Financial Data Analysis by SDE Modeling with YUIMA

Key Points

• This research aims to demonstrate financial time series modeling using stochastic differential equations through the YUIMA package in R.
• Utilized the YUIMA package in R for statistical modeling of financial time series data.
• Analyzed daily time series data of USD/JPY exchange rates from 2001 to 2024.
• Conducted model selection to identify volatility-induced stationarity in the exchange rate.
• Demonstrated the possibility of volatility-induced stationarity in USD/JPY exchange rates.
• Identified model selection findings that align with previous research on U.S. short-term interest rates.