First Trust Cloud Computing ETF (SKYY) Chart

NASDAQ: SKYYInteractive price chart with technical indicators and price history.

SKYY price chart

Daily prices adjusted for splits and distributions. 1D and 5D show delayed intraday prices. Markers: D distribution, S split.

Technical snapshot

Key levels & statistics

SKYY historical prices

SKYY distributions & splits

About the SKYY chart

First Trust Cloud Computing ETF (SKYY) closed at $167.36 on October 23, 2026, up 28.7% so far this year. It is trading 23.5% above its 200-day moving average of $135.52. Over the past year SKYY returned +22.4% including distributions, ahead of the S&P 500 (+14.4%).

This page charts the trading history of SKYY since 2011. Daily prices come from EODHD and are adjusted for splits and distributions, so returns over long periods are comparable. For fund facts and the latest quote see the SKYY overview.

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SKYY chart FAQ

What is the all-time high of SKYY?

The highest closing price for SKYY was $174.89 on October 9, 2026. As of the October 23, 2026 close it traded 4.3% below that level.

What is the 52-week range of SKYY?

Over the 52 weeks to October 23, 2026, SKYY traded between an intraday low of $103.76 on April 10, 2026 and an intraday high of $175.81 on October 12, 2026.

Is SKYY above its 200-day moving average?

Yes. On October 23, 2026 SKYY closed at $167.36, 23.5% above its 200-day simple moving average of $135.52. The 50-day average was $164.17.

How has SKYY performed compared with the S&P 500?

Including reinvested distributions, SKYY returned +22.4% over the past year, compared with +14.4% for SPY. Over five years the figures were +46.8% and +79.3%. See the SKYY performance page for annual returns and drawdowns.

How do I read the SKYY chart?

Pick a time range above the chart and choose candlesticks, a line or an area chart. Moving averages, Bollinger Bands, volume, RSI and MACD can be switched on with the indicator buttons, and "Compare" plots SKYY against another fund as a percentage change. Chart prices are adjusted for splits and distributions.