#CurrencyPairPrediction
Step 1: Data Collection
Collect data from sources like:
Exchange rates: e.g., from Yahoo Finance, OANDA, or Alpha Vantage
Economic indicators: e.g., FRED, World Bank, IMF
News and sentiment data: e.g., Google News, Twitter API
Market data: e.g., order book, volume, open/close/high/low
Step 2: Data Preprocessing
Normalize/scale exchange rate data
Convert time series into supervised format (e.g., lagged variables)
Handle missing data and outliers
Convert dates to features (e.g., day of week, month)
Step 3: Feature Engineering
Create meaningful predictors such as:
Technical indicators: RSI, MACD, Bollinger Bands
Lag features: past exchange rates
Rolling averages: moving average of prices
Volatility indicators
#CurrencyPairPrediction
Step 1: Data Collection
Collect data from sources like:
Exchange rates: e.g., from Yahoo Finance, OANDA, or Alpha Vantage
Economic indicators: e.g., FRED, World Bank, IMF
News and sentiment data: e.g., Google News, Twitter API
Market data: e.g., order book, volume, open/close/high/low
Step 2: Data Preprocessing
Normalize/scale exchange rate data
Convert time series into supervised format (e.g., lagged variables)
Handle missing data and outliers
Convert dates to features (e.g., day of week, month)
Step 3: Feature Engineering
Create meaningful predictors such as:
Technical indicators: RSI, MACD, Bollinger Bands
Lag features: past exchange rates
Rolling averages: moving average of prices
Volatility indicators