W-pivot instead of Mark Fisher's ACD system pivot
  1. Data for testing
  2. Point A
  3. Failed Point A
  4. Point C
  5. Pivot range
  6. W-pivot range -new
  7. Points A and C through the pivot
  8. Closing method -new
  9. Dynamics of Points A and C
  10. Significant time frames
  11. Entry and exit


6. W-pivot range

In chapter 5 some of the drawbacks of Mark Fisher’s pivot were revealed, which prompted me to create my own pivot.

In order to somehow distinguish it from Mark Fisher’s pivot, I called it the w-pivot, because it is based on the weight of the candle, as described below. The w-pivot range is calculated in a more complex way. Before presenting the formulas, I will describe its calculation in words. Let's take the daily w-pivot range as a basis. Each candle on a 1-minute price chart can be represented as a set of prices from low to high in increments of 1 tick. We assign weight to each candle and the price inside it. Weight is equal to the trading volume for a candle divided by the number of ticks in it and multiplied by the serial number of the candle within the day. The trading day for stocks on the Moscow Exchange starts at 10 a.m., and ends at 18-45 p.m. and lasts 525 minutes. So for stocks, the serial number of candles during the trading day varies from 1 to 525. The greater the trading volume of the candle and the closer the candle is to the end of the trading day, the greater the weight of the candle and the price levels inside it.

Weighted prices in increments of 1 tick of all candles within the trading day are summed up and divided by the sum of the weights. Thus, the average weighted price Ā for the previous trading day is obtained. After that, the standard deviation S of the weighted prices is calculated. Now we can define the w-pivot range as Ā±S/2. Candles with a large trading volume and towards the end of the trading day make the largest contribution to the w-pivot due to weight.

The formulas for calculating Ā, S and the w-pivot range are as follows:

Formulas for w-pivot range

w-pivot range =Ā± S/2

Ā – average weighted price
– average weighted price squared
S – standard deviation of average weighted price
Pij – price at j ticks above the low of candle number i (for the low j=1)
ni – number of ticks in candle number i
Vi – trading volume for candle number i
N – number of candles for the previous trading day

If the w-pivot is based on more than one day, then formulas are the same, only N is the number of candles for the previous several trading days.

The w-pivot is not the same for patterns (a) and (b) in Fig 5.2-5.3 from chapter 5 as Mark Fisher’s pivot. For pattern (a), the w-pivot is narrower and closer to the closing price of the trading day.

For a visual comparison of Mark Fisher’s pivot and the w-pivot, you can look at Fig 6.1.

Figure 6.1. Comparison of w-pivot and Fisher's pivot

Let's apply the mirror pivot approach described in chapter 5 for the w-pivot and compare the results with similar results for Mark Fisher's pivot. From a comparison of both pivots presented in Table A7, the following conclusions can be drawn:

The latter conclusion seems to favor w-pivot. On the other hand, the advantage of w-pivot is not absolute, because w-pivot does not always show better results. Point A and C through w-pivot approach does not always bring more profit than Point A and C through the pivot approach described in Chapter 7.