Pacer Lunt Large Etf Market Value
| PALC Etf | USD 52.39 0.43 0.83% |
| Symbol | Pacer |
The market value of Pacer Lunt Large is measured differently than its book value, which is the value of Pacer that is recorded on the company's balance sheet. Investors also form their own opinion of Pacer Lunt's value that differs from its market value or its book value, called intrinsic value, which is Pacer Lunt'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 Pacer Lunt's market value can be influenced by many factors that don't directly affect Pacer Lunt'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 Pacer Lunt's value and its price as these two are different measures arrived at by different means. Investors typically determine if Pacer Lunt is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Pacer Lunt'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.
Pacer Lunt '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 Pacer Lunt'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 Pacer Lunt.
| 11/30/2023 |
| 11/24/2024 |
If you would invest 0.00 in Pacer Lunt on November 30, 2023 and sell it all today you would earn a total of 0.00 from holding Pacer Lunt Large or generate 0.0% return on investment in Pacer Lunt over 360 days. Pacer Lunt is related to or competes with Pacer Lunt, Pacer Lunt, Pacer Trendpilot, Pacer Small, and Pacer Cash. The index uses an objective, rules-based methodology to provide exposure to large-capitalization U.S More
Pacer Lunt 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 Pacer Lunt'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 Pacer Lunt Large upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.6045 | |||
| Information Ratio | 8.0E-4 | |||
| Maximum Drawdown | 3.74 | |||
| Value At Risk | (0.94) | |||
| Potential Upside | 1.16 |
Pacer Lunt Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Pacer Lunt's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Pacer Lunt's standard deviation. In reality, there are many statistical measures that can use Pacer Lunt historical prices to predict the future Pacer Lunt's volatility.| Risk Adjusted Performance | 0.1421 | |||
| Jensen Alpha | 0.0233 | |||
| Total Risk Alpha | 0.0104 | |||
| Sortino Ratio | 9.0E-4 | |||
| Treynor Ratio | 0.1495 |
Pacer Lunt Large Backtested Returns
At this point, Pacer Lunt is very steady. Pacer Lunt Large maintains Sharpe Ratio (i.e., Efficiency) of 0.18, which implies the entity had a 0.18% return per unit of risk over the last 3 months. We have found thirty technical indicators for Pacer Lunt Large, which you can use to evaluate the volatility of the etf. Please check Pacer Lunt's Coefficient Of Variation of 536.47, semi deviation of 0.421, and Risk Adjusted Performance of 0.1421 to confirm if the risk estimate we provide is consistent with the expected return of 0.12%. The etf holds a Beta of 0.81, which implies possible diversification benefits within a given portfolio. As returns on the market increase, Pacer Lunt's returns are expected to increase less than the market. However, during the bear market, the loss of holding Pacer Lunt is expected to be smaller as well.
Auto-correlation | 0.49 |
Average predictability
Pacer Lunt Large has average predictability. Overlapping area represents the amount of predictability between Pacer Lunt time series from 30th of November 2023 to 28th of May 2024 and 28th of May 2024 to 24th of November 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Pacer Lunt Large price movement. The serial correlation of 0.49 indicates that about 49.0% of current Pacer Lunt price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.49 | |
| Spearman Rank Test | 0.56 | |
| Residual Average | 0.0 | |
| Price Variance | 2.13 |
Pacer Lunt Large lagged returns against current returns
Autocorrelation, which is Pacer Lunt 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 Pacer Lunt's etf expected returns. We can calculate the autocorrelation of Pacer Lunt returns to help us make a trade decision. For example, suppose you find that Pacer Lunt 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 |
Pacer Lunt 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 Pacer Lunt etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Pacer Lunt etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Pacer Lunt etf over time.
Current vs Lagged Prices |
| Timeline |
Pacer Lunt Lagged Returns
When evaluating Pacer Lunt's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Pacer Lunt etf have on its future price. Pacer Lunt 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, Pacer Lunt autocorrelation shows the relationship between Pacer Lunt etf current value and its past values and can show if there is a momentum factor associated with investing in Pacer Lunt Large.
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 Pacer Lunt Large offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Pacer Lunt'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 Pacer Lunt Large Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Pacer Lunt Large Etf:Check out Pacer Lunt Correlation, Pacer Lunt Volatility and Pacer Lunt Alpha and Beta module to complement your research on Pacer Lunt. You can also try the AI Portfolio Architect module to use AI to generate optimal portfolios and find profitable investment opportunities.
Pacer Lunt 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.