---

volume_max: int

Filter by volume less than this value.

• Optional: True

---

beta_min: float

Filter by a beta greater than this value.

• Optional: True

---

beta_max: float

Filter by a beta less than this value.

• Optional: True

---

limit: int

Limit the number of results returned. Default is, 200. Set to, 0, for all results.

• Default: 200

• Optional: True

---

Returns

results: list[EquityScreener]

Serializable results.

---

provider: Optional[Literal['finviz', 'fmp', 'nasdaq', 'yfinance']]

Provider name.

---

warnings: Optional[list[Warning_]]

list of warnings.

---

chart: Optional[Chart]

Chart object.

---

extra: dict[str, Any]

Extra info.

---

Data

• standard
• finviz
• fmp
• nasdaq
• yfinance

symbol: str

Symbol representing the entity requested in the data.

name: str

Name of the company.

symbol: str

Symbol representing the entity requested in the data.

name: str

Name of the company.

earnings_date: str

Earnings date, where 'a' and 'b' mean after and before market close, respectively.

country: str

Country of the company.

sector: str

Sector of the company.

industry: str

Industry of the company.

beta: float

Beta of the stock.

analyst_recommendation: float

Analyst's mean recommendation. (1=Buy 5=Sell).

market_cap: float

Market capitalization of the company.

price: float

Price of a share.

change_percent: float

Price change percentage.

change_from_open: float

Price change percentage, from the opening price.

gap: float

Price gap percentage, from the previous close.

volume: Union[float, int]

The trading volume.

volume_avg: Union[float, int]

3-month average daily volume.

volume_relative: float

Current volume relative to the average.

average_true_range: float

Average true range (14).

price_change_1w: float

One-week price return.

price_change_1m: float

One-month price return.

price_change_3m: float

Three-month price return.

price_change_6m: float

Six-month price return.

price_change_1y: float

One-year price return.

price_change_ytd: float

Year-to-date price return.

volatility_1w: float

One-week volatility.

volatility_1m: float

One-month volatility.

year_high_percent: float

Percent difference from current price to the 52-week high.

year_low_percent: float

Percent difference from current price to the 52-week low.

sma20_percent: float

Percent difference from current price to the 20-day simple moving average.

sma50_percent: float

Percent difference from current price to the 50-day simple moving average.

sma200_percent: float

Percent difference from current price to the 200-day simple moving average.

rsi: float

Relative strength index (14).

shares_outstanding: Union[float, int]

Number of shares outstanding.

shares_float: Union[float, int]

Number of shares available to trade.

short_interest: float

Percent of float reported as short.

short_ratio: float

Short interest ratio

insider_ownership: float

Insider ownership as a percentage.

insider_ownership_change: float

6-month change in insider ownership percentage.

institutional_ownership: float

Institutional ownership as a percentage.

institutional_ownership_change: float

3-month change in institutional ownership percentage.

price_to_earnings: float

Price to earnings ratio.

forward_pe: float

Forward price to earnings ratio.

peg_ratio: float

Price/Earnings-To-Growth (PEG) ratio.

price_to_sales: float

Price to sales ratio.

price_to_book: float

Price to book ratio.

price_to_cash: float

Price to cash ratio.

price_to_fcf: float

Price to free cash flow ratio.

eps_growth_past_1y: float

EPS growth for this year.

eps_growth_next_1y: float

EPS growth next year.

eps_growth_past_5y: float

EPS growth for the previous 5 years.

eps_growth_next_5y: float

EPS growth for the next 5 years.

sales_growth_past_5y: float

Sales growth for the previous 5 years.

dividend_yield: float

Annualized dividend yield.

return_on_assets: float

Return on assets.

return_on_equity: float

Return on equity.

return_on_investment: float

Return on investment.

current_ratio: float

Current ratio.

quick_ratio: float

Quick ratio.

long_term_debt_to_equity: float

Long term debt to equity ratio.

debt_to_equity: float

Total debt to equity ratio.

gross_margin: float

Gross margin.

operating_margin: float

Operating margin.

profit_margin: float

Profit margin.

symbol: str

Symbol representing the entity requested in the data.

name: str

Name of the company.

market_cap: int

The market cap of ticker.

sector: str

The sector the ticker belongs to.

industry: str

The industry ticker belongs to.

beta: float

The beta of the ETF.

price: float

The current price.

last_annual_dividend: float

The last annual amount dividend paid.

volume: int

The current trading volume.

exchange: str

The exchange code the asset trades on.

exchange_name: str

The full name of the primary exchange.

country: str

The two-letter country abbreviation where the head office is located.

is_etf: Literal[True, False]

Whether the ticker is an ETF.

actively_trading: Literal[True, False]

Whether the ETF is actively trading.

symbol: str

Symbol representing the entity requested in the data.

name: str

Name of the company.

last_price: float

Last sale price.

change: float

1-day change in price.

change_percent: float

1-day percent change in price.

market_cap: int

Market cap.

symbol: str

Symbol representing the entity requested in the data.

name: str

Name of the company.

open: float

Open price for the day.

high: float

High price for the day.

low: float

Low price for the day.

previous_close: float

Previous close price.

ma50: float

50-day moving average.

ma200: float

200-day moving average.

year_high: float

52-week high.

year_low: float

52-week low.

market_cap: float

Market Cap.

shares_outstanding: float

Shares outstanding.

book_value: float

Book value per share.

price_to_book: float

Price to book ratio.

eps_ttm: float

Earnings per share over the trailing twelve months.

eps_forward: float

Forward earnings per share.

pe_forward: float

Forward price-to-earnings ratio.

dividend_yield: float

Trailing twelve month dividend yield.

exchange: str

Exchange where the stock is listed.

exchange_timezone: str

Timezone of the exchange.

earnings_date: datetime

Most recent earnings date.

currency: str

Currency of the price data.