NDK_XCFTEST

Last Modified on 04/20/2016 1:39 pm CDT
int __stdcall NDK_XCFTEST ( double *  X,
double *  Y,
size_t  N,
int  K,
double  target,
double  alpha,
WORD  method,
WORD  retType,
double *  retVal 
)

Calculates the test stats, p-value or critical value of the correlation test.

Returns
status code of the operation
Return values
NDK_SUCCESS  Operation successful
NDK_FAILED  Operation unsuccessful. See Macros for full list.
Parameters
[in] X is the first univariate time series data (a one dimensional array).
[in] Y is the second univariate time series data (a one dimensional array).
[in] N is the number of observations in X (or Y).
[in] K is the lag order (e.g. k=0 (no lag), k=1 (1st lag), etc.).
[in] target is the assumed correlation value. If missing, a default of zero is assumed.
[in] alpha is the statistical significance level. If missing, a default of 5% is assumed.
[in] method is the desired correlation coefficient (1=Pearson (default), 2=Spearman, 3=Kendall). If missing, a Pearson coefficient is assumed.
[in] retType is a switch to select the return output:
Method Value Description
TEST_PVALUE 1 P-Value
TEST_SCORE 2 Test statistics (aka score)
TEST_CRITICALVALUE 3 Critical value.
[out] retVal is the calculated test statistics.
Remarks
  1. The XCF test hypothesis: \[H_{o}: \rho_{x,y}=0\] \[H_{1}: \rho_{x,y} \neq 0\] Where:
    • \(H_{o}\) is the null hypothesis ($\hat\rho$ is not different from zero)
    • \(H_{1}\) is the alternate hypothesis (\(\hat\rho\) is statistically significant)
    • \(\rho_{x,y}\) is the correlation factor between population X and Y
  2. The time series is homogeneous or equally spaced.
  3. The significance level (i.e. alpha) is only needed for calculating the test critical value.
  4. The time series may include missing values (NaN) at either end.
  5. This is a two-tails (sides) test, so the computed p-value should be compared with half of the significance level (\(\alpha\)).
Requirements
Header SFSDK.H
Library SFSDK.LIB
DLL SFSDK.DLL
Examples
Namespace:  NumXLAPI
Class:  SFSDK
Scope:  Public
Lifetime:  Static
int NDK_XCFTEST ( double[]  pData1,
double[]  pData2,
UInPtr  nSize,
int  nLag,
double  target,
double  alpha,
UInt16  method,
UInt16  retType,
out double  retVal 
)

Calculates the test stats, p-value or critical value of the correlation test.

Returns
status code of the operation
Return values
NDK_SUCCESS  Operation successful
NDK_FAILED  Operation unsuccessful. See Macros for full list.
Parameters
[in] pData1 is the first univariate time series data (a one dimensional array).
[in] pData2 is the second univariate time series data (a one dimensional array).
[in] nSize is the number of observations in X (or Y).
[in] nLag is the lag order (e.g. k=0 (no lag), k=1 (1st lag), etc.).
[in] target is the assumed correlation value. If missing, a default of zero is assumed.
[in] alpha is the statistical significance level. If missing, a default of 5% is assumed.
[in] method is the desired correlation coefficient (1=Pearson (default), 2=Spearman, 3=Kendall). If missing, a Pearson coefficient is assumed.
[in] retType is a switch to select the return output:
Method Value Description
TEST_PVALUE 1 P-Value
TEST_SCORE 2 Test statistics (aka score)
TEST_CRITICALVALUE 3 Critical value.
[out] retVal is the calculated test statistics.
Remarks
  1. The XCF test hypothesis: \[H_{o}: \rho_{x,y}=0\] \[H_{1}: \rho_{x,y} \neq 0\] Where:
    • \(H_{o}\) is the null hypothesis ($\hat\rho$ is not different from zero)
    • \(H_{1}\) is the alternate hypothesis (\(\hat\rho\) is statistically significant)
    • \(\rho_{x,y}\) is the correlation factor between population X and Y
  2. The time series is homogeneous or equally spaced.
  3. The significance level (i.e. alpha) is only needed for calculating the test critical value.
  4. The time series may include missing values (NaN) at either end.
  5. This is a two-tails (sides) test, so the computed p-value should be compared with half of the significance level (\(\alpha\)).
Exceptions
Exception Type Condition
None N/A
Requirements
Namespace NumXLAPI
Class SFSDK
Scope Public
Lifetime Static
Package NumXLAPI.DLL
Examples

	







  




	
References

	
Hull, John C.; Options, Futures and Other DerivativesFinancial Times/ Prentice Hall (2011), ISBN 978-0132777421 


Hans-Peter Deutsch; , Derivatives and Internal Models, Palgrave Macmillan (2002), ISBN 0333977068



John Y. Campbell,  Andrew W. Lo,  A. Craig MacKinlay,  Andrew Y. Lo; The Econometrics of Financial Markets; Princeton University Press; 2nd edition(Dec 09, 1996), ISBN: 691043019
 
* Hamilton, J .D.; Time Series Analysis  , Princeton University Press (1994), ISBN 0-691-04289-6 


* Tsay, Ruey S.;  Analysis of Financial Time Series  John Wiley & SONS. (2005), ISBN 0-471-690740 


* D. S.G. Pollock; Handbook of Time Series Analysis, Signal Processing, and Dynamics; Academic Press; Har/Cdr edition(Nov 17, 1999), ISBN: 125609906


* Box, Jenkins and Reisel; Time Series Analysis: Forecasting and Control; John Wiley & SONS.; 4th edition(Jun 30, 2008), ISBN: 470272848




	

    

   		
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