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Technical Analysis Highlights - ACWA POWER Co.
By KlickAnalytics Data Insights | May 16, 2024 07:41AM ET
Technical Indicators
Technical Indicators - Analysis
| Data | Analysis |
|---|---|
| Trend based on SMA 50/200 | Uptrend |
| RSI (14 days): 53.87 | Neutral |
| Bollinger Bands %b: 0.39 | No clear signal |
| RSI (14 days): 53.87 | Neutral |
| MACD: 10.49 | Bullish - Potential Buy Signal |
| Average Directional Index (ADX): 27.74 | Trend strength is significant |
| Commodity Channel Index (CCI): -56.87 | Neutral |
Volatility - Analysis
| Data | Analysis |
|---|---|
| Volatility (7 days) | 6.37% |
| Volatility (30 days) | 4.18% |
| Volatility (60 days) | 3.43% |
| Volatility (90 days) | 3.05% |
| Volatility (180 days) | 2.67% |
| Volatility (365 days) | 2.25% |
| Volatility (year-to-date) | 3.05% |
Volume - Analysis
| Data | Analysis |
|---|---|
| Highest Volume (7 days) | 2,000,985 on 05-08-2024 (5 days ago) |
| Lowest Volume (7 days) | 120,755 on 05-05-2024 (8 days ago) |
| Highest Volume (30 days) | 2,000,985 on 05-08-2024 (5 days ago) |
| Lowest Volume (30 days) | 68,133 on 03-31-2024 (43 days ago) |
| Highest Volume (60 days) | 3,848,455 on 03-14-2024 (60 days ago) |
| Lowest Volume (60 days) | 68,133 on 03-31-2024 (43 days ago) |
| Highest Volume (90 days) | 3,848,455 on 03-14-2024 (60 days ago) |
| Lowest Volume (90 days) | 53,010 on 02-04-2024 (99 days ago) |
| Highest Volume (180 days) | 3,848,455 on 03-14-2024 (60 days ago) |
| Lowest Volume (180 days) | 39,960 on 10-01-2023 (225 days ago) |
| Highest Volume (365 days) | 3,848,455 on 03-14-2024 (60 days ago) |
| Lowest Volume (365 days) | 35,232 on 02-12-2023 (456 days ago) |
| Highest Volume (year-to-date) | 3,848,455 on 03-14-2024 (60 days ago) |
| Lowest Volume (year-to-date) | 53,010 on 02-04-2024 (99 days ago) |
Ask the market a question. Get a calculated answer.
The AI is not a chatbot bolted onto a document store. It calls the same analytics engine that powers every screen on this platform — so what comes back is a number it computed from raw history, with the command that produced it.
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Screening, backtesting, technicals, options analytics, correlations, seasonality and factor models — computed on demand from raw prices, never a stale cache.
It shows its working
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Your own documents
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Agents and workflows
Multi-step research that runs the platform's tools for you — screen, pull the history, compute, compare, then write it up.
MCP, CLI and API
The same command catalogue from Claude, your own agent, a shell or your pipeline. The answer on screen is the answer your job gets at 4am.
You ask
“How does NVDA usually trade through earnings?”
It calls
→ ka.options_expected_move(NVDA)
It answers
NVDA has averaged a 9.2% absolute move on the day after earnings and closed higher 67% of the time. Two in three reactions land between −4.2% and +16.3% — the distribution is skewed right, not symmetric.
Every figure computed live from our own history — not scraped, not summarised.
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