Currency Exchange Rate Forecasting
Overview
The USD – INR conversion rate is a crucial economic indicator for India and the United States that impacts various sectors including import-export business, foreign investment, tourism, etc. Analyzing historical data and forecasting future exchange rates can provide valuable insights and help stakeholders mitigate risk, optimize currency conversions, and plan financial strategies effectively.
The dataset contains the value of INR for 1 USD for a given time. Below are all the features in the data:
- Date: The date represents the specific day of the exchange rate data. It is important to follow the chronological order of the observations of the exchange rate.
- Open: The opening price refers to the exchange rate at the start of a specific trading period, such as the opening price for the day or the week. It represents the initial value at which the USD-INR conversion rate was traded.
- High: The high price represents the highest exchange rate observed during a specific trading period. It means the maximum value reached by the USD-INR conversion rate during this period.
- Low: The low price represents the lowest exchange rate observed during a specific trading period. It indicates the minimum value reached by the USD-INR conversion rate during this period.
- Closing: The closing price represents the exchange rate at the end of a specific trading period, such as the closing price for the day or the week. It shows the final value at which the USD-INR conversion rate was traded.
- Adjusted Closing: The Adjusted Closing Price takes into account any corporate actions, such as stock splits or dividends, that may affect the Closing Price. In the context of USD-INR conversions, this feature could represent an adjusted closing exchange rate.
- Volume: Volume refers to the total number of USD-INR currency pairs traded during a specific trading period. It quantifies market activity and liquidity for the given exchange rate.
Objectives
Your task is to analyze historical USD – INR exchange rate data and develop a forecasting model to predict future exchange rates. The goal is to help individuals, businesses, and financial institutions make informed decisions about foreign exchange and international trade.