Vivaldi Merger Arbitrage Fund Market Value
| VARAX Fund | USD 10.58 0.01 0.09% |
| Symbol | Vivaldi |
Vivaldi Merger '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 Vivaldi Merger'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 Vivaldi Merger.
| 03/17/2024 |
| 04/16/2024 |
If you would invest 0.00 in Vivaldi Merger on March 17, 2024 and sell it all today you would earn a total of 0.00 from holding Vivaldi Merger Arbitrage or generate 0.0% return on investment in Vivaldi Merger over 30 days. Vivaldi Merger is related to or competes with First Trust, First Trust, First Trust, First Trustconfluence, First Trustconfluence, First Trust, and First Trust. Under normal market conditions, the funds adviser intends to invest in equity securities and derivatives thereof of comp... More
Vivaldi Merger 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 Vivaldi Merger'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 Vivaldi Merger Arbitrage upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.93) | |||
| Maximum Drawdown | 0.1903 | |||
| Potential Upside | 0.0955 |
Vivaldi Merger Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Vivaldi Merger's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Vivaldi Merger's standard deviation. In reality, there are many statistical measures that can use Vivaldi Merger historical prices to predict the future Vivaldi Merger's volatility.| Risk Adjusted Performance | 0.1499 | |||
| Jensen Alpha | 0.0095 | |||
| Total Risk Alpha | 0.0064 | |||
| Treynor Ratio | 0.7609 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Vivaldi Merger'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.
Vivaldi Merger Arbitrage Backtested Returns
We consider Vivaldi Merger very steady. Vivaldi Merger Arbitrage owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.43, which indicates the fund had a 0.43% return per unit of risk over the last 3 months. We have found twenty technical indicators for Vivaldi Merger Arbitrage, which you can use to evaluate the volatility of the fund. Please validate Vivaldi Merger's Risk Adjusted Performance of 0.1499, variance of 0.0021, and Coefficient Of Variation of 226.23 to confirm if the risk estimate we provide is consistent with the expected return of 0.02%. The entity has a beta of 0.0134, which indicates not very significant fluctuations relative to the market. As returns on the market increase, Vivaldi Merger's returns are expected to increase less than the market. However, during the bear market, the loss of holding Vivaldi Merger is expected to be smaller as well.
Auto-correlation | 0.68 |
Good predictability
Vivaldi Merger Arbitrage has good predictability. Overlapping area represents the amount of predictability between Vivaldi Merger time series from 17th of March 2024 to 1st of April 2024 and 1st of April 2024 to 16th 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 Vivaldi Merger Arbitrage price movement. The serial correlation of 0.68 indicates that around 68.0% of current Vivaldi Merger price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.68 | |
| Spearman Rank Test | 0.99 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Vivaldi Merger Arbitrage lagged returns against current returns
Autocorrelation, which is Vivaldi Merger 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 Vivaldi Merger's mutual fund expected returns. We can calculate the autocorrelation of Vivaldi Merger returns to help us make a trade decision. For example, suppose you find that Vivaldi Merger 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 |
Vivaldi Merger 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 Vivaldi Merger mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Vivaldi Merger mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Vivaldi Merger mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Vivaldi Merger Lagged Returns
When evaluating Vivaldi Merger's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Vivaldi Merger mutual fund have on its future price. Vivaldi Merger 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, Vivaldi Merger autocorrelation shows the relationship between Vivaldi Merger mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Vivaldi Merger Arbitrage.
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 Vivaldi Merger 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, Vivaldi Merger's short interest history, or implied volatility extrapolated from Vivaldi Merger options trading.
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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.| LTC | Litecoin | |
| STETH | Staked Ether | |
| LINK | Chainlink |
Check out Vivaldi Merger Correlation, Vivaldi Merger Volatility and Vivaldi Merger Alpha and Beta module to complement your research on Vivaldi Merger. Note that the Vivaldi Merger Arbitrage information on this page should be used as a complementary analysis to other Vivaldi Merger'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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
Vivaldi Merger 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.