Least Squares Moving Average (LSMA)
Last updated
Last updated
The Least Squares Moving Average (LSMA), also known as the Linear Regression Indicator or Time Series Forecast, is a type of moving average that uses linear regression to determine the best-fit line for price over a specific period. Instead of simply averaging prices, LSMA projects the current value based on the slope of that line — essentially estimating where price should be based on recent trends.
This makes LSMA a predictive trend-following tool, which not only smooths price data but also aims to forecast short-term direction with a higher degree of accuracy than many traditional moving averages.
The LSMA calculates a straight line that best fits the prices over a defined period using the least squares method — a statistical technique that minimizes the sum of the squared differences between actual prices and the estimated trendline.
Once the best-fit line is calculated, the value at the last point of the line becomes the LSMA for the current candle. As price data updates, the regression line shifts, and a new LSMA value is plotted.
This process allows LSMA to react more quickly to market changes compared to traditional moving averages like SMA (Simple Moving Average) or EMA (Exponential Moving Average).
When price is above the LSMA and the line is sloping upward, the market is generally considered to be in an uptrend.
When price is below the LSMA and the line is sloping downward, the market is considered to be in a downtrend.
A crossover of price above or below the LSMA can be used as a potential entry or exit signal.
Because LSMA reacts faster to price changes, it may offer early trend detection, but this also increases the chance of false signals during choppy markets.
The LSMA can be customized with different lengths depending on the trader’s strategy:
14-period LSMA: Useful for capturing short-term trends and momentum changes.
25–50-period LSMA: Offers a balanced view, reducing noise while staying reactive.
100+ periods: Used by long-term traders for identifying macro trend direction.
A popular approach is to use two LSMAs with different periods — one fast and one slow — and trade based on their crossovers, similar to a dual-moving-average strategy.
Use LSMA to confirm trend direction before entering trades. For example:
Enter long trades only when price is above a rising LSMA.
Enter short trades only when price is below a falling LSMA.
Combine a short-period LSMA with a longer-period LSMA:
When the short LSMA crosses above the long LSMA → Buy Signal
When the short LSMA crosses below the long LSMA → Sell Signal
Watch for sharp LSMA bends or flattening slopes. These often signal momentum shifts and can provide early warning signs of trend changes.
In some cases, LSMA can act as dynamic support or resistance, especially in trending markets. Price may "bounce" off the line, offering entry or exit points.
🔸 Overtrading in Sideways Markets LSMA is highly responsive to price movements, which can lead to false signals in ranging markets. Always confirm with volume or additional indicators.
🔸 Relying on LSMA Alone While LSMA is powerful, it works best when combined with other tools such as MACD, RSI, or volume indicators for better confirmation.
🔸 Improper Settings Using extremely short periods can make the LSMA too sensitive, while very long periods may lag excessively. Backtest to find a balance suitable for your trading style.
The Least Squares Moving Average offers traders a forward-looking perspective by applying linear regression to price action. Its predictive nature and quick responsiveness make it a powerful tool for identifying trends and potential reversals early.
However, with this power comes the risk of overreacting to noise, so it should be used with discipline and confirmed by other indicators or market context.
Whether you're a short-term scalper or a long-term trend follower, LSMA deserves a spot in your trading toolkit — especially if you’re seeking an edge in fast-moving crypto markets.
