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281 to 290 of 691 Results

DJIIQDr.npy Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems Unknown - 41.4 KB - MD5: 7dfeecb07d4935ab9979ba694a5e051b Numpy file for the quasi-derivative of the mean of DJI daily fractional return between 1 Jan 2003 and 31 Dec 2023.
DJIIQDvar.npy Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems Unknown - 41.4 KB - MD5: 0d7a4d552e25f9aeb6dd220ba3acc1b1 Numpy file for the quasi-derivative of the variance of DJI daily fractional return between 1 Jan 2003 and 31 Dec 2023.
GOOGdates.npy Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems Unknown - 144.4 KB - MD5: 930cecec0b93bf738b2518d1eece5b2a Numpy file for trading dates of GOOG between 2005 and 2023.
GOOGprices.npy Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems Unknown - 37.5 KB - MD5: 1117bdf493d0cbdc83290dcd11ac87be Numpy file for daily closing prices of GOOG between 2005 and 2023.
GOOGr.npy Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems Unknown - 37.5 KB - MD5: ff26ed7c78458289af8056b624e2c269 Numpy file for daily fractional returns of GOOG between 2005 and 2023.
GOOGt.npy Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems Unknown - 144.3 KB - MD5: 61e2f2933f4af6b1185cf01ae53fa4d6 Numpy file for trading dates of GOOG daily fractional returns between 2005 and 2023.
IQDDJIAHurst.py Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems Python Source Code - 5.6 KB - MD5: d26e474c1e38ee77580c62dcca96011a Python script to compute the integrated quasi-derivative of the Hurst exponent for the DJI daily fractional return between 1 Jan 2003 and 31 Dec 2023.
IQDDJIA.py Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems Python Source Code - 1.8 KB - MD5: 30ec34e5a62c9a106bc0d3e43aeed592 Python script to compute and plot the integrated quasi-derivative of the mean of the DJI daily fractional return between 1 Jan 2003 and 31 Dec 2023, using w = 100.
IQDDJIAvar.py Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems Python Source Code - 1.8 KB - MD5: 03c3b7107adbb10cbaed1054cd8f181a Python script to compute and plot the integrated quasi-derivative of the variance of the DJI daily fractional return between 1 Jan 2003 and 31 Dec 2023, using w = 100.
MSFTprices.npy Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems Unknown - 37.5 KB - MD5: 8be420856133e3ebaa393e07e98a96fa Numpy file for daily closing prices of MSFT between 2005 and 2023.

DJIIQDr.npy

Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems

Unknown - 41.4 KB -

Numpy file for the quasi-derivative of the mean of DJI daily fractional return between 1 Jan 2003 and 31 Dec 2023.

DJIIQDvar.npy

Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems

Unknown - 41.4 KB -

Numpy file for the quasi-derivative of the variance of DJI daily fractional return between 1 Jan 2003 and 31 Dec 2023.

GOOGdates.npy

Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems

Unknown - 144.4 KB -

Numpy file for trading dates of GOOG between 2005 and 2023.

GOOGprices.npy

Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems

Unknown - 37.5 KB -

Numpy file for daily closing prices of GOOG between 2005 and 2023.

GOOGr.npy

Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems

Unknown - 37.5 KB -

Numpy file for daily fractional returns of GOOG between 2005 and 2023.

GOOGt.npy

Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems

Unknown - 144.3 KB -

Numpy file for trading dates of GOOG daily fractional returns between 2005 and 2023.

IQDDJIAHurst.py

Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems

Python Source Code - 5.6 KB -

Python script to compute the integrated quasi-derivative of the Hurst exponent for the DJI daily fractional return between 1 Jan 2003 and 31 Dec 2023.

IQDDJIA.py

Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems

Python Source Code - 1.8 KB -

Python script to compute and plot the integrated quasi-derivative of the mean of the DJI daily fractional return between 1 Jan 2003 and 31 Dec 2023, using w = 100.

IQDDJIAvar.py

Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems

Python Source Code - 1.8 KB -

Python script to compute and plot the integrated quasi-derivative of the variance of the DJI daily fractional return between 1 Jan 2003 and 31 Dec 2023, using w = 100.

MSFTprices.npy

Sep 23, 2024 - Quasi-Differentiation and Its Applications to Noisy Time Series Data from Complex Systems

Unknown - 37.5 KB -

Numpy file for daily closing prices of MSFT between 2005 and 2023.

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