Types of Means and Averages

The Simple Moving Average (SMA) calculates the arithmetic mean of a security's prices over a specified period. It smooths price data. It reduces noise. Traders use SMAs to identify trends and potentia

The Exponential Moving Average (EMA) assigns greater weight to recent data points. It reacts faster to price changes than a Simple Moving Average (SMA). This responsiveness makes it useful for identif

Volume-Weighted Average Price (VWAP) shows a security's average price over time. It factors in both price and traded volume. Institutions use VWAP to measure execution quality. Big orders move market

Time-Weighted Average Price (TWAP) orders execute a large order over a specified time. The algorithm aims to match the average price of the asset during that period. Traders use TWAP to minimize marke

The Bollinger Band midline and the Simple Moving Average (SMA) often look the same. Both calculate an average price over a set period. Their uses and implications for mean reversion strategies differ.

Traditional moving averages lag price. They use a fixed lookback period. Adaptive moving averages (AMAs) adjust their sensitivity. They react faster to trending markets and slower to choppy markets. T

Kernel-weighted averages assign distinct weights to data points. This differs from simple moving averages. Simple averages assign equal weight. It also differs from exponential moving averages. Expone

The arithmetic mean calculates a dataset's average. Sum all values. Divide by the count of values. It shows a central tendency. For example, five daily returns for AAPL: 1.0%, 0.5%, 1.2%, -0.8%, 1.1%.

Mean reversion strategies use an asset's average price. A simple arithmetic mean is highly sensitive to outliers. Extreme price movements skew the average. This distortion causes incorrect entry and e

Mean reversion posits asset prices return to an average over time. This average acts as a gravitational pull. Traders profit by identifying deviations from this mean. They buy undervalued assets and s