Mid Cap Growth Profund Fund Market Value
| MGPIX Fund | USD 100.88 1.03 1.01% |
| Symbol | Mid |
Mid Cap '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 Mid Cap'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 Mid Cap.
| 03/19/2024 |
| 04/18/2024 |
If you would invest 0.00 in Mid Cap on March 19, 2024 and sell it all today you would earn a total of 0.00 from holding Mid Cap Growth Profund or generate 0.0% return on investment in Mid Cap over 30 days. Mid Cap is related to or competes with Small Cap, Mid Cap, Small Cap, Mid Cap, and Large Cap. The fund invests in financial instruments that the fund advisors believes, in combination, should track the performance ... More
Mid Cap 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 Mid Cap'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 Mid Cap Growth Profund upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.9629 | |||
| Information Ratio | 0.0816 | |||
| Maximum Drawdown | 3.99 | |||
| Value At Risk | (1.54) | |||
| Potential Upside | 1.63 |
Mid Cap Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Mid Cap's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Mid Cap's standard deviation. In reality, there are many statistical measures that can use Mid Cap historical prices to predict the future Mid Cap's volatility.| Risk Adjusted Performance | 0.0916 | |||
| Jensen Alpha | 0.0619 | |||
| Total Risk Alpha | 0.0545 | |||
| Sortino Ratio | 0.0807 | |||
| Treynor Ratio | 0.0915 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Mid Cap'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.
Mid Cap Growth Backtested Returns
We consider Mid Cap very steady. Mid Cap Growth has Sharpe Ratio of 0.13, which conveys that the entity had a 0.13% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Mid Cap, which you can use to evaluate the volatility of the fund. Please verify Mid Cap's Mean Deviation of 0.7872, risk adjusted performance of 0.0916, and Downside Deviation of 0.9629 to check out if the risk estimate we provide is consistent with the expected return of 0.12%. The fund secures a Beta (Market Risk) of 1.35, which conveys a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, Mid Cap will likely underperform.
Auto-correlation | -0.21 |
Weak reverse predictability
Mid Cap Growth Profund has weak reverse predictability. Overlapping area represents the amount of predictability between Mid Cap time series from 19th of March 2024 to 3rd of April 2024 and 3rd of April 2024 to 18th 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 Mid Cap Growth price movement. The serial correlation of -0.21 indicates that over 21.0% of current Mid Cap price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.21 | |
| Spearman Rank Test | -0.19 | |
| Residual Average | 0.0 | |
| Price Variance | 4.21 |
Mid Cap Growth lagged returns against current returns
Autocorrelation, which is Mid Cap 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 Mid Cap's mutual fund expected returns. We can calculate the autocorrelation of Mid Cap returns to help us make a trade decision. For example, suppose you find that Mid Cap 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 |
Mid Cap 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 Mid Cap mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Mid Cap mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Mid Cap mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Mid Cap Lagged Returns
When evaluating Mid Cap's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Mid Cap mutual fund have on its future price. Mid Cap 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, Mid Cap autocorrelation shows the relationship between Mid Cap mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Mid Cap Growth Profund.
Regressed Prices |
| Timeline |
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Mid Cap 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.