Qs Strategic Real Fund Market Value
LRRCX Fund | USD 9.27 0.01 0.11% |
Symbol | LRRCX |
Qs Strategic '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 Qs Strategic'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 Qs Strategic.
03/18/2024 |
| 04/17/2024 |
If you would invest 0.00 in Qs Strategic on March 18, 2024 and sell it all today you would earn a total of 0.00 from holding Qs Strategic Real or generate 0.0% return on investment in Qs Strategic over 30 days. Qs Strategic is related to or competes with Clearbridge Aggressive, Clearbridge Small, Qs International, Qs International, Qs International, Clearbridge Appreciation, and Legg Mason. In seeking to meet its investment goal, the fund implements a tactical asset allocation program overseen by the funds ad... More
Qs Strategic 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 Qs Strategic'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 Qs Strategic Real upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 0.5 | |||
Information Ratio | (0.01) | |||
Maximum Drawdown | 1.89 | |||
Value At Risk | (0.78) | |||
Potential Upside | 0.6667 |
Qs Strategic Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Qs Strategic's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Qs Strategic's standard deviation. In reality, there are many statistical measures that can use Qs Strategic historical prices to predict the future Qs Strategic's volatility.Risk Adjusted Performance | 0.0729 | |||
Jensen Alpha | 0.0409 | |||
Total Risk Alpha | 0.01 | |||
Sortino Ratio | (0.01) | |||
Treynor Ratio | 1.31 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Qs Strategic'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.
Qs Strategic Real Backtested Returns
We consider Qs Strategic very steady. Qs Strategic Real retains Efficiency (Sharpe Ratio) of 0.17, which implies the entity had a 0.17% return per unit of price deviation over the last 3 months. We have found twenty-eight technical indicators for Qs Strategic, which you can use to evaluate the volatility of the fund. Please check Qs Strategic's market risk adjusted performance of 1.32, and Standard Deviation of 0.425 to confirm if the risk estimate we provide is consistent with the expected return of 0.0684%. The fund owns a Beta (Systematic Risk) of 0.0325, which implies not very significant fluctuations relative to the market. As returns on the market increase, Qs Strategic's returns are expected to increase less than the market. However, during the bear market, the loss of holding Qs Strategic is expected to be smaller as well.
Auto-correlation | 0.15 |
Insignificant predictability
Qs Strategic Real has insignificant predictability. Overlapping area represents the amount of predictability between Qs Strategic time series from 18th of March 2024 to 2nd of April 2024 and 2nd of April 2024 to 17th 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 Qs Strategic Real price movement. The serial correlation of 0.15 indicates that less than 15.0% of current Qs Strategic price fluctuation can be explain by its past prices.
Correlation Coefficient | 0.15 | |
Spearman Rank Test | 0.31 | |
Residual Average | 0.0 | |
Price Variance | 0.0 |
Qs Strategic Real lagged returns against current returns
Autocorrelation, which is Qs Strategic 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 Qs Strategic's mutual fund expected returns. We can calculate the autocorrelation of Qs Strategic returns to help us make a trade decision. For example, suppose you find that Qs Strategic 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 |
Qs Strategic 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 Qs Strategic mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Qs Strategic mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Qs Strategic mutual fund over time.
Current vs Lagged Prices |
Timeline |
Qs Strategic Lagged Returns
When evaluating Qs Strategic's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Qs Strategic mutual fund have on its future price. Qs Strategic 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, Qs Strategic autocorrelation shows the relationship between Qs Strategic mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Qs Strategic Real.
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 Qs Strategic 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, Qs Strategic's short interest history, or implied volatility extrapolated from Qs Strategic options trading.
Building efficient market-beating portfolios requires time, education, and a lot of computing power!
The Portfolio Architect is an AI-driven system that provides multiple benefits to our users by leveraging cutting-edge machine learning algorithms, statistical analysis, and predictive modeling to automate the process of asset selection and portfolio construction, saving time and reducing human error for individual and institutional investors.
Try AI Portfolio ArchitectCheck out Qs Strategic Correlation, Qs Strategic Volatility and Qs Strategic Alpha and Beta module to complement your research on Qs Strategic. Note that the Qs Strategic Real information on this page should be used as a complementary analysis to other Qs Strategic'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 Instant Ratings module to determine any equity ratings based on digital recommendations. Macroaxis instant equity ratings are based on combination of fundamental analysis and risk-adjusted market performance.
Qs Strategic 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.