Enterprise Mergers And Fund Market Value
EMACX Fund | USD 12.11 0.02 0.16% |
Symbol | Enterprise |
Enterprise Mergers '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 Enterprise Mergers' 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 Enterprise Mergers.
02/26/2024 |
| 04/26/2024 |
If you would invest 0.00 in Enterprise Mergers on February 26, 2024 and sell it all today you would earn a total of 0.00 from holding Enterprise Mergers And or generate 0.0% return on investment in Enterprise Mergers over 60 days. Enterprise Mergers is related to or competes with Blckrk Lc, Blckrk Lc, Blkrk Lc, Merger Fund, Vivaldi Merger, Vivaldi Merger, and The Arbitrage. The advisor intends to invest primarily in equity securities of companies believed to be likely acquisition targets with... More
Enterprise Mergers 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 Enterprise Mergers' 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 Enterprise Mergers And upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 0.7675 | |||
Information Ratio | (0.15) | |||
Maximum Drawdown | 2.83 | |||
Value At Risk | (1.16) | |||
Potential Upside | 0.8439 |
Enterprise Mergers Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Enterprise Mergers' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Enterprise Mergers' standard deviation. In reality, there are many statistical measures that can use Enterprise Mergers historical prices to predict the future Enterprise Mergers' volatility.Risk Adjusted Performance | 3.0E-4 | |||
Jensen Alpha | (0) | |||
Total Risk Alpha | (0.09) | |||
Sortino Ratio | (0.12) | |||
Treynor Ratio | 0.1311 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Enterprise Mergers' 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.
Enterprise Mergers And Backtested Returns
Enterprise Mergers And secures Sharpe Ratio (or Efficiency) of -0.0119, which denotes the fund had a -0.0119% return per unit of risk over the last 3 months. Enterprise Mergers And exposes twenty-seven different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm Enterprise Mergers' Coefficient Of Variation of 107990.29, downside deviation of 0.7675, and Mean Deviation of 0.4504 to check the risk estimate we provide. The fund shows a Beta (market volatility) of -0.072, which means not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Enterprise Mergers are expected to decrease at a much lower rate. During the bear market, Enterprise Mergers is likely to outperform the market.
Auto-correlation | -0.42 |
Modest reverse predictability
Enterprise Mergers And has modest reverse predictability. Overlapping area represents the amount of predictability between Enterprise Mergers time series from 26th of February 2024 to 27th of March 2024 and 27th of March 2024 to 26th of April 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 Enterprise Mergers And price movement. The serial correlation of -0.42 indicates that just about 42.0% of current Enterprise Mergers price fluctuation can be explain by its past prices.
Correlation Coefficient | -0.42 | |
Spearman Rank Test | -0.57 | |
Residual Average | 0.0 | |
Price Variance | 0.02 |
Enterprise Mergers And lagged returns against current returns
Autocorrelation, which is Enterprise Mergers 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 Enterprise Mergers' mutual fund expected returns. We can calculate the autocorrelation of Enterprise Mergers returns to help us make a trade decision. For example, suppose you find that Enterprise Mergers 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 |
Enterprise Mergers 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 Enterprise Mergers mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Enterprise Mergers mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Enterprise Mergers mutual fund over time.
Current vs Lagged Prices |
Timeline |
Enterprise Mergers Lagged Returns
When evaluating Enterprise Mergers' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Enterprise Mergers mutual fund have on its future price. Enterprise Mergers 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, Enterprise Mergers autocorrelation shows the relationship between Enterprise Mergers mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Enterprise Mergers And.
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 Enterprise Mergers 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, Enterprise Mergers' short interest history, or implied volatility extrapolated from Enterprise Mergers options trading.
Pair Trading with Enterprise Mergers
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 Enterprise Mergers 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 Enterprise Mergers will appreciate offsetting losses from the drop in the long position's value.Moving together with Enterprise Mutual Fund
0.72 | GCFSX | Gabelli Global Financial | PairCorr |
0.79 | GCIEX | Gabelli Equity | PairCorr |
1.0 | EMAAX | Enterprise Mergers And | PairCorr |
The ability to find closely correlated positions to Enterprise Mergers could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Enterprise Mergers 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 Enterprise Mergers - 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 Enterprise Mergers And to buy it.
The correlation of Enterprise Mergers 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 Enterprise Mergers moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Enterprise Mergers And 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 Enterprise Mergers 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 Enterprise Mergers Correlation, Enterprise Mergers Volatility and Enterprise Mergers Alpha and Beta module to complement your research on Enterprise Mergers. Note that the Enterprise Mergers And information on this page should be used as a complementary analysis to other Enterprise Mergers' 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 Portfolio Center module to all portfolio management and optimization tools to improve performance of your portfolios.
Enterprise Mergers 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.