READY SIGNAL CONTROL DATA

Indian Rupees to U.S. Dollar Spot Exchange Rate

Why Use This Data Source In Your Models?

Incorporating the Indian Rupees to U.S. Dollar Spot Exchange Rate into your models can be helpful in analyzing trade dynamics, managing currency risk, forecasting financial outcomes, and conducting macroeconomic analysis. The Indian Rupees to U.S. Dollar Spot Exchange Rate is pivotal due to India's significant role in the global economy. Reflecting international trade dynamics and economic sentiment, fluctuations in this exchange rate offer insights into investor confidence, capital flows, and market trends both domestically and internationally. Managed by the Reserve Bank of India, changes in the exchange rate also indicate adjustments in monetary policy, impacting inflation, interest rates, and overall economic conditions. Given India's large and diverse economy, movements in the exchange rate directly affect trade competitiveness, while also serving as an indicator of broader economic trends in the South Asian region, emphasizing its importance for economic analysis and decision-making.

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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.

Following first order differencing, no further differencing is required based on the differenced ACF at lag one of -0.03

Trend Analysis:

The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 1.33 p-value = 0.01 indicates that the data is not stationary.

Distribution Analysis:

The Shapiro-Wilk test returned W = 0.98 with a p-value =0.00 indicating the data does not follow a normal distribution.

A skewness score of -0.04 indicates the data are fairly symmetrical.

Hartigan's dip test score of 0.04 with a p-value of 0.00 inidcates the data is multimodal

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

No transform

37.35

Box-cox

4.26

Log_b(x-a)

6.22

sqrt(x+a)

5.01

exp(x)

251.44

arcsinh(x)

6.22

Yeo-Johnson

4.26

OrderNorm

1.06

Auto Correlation Function

Auto Correlation Function After Differencing

Partial Auto Correlation Function

Seasonal Impact

Seasonal and Trend Decompostion

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