This guide explores several time series features using FactSet Tick Data, including TIME_SLICE, ASOF_JOIN, and RANGE BETWEEN for insights into trade data. Aggregating time-series data through downsampling reduces data size and storage needs, using functions like TIME_SLICE and DATE_TRUNC for efficiency. ASOF JOIN simplifies joining time-series tables, matching trades with the closest previous quote, ideal for transaction-cost analysis in financial trading. Windowed aggregate functions, such as moving averages using the RANGE BETWEEN window frame, allow trend analysis over time, accommodating data gaps for flexible rolling calculations.
For prerequisites, environment setup, step-by-step guide and instructions, please refer to the QuickStart Guide.