TWAP

Prices are susceptible to noise and volatility. Therefore, financial applications often average prices over time. Well-known methods include Moving Average, Exponential Smoothing, Time-weighted Average Price (TWAP), and Volume-weighted Average Price (VWAP)

Definition

TWAP (Time-Weighted Average Price) - calculates an average value over a specified time period, weighting each data point by the duration or frequency of updates.

TWAP is calculated as follows:

$$P_{\text{TWAP}} = \frac{\sum_{j} P_j \cdot T_j}{\sum_{j} T_j}$$

where $P_j$ is the value of the at the $j$-th measurement and $T_j$ is the change in time since the previous measurement.

Rationale and Properties

• Reduces the impact of rapid fluctuations in the data by spreading them out over time.

• Incorporates time factors, making the final output reflective of trends rather than single-point events.

• Offers smoother price data for algorithmic trading and liquidity management.

Limitations

• Less appropriate sensitive to fast market shifts or abrupt changes -smoothing over time makes TWAP less responsive than other algorithms.

• Requires additional storage of the historic data.