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    Using SAS to Analyze Data Entered In Excel
    Source: http://www.at.vcu.edu/ucs/faq/sasexcel.htm

    SAS Import Wizard

    Both SAS Version 6.12 and Version 8 on the PC have Import Data features on the File menu. These "Wizards" will create SAS datasets from Excel spreadsheets as well as delimited and other types of files. The disadvantage of this method is that the Wizard chooses the amount of space to store the data. It is usually NOT the most efficient storage. For very large files this may become a serious handicap. Also SAS has reported problems that can result in missing data (http://www.sas.com/service/techsup/unotes/SN/006/006123.html). Therefore we recommend using the method below of saving your Excel worksheet as a csv file and writing your own DATA step to import the csv file.

    1. Creating a .csv file in Excel:

    Use Excel spreadsheet as a quick data entry tool. Enter the name of the variables on the first row of the spreadsheet (remember to use a maximum of 8 characters foryour variable names) and then enter your data in subsequent rows in the appropriate columns. If a column is too narrow to contain the values of that variable, simply position your mouse on the right margin for that column and drag it as far to the right as necessary. Do not have any blank rows in the spreadsheet. Enter data on only one sheet.

    If you have any dates:

    Select the cells containing the dates and format them with leading zeros:

    Select Format, Cells..., Number tab
    In the Category: list select: Date
    In the Type: list select 03/04/97.
    Select the OK button.

    When you have entered all of your data and are ready to save it:

    Select File, Save As.

    In the box labeled File name: enter the name of your file.
    In the Save as type box, choose CSV (Comma delimited) (*.csv).
    Select the Save button.
    You will see a message that the selected file type will save only the
    active sheet.
    Click OK .

    2. Creating a SAS Program to read a .csv file:
    SAMPLE SAS PROGRAM FOR PC SAS:

    * This sample program reads a file named study.csv in c:\sasrawd
    data new;
    infile ¡¥C:\sasrawd\study.csv' dsd missover firstobs=2;
    length lname $ 15;
    input id lname $ fname $ age sex $;
    run;
    proc print;
    title ¡¥Study Data Saved As Comma Delimited From Excel';
    run;



    SAMPLE SAS PROGRAM FOR UNIX SYSTEMS:

    *This sample program for UNIX reads a file study.csv in the data;
    *subdirectory for username jouser in department dep.;
    data new;
    infile ¡¥/home/dep/jouser/data/study.csv' dsd missover firstobs=2;
    length lname $ 15;
    input id lname $ fname $ age sex $;
    run;
    proc print;
    title ¡¥Study Data Saved As Comma Delimited From Excel';
    run;

    In the above examples, in the infile statement dsd tells SAS the data is comma delimited. missover tells SAS there may be missing data at the end of a line and that SAS should not skip to the next line searching for that data. firstobs=2 causes SAS to skip the first line of the data file, which contains the names of your variables.

    The length statement is necessary because you are using list input to read your data. Without a preceding length statement, SAS assumes that character variables (designated by the $ following the variable name) are a maximum of eight characters long. Be sure the value specified on the length statement accommodates the maximum length for that variable or the value will be truncated.

    Note: A quick way to build your input statement with the same variables as in your Excel spreadsheet is to use Windows Copy and Paste. To do so on the PC open your .csv file in Notepad (Start, Programs, Accessories, Notepad). To do so on our UNIX systems, use HostExplorer to login and open the .csv file in your favorite editor. Select the variable names. Select Edit, Copy. In your editor, open the SAS program file and position the insertion point on your input statement line.
    Select Edit, Paste. To complete your input statement, delete the commas, insert $
    for character variables and add the ending semicolon. Use a length statement for
    variables longer than 8 characters.
    ¡@
    Other useful SAS links: SAS sample online
    ¡@ SAS sample program library
    ¡@ SAMPLE
    ¡@ CU
    ¡@ NCSU
    ¡@ LECTURE
    ¡@ LABEL
    ¡@ STATISTICAL MATERIAL
    ¡@ Useful SAS Program            
    SAS Program description

    libname my 'c:\China';

    run;

    ¡@

    data d; set my.kstar;

    LNGDP=log(GDP);

    LNLAB=log(LAB);

    LNCAP=log(CAP);

    RATIO=CAP/LAB;

    LNRAT=log(RATIO);

    /*

    LNRATSQ=LNRAT**2;

    */

    GDPLAB=GDP/LAB;

    LNGDPL=log(GDP/LAB);

    LAGLAB=lag(LNLAB);

    LAGCAP=lag(LNCAP);

    LAGGDPL=lag(LNGDPL);

    LAGRAT =lag(LNRAT);

    LAGTREND=lag(TREND);

    DLNGDPL=LNGDPL-LAGGDPL;

    DLNRAT=LNRAT-LAGRAT;

    DLNLAB=LNLAB-LAGLAB;

    /******************************SERIAL CORRELATION*********/

    /*

    GDPLSTAR=LNGDPL-0.555951*LAGGDPL;

    RATSTAR=LNRAT-0.555951*LAGRAT;

    TRENDST=TREND-0.555951*LAGTREND;

    */

    /****************************** TIFA 4 sources********************/

    ¡@

    LAGSA=lag(SA);

    LAGDL=lag(DL);

    LAGFI=lag(FI);

    LAGSRF=lag(SRF);

    ¡@

    ¡@

    DLFISR=DL+FI+SRF;

    FISRSA=FI+SRF+SA;

    SRSADL=SRF+SA+DL;

    SADLFI=SA+DL+FI;

    LADLFISR=lag(DLFISR);

    LAFISRSA=lag(FISRSA);

    LASRSADL=lag(SRSADL);

    LASADLFI=lag(SADLFI);

    ¡@

    LNSADLFI=log(SADLFI);

    LNDLFISR=log(DLFISR);

    LNFISRSA=log(FISRSA);

    LNSRSADL=log(SRSADL);

    LNSA=log(SA);

    LNDL=log(DL);

    LNFI=log(FI);

    LNSRF=log(SRF);

    ¡@

    Y=(DLNGDPL-0.020251)/0.578033+DLNLAB;

    SAL=SA/LAB;

    DLL=DL/LAB;

    FIL=FI/LAB;

    SRL=SRF/LAB;

    LNSAL=log(SAL);

    LNDLL=log(DLL);

    LNFIL=log(FIL);

    LNSRL=log(SRL);

    run;

    ¡@

    /******************************** eq 4**************/

    data source; set d;

    if _n_ >= 17;

    run;

    pro reg data=source;

    title 'regression using 1980-1998 observations';

    model LNGDPL= LNSAL LNDLL LNFIL LNSRL;

    model LNGDPL= LNSAL LNDLL LNFIL LNSRL TREND;

    model LNGDPL= LNRAT TREND;

    model LNGDPL= LNRAT;

    run;

    proc print data= source;

    var YEAR LNGDPL CAP SA DL FI SRF LAB LNSAL LNDLL LNFIL LNSRL;

    run;

    ¡@

    ¡@

    /* CAP Y SADLFI DLFISR FISRSA SRSADL SA DL FI SRF;*/

    ¡@

    ¡@

    /*

    pro reg data=source;

    model LNGDP= LNLAB LNSADLFI LNSRF;

    model LNGDP= LNLAB LNDLFISR LNSA;

    model LNGDP= LNLAB LNFISRSA LNDL;

    model LNGDP= LNLAB LNSRSADL LNFI;

    run;

    */

    /*

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations: DLFISR SA';

    Y=log(DLFISR+B1*SA)-log(LADLFISR+B2*LAGSA);

    ENDO Y; EXO DLFISR SA LADLFISR LAGSA;

    PARMS B1 B2;

    run;

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations, FISRSA DL';

    Y=log(FISRSA+B1*DL)-log(LAFISRSA+B2*LAGDL);

    ENDO Y; EXO FISRSA DL LAFISRSA LAGDL;

    PARMS B1 B2;

    run;

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations, SRSADL FI';

    Y=log(SRSADL+B1*FI)-log(LASRSADL+B2*LAGFI);

    ENDO Y; EXO SRSADL FI LASRSADL LAGFI;

    PARMS B1 B2;

    run;

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations: SADLFI SRF';

    Y=log(SADLFI+B1*SRF)-log(LASADLFI+B2*LAGSRF);

    ENDO Y; EXO SADLFI SRF LASADLFI LAGSRF;

    PARMS B1 B2;

    run;

    */

    /*

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations: SADLFI SRF';

    Y=A*log(SADLFI+B*SRF);

    ENDO Y; EXO SADLFI SRF;

    PARMS A B;

    run;

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations: DLFISR SA';

    Y=A*log(DLFISR+B*SA);

    ENDO Y; EXO DLFISR SA;

    PARMS A B;

    run;

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations, FISRSA DL';

    Y=A*log(FISRSA+B*DL);

    ENDO Y; EXO FISRSA DL;

    PARMS A B;

    run;

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations, SRSADL FI';

    Y=A*log(SRSADL+B*FI);

    ENDO Y; EXO SRSADL FI;

    PARMS A B;

    run;

    */

    ¡@

    ¡@

    /********************************** WHOLE DATASET 1952-1998 ************/

    ¡@

    /****************************************EQUATION 3******/

    /*

    proc reg data=d;

    title 'USE I hat: regression using 1952-1998 observations';

    model DLNGDPL=DLNRAT /dw;

    run;

    proc print data=d;

    title 'regression using 1952-1998 observations';

    run;

    */

    ¡@

    ¡@

    /*model GDPLSTAR=RATSTAR TRENDST/dw;

    run;*/ /****************************SERIAL CORRELATION******/

    ¡@

    /*

    proc reg data=d;

    title 'regression using 1952-1998 observations';

    model LNGDP=LNCAP LNLAB /dw;

    model LNGDP=LNCAP LNLAB TREND /dw;

    model LNGDPL=LNRAT /dw;

    model LNGDPL=LNRAT TREND /dw;

    output out=b r=residual p=yhat /dw;

    model LNGDPL=LNRAT LNRATSQ TREND /dw;

    run;

    */

    ¡@

    /*

    data b; set b;

    run;

    proc print data=b;

    title 'residual of the model LNGDPL=LNRAT TREND';

    var residual;

    run;

    */

    /************************* 1978-1998**************************/

    /*

    data post; set d;

    if _n_ >= 15;

    run;

    proc print data=post;

    title 'regression using 1978-1998 observations';

    run;

    ¡@

    proc reg data=post;

    title 'regression using 1978-1998 observations';

    model GDPLSTAR=RATSTAR TRENDST/dw;

    run;

    */

    /*

    model LNGDP=LNCAP LNLAB /dw;

    model LNGDP=LNCAP LNLAB TREND /dw;

    model LNGDPL=LNRAT /dw;

    model LNGDPL=LNRAT TREND /dw;

    model LNGDPL=LNRAT LNRATSQ TREND /dw;

    run;

    */

    ¡@

    /********************************** CHOW TEST ************/

    /*

    proc reg data=d;

    title 'Chow Test:regression using 1952-1998 observations';

    model LNGDPL=LNRAT TREND;

    run;

    ¡@

    ¡@

    ¡@

    data pre; set d;

    if _n_ < 15;

    run;

    proc print data=pre;

    title 'Chow Test:regression using 1952-1977 observations';

    var YEAR LNGDPL LNRAT ;

    run;

    proc reg data=pre;

    title 'Chow Test:regression using 1952-1977 observations';

    model LNGDPL=LNRAT ;

    run;

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    proc print data=post;

    title 'Chow Test:regression using 1978-1998 observations';

    var YEAR LNGDPL LNRAT TREND;

    run;

    proc reg data=post;

    title 'Chow Test:regression using 1978-1998 observations';

    model LNGDPL=LNRAT TREND;

    run;

    */

    ¡@

    /************** TIFA 4 SOURCES this is not used as the coeff is out of expectation*********/

    ¡@

    /*

    data post; set d;

    if _n_ >= 17;

    run;

    proc print data=post;

    title 'regression using 1980-1998 observations';

    run;

    proc reg data=post;

    title 'regression using 1980-1998 observations';

    model LNGDP= LNLAB LNSADLFI LNSRF;

    model LNGDP= LNLAB LNDLFISR LNSA;

    model LNGDP= LNLAB LNFISRSA LNDL;

    model LNGDP= LNLAB LNSRSADL LNFI;

    run;

    ¡@

    */
    Libname
    SAS Program description

    option linesize=76 pagesize=65;

    libname my 'c:\China';

    data my.second;

    set work.first;

    run;
    After Importing the data.csv file and defining its name as "work.first", we can create a permanent SAS data set in a subdirectory 'c:\China'.

    To do this, we first define a location in your c drive to carry the file and name this library as "my" or anything you like. The syntax is:

    libname name of the ref 'location';

    We then put the "work.first" temporary set into a new data set call it  "my.second"
     

    option linesize=76 pagesize=65;

    libname my 'c:\China';

    data my.second;

    run;
    To use the permanent data set, we just need to tell which the library it was stored and the name of the data we created earlier.
    Non-Linear
    SAS Program description

    option linesize=76 pagesize=65;

    libname my 'c:\China';

    run;

    ¡@

    data d; set my.kstar;

    LNGDP=log(GDP);

    LNLAB=log(LAB);

    LNCAP=log(CAP);

    RATIO=CAP/LAB;

    LNRAT=log(RATIO);

    GDPLAB=GDP/LAB;

    LNGDPL=log(GDP/LAB);

    LAGLAB=lag(LNLAB);

    LAGCAP=lag(LNCAP);

    LAGGDPL=lag(LNGDPL);

    LAGRAT =lag(LNRAT);

    LAGTREND=lag(TREND);

    DLNGDPL=LNGDPL-LAGGDPL;

    DLNRAT=LNRAT-LAGRAT;

    DLNLAB=LNLAB-LAGLAB;

    /****************************** TIFA 4 sources********************/

    ¡@

    LAGSA=lag(SA);

    LAGDL=lag(DL);

    LAGFI=lag(FI);

    LAGSRF=lag(SRF);

    ¡@

    DLFISR=DL+FI+SRF;

    FISRSA=FI+SRF+SA;

    SRSADL=SRF+SA+DL;

    SADLFI=SA+DL+FI;

    LADLFISR=lag(DLFISR);

    LAFISRSA=lag(FISRSA);

    LASRSADL=lag(SRSADL);

    LASADLFI=lag(SADLFI);

    ¡@

    LNSADLFI=log(SADLFI);

    LNDLFISR=log(DLFISR);

    LNFISRSA=log(FISRSA);

    LNSRSADL=log(SRSADL);

    LNSA=log(SA);

    LNDL=log(DL);

    LNFI=log(FI);

    LNSRF=log(SRF);

    ¡@

    Y=(DLNGDPL-0.020251)/0.578033+DLNLAB;

    SAL=SA/LAB;

    DLL=DL/LAB;

    FIL=FI/LAB;

    SRL=SRF/LAB;

    LNSAL=log(SAL);

    LNDLL=log(DLL);

    LNFIL=log(FIL);

    LNSRL=log(SRL);

    run;
    Use the permanent data file.

    ¡@

    ¡@

    Define variable.

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations: DLFISR SA';

    Y=log(DLFISR+B1*SA)-log(LADLFISR+B2*LAGSA);

    ENDO Y; EXO DLFISR SA LADLFISR LAGSA;

    PARMS B1 B2;

    run;

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations, FISRSA DL';

    Y=log(FISRSA+B1*DL)-log(LAFISRSA+B2*LAGDL);

    ENDO Y; EXO FISRSA DL LAFISRSA LAGDL;

    PARMS B1 B2;

    run;

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations, SRSADL FI';

    Y=log(SRSADL+B1*FI)-log(LASRSADL+B2*LAGFI);

    ENDO Y; EXO SRSADL FI LASRSADL LAGFI;

    PARMS B1 B2;

    run;

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations: SADLFI SRF';

    Y=log(SADLFI+B1*SRF)-log(LASADLFI+B2*LAGSRF);

    ENDO Y; EXO SADLFI SRF LASADLFI LAGSRF;

    PARMS B1 B2;

    run;

    /************************************************/

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations: SADLFI SRF';

    Y=A*log(SADLFI+B*SRF);

    ENDO Y; EXO SADLFI SRF;

    PARMS A B;

    run;

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations: DLFISR SA';

    Y=A*log(DLFISR+B*SA);

    ENDO Y; EXO DLFISR SA;

    PARMS A B;

    run;

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations, FISRSA DL';

    Y=A*log(FISRSA+B*DL);

    ENDO Y; EXO FISRSA DL;

    PARMS A B;

    run;

    proc sysnlin data=source;

    title 'regression using 1980-1998 observations, SRSADL FI';

    Y=A*log(SRSADL+B*FI);

    ENDO Y; EXO SRSADL FI;

    PARMS A B;

    run;
    Use non-linear OLS to estimate the variables.

    ¡@

    Define model, exogenous variables and endogenous variables.

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    ¡@

    An other non-linear example.

    ¡@

    ¡@

    ¡@
    First Step
    SAS Program description

    model LNGDPL=LNRAT TREND /dw;

    output out=b r=residual p=yhat /dw;

    run;
    Collect the residual.

    ¡@
    SecondStep
    SAS Program description

    data d; set b

    lagres=lag(residual); run;

    proc reg;

    model residual = lagres / noint;

    run;
    Run regression Ut again Ut-1.

    ¡@
    ThirdStep:Cochrane-Orcutt 2-step model
    SAS Program description

    GDPLSTAR=LNGDPL-0.555951*LAGGDPL;

    RATSTAR=LNRAT-0.555951*LAGRAT;

    TRENDST=TREND-0.555951*LAGTREND;

    model GDPLSTAR=RATSTAR TRENDST/dw;
    To solve the problem of serial correlation, we define y* and x* using the coefficient of the last regression( 0.55595).

    ¡@

    Chow Test

    SAS Program description

    proc reg data=d;

    title 'Chow Test:regression using 1952-1998 observations';

    model LNGDPL=LNRAT TREND;

    run;

    data pre; set d;

    if _n_ < 15;

    run;

    proc print data=pre;

    title 'Chow Test:regression using 1952-1977 observations';

    var YEAR LNGDPL LNRAT ;

    run;

    proc reg data=pre;

    title 'Chow Test:regression using 1952-1977 observations';

    model LNGDPL=LNRAT ;

    run;

    data post; set d;

    if _n_ >= 15;

    run;

    proc print data=post;

    title 'Chow Test:regression using 1978-1998 observations';

    var YEAR LNGDPL LNRAT TREND;

    run;

    proc reg data=post;

    title 'Chow Test:regression using 1978-1998 observations';

    model LNGDPL=LNRAT TREND;

    run;
    Use all observations to get the ESSR

     

     

     

     

    Use the first 15 observations to get the ESS1

     

     

     

     

     

     

     

     

     

    Use the rest observations to get the ESS2

    Calculate the F statistic:

    =[ (ESSR - ESS1 -ESS2)/(N-K)]/
    [ ESS1 + ESS2] / (N-K)

    N is number of observations
    K is number of parameters include intercept

    E.G. ESSR 's degree of freedom is 35-3 = 32 
    ESS1 's degree of freedom is 14-2 = 12 
    ESSR 's degree of freedom is 21-3 = 18
    ¡@

    We have  F(2,30)   distriburion.

    ¡@

     Recommended References
    Topic Book/Publication Author Comments
    All markets www.finmath.com Various Comprehensive website on references, seminars, workshops, etc.
    All markets www.e-analytics.com Equity Analytics, Ltd. Comprehensive website for cash and derivatives instruments and analytics
    Bonds How the Bond Market Works Robert Zipf Good book for understanding the basic features of the US bond market and how it operates
    Credit derivatives Credit Derivatives and Credit Linked Notes Satyajit Das Intermediate to advanced text on credit derivatives
    Derivatives Mastering Derivatives Markets Francesca Taylor Derivatives explained in simple terms
    Derivatives Derivatives in Plain Words Hong Kong Monetary Authority Good book for understanding derivatives, without much mathematics
    Derivatives from a back office perspective www.swapjungle.com Roseanne Stanzione Good site for back-office professionals working with derivatives
    Equity How the Stock Market Works John Dalton Good book for understanding the basic features of the US stock market and how it operates
    Investing across asset classes Pioneering Portfolio Management David Swensen An excellent resource filled with tips and anecdotes from the CIO of the Yale University endowment.
    Many fixed income securities and derivatives The Handbook of Fixed Income Securities Frank Fabozzi Excellent resource covering many types of fixed income securities with emphasis on pricing and market terminology
    Money Market Money Market and Bond Calculations Marica Stigum and Franklin Robinson Excellent guide to money market instruments and calculations
    Options and Futures Options, Futures, and other Derivatives John Hull Excellent resource for understanding pricing and market terminology
    Repos Mastering Repo Markets Robert Steiner Excellent resource covering all aspects of repos, without much mathematics
    Settlement After the Trade is Made David Weiss Excellent resource for operational flow of securities transactions
    Swaps Mastering Swaps Markets Alan McDougall Swaps explained in simple terms
    Swaps The Swaps Handbook Kenneth Kapner and John Marshall Excellent resource for understanding the basic to intermediate levels of swaps
    Various mathematical and financial models http://finance.bi.no/~bernt/ gcc_prog/algoritms/ algoritms/node73.html Bernt Arne Odegaard Excellent resource for mathematical and financial models
    Various www.finpipe.com Financial Pipeline, Inc. Educational website dedicated to finance

    ¡@
    Market Risk Topic Book/Publication Author Comments
    Market Risk Management The Professional´s Handbook of Financial Risk Management Marc Lore and Lev Borodovsky Many chapters written by different risk managers, explaining practical issues to managing risk
    Overall Risk Management Risk Standards For Institutional Investment Managers and Institutional Investors Risk Standards Working Group http://www.cmra.com/html/ the_risk_standards.html
    Value-at-risk Value at Risk Philippe Jorion Good resource for understanding VAR and its limitations
    ¡@ ¡@ ¡@ ¡@
    Credit Risk Topic Book/Publication Author Comments
    Credit Rating Agencies Credit ratings and complementary sources of credit quality information [www.bis.org/publ/index.htm] BIS Basle Committee on Banking Supervision Comprehenisve resource for understanding the global picture with regards to credit ratings

    Pricing & Risk Models

    Type Organization Website
    Basic finance calculators - NPV, IRR, etc. DataDynamica International Inc. www.jamesko.com
    Basic finance calculators - PV, FV, annuities, etc. Datachimp www.datachimp.com
    Bonds CMS BondEdge www.cms-info.com
    Bond, CB, option, and warrant pricing models University of California at Irvine www-sci.lib.uci.edu/HSG/RefCalculators.html (for securities and derivatives calculators, select "Part I: O-Z" and then select "Stocks, Bonds, Options, Commodities")
    Convertibles, options, etc. Numa Financial Systems Ltd. www.numa.com
    Market risk management Barra www.barra.com
    Models to price energy, equity, fixed income and weather options, VAR, yield curve generators, etc. Financial Engineering Associates www.fea.com
    Models to price equity and fixed income options, VAR and volatility FinTools Software www.fintools.com
    Option pricing models In-The-Money www.in-the-money.com
    Option pricing models Chicago Board Options Exchange www.cboe.com/tools
    Option pricing models The William Margrabe Group, Inc www.FreeOptionPricing.com
    Option pricing models Schaeffer´s Investment Research, Inc. www.adtrading.com
    Personal finance calculators Financenter www.financenter.com
    Personal and business finance calculators Smart Money Magazine www.smartmoney.com
    VAR GloriaMundi www.gloriamundi.org
    Various - links to software vendors supplying various pricing models Swaps Monitor Publications, Inc. www.swapsmonitor.com

    Useful trade organizations

    Scope Organization Website
    Accounting International Accounting Standards "IAS" www.ias.org
    Banking Regulators Bank for International Settlements www.bis.org
    Derivatives International Swaps and Derivatives Association "ISDA" www.isda.org
    Fund Management Association for Investment Management and Research "AIMR" www.aimr.com
    Hedge Funds Alternative Investment Management Association "AIMA" www.aima.org
    Risk Management Global Association of Risk Professionals "GARP" www.garp.com

    Market Data

    Type Organization Website
    Bonds Bond Market Association www.bondmarkets.com
    Bonds Bondsonline Group Inc. www.bondsonline.com
    Bonds BondBasics, Inc. www.bondbasics.com
    Bonds Cambridge Group Investments, Ltd. www.bondpage.com
    Bonds Debttraders, Inc. www.debttraders.com
    Bonds in emerging markets BradyNet, Inc. www.bradynet.com
    Convertible bonds Morgan Stanley www.convertbond.com
    Economic data and commentaries Global Insight, Inc. economics.dri-wefa.com
    Economic data and commentaries Deutsche Bank www.yardeni.com
    Economic data and commentaries The US government www.whitehouse.gov/news/fsbr.html
    Economic data and commentaries The US Federal Reserve www.federalreserve.gov
    Economic data and commentaries The World Bank www.worldbank.org
    Economic data and commentaries Bank of Japan www.boj.or.jp
    Economic data and commentaries Bundesbank www.bundesbank.de
    Economic data and commentaries Bank of France www.banque-france.fr
    Economic data and commentaries Bank of England www.bankofengland.co.uk
    Economic data and commentaries US Conference Board www.conference-board.org
    Economic data and commentaries - links to many useful sites US National Association for Business Economics www.nabe.com/a>
    Energy GlobalView Software, Inc. www.gvsi.com
    Equities, futures, and options Tenfore Systems, Ltd. www.itrader.org
    Equities and mutual funds William F. Sharpe www.wsharpe.com
    Equities and mutual funds Morningstar, Inc. www.morningstar.com
    Equities, mutual funds, and other WebFinance, Inc. www.investorguide.com
    Equities and mutual funds Intuit, Inc. www.quicken.com
    Emerging markets The Emerging Markets Companion, Inc. www.emgmkts.com
    Fund managers Nelson Management Network www.nelnet.com
    Hang Seng Index constituents HSI Services Ltd. www.hsi.com.hk
    Japan investing Gaijin Investor Inc. www.gaijininvestor.com
    Mutual funds Standard & Poor´s www.funds-sp.com
    Indexes Ryan Labs, Inc. www.ryanlabs.com
    Mutual Funds The Mutual Fund Education Alliance www.mfea.com
    News in Asian finance FinanceAsia www.financeasia.com
    Options and volatility figures ivolatility.com www.ivolatility.com
    Options Options Clearing Corporation www.optionsclearing.com
    Options Chicago Board Options Exchange www.cboe.com
    Options Options Industry Council www.optionscentral.com
    Real estate investment trusts National Association of Real Estate Investment Trusts www.nareit.com
    Real estate, equities, and other financial products InRealty www.inrealty.com
    Real estate, equities, and other financial products Investor Home www.investorhome.com
    US Treasuries US Bureau of Public Debt www.publicdebt.treas.gov
    Various Amex and Nasdaq exchanges www.amex.com
    Various Bloomberg www.bloomberg.com/asia
    Various CQG, Inc. www.cqg.com
    Various World Federation of Exchanges www.fibv.com
    Various Moneyline www.moneyline.com
    Various - data provided by various vendors Smart Money Magazine www.smartmoney.com
    Various - data, models, and useful links James Garven www.finweb.com
    Various - data, models, and useful links Ibbotson Associates www.ibbotson.com
    Various - links to software vendors supplying various pricing models Swaps Monitor Publications, Inc. www.swapsmonitor.com
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