Forecasting of airfare prices using time series

Airline ticket purchase timing is a strategic problem that requires both historical data and domain knowledge to be solved consistently. Even with some historical information (often a feature of modern travel reservation web sites), it is difficult for consumers to make true cost-minimizing decisions. As product prices become increasingly available on the World Wide Web, consumers attempt to understand how corporations vary these prices over time. However, corporations change the prices based on proprietary algorithms and hidden variables. This work is devoted to the analysis of time series forecasting methods on the example of air tickets forecasting prices. Then, that information it is planned to build a system that will help customers to make purchasing decisions by forecasting how air ticket prices will evolve in the future.