READY SIGNAL CONTROL DATA

US / Euro Foreign Exchange Rate

Why Use This Data Source In Your Models?

Incorporating the U.S. Dollar to Euro foreign exchange rate into your models is crucial for assessing the economic health and GDP performance of both the United States and European Union countries. This exchange rate serves as a key indicator, reflecting the strength of both economies and their relative competitiveness in global markets. Fluctuations in the exchange rate provide insights into investor sentiment, capital flows, and market trends, influencing trade dynamics and investment decisions between the U.S. and EU. Additionally, changes in the exchange rate may indicate shifts in monetary policy by the Federal Reserve and the European Central Bank, impacting inflation, interest rates, and overall economic conditions in both regions. Overall, the U.S. Dollar to Euro exchange rate plays a vital role in economic analysis and decision-making, offering valuable insights into the intertwined economic fortunes of the United States and the European Union.

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Automated Data Profiling

Ready Signal automatically profiles each data set and offers up suggested industry standard data science treatments to utilize with these data in your models.

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 = 2.27 p-value = 0.01 indicates that the data is not stationary.

Distribution Analysis:

The Shapiro-Wilk test returned W = 0.95 with a p-value =0.00 indicating the data does not follow a normal distribution.

A skewness score of 0.47 indicates the data are fairly symmetrical.

Hartigan's dip test score of 0.02 with a p-value of 0.00 inidcates the data is multimodal

Statistics (Pearson P/ df, lower => more normal)

No transform

23.57

Box-cox

4.60

Log_b(x-a)

5.12

sqrt(x+a)

5.55

exp(x)

7.21

arcsinh(x)

5.51

Yeo-Johnson

4.45

OrderNorm

1.10

Auto Correlation Function

Auto Correlation Function After Differencing

Partial Auto Correlation Function

Seasonal Impact

Seasonal and Trend Decompostion

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