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Upturn AI Summary
Amplify AI Powered Equity ETF(AIEQ)
Advisory History & Simulated Performance *
*as per simulation (see disclosures)- ALL
- 1Y
- 1M
- 1W
- BUY Advisory
- SELL Advisory (Profit)
- SELL Advisory (Loss)
- Profit
- Loss
- PASS (Skip)
Advisory Performance History (Simulated)
Upturn Advisory & Investor View for AIEQ
09/25/2026: AIEQ (2-star) is currently NOT-A-BUY. Pass it for now.
AIEQ is an actively managed ETF that uses a proprietary AI engine to pick US stocks by analyzing vast amounts of market and sentiment data. Its core strengths include the ability to remove human emotional bias and quickly adapt to changing data points, though it carries a higher expense ratio than passive counterparts. It serves well as a speculative, growth-oriented satellite position in a diversified portfolio. Primary risks involve 'black box' algorithmic decisions and higher volatility. It is best suited for growth-minded investors who want exposure to AI-driven systematic strategy and can monitor performance against passive benchmarks.
How to Read the Upturn Advisory
The Upturn Star Rating and the current BUY, SELL, or PASS advisory are generated by Upturn’s AI advisory engine based on proprietary signal analysis, price behavior, advisory history, and historical signal performance.
ETF holdings, costs, diversification, valuation, risks, and market conditions provide supporting context about the fund.
Investor Fit
| Investor style | Fit | Why |
|---|---|---|
| Growth investor | Strong fit | The AI model is designed to hunt for stocks with high growth potential and improving fundamental data. |
| Momentum investor | Strong fit while signal remains positive | The AI algorithm is specifically built to detect and capitalize on emerging positive market sentiment and trends. |
| Value investor | Mixed fit | While the model can identify undervalued stocks, it often prioritizes growth and momentum metrics over deep value. |
| Dividend/Income investor | Weak fit | AIEQ is focused on capital appreciation rather than consistent yield or dividend generation. |
| Low-risk investor | Weak fit | The strategy is actively managed and can be volatile, making it unsuitable for capital preservation goals. |
Investor Profile
Ideal Investor Profile
The ideal investor is a sophisticated individual who believes in the future of machine learning and wants to add a satellite, growth-oriented position to a core portfolio.
Suitability
AIEQ is best for long-term investors comfortable with algorithmic, active management and capable of weathering periods of underperformance.
Risk Profile
| Risk factor | Level | Why it matters |
|---|---|---|
| Volatility | High | The AI's active rebalancing can lead to rapid shifts in portfolio composition, increasing short-term price fluctuations. |
| Market risk | Medium / high | As an equity-heavy fund, it is fully exposed to systemic market declines. |
| Concentration | Medium | The AI may periodically concentrate holdings in specific sectors that it identifies as showing high growth potential. |
| Tracking/expense | Medium | The higher expense ratio requires the active strategy to consistently outperform passive alternatives to be cost-effective. |
| Liquidity | Medium | Lower average volumes than massive index funds could result in higher slippage for large trades. |
| Business/sector quality | Medium | The algorithm might overweight sectors based on temporary noise or 'hyped' data. |
Risk Analysis
Volatility
AIEQ historically demonstrates moderate to high volatility as it actively switches positions based on algorithmic signals.
Market Risk
The fund is subject to general US equity market risk; however, its specific risk is the potential for the AI model to make incorrect projections based on sentiment analysis.
What the ETF Owns
| Exposure Type | Exposure | Weight (%) | Retail Investor Read |
|---|---|---|---|
| Market capitalization | US Large-Cap Equities | 65 | The fund leans toward large-cap companies that show strong fundamental and sentiment-based signals according to the AI. |
| Market capitalization | US Mid-Cap Equities | 25 | AI selection often includes mid-cap stocks to capture growth potential that traditional, larger-index strategies might overlook. |
| Cash/collateral | Cash and Cash Equivalents | 10 | A small liquidity buffer is maintained to facilitate daily trading and adjustments in the AI-driven portfolio. |
Price Behavior

Strong Uptrend
The stock has maintained a strong upward price trend across the last three quarters.

Very Smooth
The stock has followed a highly orderly price path with minimal short-term disruption.
Analysis of Past Performance
Type ETF | Historic Profit 31.49% | Avg. Invested days 63 | Today’s Advisory PASS |
Upturn Advisory Rating ![]() | Upturn Advisory Performance | ETF Returns Performance |
ETF Fundamentals 
Source: EOD Historical Data • Updated Sep 25, 2026
Fund Basics
| Metric | Value |
|---|---|
| Fund Size (AUM) | $109.57M |
| Issuer | ETFMG |
| Expense Ratio | 0.75% |
| Distribution Yield | 0.38% |
| Inception | Oct 17, 2017 |
| Index Tracked | AI Powered Equity Index |
Performance
| Period | Total Return |
|---|---|
| YTD | +1.08% |
| 1 Year | +15.40% |
| 3 Year | -3.34% |
| 5 Year | +7.91% |
| 10 Year | +0.00% |
Risk Metrics
| Metric | Value |
|---|---|
| 1Y Volatility | 27.78% |
| 3Y Volatility | 25.04% |
| 3Y Sharpe Ratio | 0.07 |
Ratings
| Metric | Value |
|---|---|
| Morningstar Rating | ★★★★★ |
Market Cap Distribution
| Cap Size | Weight |
|---|---|
| Mid Cap | 36.39% |
| Mega Cap | 34.38% |
| Large Cap | 25.62% |
| Small Cap | 3.25% |
Top Sectors
| Sector | Weight |
|---|---|
| Technology | 31.44% |
| Communication Services | 16.38% |
| Financial Services | 15.38% |
| Industrials | 10.19% |
Asset Allocation
Portfolio Characteristics
| Metric | Value |
|---|---|
| Portfolio P/E | 18.59x |
| Portfolio P/B | 3.43x |
| Portfolio P/S | 2.42x |
| Holdings Turnover | 0.0% |
Top Holdings
| Holding | Weight |
|---|---|
| TE Connectivity | 6.22% |
| Netflix | 4.98% |
| Chubb | 4.89% |
| GE Vernova LLC | 4.60% |
| NVIDIA | 4.50% |
Upturn AI Summary
AI Summarization is directionally correct and might not be accurate.
Summarized information shown could be a few years old and not current.
Fundamental Rating based on AI could be based on old data.
AI-generated summaries may have inaccuracies (hallucinations). Please verify the information before taking action.

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