Long/short etfs that have underperformed
Intellectia 209 candidates
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Our AI identifies and quantifies criteria, auto-filters ranges to match intent, and displays conditions, parameters, and results below, with 209 candidates fitting the screener.
Filters & Rationale
Screening Filters & Rationale
Names: ["long", "short"]:
- Purpose: To identify ETFs that employ long/short strategies.
- Rationale: These strategies are designed to profit from both rising and falling markets, aligning with the user's interest in underperforming ETFs.
Weekly Average Turnover (min: 1,000,000):
- Purpose: To focus on ETFs with significant trading activity.
- Rationale: High turnover ensures liquidity, making the ETFs more accessible for trading and reflective of market sentiment.
Month Price Change Percentage (min: -10%):
- Purpose: To filter for ETFs that have experienced significant underperformance recently.
- Rationale: A decline of at least 10% in the past month highlights ETFs that may be struggling, aligning with the user's query.
This list is generated based on data from one or more third party data providers. It is provided for informational purposes only by Intellectia.AI, and is not investment advice or a recommendation. Intellectia does not make any warranty or guarantee relating to the accuracy, timeliness or completeness of any third-party information, and the provision of this information does not constitute a recommendation.
Frequently Asked Questions
How does the screener result generated?
This is a natural language screener issue. Our AI identifies and quantifies criteria, auto-filters ranges to match intent, and displays conditions, parameters, and results below, with 209 candidates fitting the screener.
Which symbols are included in the screener of long/short etfs that have underperformed
The list includes top performers like ProShares UltraShort Energy (DUG), Leverage Shares 2X Long NET Daily ETF (NETG), KraneShares 2x Long PDD Daily ETF (KPDD), ProShares UltraPro Short Russell2000 (SRTY), among others. These stocks are representative examples from the screener results.