Innovator Etfs Trust Etf Market Value
| IGTR Etf | USD 25.88 0.17 0.66% |
| Symbol | Innovator |
The market value of Innovator ETFs Trust is measured differently than its book value, which is the value of Innovator that is recorded on the company's balance sheet. Investors also form their own opinion of Innovator ETFs' value that differs from its market value or its book value, called intrinsic value, which is Innovator ETFs' 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 Innovator ETFs' market value can be influenced by many factors that don't directly affect Innovator ETFs' 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 Innovator ETFs' value and its price as these two are different measures arrived at by different means. Investors typically determine if Innovator ETFs is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Innovator ETFs' 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.
Innovator ETFs '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 Innovator ETFs' 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 Innovator ETFs.
| 09/27/2024 |
| 11/26/2024 |
If you would invest 0.00 in Innovator ETFs on September 27, 2024 and sell it all today you would earn a total of 0.00 from holding Innovator ETFs Trust or generate 0.0% return on investment in Innovator ETFs over 60 days. Innovator ETFs is related to or competes with Tidal ETF, Capital Group, Dimensional ETF, Pacer Developed, and ETF Series. Innovator ETFs is entity of United States More
Innovator ETFs 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 Innovator ETFs' 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 Innovator ETFs Trust upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.27) | |||
| Maximum Drawdown | 4.23 | |||
| Value At Risk | (2.06) | |||
| Potential Upside | 1.5 |
Innovator ETFs Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Innovator ETFs' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Innovator ETFs' standard deviation. In reality, there are many statistical measures that can use Innovator ETFs historical prices to predict the future Innovator ETFs' volatility.| Risk Adjusted Performance | (0.1) | |||
| Jensen Alpha | (0.13) | |||
| Total Risk Alpha | (0.29) | |||
| Treynor Ratio | 2.65 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Innovator ETFs' price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Innovator ETFs Trust Backtested Returns
Innovator ETFs Trust holds Efficiency (Sharpe) Ratio of -0.15, which attests that the entity had a -0.15% return per unit of risk over the last 3 months. Innovator ETFs Trust exposes twenty-two different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check out Innovator ETFs' Market Risk Adjusted Performance of 2.66, risk adjusted performance of (0.1), and Standard Deviation of 0.9563 to validate the risk estimate we provide. The etf retains a Market Volatility (i.e., Beta) of -0.0519, which attests to not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Innovator ETFs are expected to decrease at a much lower rate. During the bear market, Innovator ETFs is likely to outperform the market.
Auto-correlation | 0.65 |
Good predictability
Innovator ETFs Trust has good predictability. Overlapping area represents the amount of predictability between Innovator ETFs time series from 27th of September 2024 to 27th of October 2024 and 27th of October 2024 to 26th 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 Innovator ETFs Trust price movement. The serial correlation of 0.65 indicates that roughly 65.0% of current Innovator ETFs price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.65 | |
| Spearman Rank Test | 0.76 | |
| Residual Average | 0.0 | |
| Price Variance | 0.21 |
Innovator ETFs Trust lagged returns against current returns
Autocorrelation, which is Innovator ETFs 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 Innovator ETFs' etf expected returns. We can calculate the autocorrelation of Innovator ETFs returns to help us make a trade decision. For example, suppose you find that Innovator ETFs 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 |
Innovator ETFs 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 Innovator ETFs etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Innovator ETFs etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Innovator ETFs etf over time.
Current vs Lagged Prices |
| Timeline |
Innovator ETFs Lagged Returns
When evaluating Innovator ETFs' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Innovator ETFs etf have on its future price. Innovator ETFs 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, Innovator ETFs autocorrelation shows the relationship between Innovator ETFs etf current value and its past values and can show if there is a momentum factor associated with investing in Innovator ETFs Trust.
Regressed Prices |
| Timeline |
Pair Trading with Innovator ETFs
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Innovator ETFs position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Innovator ETFs will appreciate offsetting losses from the drop in the long position's value.Moving against Innovator Etf
| 0.95 | RSPY | Tuttle Capital Management | PairCorr |
| 0.93 | DSJA | DSJA | PairCorr |
| 0.91 | MEME | Roundhill Investments | PairCorr |
| 0.9 | MSTY | YieldMax MSTR Option | PairCorr |
| 0.83 | BTC | Grayscale Bitcoin Mini | PairCorr |
The ability to find closely correlated positions to Innovator ETFs could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Innovator ETFs when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Innovator ETFs - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Innovator ETFs Trust to buy it.
The correlation of Innovator ETFs is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Innovator ETFs moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Innovator ETFs Trust moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Innovator ETFs can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Check out Innovator ETFs Correlation, Innovator ETFs Volatility and Innovator ETFs Alpha and Beta module to complement your research on Innovator ETFs. You can also try the Financial Widgets module to easily integrated Macroaxis content with over 30 different plug-and-play financial widgets.
Innovator ETFs 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.