Lazard Active ETF Performance

GLIX Etf   25.96  -0.61  -2.30%   
The etf maintains a market beta of -0.0832, which means very low measured sensitivity to broad market movements. Lazard Active shows a mild inverse relationship with the market, drifting lower in rallies and holding up during downturns.
Risk-Adjusted Performance
Moderate
 
Weak
 
Strong
On a recent 90-day basis, Lazard Active ETF sits below 8% of comparable global equities and portfolios in risk-adjusted performance. The current category mapping is Infrastructure. Despite somewhat strong forward indicators, Lazard Active is not utilizing all of its potential. The latest price disturbance may contribute to short-term losses for investors. Learn More

Relative Risk vs. Return Landscape

If you had invested $ 2,465 in Lazard Active ETF on December 22, 2025 and sold it today you would have earned a total of $ 131.00 from holding Lazard Active ETF or generated 5.31% return on investment over 90 days. Lazard Active ETF is currently generating a 0.0871% daily expected return and carries 0.8434% risk (volatility on return distribution) over a 90-day horizon. In different words, 7% of etfs are less volatile than Lazard, and 99% of all traded equity instruments are projected to make higher returns than the ETF over the 90 days investment horizon.
  Expected Return   
       Risk  
This comparison focuses on expected return, realized volatility, and risk efficiency versus the market. It highlights whether the current reward profile compensates for the level of uncertainty assumed. Given the investment horizon of 90 days Lazard Active is expected to generate 1.03 times more return on investment than the market. However, the ETF is 1.03 times more volatile than its market benchmark. It trades about 0.1 of its potential returns per unit of risk. The Dow Jones Industrial is currently generating roughly -0.11 per unit of risk.

Target Price Odds to finish over Current Price

For Lazard Etf, the tendency of price to converge toward a long-term average provides a useful forecasting baseline. Investors have relied on this tendency for decades, though persistent mispricings in some instruments suggest additional risk factors. Certain ETFs show persistent deviations from fair value, typically explained by the risk investors bear. Applying mean reversion analysis to Lazard Etf helps identify potential entry points when prices are extended.
Current PriceHorizonTarget PriceOdds moving above the current price in 90 days
25.96 90 days 25.96
about 57.4
Based on standard probability analysis, the odds of Lazard Active moving above the current price in 90 days from now are about 57.4 . Historical price behavior and variance analysis form the basis of this probability estimate. This probability is most useful when combined with fundamental analysis and current market context. This data helps frame realistic expectations for this ETF's price trajectory. (The chart above shows the probability distribution of Lazard Etf prices over the next 90 days). The tails of the distribution show the probability of extreme price movements in Lazard Etf over 90 days. The probability density function is a practical tool for framing expectations about Lazard Etf. Use the probability data to support structured thinking about potential outcomes for Lazard Etf.
Given the investment horizon of 90 days Lazard Active ETF has a beta of -0.0832. This usually indicates that as returns on the benchmark increase, returns on Lazard Active tend to move in the opposite direction, though by a smaller magnitude. During a bear market, however, Lazard Active ETF is likely to outperform the market. Additionally, Lazard Active ETF has an alpha of 0.0689, implying that it can generate a 0.0689 percent excess return over Dow Jones Industrial after adjusting for the inherent market risk (beta).
   Lazard Active Price Density   
       Price  

Predictive Modules for Lazard Active

A variety of analytical techniques are available for forecasting Lazard Active ETF and the broader ETF market. From technical pattern analysis to statistical models, each method contributes a different perspective on Lazard Active ETF. A systematic comparison of model outputs provides context to form a more balanced perspective on Lazard Active ETF. Refining forecasting methods over time can incrementally improve the quality of decisions made about Lazard Active ETF.
The mean reversion principle applied to Lazard Active's suggests that neither prolonged outperformance nor underperformance is permanent. Identifying the root cause of Lazard Active's price dislocation is essential before acting on a mean reversion signal. The mean reversion tendency in Lazard Active's price is a well-documented phenomenon in academic research. In many cases, Lazard Active's price extremes present statistical patterns that have recurred historically.
Hype
Prediction
LowEstimatedHigh
25.1225.9626.80
Details
Intrinsic
Valuation
LowRealHigh
25.2426.0826.92
Details
No single-company analysis of Lazard Active ETF is complete without peer benchmarking. A company that looks attractive in isolation may be significantly outperformed by competitors. Standalone analysis captures Lazard Active's individual story, but peers reveal if it is truly exceptional. Disciplined peer analysis separates conviction-grade insights from superficial Lazard Active observations.

Primary Risk Indicators

The past 10-20 years have brought considerable volatility to the etf market, with Lazard Active experiencing notable price swings. Lazard Active has reflected this volatile environment with periods of significant price swings. Investors in Lazard Active ETF can mitigate this risk by tracking shifts in Lazard Active's fundamental risk indicators. This risk data equips investors with the information needed to adjust Lazard Active ETF exposure proactively.
α
Alpha over Dow Jones
0.07
β
Beta against Dow Jones-0.0832
σ
Overall volatility
1.18
Ir
Information ratio 0.21

Performance Metrics & Calculation Methodology

Lazard Active performance is typically evaluated relative to its benchmark and tracking difference over time. Certain defensive traits may reduce sensitivity to broader macroeconomic fluctuations.

Inputs for Lazard Active ETF come from fund disclosures and market reference feeds and are mapped into a consistent schema for analysis. Some fields can appear with publication lag. Return and risk statistics are calculated from historical price series.

This content is curated and reviewed by:

Michael Smolkin - Member of Macroaxis Board of Directors
Last reviewed on March 16th, 2026