T Rowe Price Fund Market Value
RGGIX Fund | USD 38.92 0.53 1.38% |
Symbol | RGGIX |
T Rowe '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 T Rowe'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 T Rowe.
03/01/2023 |
| 04/24/2024 |
If you would invest 0.00 in T Rowe on March 1, 2023 and sell it all today you would earn a total of 0.00 from holding T Rowe Price or generate 0.0% return on investment in T Rowe over 420 days. T Rowe is related to or competes with T Rowe, T Rowe, T Rowe, T Rowe, T Rowe, Maryland Tax-free, and T Rowe. The fund normally invests at least 80 percent of its net assets in stocks More
T Rowe 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 T Rowe'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 T Rowe Price upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 0.6492 | |||
Information Ratio | 0.014 | |||
Maximum Drawdown | 3.31 | |||
Value At Risk | (1.15) | |||
Potential Upside | 1.13 |
T Rowe Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for T Rowe's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as T Rowe's standard deviation. In reality, there are many statistical measures that can use T Rowe historical prices to predict the future T Rowe's volatility.Risk Adjusted Performance | 0.0888 | |||
Jensen Alpha | 0.0173 | |||
Total Risk Alpha | (0.0005) | |||
Sortino Ratio | 0.015 | |||
Treynor Ratio | 0.0983 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of T Rowe'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.
T Rowe Price Backtested Returns
We consider T Rowe very steady. T Rowe Price owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.13, which indicates the fund had a 0.13% return per unit of standard deviation over the last 3 months. We have found twenty-seven technical indicators for T Rowe Price, which you can use to evaluate the volatility of the entity. Please validate T Rowe's Downside Deviation of 0.6492, market risk adjusted performance of 0.1083, and Risk Adjusted Performance of 0.0888 to confirm if the risk estimate we provide is consistent with the expected return of 0.0943%. The entity has a beta of 0.91, which indicates possible diversification benefits within a given portfolio. T Rowe returns are very sensitive to returns on the market. As the market goes up or down, T Rowe is expected to follow.
Auto-correlation | 0.85 |
Very good predictability
T Rowe Price has very good predictability. Overlapping area represents the amount of predictability between T Rowe time series from 1st of March 2023 to 27th of September 2023 and 27th of September 2023 to 24th 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 T Rowe Price price movement. The serial correlation of 0.85 indicates that around 85.0% of current T Rowe price fluctuation can be explain by its past prices.
Correlation Coefficient | 0.85 | |
Spearman Rank Test | 0.83 | |
Residual Average | 0.0 | |
Price Variance | 5.55 |
T Rowe Price lagged returns against current returns
Autocorrelation, which is T Rowe 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 T Rowe's mutual fund expected returns. We can calculate the autocorrelation of T Rowe returns to help us make a trade decision. For example, suppose you find that T Rowe 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 |
T Rowe 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 T Rowe mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if T Rowe mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in T Rowe mutual fund over time.
Current vs Lagged Prices |
Timeline |
T Rowe Lagged Returns
When evaluating T Rowe's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of T Rowe mutual fund have on its future price. T Rowe 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, T Rowe autocorrelation shows the relationship between T Rowe mutual fund current value and its past values and can show if there is a momentum factor associated with investing in T Rowe Price.
Regressed Prices |
Timeline |
Currently Active Assets on Macroaxis
Check out T Rowe Correlation, T Rowe Volatility and T Rowe Alpha and Beta module to complement your research on T Rowe. You can also try the Money Managers module to screen money managers from public funds and ETFs managed around the world.
T Rowe 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.