LSMA: Least Squares Moving Average

ایده به زبان ساده

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.

روش محاسبه

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)

نحوه استفاده

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

نتیجه‌گیری

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

مراقب این‌ها باشید

• It reacts fast and therefore overshoots at turning points.

کمی تاریخچه

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