[1]
Here are representative usage examples of IQML [2]. Many more examples and detailed information are available in the IQML User Guide [3]. Please email us (IQML@undocumentedmatlab.com [4]) if you have any questions.
The following examples are listed below:
- Get market data (snapshot) for a security [5]
- Get fundamental data for a security [6]
- Get latest interval bars for a security [7]
- Calculate option Greeks, fair value and implied volatility [8]
- Get historic/intra-day data [9]
- Get streaming quotes data [10]
- Get news data [11]
- Get options/futures chain [12]
- Connect/disconnect from IQFeed [13]
- Get connection information/stats [14]
- Specify message event callbacks [15]
1) Get market data (snapshot) for a security
[3]
>> 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 [3] for a detailed description of the available functionality.
No other solution provides this rich set of features – not even close.
Don’t take our word for it – request a fully-functional free trial version, and check for yourself! You will not be disappointed.
If you have any question, don’t hesitate to email us at IQML@undocumentedmatlab.com for additional information.
Free trial version
[1]Download a free trial of IQML with detailed installation and usage instructions. There are absolutely no strings attached: the trial is completely free and fully functional, just limited in duration (15 days).
You only need the basic Matlab, no toolbox is required. You can be up and running within minutes. We are confident that you will love the product, so we encourage you to test it:
Download your free 15-day trial now! [1] (or email us at IQML@undocumentedmatlab.com for additional information)
Legal disclaimer
THIS SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESSED OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES, LOSS OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
(detailed disclaimer is available in IQML’s User Guide [3])