MarketAPI logoMarketAPI

Extra indicators

LSMA: Least Squares Moving Average

The end point of the straight line that fits the last N closes best: a moving average that follows the slope.

阅读约 2 分钟 · 在实时图表上试用 ↗

用通俗的话解释

Instead of averaging, LSMA fits a straight line through the recent closes (linear regression) and takes where that line ends today. In a steady trend it sits almost on the price.

计算方法

For the last N closes, find the line a + b·k with the smallest squared distances (least squares) and plot its value at the newest candle.

b = (N Σk·y − Σk Σy) ÷ (N Σk² − (Σk)²),  a = (Σy − b Σk) ÷ N
LSMA = a + b × (N − 1)

如何使用

  • As a responsive trend line.
  • The slope (rising or falling) shows the direction of the last N candles.

得出结论

  • When the price moves far away from LSMA the trend is accelerating; returning to it means it is fading.

示例

EURUSD H1, LSMA(25): during a steady climb the line almost touches every close; the first close well below it signals the climb has broken.

示例中的价格仅作说明。

注意事项

  • It reacts fast and therefore overshoots at turning points.

一点历史

Linear regression goes back to Legendre and Gauss (early 1800s); traders adopted the rolling version in the 1980s and 1990s.

仅供学习参考。 没有任何指标或形态能预测未来，本页内容均不构成投资建议。