TED Interest Rate Spread
Why Use This Data Source In Your Models?
The TED spread measures the difference between the interest rate on risk free debt, short-term US government treasury bills, and the interest rate on interbank loans. This indicates credit risk in the US.
TED Interest Rate Spread
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Automated Data Profiling
Suggested Treatment:
Grain Transformation:
Source:
Board of Governors of Fed Reserve System
Release:
Selected Interest Rates
Units:
Percent, Not Seasonally Adjusted
Frequency:
Daily
Available Through:
01/21/2022
Suggested Treatment:
The data shows auto correlation and a non-normal distribution. The data should be differenced. While the Order Norm transformation, provides the best normality, the Yeo Johnson variable will also perform well.
Grain Transformation:
Data is unable to be distributed by time or geography. The roll up method used is Weighted Average.
Auto Correlation Analysis:
Data shows auto correlation indicating a need for differencing
The ACF indicates 1 order differencing is appropriate.
Further differencing is reccommended
Trend Analysis:
The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 1.59 p-value = 0.01 indicates that the data is not stationary.
Distribution Analysis:
The Shapiro-Wilk test returned W = 0.83 with a p-value =0.00 indicating the data does not follow a normal distribution.
A skewness score of 2.48 indicates the data are substantially skewed.
Hartigan's dip test score of 0.03 with a p-value of 0.00 inidcates the data is multimodal
Statistics (Pearson P/ df, lower => more normal)
Auto Correlation Function
Auto Correlation Function After Differencing
Partial Auto Correlation Function
Seasonal Impact
Seasonal and Trend Decompostion
Citation:
Federal Reserve Bank of St. Louis, TED Spread [TEDRATE], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/TEDRATE, December 15, 2019.