Power Momentum Index Fund Market Value
| MOJAX Fund | USD 13.08 0.12 0.91% |
| Symbol | Power |
Power Momentum '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 Power Momentum'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 Power Momentum.
| 03/20/2024 |
| 04/19/2024 |
If you would invest 0.00 in Power Momentum on March 20, 2024 and sell it all today you would earn a total of 0.00 from holding Power Momentum Index or generate 0.0% return on investment in Power Momentum over 30 days. Power Momentum is related to or competes with Calamos Dynamic, Lord Abbett, Absolute Convertible, Virtus Convertible, and Gabelli Convertible. The adviser seeks to achieve the funds objectives by seeking to track the FCF Risk Managed Sector Neutral Momentum Index... More
Power Momentum 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 Power Momentum'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 Power Momentum Index upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.9045 | |||
| Information Ratio | 0.1151 | |||
| Maximum Drawdown | 4.75 | |||
| Value At Risk | (1.34) | |||
| Potential Upside | 1.8 |
Power Momentum Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Power Momentum's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Power Momentum's standard deviation. In reality, there are many statistical measures that can use Power Momentum historical prices to predict the future Power Momentum's volatility.| Risk Adjusted Performance | 0.1173 | |||
| Jensen Alpha | 0.1764 | |||
| Total Risk Alpha | 0.0789 | |||
| Sortino Ratio | 0.1276 | |||
| Treynor Ratio | (4.17) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Power Momentum'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.
Power Momentum Index Backtested Returns
We consider Power Momentum very steady. Power Momentum Index maintains Sharpe Ratio (i.e., Efficiency) of 0.13, which implies the entity had a 0.13% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Power Momentum Index, which you can use to evaluate the volatility of the fund. Please check Power Momentum's Semi Deviation of 0.6653, risk adjusted performance of 0.1173, and Coefficient Of Variation of 544.87 to confirm if the risk estimate we provide is consistent with the expected return of 0.14%. The fund holds a Beta of -0.0417, which implies not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Power Momentum are expected to decrease at a much lower rate. During the bear market, Power Momentum is likely to outperform the market.
Auto-correlation | 0.70 |
Good predictability
Power Momentum Index has good predictability. Overlapping area represents the amount of predictability between Power Momentum time series from 20th of March 2024 to 4th of April 2024 and 4th of April 2024 to 19th 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 Power Momentum Index price movement. The serial correlation of 0.7 indicates that around 70.0% of current Power Momentum price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.7 | |
| Spearman Rank Test | 0.09 | |
| Residual Average | 0.0 | |
| Price Variance | 0.05 |
Power Momentum Index lagged returns against current returns
Autocorrelation, which is Power Momentum 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 Power Momentum's mutual fund expected returns. We can calculate the autocorrelation of Power Momentum returns to help us make a trade decision. For example, suppose you find that Power Momentum 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 |
Power Momentum 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 Power Momentum mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Power Momentum mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Power Momentum mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Power Momentum Lagged Returns
When evaluating Power Momentum's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Power Momentum mutual fund have on its future price. Power Momentum 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, Power Momentum autocorrelation shows the relationship between Power Momentum mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Power Momentum Index.
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 Power Momentum 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, Power Momentum's short interest history, or implied volatility extrapolated from Power Momentum options trading.
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Try AI Portfolio ArchitectCheck out Power Momentum Correlation, Power Momentum Volatility and Power Momentum Alpha and Beta module to complement your research on Power Momentum. Note that the Power Momentum Index information on this page should be used as a complementary analysis to other Power Momentum'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 Bollinger Bands module to use Bollinger Bands indicator to analyze target price for a given investing horizon.
Power Momentum 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.