Lazard Next Gen Etf Market Value
| TEKY Etf | 37.92 0.05 0.13% |
| Symbol | Lazard |
The market value of Lazard Next Gen is measured differently than its book value, which is the value of Lazard that is recorded on the company's balance sheet. Investors also form their own opinion of Lazard Next's value that differs from its market value or its book value, called intrinsic value, which is Lazard Next's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Lazard Next's market value can be influenced by many factors that don't directly affect Lazard Next's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Lazard Next's value and its price as these two are different measures arrived at by different means. Investors typically determine if Lazard Next is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Lazard Next's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.
Lazard Next 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Lazard Next's etf what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Lazard Next.
| 11/26/2025 |
| 12/26/2025 |
If you would invest 0.00 in Lazard Next on November 26, 2025 and sell it all today you would earn a total of 0.00 from holding Lazard Next Gen or generate 0.0% return on investment in Lazard Next over 30 days. Lazard Next is related to or competes with Amplify Video, KraneShares SSE, Global X, Pinnacle Focused, Pacer Swan, Invesco Active, and Innovator Uncapped. Lazard Next is entity of United States. It is traded as Etf on NASDAQ exchange. More
Lazard Next Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Lazard Next's etf current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Lazard Next Gen upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.06) | |||
| Maximum Drawdown | 6.45 | |||
| Value At Risk | (2.72) | |||
| Potential Upside | 2.36 |
Lazard Next Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Lazard Next's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Lazard Next's standard deviation. In reality, there are many statistical measures that can use Lazard Next historical prices to predict the future Lazard Next's volatility.| Risk Adjusted Performance | 0.0034 | |||
| Jensen Alpha | (0.1) | |||
| Total Risk Alpha | (0.16) | |||
| Treynor Ratio | (0.01) |
Lazard Next Gen Backtested Returns
At this stage we consider Lazard Etf to be very steady. Lazard Next Gen has Sharpe Ratio of close to zero, which conveys that the entity had a close to zero % return per unit of risk over the last 3 months. We have found twenty-one technical indicators for Lazard Next, which you can use to evaluate the volatility of the etf. Please verify Lazard Next's Risk Adjusted Performance of 0.0034, standard deviation of 1.43, and Mean Deviation of 1.09 to check out if the risk estimate we provide is consistent with the expected return of 0.0046%. The etf secures a Beta (Market Risk) of 1.22, which conveys a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, Lazard Next will likely underperform.
Auto-correlation | 0.08 |
Virtually no predictability
Lazard Next Gen has virtually no predictability. Overlapping area represents the amount of predictability between Lazard Next time series from 26th of November 2025 to 11th of December 2025 and 11th of December 2025 to 26th of December 2025. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Lazard Next Gen price movement. The serial correlation of 0.08 indicates that barely 8.0% of current Lazard Next price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.08 | |
| Spearman Rank Test | 0.41 | |
| Residual Average | 0.0 | |
| Price Variance | 0.31 |
Lazard Next Gen lagged returns against current returns
Autocorrelation, which is Lazard Next etf's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Lazard Next's etf expected returns. We can calculate the autocorrelation of Lazard Next returns to help us make a trade decision. For example, suppose you find that Lazard Next has exhibited high autocorrelation historically, and you observe that the etf is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Lazard Next regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Lazard Next etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Lazard Next etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Lazard Next etf over time.
Current vs Lagged Prices |
| Timeline |
Lazard Next Lagged Returns
When evaluating Lazard Next's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Lazard Next etf have on its future price. Lazard Next autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Lazard Next autocorrelation shows the relationship between Lazard Next etf current value and its past values and can show if there is a momentum factor associated with investing in Lazard Next Gen.
Regressed Prices |
| Timeline |
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.When determining whether Lazard Next Gen offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Lazard Next's financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Lazard Next Gen Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Lazard Next Gen Etf:Check out Lazard Next Correlation, Lazard Next Volatility and Lazard Next Alpha and Beta module to complement your research on Lazard Next. You can also try the Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
Lazard Next technical etf analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, etf market cycles, or different charting patterns.