A Weighted Moving Average is designed to give the current or the recent price more weight than the previous prices - this is calculated by multiplying each of the previous interval's data by a weight based on the period length in the Weighted Moving Average. Each price is multiplied by a factor of the period; the current price has the highest weighing factor, with the weighing factor decreasing by a value of 1 throughout the previous prices in the period.

**Pane**: Overlay

Formula

MOV_Wt = ((Xt * W1) + (Xt-1* W2) + ... (Xt-n+1 * Wn)) / (W1 + W2 + ... Wn)

X = Symbol price (Workstation uses "close" as the default)

W = Weight factor; calculated by assigning a position number, "P" (starting with the most recent bar) to apply to the calculation: Wn = | Position - n | + 1

n = Period length

Example

3-day Weighted Moving Average:

X-Factor |
X-Value |
W |
Position |
n |
W-Value (|Position - n|) + 1 |

Xt |
1284.2 |
W1 |
1 |
3 |
3 |

Xt-1 |
1311.7 |
W2 |
2 |
3 |
2 |

Xt-1+n |
1334.4 |
Wn |
3 |
3 |
1 |

1. |
Weighting Factor: |
W1 = | 1 - 3 | + 1 = 3 W2 = | 2 - 3 | + 1 = 2 W3 = | 3 - 3 | + 1 = 1 |

2. |
MOV_Wt = |
((1284.2 * 3) + (1311.7 * 2) + (1334.4 * 1)) / (3 + 2 + 1) |

3. |
MOV_Wt = |
((3852.6) + (2623.4) + (1334.4)) / 6 |

4. |
MOV_Wt = |
7810.4 / 6 |

5. |
MOV_Wt = |
1301.73 |

Parameters

*Period*. The number of bars
in a chart. If the chart displays daily data, then period denotes days;
in weekly charts, the period will stand for weeks, and so on. Workstation
uses a default period of 9.

Interpretation

Since a Weighted Moving Average assigns more importance to recent price values, it is more sensitive to price activity than the Simple Moving Average. The Weighted Moving Average tends to stick closer to the trend. Analysts use the Weighted Moving Average in the same manner and for the same purposes as the other Moving Averages, although the advantage of the Weighted Moving Average is that it provides stronger and earlier indications to trend direction and reversal because it focuses on the more recent price data.

Literature

Kaufman, Perry J. The New Commodity Trading System and Methods. 1987.

Murphy, John J. The Visual Investor. New York, NY: John Wiley & Sons, Inc. 1996.

Maxwell, J. R. Commodity Futures Trading with Moving Averages. 1976.

Colby, Robert F., Myers, Thomas. A. The Encyclopedia of Technical Market Indicators. Dow Jones – Irwin. Homewood, IL. 1988.

Pring, Martin J. Technical Analysis Explained.

Lebeau, Charles, and Lucas, David. Technical Trader’s Guide to Computer Analysis of the Futures Market. Homewood, IL: Business One Irwin, 1991.