***Maximum possible ids limit** = 3500 per request*
`NOTE:` *The maximum possible ids limit for a request will **decrease** based on the size of the historical date range, the number of factors or factorGroups requested.* *GET Method URL request lines are also limited to a total length of 8192 bytes (8KB). In cases where the service allows for thousands of ids, which may lead to exceeding this request line limit of 8KB, its advised for any requests with large request lines to be requested through the respective "POST" method.
* examples: oneId: summary: Single id value: - FDS-US multipleIds: summary: Multiple ids value: - FDS-US - IBM-US - AAPL-US factors: name: factors in: query required: true schema: type: array items: type: string minItems: 1 maxItems: 20 explode: false description: > Array of individual Factor Items requested. For a list of all available factors and descriptions use the `/library` endpoint.***factors limit** = 20 individual factors per request* example: - rsi21D - ulcer252D - turbulence21D factorsLibrary: name: factors in: query required: false schema: type: array items: type: string minItems: 1 maxItems: 20 explode: false description: > Array of individual Factor Items requested for the library endpoint. Use the factorGroups parameter to pull for a full list of factors based off the input group. example: - rsi21D - ulcer252D - turbulence21D factorGroups: name: factorGroups in: query required: false schema: type: array items: type: string minItems: 1 maxItems: 5 description: > Fetch a collection of Factors that fall within one of the below "groups". For example, resting factorGroup=Momentum will return all factors under the momentum group. To know which items are available in each group use the /library endpoint.***
factor groups limit** = 5 factor groups per request* ### Classification and Reference |Group|Descriptions| ||| |Asset_Data|Easily input security-level metadata into your quantitative research process. Common metrics used include Days Since Report, Days to Report, ADR Flag, and Minimum Lot Size. Integrate variables from FactSet Reference, FactSet Fundamentals, and FactSet Estimates databases to impose portfolio constraints and access general reference data.| |Country|Evaluate securities based on the countries in which they have the highest exposure. Analyze company-level exposures across various countries and measure how concentrated a firm’s business is within their countries of operation. Metrics are derived from FactSet Reference and FactSet Geographic Revenue Exposure (GeoRev) databases and include Country Exposure, Country of Incorporation, and Country of Risk.| |Industry|Classify securities based on the industries in which they generate the majority of their revenues. Incorporate variables from the FactSet Revere Business and Industry Classification System (RBICS) database to measure how concentrated a firm’s business is within the industries they operate and across various sub-sectors. Common metrics include Industry Classifications, Industry Exposures, and Industry Concentration.| |Size|Assess how large or small a company is relative to industry peers. Create size buckets and clarify the systematic portion of company returns using variables from FactSet Prices, FactSet RBICS, FactSet Fundamentals, and FactSet Estimates. Common metrics include Size Classification, Enterprise Value, and Market Share.| ### Market Factors |Group|Descriptions| ||| |Liquidity|Assess how investible a security is, as well as the potential market impact of a trade using signals built off pricing and volume data from FactSet Prices. Integrate factors as components into your alpha models to evaluate systematic risk or input them into your portfolio construction models to dictate how much of an asset can be bought or sold based on liquidity levels. Common metrics include Average Dollars Traded, Share Turnover, and Bid Ask Spread.| |Market Sensitivity|Clarify the common variations in stock returns attributable to the performance of their local market indices. Leverage regressions performed between security-level and market-index returns across different return horizons and methodologies. Metrics are derived from FactSet Prices and include Beta R-Squared, Up Market Beta, and Down Market Beta.| |Momentum|Analyze the historical momentum of a security and uncover how each underlying data item, calculation, and horizon can be meaningful in different situations. Metrics are derived from FactSet Prices and include 52W Position, Return Momentum, and Velocity.| |Technical|Forecast the direction of future price movements based on historical market data and leverage heuristic or pattern-based signals from FactSet Prices. Common metrics include Average True Range, Ulcer Performance Index, and Money Flow Volume.| |Volatility|Measure the uncertainty in asset price movements with indicators from the FactSet Prices database. Capture various forms of uncertainty by employing statistical calculations on security performance data. Common metrics include Return Volatility, Semivariance, and Turbulence.| ### Core Fundamentals |Group|Descriptions| ||| |Efficiency|Leverage core financial data to determine how effectively a company uses its assets, collects payments, and operates its business. Most variables are measured as turnover ratios and include changes over time to provide transparency into the efficiency of each business process. Metrics are derived from FactSet Fundamentals and FactSet Estimates and include Asset Turnover, Receivables Turnover, and Cash Conversion Cycle| |Growth|Measure a company’s ability to grow faster than its peers. Compare the future expected growth of a company with its historical growth and view growth rates adjusted for stability. Integrate variables from FactSet RBICS, FactSet Fundamentals, and FactSet Estimates to analyze growth rates over multiple horizons including Market Share, Sales, and EPS Growth| |Management|Gain insight into how management finances their business and the decisions they make that impact the core financial statements. These choices are reflected in changes to total debt or equity, the overall size of the balance sheet, and decisions around the accounting methods used. Metrics are derived from FactSet Fundamentals and FactSet Estimates and include Capital Expenditures (CAPEX) Growth, Equity Buyback Ratio, and Depreciation & Amortization Variability| |Profitability|Evaluate a company’s ability to generate income relative to its revenue or balance sheet metrics. Identify lucrative businesses relative to their industry, region, and size profile. Metrics are derived from FactSet Fundamentals and FactSet Estimates and include Return on Assets, Return on Invested Capital Change, and Return on Total Equity |Quality|Understand the overall financial health and quality of a company’s business. Use historical data from FactSet Fundamentals to analyze balance sheet health, stability of earnings and profit margins, variability in cash flows, and trends that look beyond headline financial metrics. Common metrics include Cash Earnings Ratio Variability, Revenue Stability, and Accruals Ratios. Composite quality scores (i.e., the Piotroski F-Score, Beneish M-Score, and Altman Z-Score) and their underlying components are also available as individual metrics.| |Solvency|Measure a company’s ability to meet their short- and long-term financial obligations and determine the degree of leverage employed to run their business. Incorporate financial ratios from FactSet Fundamentals and FactSet Estimates to quantify liability or debt obligation relative to earnings, cash flows, equities, or items from the asset side of the balance sheet. Common metrics include Current Ratio, Current Asset Liquidity, and Debt to Equity Change.| |Value|Quickly determine how cheap or expensive a company is based on common security-level characteristics from FactSet Prices, FactSet Fundamentals, and FactSet Estimates. Apply factors as an intersection between other factors for a more customized analysis, such as finding the cheapest stocks among the highest quality companies. Common metrics include Earnings Yield, Book to Price, and Revenue to Enterprise Value.| ### Macro and Cross-Asset |Group|Descriptions| ||| |Commodity|Quantify the impact movements in the commodity markets have on equity prices. Metrics are derived from FactSet Prices and allow you to measure company-level exposure to commodities such as Gold, Crude Oil, Coffee, and Live Cattle.| |FX_Sensitivity| Analyze security-level sensitivity to fluctuations in the currency markets. Metrics are derived from FactSet Prices and allow you to identify company exposures to currencies such as USD, EUR, JPY, and CNY. |Debt|Uncover details related to company debt through issuer-level factor exposures. Use the FactSet Fixed Income Prices & Derived Analytics database to aggregate metrics at the company level. Common metrics include Effective Duration, Option Adjusted Spread, and Yield to Worst.| |Economic|Capture daily security exposures to leading economic indicator forecasts. Leverage the Quant Factor Library’s detailed country exposure model to attribute economic measures to individual companies. Metrics are derived from FactSet Economic Estimates and include Real GPD Growth, Industrial Production Growth, Core CPI Inflation, and Policy Rates. ### Alternative |Group|Descriptions| ||| |Analyst_Sentiment|Analyze a security’s outlook from the perspective of a sell-side research analyst. Leverage consensus estimates data from the FactSet Estimates database to analyze the directional change in estimate revisions for various financial statement items and time periods. Common metrics include Sales Estimate Revisions, Free Cash Flow Estimate Revisions, and Robust Estimate Revisions.| |Corporate_Governance|Identify companies with strong corporate governance. Analyze the profile of a company’s management and board based on tenure, diversity, compensation incentives, and more factors from the FactSet People database. Common metrics include Management - Average Age, Board - Activist Member, and Executives - Average Bonus.| |Crowding|Understand the degree to which investors own, purchase, or sell a security. View characteristics of each investor’s profile and characterize crowding from passive, active, institutional, ETF, and hedge fund investors. Use metrics from FactSet Ownership, FactSet Prices, and FactSet Fundamentals to help identify potential effects of crowding such as whether certain investor types are acquiring or divesting from a given security. Common metrics include Active Buyer Percent of Portfolio Change, ETF Days to Liquidate, and Hedge Fund Percent Outstanding.| |Insider_Activity|Measure the degree to which insiders own, purchase, or sell their company’s stock. Analyze the sentiment of those with access to material non-public information or determine how the amount of insider ownership may impact management’s key business decisions. Metrics are derived from FactSet Ownership and include Insider Percent Outstanding, Insider Number of Buys, and Insider Seller Position Change. |ESG|Analyze Environmental, Social and Governance (ESG) behavior, which are aggregated and categorized into continuously updated, material ESG scores to uncover risks and opportunities from companies. Truvalue Labs focuses on company ESG behavior from external sources and includes both positive and negative events that go beyond traditional sources of ESG risk data. explode: false example: - Momentum - Technical - Volatility startDate: name: startDate in: query required: true schema: type: string description: > The start date requested for a given date range in **YYYY-MM-DD** format. Future dates (T+1) are not accepted in this endpoint. example: '2020-11-30' endDate: name: endDate in: query required: true schema: type: string description: > The end date requested for a given date range in **YYYY-MM-DD** format. Future dates (T+1) are not accepted in this endpoint. **NOTE:** The input endDate must come AFTER the input startDate. example: '2021-11-30' frequency: name: frequency in: query schema: type: string enum: - D - W - M - AM - CQ - AY - CY - '' default: M description: | Controls the display frequency of the data returned. * **D** = Daily * **W** = Weekly, based on the last day of the week of the start date. * **M** = Monthly, based on the last trading day of the month. * **AM** = Monthly, based on the start date (e.g., if the start date is June 16, data is displayed for June 16, May 16, April 16 etc.). * **CQ** = Quarterly based on the last trading day of the calendar quarter (March, June, September, or December). * **AY** = Actual Annual, based on the start date. * **CY** = Calendar Annual, based on the last trading day of the calendar year. example: M schemas: factorsRequest: title: Factors Request Body description: Request object for requesting factors. type: object properties: ids: $ref: '#/components/schemas/ids' factors: $ref: '#/components/schemas/factorsParam' factorGroups: $ref: '#/components/schemas/factorGroupsParam' startDate: $ref: '#/components/schemas/startDate' endDate: $ref: '#/components/schemas/endDate' frequency: $ref: '#/components/schemas/frequency' required: - ids - factors - startDate - endDate factorsResponse: type: object title: Factors Response Object properties: data: description: Array of factors objects type: array items: $ref: '#/components/schemas/factors' factors: title: Factors Object type: object properties: requestId: description: Identifier that was used for the request. type: string example: TSLA-US fsymId: description: >- Factset Regional Security Identifier. Six alpha-numeric characters, excluding vowels, with an -R suffix (XXXXXX-R). Identifies the security’s best regional security data series per currency. For equities, all primary listings per region and currency are allocated a regional-level permanent identifier. The regional-level permanent identifier will be available once a SEDOL representing the region/currency has been allocated and the identifiers are on FactSet. type: string example: HTM0LK-R date: description: The as of date of the factors in YYYY-MM-DD format. type: integer example: 20210204 additionalProperties: type: object properties: integer: description: >- Factors with an Integer Data Type. These include commonly Flags or Indicators. type: integer example: adrFlag: 1 text: description: >- Factors with a String Data Type. These include reference and classification fields. type: string example: countryOfRisk: US number: description: >- Factors with a Number/Double data type. This is the most common factor type, encompassing the pre-calculated factor values. type: number format: double example: rsi21D: 12.34 required: - requestId - fsymId - date libraryRequest: title: Factors Request Body description: Request object for requesting factors. type: object properties: factors: $ref: '#/components/schemas/factorsParam' factorGroups: $ref: '#/components/schemas/factorGroupsParam' libraryResponse: type: object title: Library Response Object properties: data: description: Array of library objects type: array items: $ref: '#/components/schemas/library' library: title: Library Object type: object properties: factor: description: The Factor field that can be requested in the factors endpoint. type: string example: rsi21D name: description: The Name or Description of the Factor type: string example: 21D Relative Strength Index factorGroup: description: The Factor Group associated to the Factor. type: string example: Momentum sdfName: description: The Standard DataFeed name of the factor for use of mapping. type: string example: RSI_21D formula: description: The FactSet formula associated to the factor type: string example: QFL_RSI(0,21D) tags: description: Associated Tags regarding the factor for enhanced searching. type: string example: momentum,prices format: description: The data type of the factor, including integer, double, or string. type: string example: double ids: type: array items: type: string minItems: 1 maxItems: 3500 description: > The requested list of security identifiers. Accepted ID types include Market Tickers, SEDOL, ISINs, CUSIPs, or FactSet Permanent Ids. * Make Note - id limit of 3000 for defaults, otherwise the service is limited to a 30 second duration. This can be reached when increasing total number of metrics requested and depth of history. * example: - FDS-US factorsParam: type: array items: type: string minItems: 1 maxItems: 20 description: | List of Factors. example: - rsi21D - ulcer252D factorGroupsParam: type: array items: type: string minItems: 1 maxItems: 5 description: | List of Factor Groupings to return all factors within the group. example: - Momentum - Technical startDate: type: string description: > The start date requested for a given date range in **YYYY-MM-DD** format. Future dates (T+1) are not accepted in this endpoint. example: '2019-01-01' endDate: type: string description: > The end date requested for a given date range in **YYYY-MM-DD** format. Future dates (T+1) are not accepted in this endpoint. **NOTE:** The input endDate must come AFTER the input startDate. example: '2019-12-31' frequency: type: string enum: - D - W - M - AM - CQ - AY - CY - '' default: D description: | Controls the display frequency of the data returned. * **D** = Daily * **W** = Weekly, based on the last day of the week of the start date. * **M** = Monthly, based on the last trading day of the month. * **AM** = Monthly, based on the start date (e.g., if the start date is June 16, data is displayed for June 16, May 16, April 16 etc.). * **CQ** = Quarterly based on the last trading day of the calendar quarter (March, June, September, or December). * **AY** = Actual Annual, based on the start date. * **CY** = Calendar Annual, based on the last trading day of the calendar year. example: D errorResponse: type: object title: Error Response properties: status: description: status type: string example: Bad Request timestamp: description: timestamp in YYYY-MM-DD HH:MM:SS.SSS type: string example: '2019-11-01 11:09:41.918' format: date-time path: description: The Endpoint path {package}/version/{endpoint} type: string example: /factset-quant-factor-library/v1/factors message: description: The plain text error message type: string example: Validation Error subErrors: description: subErrors related to the error message. Null if not applicable. type: object properties: object: description: the operation ID type: string field: description: Parameter Field Name type: string message: description: Error message type: string rejectedValue: description: Rejected Values in an Array type: array items: type: string responses: '400': description: >- Bad Request. This can occur for several reasons. Please review the "message" for more details. content: application/json: schema: $ref: '#/components/schemas/errorResponse' examples: Bad Request - Date Format: $ref: '#/components/examples/badRequestDateFormat' Bad Request - Missing Required Parameter: $ref: '#/components/examples/badRequestRequiredParameter' Bad Request - Future Date: $ref: '#/components/examples/badRequestFutureDate' Bad Request - Invalid Parameter: $ref: '#/components/examples/badRequestInvalidParameters' Bad Request - Malformed JSON: $ref: '#/components/examples/badRequestMalformedJSON' Bad Request - Read Timeout: $ref: '#/components/examples/badRequestReadTimeout' '401': description: >- Unauthenticated USERNAME-SERIAL. Ensure you are logged in and have successfully generated an API KEY for the IP range you are connecting from. For more help, select the **Report Issue** in the top right corner of this Developer Portal specification card and choose Connectivity 401 or 403 Responses. content: application/json: schema: $ref: '#/components/schemas/errorResponse' examples: Bad Request - Date Format: $ref: '#/components/examples/unauthenticated' '403': description: >- The USERNAME-SERIAL attempted to request the endpoint is not authorized to access. The request was a legal request, but the servier is refusing to respond. Please reach out to FactSet Account Team for assistance with authorization. content: application/json: schema: $ref: '#/components/schemas/errorResponse' examples: Bad Request - Date Format: $ref: '#/components/examples/forbidden' '415': description: >- Unsupported Media Type. This error may be returned when the caller sends a resource in a format that is not accepted by the server. This can be fixed by ensuring that Content-Type header is set to the correct value. In this instance, "application/json" would be the appropriate value. content: application/json: schema: $ref: '#/components/schemas/errorResponse' examples: Bad Request - Date Format: $ref: '#/components/examples/unsupportedMediaType' '500': description: Internal Server Error. content: application/json: schema: $ref: '#/components/schemas/errorResponse' examples: Internal Server Error - Not Writable: $ref: '#/components/examples/notWritable' Internal Server Error - General Exception: $ref: '#/components/examples/generalException' examples: badRequestDateFormat: summary: Bad Request - Date Format description: >- This bad request occurs when a request doesn't use the YYYY-MM-DD in the date parameters. To resolve, convert your date to YYYY-MM-DD. value: status: Bad Request timestamp: '2019-10-31 16:08:07.945' path: /factset-quant-factor-library/v1/{endpoint} message: >- The date parameter 'startDate' must be in the following date format: YYYY-MM-DD subErrors: badRequestRequiredParameter: summary: Bad Request - Required Parameter Missing description: >- This error message occurs when the request does not include the required parameters. Required parameters are indicated with a red asterisks symbol in the specification file. value: status: Bad Request timestamp: '2020-06-12 15:48:42.016' path: /factset-quant-factor-library/v1/{endpoint} message: The parameter 'ids' is required and may not be empty. subErrors: badRequestFutureDate: summary: Bad Request - Future Date description: >- This error message occurs when a future date is requested in the startDate and endDate parameters. Please revise your request to include dates as of today's current date or any prior historical date. value: status: Bad Request timestamp: '2020-06-12 15:52:48.091' path: /factset-quant-factor-library/v1/{endpoint} message: >- The use of future dates is not applicable in this endpoint. Please revise your request to include dates up to today's current date. subErrors: badRequestInvalidParameters: summary: Bad Request - Invalid Parameters description: >- This error message occurs when a request parameter is used in which is not recognized by the service. Please revise your request to include only the parameters listed in the specification. Typical causes are spelling mistakes and use of improper casing. value: status: Bad Request timestamp: '2020-06-12 15:58:54.068' path: /factset-quant-factor-library/v1/{endpoint} message: >- Invalid Parameter (s): fakeParameterName1 fakeParameterName2. Please modify your request to use parameters outlined in the specification for this endpoint. subErrors: badRequestMalformedJSON: summary: Bad Request - Malformed JSON Request description: >- This error may be returned when the request body is specified as JSON, but is not in proper JSON format. value: status: Bad Request timestamp: '2019-11-05 09:48:29.18' path: /factset-quant-factor-library/v1/{endpoint} message: Malformed JSON Request subErrors: badRequestReadTimeout: summary: Bad Request - Read Timeout description: >- This error may be returned if it takes more than 29 seconds to hear back from the data fetch service. value: status: Bad Request timestamp: '2019-11-04 16:18:38.949' path: /factset-quant-factor-library/v1/{endpoint} message: The request took too long. Try again with a smaller request. subErrors: unauthenticated: summary: User Authentication Failed description: >- This occurs when a user is not properly authenticated or recognized by the service. Please double check the USERNAME-SERIAL and API-Key used to request and ensure you are within the IP range specified for the Key. Report Issue under 401 error for help with troubleshooting. value: status: User Authentication Failed timestamp: '2019-10-31 16:08:07.945' path: /factset-quant-factor-library/v1/{endpoint} message: User Authentication Failed. subErrors: forbidden: summary: Forbidden description: >- The USERNAME-SERIAL attempted to request the endpoint is not authorized to access. The request was a legal request, but the server is refusing to respond. Please reach out to FactSet Account Team for assistance with authorization. value: status: Forbidden timestamp: '2020-06-12 16:08:51.731' path: /factset-quant-factor-library/v1/{endpoint} message: >- USERNAME-SERIAL does not have permission to use /factset-quant-factor-library /v1/{endpoint} subErrors: unsupportedMediaType: summary: Unsupported Media Type description: >- This bad request occurs when the media type passed in the request is not supported. Currently the APIs only support 'application/json'. value: status: Unsupported Media Type timestamp: '2019-11-05 09:42:27.237' path: /factset-quant-factor-library/v1/{endpoint} message: >- text/html media type is not supported. Supported media types are application/json subErrors: notWritable: summary: Internal Server Error - Not Writable description: >- This error may be returned when the server encounters an error writing the JSON response. value: status: Internal Server Error timestamp: '2019-11-05 09:48:29.18' path: /factset-quant-factor-library/v1/{endpoint} message: Error writing JSON output subErrors: generalException: summary: Internal Server Error - General Exception description: >- This is the most general error that can be returned to by the service. Please `Report Issue` to FactSet. value: status: Internal Server Error timestamp: '2019-11-01 10:36:01.944' path: /factset-quant-factor-library/v1/{endpoint} message: Unexpected error subErrors: allMomentumFactors: summary: All Factors within the Momentum Factor Group description: > The full list of all Available Factors within the Quant Factor Library and associated metadata. value: data: - requestId: TSLA-US fsymId: HTM0LK-R date: 20210204 velocity63D: -1.191401 stochastic63D: 90.9372 retMom63D: 98.78822 resRetMom63D: 78.54154 rsi63D: 56.67103 accel63D: -0.028765 velocity60M: -3.235736 stochastic60M: 94.75916 retMom60M: 2363.3677 resRetMom60M: 591.6738 rsi60M: 64.24066 accel60M: 0.267243 pos52W: 0.944948 velocity36M: -6.626828 stochastic36M: 94.715614 retMom36M: 1143.1854 resRetMom36M: 638.36676 rsi36M: 65.190384 accel36M: 0.979066 velocity252D: -0.852137 stochastic252D: 94.49475 retMom252D: 434.1612 resRetMom252D: 367.46252 rsi252D: 53.134323 accel252D: 0.000095 velocity21D: -0.217818 stochastic21D: 74.77372 retMom21D: 16.266954 resRetMom21D: 9.280276 rsi21D: 52.803776 accel21D: -0.072563 pctb52Wh: -5.076635 pcta52Wl: 1119.2091 - requestId: AMZN-US fsymId: MCNYYL-R date: 20210204 velocity63D: -0.072986 stochastic63D: 70.69603 retMom63D: 0.035024 resRetMom63D: -7.520044 rsi63D: 48.196167 accel63D: 0.000632 velocity60M: -2.669928 stochastic60M: 92.212456 retMom60M: 523.7464 resRetMom60M: 228.5747 rsi60M: 56.239384 accel60M: -0.018686 pos52W: 0.875549 velocity36M: -2.098244 stochastic36M: 89.51504 retMom36M: 131.65356 resRetMom36M: 70.30792 rsi36M: 55.38508 accel36M: 0.187087 velocity252D: -0.226741 stochastic252D: 87.55489 retMom252D: 55.163074 resRetMom252D: 40.32742 rsi252D: 49.944817 accel252D: -0.003409 velocity21D: -0.34496 stochastic21D: 65.09483 retMom21D: 2.921224 resRetMom21D: -0.375038 rsi21D: 45.717327 accel21D: 0.021291 pctb52Wh: -6.748396 pcta52Wl: 103.718636 factorLibraryMomentum: summary: All Factors within the Momentum Factor Group description: > The full list of all Available Factors within the Quant Factor Library and associated metadata. value: data: - factor: velocity63D name: 63D Velocity factorGroup: Momentum sdfName: VELOCITY_63D formula: QFL_VELOCITY(0,63D) tags: momentum,prices format: double - factor: stochastic63D name: 63D Stochastic Oscillator" factorGroup: Momentum sdfName: STOCHASTIC_63D formula: QFL_STOCHASTIC(0,63D) tags: momentum,prices format: double - factor: retMom63D name: 63D Return Momentum factorGroup: Momentum sdfName: RET_MOM_63D formula: QFL_RET_MOM(0,63D) tags: momentum,prices format: double - factor: resRetMom63D name: 63D Residual Momentum factorGroup: Momentum sdfName: RES_RET_MOM_63D formula: QFL_RES_RET_MOM(0,63D) tags: momentum,prices format: double - factor: rsi63D name: 63D Relative Strength Index factorGroup: Momentum sdfName: RSI_63D formula: QFL_RSI(0,63D) tags: momentum,prices format: double - factor: accel63D name: 63D Acceleration factorGroup: Momentum sdfName: ACCEL_63D formula: QFL_ACCEL(0,63D) tags: momentum,prices format: double - factor: velocity60M name: 60M Velocity factorGroup: Momentum sdfName: VELOCITY_60M formula: QFL_VELOCITY(0,60M) tags: momentum,prices format: double - factor: stochastic60M name: 60M Stochastic Oscillator factorGroup: Momentum sdfName: STOCHASTIC_60M formula: QFL_STOCHASTIC(0,60M) tags: momentum,prices format: double - factor: retMom60M name: 60M Return Momentum factorGroup: Momentum sdfName: RET_MOM_60M formula: QFL_RET_MOM(0,60M) tags: momentum,prices format: double - factor: resRetMom60M name: 60M Residual Momentum factorGroup: Momentum sdfName: RES_RET_MOM_60M formula: QFL_RES_RET_MOM(0,60M) tags: momentum,prices format: double - factor: rsi60M name: 60M Relative Strength Index factorGroup: Momentum sdfName: RSI_60M formula: QFL_RSI(0,60M) tags: momentum,prices format: double - factor: accel60M name: 60M Acceleration factorGroup: Momentum sdfName: ACCEL_60M formula: QFL_ACCEL(0,60M) tags: momentum,prices format: double - factor: pos52W name: 52W Position factorGroup: Momentum sdfName: POS52W formula: QFL_POS52W(0) tags: momentum,prices format: double - factor: velocity36M name: 36M Velocity factorGroup: Momentum sdfName: VELOCITY_36M formula: QFL_VELOCITY(0,36M) tags: momentum,prices format: double - factor: stochastic36M name: 36M Stochastic Oscillator factorGroup: Momentum sdfName: STOCHASTIC_36M formula: QFL_STOCHASTIC(0,36M) tags: momentum,prices format: double - factor: retMom36M name: 36M Return Momentum factorGroup: Momentum sdfName: RET_MOM_36M formula: QFL_RET_MOM(0,36M) tags: momentum,prices format: double - factor: resRetMom36M name: 36M Residual Momentum factorGroup: Momentum sdfName: RES_RET_MOM_36M formula: QFL_RES_RET_MOM(0,36M) tags: momentum,prices format: double - factor: rsi36M name: 36M Relative Strength Index factorGroup: Momentum sdfName: RSI_36M formula: QFL_RSI(0,36M) tags: momentum,prices format: double - factor: accel36M name: 36M Acceleration factorGroup: Momentum sdfName: ACCEL_36M formula: QFL_ACCEL(0,36M) tags: momentum,prices format: double - factor: velocity252D name: 252D Velocity factorGroup: Momentum sdfName: VELOCITY_252D formula: QFL_VELOCITY(0,252D) tags: momentum,prices format: double - factor: stochastic252D name: 252D Stochastic Oscillator factorGroup: Momentum sdfName: STOCHASTIC_252D formula: QFL_STOCHASTIC(0,252D) tags: momentum,prices format: double - factor: retMom252D name: 252D Return Momentum factorGroup: Momentum sdfName: RET_MOM_252D formula: QFL_RET_MOM(0,252D) tags: momentum,prices format: double - factor: resRetMom252D name: 252D Residual Momentum factorGroup: Momentum sdfName: RES_RET_MOM_252D formula: QFL_RES_RET_MOM(0,252D) tags: momentum,prices format: double - factor: rsi252D name: 252D Relative Strength Index factorGroup: Momentum sdfName: RSI_252D formula: QFL_RSI(0,252D) tags: momentum,prices format: double - factor: accel252D name: 252D Acceleration factorGroup: Momentum sdfName: ACCEL_252D formula: QFL_ACCEL(0,252D) tags: momentum,prices format: double - factor: velocity21D name: 21D Velocity factorGroup: Momentum sdfName: VELOCITY_21D formula: QFL_VELOCITY(0,21D) tags: momentum,prices format: double - factor: stochastic21D name: 21D Stochastic Oscillator factorGroup: Momentum sdfName: STOCHASTIC_21D formula: QFL_STOCHASTIC(0,21D) tags: momentum,prices format: double - factor: retMom21D name: 21D Return Momentum factorGroup: Momentum sdfName: RET_MOM_21D formula: QFL_RET_MOM(0,21D) tags: momentum,prices format: double - factor: resRetMom21D name: 21D Residual Momentum factorGroup: Momentum sdfName: RES_RET_MOM_21D formula: QFL_RES_RET_MOM(0,21D) tags: momentum,prices format: double - factor: rsi21D name: 21D Relative Strength Index factorGroup: Momentum sdfName: RSI_21D formula: QFL_RSI(0,21D) tags: momentum,prices format: double - factor: accel21D name: 21D Acceleration factorGroup: Momentum sdfName: ACCEL_21D formula: QFL_ACCEL(0,21D) tags: momentum,prices format: double - factor: pctb52Wh name: '% Below 52W High' factorGroup: Momentum sdfName: PCTB52WH formula: QFL_PCTB52WH(0) tags: momentum,prices format: double - factor: pcta52Wl name: '% Above 52W Low' factorGroup: Momentum sdfName: PCTA52WL formula: QFL_PCTA52WL(0) tags: momentum,prices format: double