Q3 All Weather Sector Fund Market Value
| QAISX Fund | USD 9.70 0.01 0.10% |
| Symbol | QAISX |
Q3 All-weather '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 Q3 All-weather'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 Q3 All-weather.
| 11/30/2023 |
| 11/24/2024 |
If you would invest 0.00 in Q3 All-weather on November 30, 2023 and sell it all today you would earn a total of 0.00 from holding Q3 All Weather Sector or generate 0.0% return on investment in Q3 All-weather over 360 days. Q3 All-weather is related to or competes with Q3 All, Q3 All, William Blair, Longleaf Partners, Lazard Enhanced, Morgan Stanley, and Fidelity Series. Under normal circumstances, the fund will invest primarily in shares of other investment companies, including exchange-t... More
Q3 All-weather 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 Q3 All-weather'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 Q3 All Weather Sector upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.28 | |||
| Information Ratio | (0.08) | |||
| Maximum Drawdown | 3.9 | |||
| Value At Risk | (1.48) | |||
| Potential Upside | 1.21 |
Q3 All-weather Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Q3 All-weather's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Q3 All-weather's standard deviation. In reality, there are many statistical measures that can use Q3 All-weather historical prices to predict the future Q3 All-weather's volatility.| Risk Adjusted Performance | 0.0768 | |||
| Jensen Alpha | (0.0009) | |||
| Total Risk Alpha | (0.05) | |||
| Sortino Ratio | (0.05) | |||
| Treynor Ratio | 0.1191 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Q3 All-weather'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.
Q3 All Weather Backtested Returns
At this stage we consider QAISX Mutual Fund to be very steady. Q3 All Weather retains Efficiency (Sharpe Ratio) of 0.0847, which implies the fund had a 0.0847% return per unit of price deviation over the last 3 months. We have found twenty-eight technical indicators for Q3 All-weather, which you can use to evaluate the volatility of the entity. Please check Q3 All-weather's market risk adjusted performance of 0.1291, and Standard Deviation of 0.7028 to confirm if the risk estimate we provide is consistent with the expected return of 0.059%. The entity owns a Beta (Systematic Risk) of 0.51, which implies possible diversification benefits within a given portfolio. As returns on the market increase, Q3 All-weather's returns are expected to increase less than the market. However, during the bear market, the loss of holding Q3 All-weather is expected to be smaller as well.
Auto-correlation | -0.01 |
Very weak reverse predictability
Q3 All Weather Sector has very weak reverse predictability. Overlapping area represents the amount of predictability between Q3 All-weather time series from 30th of November 2023 to 28th of May 2024 and 28th of May 2024 to 24th of November 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 Q3 All Weather price movement. The serial correlation of -0.01 indicates that just 1.0% of current Q3 All-weather price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.01 | |
| Spearman Rank Test | -0.17 | |
| Residual Average | 0.0 | |
| Price Variance | 0.04 |
Q3 All Weather lagged returns against current returns
Autocorrelation, which is Q3 All-weather 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 Q3 All-weather's mutual fund expected returns. We can calculate the autocorrelation of Q3 All-weather returns to help us make a trade decision. For example, suppose you find that Q3 All-weather 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 |
Q3 All-weather 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 Q3 All-weather mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Q3 All-weather mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Q3 All-weather mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Q3 All-weather Lagged Returns
When evaluating Q3 All-weather's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Q3 All-weather mutual fund have on its future price. Q3 All-weather 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, Q3 All-weather autocorrelation shows the relationship between Q3 All-weather mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Q3 All Weather Sector.
Regressed Prices |
| Timeline |
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.Other Information on Investing in QAISX Mutual Fund
Q3 All-weather financial ratios help investors to determine whether QAISX Mutual Fund is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in QAISX with respect to the benefits of owning Q3 All-weather security.
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