Here are representative usage examples of IQML. Many more examples and detailed information are available in the IQML User Guide. Please email us (IQML@undocumentedmatlab.com) if you have any questions.
The following examples are listed below:
- Get market data (snapshot) for a security
- Get fundamental data for a security
- Get latest interval bars for a security
- Calculate option Greeks, fair value and implied volatility
- Get historic/intra-day data
- Get streaming quotes data
- Get news data
- Get options/futures chain
- Connect/disconnect from IQFeed
- Get connection information/stats
- Specify message event callbacks
1) Get market data (snapshot) for a security
>> data = IQML('quotes', 'symbol','GOOG') data = Symbol: 'GOOG' Most_Recent_Trade: 1092.14 Most_Recent_Trade_Size: 1 Most_Recent_Trade_Time: '09:46:31.960276' Most_Recent_Trade_Market_Center: 25 Total_Volume: 113677 Bid: 1092.13 Bid_Size: 100 Ask: 1092.99 Ask_Size: 100 Open: 1099.22 High: 1099.22 Low: 1092.38 Close: 1090.93 Message_Contents: 'Cbaohlcv' Message_Description: 'Last qualified trade; A bid update occurred, An ask update occurred; An open declaration occurred; A high declaration occurred; A low declaration occurred; A close declaration occurred; A volume update occurred' Most_Recent_Trade_Conditions: '3D87' Trade_Conditions_Description: 'Intramaket Sweep; Odd lot trade' Most_Recent_Market_Name: 'Direct Edge A (EDGA)' |
Available parameters that affect the query: Symbols, Timeout, NumOfEvents, MsgParsingLevel, Fields, UseParallel.
2) Get fundamental data for a security
>> data = IQML('fundamental', 'symbol','IBM') data = Exchange_ID: 7 PE: 25.7 Average_Volume: 4588000 x52_Week_High: 180.95 x52_Week_Low: 139.13 Calendar_Year_High: 171.13 Calendar_Year_Low: 144.395 Dividend_Yield: 3.79 Dividend_Amount: 1.5 Dividend_Rate: 6 Pay_Date: '03/10/2018' Ex_dividend_Date: '02/08/2018' Short_Interest: 17484332 Current_Year_EPS: 6.17 Next_Year_EPS: [] Five_year_Growth_Percentage: -0.16 Fiscal_Year_End: 12 Company_Name: 'INTERNATIONAL BUSINESS MACHINE' Root_Option_Symbol: 'IBM' Percent_Held_By_Institutions: 59.9 Beta: 1.05 Leaps: [] Current_Assets: 49735 Current_Liabilities: 37363 Balance_Sheet_Date: '12/31/2017' Long_term_Debt: 39837 Common_Shares_Outstanding: 921168 Split_Factor_1: '0.50 05/27/1999' Split_Factor_2: '0.50 05/28/1997' Market_Center: [] Format_Code: 14 Precision: 4 SIC: 7373 Historical_Volatility: 25.79 Security_Type: 1 Listed_Market: 7 x52_Week_High_Date: '03/08/2017' x52_Week_Low_Date: '08/21/2017' Calendar_Year_High_Date: '01/18/2018' Calendar_Year_Low_Date: '02/09/2018' Year_End_Close: 153.42 Maturity_Date: [] Coupon_Rate: [] Expiration_Date: [] Strike_Price: [] NAICS: 541512 Exchange_Root: [] Option_Premium_Multiplier: [] Option_Multiple_Deliverable: [] Price_Format_Description: 'Four decimal places' Exchange_Description: 'New York Stock Exchange (NYSE)' Security_Type_Description: 'Equity' SIC_Description: 'COMPUTER INTEGRATED SYSTEMS DESIGN' NAICS_Description: 'Computer Systems Design Services' |
Available parameters that affect the query: Symbols, Timeout, MsgParsingLevel.
3) Get the latest interval bars for a security
>> data = IQML('intervalbars', 'Symbol','@VX#', 'NumOfEvents',4) data = 4×1 struct array with fields: Symbol BarType Timestamp Open High Low Close CummlativeVolume IntervalVolume NumberOfTrades >> data(1) ans = Symbol: '@VX#' BarType: 'Complete interval bar from history' Timestamp: '2018-09-05 12:36:00' Open: 14.45 High: 14.5 Low: 14.45 Close: 14.45 CummlativeVolume: 57077 IntervalVolume: 17 NumberOfTrades: 0 |
Available parameters that affect the query: Symbols, Timeout, NumOfEvents, MaxItems, MaxDays, IntervalType, IntervalSize, BeginFilterTime, EndFilterTime, BeginDateTime, MsgParsingLevel.
4) Calculate option Greeks, fair value and implied volatility
>> data = IQML('greeks', 'symbol','IBM1814L116') data = Symbol: 'IBM1814L116' Asset_Name: 'IBM DEC 2018 C 116.00' Strike_Price: 116 Expiration_Date: '12/14/2018' Days_To_Expiration: 30 Inferred_Asset_Side: 'Call' Underlying_Symbol: 'IBM' Underlying_Spot: 121.3 Underlying_Historic_Volatility: 37.1 Assumed_Risk_Free_Rate: 0 Assumed_Dividend_Yield: 0 Asset_Fair_Value: 8.1193 Asset_Latest_Price: 7.05 Asset_Price_Diff: 1.0693 Implied_Volatility: 0.28242 Delta: 0.68197 Vega: 0.12404 Theta: -0.076697 Rho: 6.1318 CRho: 6.7992 Omega: 10.189 Lambda: 10.189 Gamma: 0.027646 Vanna: -0.3527 Charm: 0.0021809 Vomma: 5.8043 Veta: 2.4262 Speed: -0.0012419 Zomma: -0.061581 Color: -0.00038078 Ultima: -45.238 Annual_Factor_Used: 365 This_Asset_Latest_Quote: [1×1 struct] Underlying_Latest_Quote: [1×1 struct] This_Asset_Fundamentals: [1×1 struct] Underlying_Fundamentals: [1×1 struct] |
Available parameters that affect the query: Symbols, Timeout, UseParallel, UnderlyingSymbol, HistoricVolatility, RiskFreeRate, DividendsYield, Side, DaysToExpiration, AnnualFactor.
5) Get historic/intra-day data
% Get historic daily data: >> data = IQML('history', 'symbol','IBM', 'dataType','day') % dataType is optional (default: 'day') data = 100×1 struct array with fields: Symbol Datestamp Datenum High Low Open Close PeriodVolume OpenInterest >> data(1) ans = Symbol: 'IBM' Datestamp: '2017-10-10' Datenum: 736978 High: 148.95 Low: 147.65 Open: 147.71 Close: 148.5 PeriodVolume: 4032601 OpenInterest: 0 >> highs = [data.High]; % array of High values % Get historic ticks data for the VIX continuous future (@VX#): >> data = IQML('history', 'symbol','@VX#', 'dataType','ticks'); >> data(1) ans = Symbol: '@VX#' Timestamp: '2018-03-09 06:47:57.899000' Datenum: 737128.283309016 Last: 17.12 LastSize: 1 TotalVolume: 3605 Bid: 17.1 Ask: 17.15 TickID: 4377589 BasisForLast: 'O' BasisDescription: 'Other trade = any trade not accounted for by C or E' TradeMarketCenter: 32 TradeMarketName: 'CBOE Futures Exchange (CFE)' TradeConditions: '4D' TradeDescription: 'Implied' |
Available parameters that affect the query: Symbols, DataType (day/week/month/interval/ticks), DataDirection, MaxItems, Days, BeginDate, EndDate, BeginDateTime, EndDateTime, BeginFilterTime, EndFilterTime, IntervalType, IntervalSize, Timeout, UseParallel, MsgParsingLevel.
6) Get streaming quotes data
The initial request to send streaming quotes for the VIX continuous future (@VX#):
IQML('quotes', 'Symbol','@VX#', 'NumOfEvents',100, 'MaxItems',10); |
Multiple symbols can be specified, as a cell-array or colon-delimited string:
IQML('quotes', 'NumOfEvents',100, 'Symbols','@VX#:GOOG:AAPL'); % alternative #1 IQML('quotes', 'NumOfEvents',100, 'Symbols',{'@VX#','GOOG','AAPL'}); % alternative #2 |
Subsequent requests to retrieve the latest accumulated data for a symbol, return a data struct that looks like this:
>> data = IQML('quotes', 'Symbol','@VX#', 'NumOfEvents',-1) data = Command: 'w@VX#' isActive: 1 EventsToProcess: 100 EventsProcessed: 43 LatestEventDatenum: 737128.637260451 LatestEventTimestamp: '20180309 15:17:39.303' DataType: 'quotes and trades' ProcessType: 'stream' BufferSize: 10 Buffer: [10×1 struct] LatestData: [1×1 struct] >> data.LatestData ans = Symbol: '@VX#' Most_Recent_Trade: 17.08 Most_Recent_Trade_Size: [] Most_Recent_Trade_Time: '08:06:20.716000' Most_Recent_Trade_Market_Center: 32 Total_Volume: 4507 Bid: 17.05 Bid_Size: 63 Ask: 17.1 Ask_Size: 244 Open: 17.2 High: 17.35 Low: 17 Close: 17.23 Message_Contents: 'Cbasohlcv' Message_Description: 'Last qualified trade; A bid update occurred; An ask update occurred; A settlement occurred; An open declaration occurred; A high declaration occurred; A low declaration occurred; A close declaration occurred; A volume update occurred' Most_Recent_Trade_Conditions: '4D' Trade_Conditions_Description: 'Implied' Most_Recent_Market_Name: 'CBOE Futures Exchange (CFE)' |
Available parameters that affect the query: Symbols, DataType (quotes/trades), NumOfEvents, MaxItems, Timeout, Fields.
Similarly, streaming interval bars, regional updates and Level-2 market depth updates can be requested using IQML('intervalbars',...), IQML('regional',...) and IQML('marketdepth',...) commands.
7) Get news data
News configuration:
>> data = IQML('news', 'DataType','config') data = Category: 'All News' Majors: [1×7 struct] >> {data.Majors.Description} ans = 1×7 cell array {'DTN News'} {'PR Newswire'} {'Business Wire'} {'Real-Time Trader'} {'GlobeNewswire Inc'} {'Marketwire'} {'Benzinga Pro'} % This shows that we are connected to 7 major news sources. We can drill-down for details about these news sources: >> data.Majors(1) % first of 7 Major news sources ans = Source: 'DTN' Description: 'DTN News' AuthenticationCode: '1D' IconID: 10 Minors: [1×4 struct] >> data.Majors(1).Minors(1) % 1st of 4 Minor DTN sources ans = Source: 'DT5' Description: 'Treasuries, Most Actives, Gainers, Losers' AuthenticationCode: '1D' >> data.Majors(1).Minors(2) % 2nd of 4 Minor DTN sources ans = Source: 'RTL' Description: 'Derivatives - Selected Futures and Options' AuthenticationCode: '2Ab' IconID: 10 |
News story headlines:
>> data = IQML('news', 'DataType','headlines') data = 1000×1 struct array with fields: Source ID Symbols Timestamp Text >> data(1) ans = Source: 'BEN' ID: 21991162633 Symbols: {'BZRatings' 'MNTX'} Timestamp: 20180305064533 Text: 'Manitex International Sees Q4 Sales $64.40M vs $64.45M Est...' % Limiting the headlines to specific symbols, events and/or news-sources: >> data = IQML('news', 'DataType','headlines', 'Symbols',{'IBM','GOOG','BZRatings'}, 'Sources',{'DTN','CPR','BEN'}); >> data = IQML('news', 'DataType','headlines', 'Symbols','IBM:GOOG:BZRatings', 'Sources','DTN:CPR:BEN'); % equivalent alternative data = 687×1 struct array with fields: Source ID ... |
News story full text:
>> data = IQML('news', 'DataType','story', 'ID',21991162633) data = ID: 21991162633 Symbols: {'BZRatings' 'MNTX'} Text: 'Manitex International Sees Q4 Sales $64.40M vs $64.45M Est. Manitex International (NASDAQ: MNTX) sees Q4 sales of $64.40M vs $64.45M estimate.' |
News story count:
>> data = IQML('news', 'DataType','number', 'Symbols','BSX:AAPL:GOOG') data = AAPL: 7 BSX: 14 GOOG: 2 % The query can be limited by symbol(s), news-source(s), and date(s): >> data = IQML('news', 'DataType','number', 'Symbols','BSX:GOOG:AAPL', 'BeginDate',20180301, 'EndDate',20180303) data = AAPL: 37 BSX: 3 GOOG: 13 |
Available parameters that affect the query: Symbols, Sources, DataType, Date, BeginDate, EndDate, MaxItems, GetStory, NumOfEvents, Timeout, UseParallel.
8) Get options/futures chains
% Report GOOG options having strike price between $1000-$1010 in next 4 months >> symbols = IQML('chain', 'symbol','goog', 'NearMonths',4, 'MinStrike',1000, 'MaxStrike',1010)' symbols = 1×58 cell array Columns 1 through 4 'GOOG1803H1000' 'GOOG1803H1010' 'GOOG1810H1000' 'GOOG1810H1005' Columns 5 through 8 'GOOG1810H1010' 'GOOG1813G1000' 'GOOG1813G1002.5' 'GOOG1813G1005' Columns 9 through 12 'GOOG1813G1007.5' 'GOOG1813G1010' 'GOOG1817H1000' 'GOOG1817H1005' ... % Fetch the options chain for a symbol along with the latest quotes for all options >> data = IQML('chain', 'symbol','GOOG', 'NearMonths',4, 'MinStrike',1000, 'MaxStrike',1010, 'WhatToShow','quotes') data = 58×1 struct array with fields: Symbol Most_Recent_Trade Most_Recent_Trade_Size Most_Recent_Trade_Time Most_Recent_Trade_Market_Center Total_Volume Bid Bid_Size Ask Ask_Size Open High Low Close ... >> data(1) ans = Symbol: 'GOOG1803H1000' Most_Recent_Trade: 120 Most_Recent_Trade_Size: 1 Most_Recent_Trade_Time: '15:57:12.930497' Most_Recent_Trade_Market_Center: 156 Total_Volume: 0 Bid: 140.5 Bid_Size: 3 Ask: 150.1 Ask_Size: 1 Open: [] High: [] Low: [] Close: 120 Message_Contents: 'Cbacv' Message_Description: 'Last qualified trade; A bid update occurred; An ask update occurred; A close declaration occurred; A volume update occurred' Most_Recent_Trade_Conditions: 1 Trade_Conditions_Description: 'Normal Trade' Most_Recent_Market_Name: 'MIAX PEARL Options exchange' % Fetch the options chain for a symbol along with the fundamental data for all options >> data = IQML('chain', 'symbol','GOOG', 'NearMonths',4, 'MinStrike',1000, 'MaxStrike',1010, 'WhatToShow','fundamental') data = 58×1 struct array with fields: Symbol Exchange_ID PE Average_Volume x52_Week_High x52_Week_Low Calendar_Year_High Calendar_Year_Low ... |
Available parameters that affect the query: Symbols, DataType (options/futures/spread/foptions), Side, WhatToShow, Months, NearMonths, Years, IncludeBinary, MinStrike, MaxStrike, NumInMoney, NumOutOfMoney, UseParallel.
9) Connect/disconnect from IQFeed
IQML('disconnect'); % disconnect from IQFeed (IQConnect) IQML('reconnect'); % disconnect and then automatically re-connect (optional parameters: Username, Password) |
10) Get connection information/stats
>> data = IQML('stats') data = ServerIP: '66.112.148.226' ServerPort: 60002 MaxSymbols: 1300 NumOfStreamingSymbols: 0 NumOfClientsConnected: 3 SecondsSinceLastUpdate: 1 NumOfReconnections: 0 NumOfAttemptedReconnections: 0 StartTime: 'Mar 07 11:03AM' MarketTime: 'Mar 07 04:34AM' ConnectionStatus: 'Connected' IQFeedVersion: '5.2.7.0' LoginID: '123456-1' TotalKBsRecv: 42.98 KBsRecvLastSecond: 0.02 AvgKBsPerSecRecv: 0.02 TotalKBsSent: 361.62 KBsSentLastSecond: 0.22 AvgKBsPerSecSent: 0.19 Exchanges: {1×16 cell} ServerVersion: '6.0.0.5' ServiceType: 'real_time' |
Additional port-specific stats can be requested using the optional AddPortStats parameter:
>> data = IQML('stats', 'AddPortStats',1) data = ServerIP: '66.112.148.224' ServerPort: 60005 ... Level2: [1×1 struct] Level2SymbolsWatched: 2 Lookup: [1×1 struct] RegionalSymbolsWatched: 2 Admin: [1×1 struct] Level1: [1×1 struct] Level1SymbolsWatched: 0 |
11) Specify message event callbacks
We can attach a user callback function to all IQFeed messages:
IQML('ProcessFunc',@IQML_Callback); % set a single callback function for all message types |
We can also specify specific callbacks for various message types, and a default callback for all other message types:
% Alternative #1: using the struct() function: callbacks = struct('System', [], ... % ignore System messages 'Quote_update',@IQML_Quote_Update_Callback, ... % Level-1 quote updates 'Market_depth',@IQML_Market_Depth_Callback, ... % Level-2 market-depth updates 'Default', @IQML_Default_Callback); % default callback for all other messages % Alternative #2: using direct field assignments: callbacks.System = []; % ignore System messages callbacks.Quote_update = @IQML_Quote_Update_Callback; callbacks.Market_depth = @IQML_Market_Depth_Callback; callbacks.Default = @IQML_Default_Callback); % Now update IQML with these callbacks: IQML('time', 'processFunc',callbacks); |
where the callback functions are defined similarly to the following (for example, in a file called IQML_Callback.m):
function IQML_Callback(iqObject, eventData, varargin) % Extract the basic event data components event_timestamp = eventData.Timestamp; % local time in Matlab's datenum format event_msg_port = eventData.MessagePort; % e.g. 'Level2' for a Market_depth event event_msg_type = eventData.MessageType; % e.g. 'Market_depth' event_msg_header = eventData.MessageHeader; % e.g. 'Z' for a Market_depth event event_msg_string = eventData.MessageString; % the complete message string from IQFeed event_msg_parts = eventData.MessageParts; % the parsed message, split into a cell-array % Now do something useful with all this information... ... end % IQML_Callback |
This was just a short sampling of IQML’s functionality. The product contains many more features and query types. Review the full IQML User Guide for a detailed description of the available functionality.
No other solution provides this rich set of features – not even close.
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If you have any question, don’t hesitate to email us at IQML@undocumentedmatlab.com for additional information.
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