valpatrad

VIX - SKEW Divergence

valpatrad 已更新   
The CBOE VIX is a well-known index representing market expectations for volatility over the next 30 days.
The CBOE SKEW is an index reflecting the perceived tail risk over the next 30 days.

When the SKEW rises over a certain level (~140/150), that means investors are hedging their exposure with options, because they are worried about an incoming market crash or a "black swan". If that happens when the VIX is very low and apparently there is no uncertainty, this can warn of a sudden change in direction of the market. You will see for yourself that an increasing divergence often anticipates a sharp fall of leading stock indexes, usually within two to four months.
This is probably not very relevant for the short-term trader but mid/long-term traders and market analysts may find it useful to clearly visualize the extent of the distance between the VIX and the SKEW. For that reason, I wrote this highly customizable script with which you can plot the two indexes and fill the space within them with a color gradient to highlight the maximum and minimum divergence. Additionally, you can fill the beneath VIX area with four different colors. It is also possible to plot the divergence value itself, so if you want you can draw trendlines and support/resistance levels on it.

Please note that the divergence per se doesn't predict anything and it's meant to be used synergistically with other technical analysis tools.

More informations here:
www.cboe.com/us/indices/dashboard/vix/
www.cboe.com/us/indices/dashboard/skew/
發布通知:
Added a table to show the latest percentage change. The table will not be shown on intraday charts.
發布通知:
Updates:

1) Added the average line of the divergence, which can be useful to analyze the historical relationship between the two indexes by comparing it to the current divergence. By default, the line represents the median value over a certain period, but you can use a moving average instead, choosing from Simple Moving Average (MA), Exponential Moving Average (EMA), and Weighted Moving Average (WMA). It is better using the median rather than a moving average, because the relationship between the two indexes is not necessarily linear or trending over time. Additionally, extreme values or outliers in the data may significantly affect the results of a moving average calculation, leading to less accurate conclusions.

2) Added another row on the table, which shows the value of the distance between the current divergence and its average.

3) Improved the menu.

4) Cleaned the code and improved its overall appearance.
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