Franklin Templeton Etf Market Value
IQM Etf | USD 67.74 0.23 0.34% |
Symbol | Franklin |
The market value of Franklin Templeton ETF is measured differently than its book value, which is the value of Franklin that is recorded on the company's balance sheet. Investors also form their own opinion of Franklin Templeton's value that differs from its market value or its book value, called intrinsic value, which is Franklin Templeton'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 Franklin Templeton's market value can be influenced by many factors that don't directly affect Franklin Templeton'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 Franklin Templeton's value and its price as these two are different measures arrived at by different means. Investors typically determine if Franklin Templeton is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Franklin Templeton'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.
Franklin Templeton '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 Franklin Templeton'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 Franklin Templeton.
12/05/2022 |
| 11/24/2024 |
If you would invest 0.00 in Franklin Templeton on December 5, 2022 and sell it all today you would earn a total of 0.00 from holding Franklin Templeton ETF or generate 0.0% return on investment in Franklin Templeton over 720 days. Franklin Templeton is related to or competes with Invesco DWA, Invesco Dynamic, Invesco Dynamic, HUMANA, Barloworld, Morningstar Unconstrained, and High-yield Municipal. Under normal market conditions, the fund invests at least 80 percent of its net assets in equity securities of companies... More
Franklin Templeton 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 Franklin Templeton'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 Franklin Templeton ETF upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 1.73 | |||
Information Ratio | 0.0119 | |||
Maximum Drawdown | 7.54 | |||
Value At Risk | (2.76) | |||
Potential Upside | 1.99 |
Franklin Templeton Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Franklin Templeton's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Franklin Templeton's standard deviation. In reality, there are many statistical measures that can use Franklin Templeton historical prices to predict the future Franklin Templeton's volatility.Risk Adjusted Performance | 0.0796 | |||
Jensen Alpha | (0.02) | |||
Total Risk Alpha | (0.10) | |||
Sortino Ratio | 0.0106 | |||
Treynor Ratio | 0.1088 |
Franklin Templeton ETF Backtested Returns
As of now, Franklin Etf is very steady. Franklin Templeton ETF secures Sharpe Ratio (or Efficiency) of 0.1, which denotes the etf had a 0.1% return per unit of standard deviation over the last 3 months. We have found thirty technical indicators for Franklin Templeton ETF, which you can use to evaluate the volatility of the entity. Please confirm Franklin Templeton's Downside Deviation of 1.73, semi deviation of 1.56, and Mean Deviation of 1.12 to check if the risk estimate we provide is consistent with the expected return of 0.15%. The etf shows a Beta (market volatility) of 1.28, which means 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, Franklin Templeton will likely underperform.
Auto-correlation | 0.80 |
Very good predictability
Franklin Templeton ETF has very good predictability. Overlapping area represents the amount of predictability between Franklin Templeton time series from 5th of December 2022 to 30th of November 2023 and 30th of November 2023 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 Franklin Templeton ETF price movement. The serial correlation of 0.8 indicates that around 80.0% of current Franklin Templeton price fluctuation can be explain by its past prices.
Correlation Coefficient | 0.8 | |
Spearman Rank Test | 0.63 | |
Residual Average | 0.0 | |
Price Variance | 26.24 |
Franklin Templeton ETF lagged returns against current returns
Autocorrelation, which is Franklin Templeton 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 Franklin Templeton's etf expected returns. We can calculate the autocorrelation of Franklin Templeton returns to help us make a trade decision. For example, suppose you find that Franklin Templeton 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 |
Franklin Templeton 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 Franklin Templeton etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Franklin Templeton etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Franklin Templeton etf over time.
Current vs Lagged Prices |
Timeline |
Franklin Templeton Lagged Returns
When evaluating Franklin Templeton's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Franklin Templeton etf have on its future price. Franklin Templeton 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, Franklin Templeton autocorrelation shows the relationship between Franklin Templeton etf current value and its past values and can show if there is a momentum factor associated with investing in Franklin Templeton ETF.
Regressed Prices |
Timeline |
Building efficient market-beating portfolios requires time, education, and a lot of computing power!
The Portfolio Architect is an AI-driven system that provides multiple benefits to our users by leveraging cutting-edge machine learning algorithms, statistical analysis, and predictive modeling to automate the process of asset selection and portfolio construction, saving time and reducing human error for individual and institutional investors.
Try AI Portfolio ArchitectCheck out Franklin Templeton Correlation, Franklin Templeton Volatility and Franklin Templeton Alpha and Beta module to complement your research on Franklin Templeton. You can also try the Stock Tickers module to use high-impact, comprehensive, and customizable stock tickers that can be easily integrated to any websites.
Franklin Templeton 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.