Cboe Vest Large Fund Market Value
| BUAGX Fund | USD 18.05 0.04 0.22% |
| Symbol | Cboe |
Cboe Vest '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 Cboe Vest's mutual fund 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 Cboe Vest.
| 03/02/2024 |
| 05/01/2024 |
If you would invest 0.00 in Cboe Vest on March 2, 2024 and sell it all today you would earn a total of 0.00 from holding Cboe Vest Large or generate 0.0% return on investment in Cboe Vest over 60 days. Cboe Vest is related to or competes with Cboe Vest, Cboe Vest, Cboe Vest, Cboe Vest, Cboe Vest, Cboe Vest. Under normal market conditions, the fund will invest at least 80 percent of the value of its net assets in a portfolio, ... More
Cboe Vest 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 Cboe Vest's mutual fund 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 Cboe Vest Large upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.09 | |||
| Information Ratio | (0.01) | |||
| Maximum Drawdown | 5.77 | |||
| Value At Risk | (0.67) | |||
| Potential Upside | 0.7295 |
Cboe Vest Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Cboe Vest's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Cboe Vest's standard deviation. In reality, there are many statistical measures that can use Cboe Vest historical prices to predict the future Cboe Vest's volatility.| Risk Adjusted Performance | 0.0396 | |||
| Jensen Alpha | 0.0497 | |||
| Total Risk Alpha | (0.03) | |||
| Sortino Ratio | (0.01) | |||
| Treynor Ratio | (0.31) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Cboe Vest's 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.
Cboe Vest Large Backtested Returns
We consider Cboe Vest very steady. Cboe Vest Large secures Sharpe Ratio (or Efficiency) of 0.0578, which signifies that the fund had a 0.0578% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Cboe Vest Large, which you can use to evaluate the volatility of the entity. Please confirm Cboe Vest's Downside Deviation of 1.09, risk adjusted performance of 0.0396, and Mean Deviation of 0.4193 to double-check if the risk estimate we provide is consistent with the expected return of 0.0543%. The fund shows a Beta (market volatility) of -0.14, which signifies not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Cboe Vest are expected to decrease at a much lower rate. During the bear market, Cboe Vest is likely to outperform the market.
Auto-correlation | -0.3 |
Weak reverse predictability
Cboe Vest Large has weak reverse predictability. Overlapping area represents the amount of predictability between Cboe Vest time series from 2nd of March 2024 to 1st of April 2024 and 1st of April 2024 to 1st of May 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 Cboe Vest Large price movement. The serial correlation of -0.3 indicates that nearly 30.0% of current Cboe Vest price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.3 | |
| Spearman Rank Test | -0.48 | |
| Residual Average | 0.0 | |
| Price Variance | 0.04 |
Cboe Vest Large lagged returns against current returns
Autocorrelation, which is Cboe Vest mutual fund'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 Cboe Vest's mutual fund expected returns. We can calculate the autocorrelation of Cboe Vest returns to help us make a trade decision. For example, suppose you find that Cboe Vest has exhibited high autocorrelation historically, and you observe that the mutual fund 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 |
Cboe Vest 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 Cboe Vest mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Cboe Vest mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Cboe Vest mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Cboe Vest Lagged Returns
When evaluating Cboe Vest's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Cboe Vest mutual fund have on its future price. Cboe Vest 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, Cboe Vest autocorrelation shows the relationship between Cboe Vest mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Cboe Vest Large.
Regressed Prices |
| Timeline |
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Cboe Vest in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Cboe Vest's short interest history, or implied volatility extrapolated from Cboe Vest options trading.
Pair Trading with Cboe Vest
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 Cboe Vest 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 Cboe Vest will appreciate offsetting losses from the drop in the long position's value.Moving together with Cboe Mutual Fund
| 0.82 | ENGLX | Cboe Vest Sp | PairCorr |
| 0.81 | ENGIX | Cboe Vest Sp | PairCorr |
| 0.89 | ENGCX | Cboe Vest Sp | PairCorr |
| 0.79 | BTCLX | Cboe Vest Bitcoin | PairCorr |
| 0.79 | BTCYX | Cboe Vest Bitcoin | PairCorr |
The ability to find closely correlated positions to Cboe Vest could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Cboe Vest 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 Cboe Vest - 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 Cboe Vest Large to buy it.
The correlation of Cboe Vest 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 Cboe Vest moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Cboe Vest Large 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 Cboe Vest 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 Cboe Vest Correlation, Cboe Vest Volatility and Cboe Vest Alpha and Beta module to complement your research on Cboe Vest. Note that the Cboe Vest Large information on this page should be used as a complementary analysis to other Cboe Vest's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Balance Of Power module to check stock momentum by analyzing Balance Of Power indicator and other technical ratios.
Cboe Vest technical mutual fund 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, fund market cycles, or different charting patterns.