Accumulative Swing Index (ASI)

What Is the Accumulative Swing Index (ASI)?

The Accumulative Swing Index (ASI) is a trendline indicator used by technical traders to gauge the long-term trend in a security’s price, drawing on candlestick charts by collectively using its opening, closing, high, and low prices.

Understanding the Accumulative Swing Index

The Accumulative Swing Index (ASI) is a variation of J. Welles Wilder's swing index. The ASI was developed by Wilder as an improvement on the swing Index. Details discussing the ASI can be found in Wilder’s book "New Concepts in Technical Trading Systems."

The Accumulative Swing Index trendline is one of several trendlines that can be followed to provide support for technical analysts deciphering buy and sell signals. Other popular indicators include weighted alpha, moving average and the volume-weighted moving average.

The Accumulative Swing Index is charted as a trendline. It can be deployed through advanced technical charting software such as MetaStock, Worden TC2000, eSignal, NinjaTrader, Wave59 PRO2, EquityFeed Workstation, ProfitSource, VectorVest, and INO MarketClub. It is typically charted below the main price chart as a standalone trendline, graphed similar to volume bar charts. Both the Accumulative Swing Index and the Swing Index can be added to a technical analyst’s chart diagram.

Computing the Swing Index

In Wilder’s research, he set out to identify an index indicator that could provide information on a security’s price by collectively analyzing the security’s open, close, high, and low price. These prices charted on a daily candlestick pattern are integrated into the following equation developed by Wilder to arrive at a Swing Index measure.

SI = 50 × ( C y − C + 1 2 ( C y − O y ) + 1 4 ( C − O ) R ) × K T where: SI = Swing index C = Today’s closing price C y = Yesterday’s closing price H = Today’s highest price H y = Yesterday’s highest price K = The larger of  H y − C  and  L y − C L = Today’s lowest price L y = Yesterday’s lowest price O = Today’s opening price O y = Yesterday’s opening price R = Varies based on the relationship between C ,  H y  and  L y  (see table below)  T = The maximum amount of price change for the day \begin{aligned} &\text{SI} = 50 \times \left ( \frac{ C_y - C + \frac {1}{2} \left ( C_y - O_y \right ) + \frac {1}{4} \left ( C - O \right ) }{R} \right ) \times \frac {K}{T} \\ &\textbf{where:}\\ &\text{SI} = \text{Swing index} \\ &C = \text{Today's closing price} \\ &C_y = \text{Yesterday's closing price} \\ &H = \text{Today's highest price} \\ &H_y = \text{Yesterday's highest price} \\ &K = \text{The larger of } H_y - C \text{ and } L_y - C \\ &L = \text{Today's lowest price} \\ &L_y = \text{Yesterday's lowest price} \\ &O = \text{Today's opening price} \\ &O_y = \text{Yesterday's opening price} \\ &R = \text{Varies based on the relationship between} \\ &C \text{, } H_y \text{ and } L_y \text{ (see table below) } \\ &T = \text{The maximum amount of price change for the day} \\ \end{aligned} SI=50×(RCy−C+21(Cy−Oy)+41(C−O))×TKwhere:SI=Swing indexC=Today’s closing priceCy=Yesterday’s closing priceH=Today’s highest priceHy=Yesterday’s highest priceK=The larger of Hy−C and Ly−CL=Today’s lowest priceLy=Yesterday’s lowest priceO=Today’s opening priceOy=Yesterday’s opening priceR=Varies based on the relationship betweenC, Hy and Ly (see table below) T=The maximum amount of price change for the day

The Swing Index calculation was developed to incorporate differences between consecutive day closing prices and opening prices in consideration with a variable R defined below:

To obtain  R , first determine the largest of: (1)  H − C y (2)  L − C y (3)  H − L If (1) is largest,  R = H − C y − 1 2 ( L − C y ) + 1 4 ( C y − O y ) If (2) is largest,  R = L − C y − 1 2 ( H − C y ) + 1 4 ( C y − O y ) If (3) is largest,  R = H − L + 1 4 ( C y − O y ) \begin{aligned} &\text{To obtain } R \text{, first determine the largest of:} \\ &\text{(1) } H - C_y \\ &\text{(2) } L - C_y \\ &\text{(3) } H - L \\ &\\ &\text{If (1) is largest, } R = H-C_y - \frac{1}{2} ( L-C_y ) + \frac{1}{4} ( C_y - O_y ) \\ &\text{If (2) is largest, } R = L-C_y - \frac{1}{2} ( H-C_y ) + \frac{1}{4} ( C_y - O_y ) \\ &\text{If (3) is largest, } R = H-L + \frac{1}{4} ( C_y - O_y ) \\ \end{aligned} To obtain R, first determine the largest of:(1) H−Cy(2) L−Cy(3) H−LIf (1) is largest, R=H−Cy−21(L−Cy)+41(Cy−Oy)If (2) is largest, R=L−Cy−21(H−Cy)+41(Cy−Oy)If (3) is largest, R=H−L+41(Cy−Oy)

This core value is multiplied times 50 and K/T, where T is the maximum amount of a price change for the day.

What the Accumulative Swing Index Tells You

The Swing Index Value is then accumulated to form the Accumulated Swing Index trendline. This trendline value typically falls within a range of 100 to -100. As a price-centric index, it will generally follow the candlestick pattern of a price. The Swing Index and ASI can be used in analyzing all types of securities. It is often used for futures trading but can be used for analyzing the price trends of other assets as well.

The ASI is known for supporting the affirmation of breakouts.

The ASI may be used in conjunction with trading channels in order to confirm breakouts as the same trendline is to be penetrated in both situations. Generally, when the ASI is positive, it supports that the long-term trend will be higher, and when the ASI is negative, it suggests that the long-term trend will be lower.