Oppenheimer Gbl Alloc Fund Market Value
QGRYX Fund | USD 18.55 0.13 0.71% |
Symbol | Oppenheimer |
Oppenheimer Gbl '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 Oppenheimer Gbl'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 Oppenheimer Gbl.
05/04/2022 |
| 04/23/2024 |
If you would invest 0.00 in Oppenheimer Gbl on May 4, 2022 and sell it all today you would earn a total of 0.00 from holding Oppenheimer Gbl Alloc or generate 0.0% return on investment in Oppenheimer Gbl over 720 days. Oppenheimer Gbl is related to or competes with Oppenheimer Cap, Oppenheimer Global, Oppenheimer Main, Oppenheimer Main, and Oppenheimer Strat. The fund allocates its assets among equity securities, fixed-income securities, and various other types of investments, ... More
Oppenheimer Gbl 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 Oppenheimer Gbl'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 Oppenheimer Gbl Alloc upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 0.5626 | |||
Information Ratio | (0.08) | |||
Maximum Drawdown | 2.56 | |||
Value At Risk | (0.76) | |||
Potential Upside | 0.8078 |
Oppenheimer Gbl Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Oppenheimer Gbl's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Oppenheimer Gbl's standard deviation. In reality, there are many statistical measures that can use Oppenheimer Gbl historical prices to predict the future Oppenheimer Gbl's volatility.Risk Adjusted Performance | 0.0537 | |||
Jensen Alpha | (0.03) | |||
Total Risk Alpha | (0.03) | |||
Sortino Ratio | (0.08) | |||
Treynor Ratio | 0.0466 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Oppenheimer Gbl'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.
Oppenheimer Gbl Alloc Backtested Returns
We consider Oppenheimer Gbl very steady. Oppenheimer Gbl Alloc maintains Sharpe Ratio (i.e., Efficiency) of 0.0703, which implies the entity had a 0.0703% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Oppenheimer Gbl Alloc, which you can use to evaluate the volatility of the fund. Please check Oppenheimer Gbl's Coefficient Of Variation of 1108.96, semi deviation of 0.4872, and Risk Adjusted Performance of 0.0537 to confirm if the risk estimate we provide is consistent with the expected return of 0.0375%. The fund holds a Beta of 0.79, which implies possible diversification benefits within a given portfolio. As returns on the market increase, Oppenheimer Gbl's returns are expected to increase less than the market. However, during the bear market, the loss of holding Oppenheimer Gbl is expected to be smaller as well.
Auto-correlation | 0.67 |
Good predictability
Oppenheimer Gbl Alloc has good predictability. Overlapping area represents the amount of predictability between Oppenheimer Gbl time series from 4th of May 2022 to 29th of April 2023 and 29th of April 2023 to 23rd 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 Oppenheimer Gbl Alloc price movement. The serial correlation of 0.67 indicates that around 67.0% of current Oppenheimer Gbl price fluctuation can be explain by its past prices.
Correlation Coefficient | 0.67 | |
Spearman Rank Test | 0.35 | |
Residual Average | 0.0 | |
Price Variance | 0.5 |
Oppenheimer Gbl Alloc lagged returns against current returns
Autocorrelation, which is Oppenheimer Gbl 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 Oppenheimer Gbl's mutual fund expected returns. We can calculate the autocorrelation of Oppenheimer Gbl returns to help us make a trade decision. For example, suppose you find that Oppenheimer Gbl 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 |
Oppenheimer Gbl 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 Oppenheimer Gbl mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Oppenheimer Gbl mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Oppenheimer Gbl mutual fund over time.
Current vs Lagged Prices |
Timeline |
Oppenheimer Gbl Lagged Returns
When evaluating Oppenheimer Gbl's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Oppenheimer Gbl mutual fund have on its future price. Oppenheimer Gbl 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, Oppenheimer Gbl autocorrelation shows the relationship between Oppenheimer Gbl mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Oppenheimer Gbl Alloc.
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 Oppenheimer Gbl 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, Oppenheimer Gbl's short interest history, or implied volatility extrapolated from Oppenheimer Gbl options trading.
Becoming a Better Investor with Macroaxis
Macroaxis puts the power of mathematics on your side. We analyze your portfolios and positions such as Oppenheimer Gbl Alloc using complex mathematical models and algorithms, but make them easy to understand. There is no real person involved in your portfolio analysis. We perform a number of calculations to compute absolute and relative portfolio volatility, correlation between your assets, value at risk, expected return as well as over 100 different fundamental and technical indicators.Build Optimal Portfolios
Align your risk with return expectations
Check out Oppenheimer Gbl Correlation, Oppenheimer Gbl Volatility and Oppenheimer Gbl Alpha and Beta module to complement your research on Oppenheimer Gbl. You can also try the Balance Of Power module to check stock momentum by analyzing Balance Of Power indicator and other technical ratios.
Oppenheimer Gbl 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.