QAISX Mutual Fund Market Value

QAISX
 Fund
  

USD 8.96  0.04  0.45%   

Q3 All-Weather's market value is the price at which a share of Q3 All-Weather stock trades on a public exchange. It measures the collective expectations of Q3 All-Weather Sector investors about the entity's future performance. With this module, you can estimate the performance of a buy and hold strategy of Q3 All-Weather Sector and determine expected loss or profit from investing in Q3 All-Weather over a given investment horizon. Please see Q3 All-Weather Hype Analysis, Q3 All-Weather Correlation, Portfolio Optimization, Q3 All-Weather Volatility, as well as analyze Q3 All-Weather Alpha and Beta and Q3 All-Weather Performance.
Symbol
Backtest

Please note, there is a significant difference between Q3 All-Weather's value and its price as these two are different measures arrived at by different means. Investors typically determine Q3 All-Weather value by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Q3 All-Weather's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.

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.
0.00
02/05/2022
No Change 0.00  0.0 
In 4 months and 31 days
07/05/2022
0.00
If you would invest  0.00  in Q3 All-Weather on February 5, 2022 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 150 days. Q3 All-Weather is related to or competes with Home Depot. Under normal circumstances, the adviser will invest in shares of other investment companies and similar products operati...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.

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.
Sophisticated investors, who have witnessed many market ups and downs, frequently view 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. Please use the tools below to analyze the current value of Q3 All-Weather in the context of predictive analytics.
Hype
Prediction
LowEstimated ValueHigh
8.038.969.89
Details
Intrinsic
Valuation
LowReal ValueHigh
8.119.049.97
Details
Naive
Forecast
LowNext ValueHigh
8.319.2310.16
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
8.629.059.49
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Q3 All-Weather. Your research has to be compared to or analyzed against Q3 All-Weather's peers to derive any actionable benefits. When done correctly, Q3 All-Weather's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy towards taking a position in Q3 All-Weather Sector.

Q3 All-Weather Sector Backtested Returns

Q3 All-Weather Sector retains Efficiency (Sharpe Ratio) of -0.12, which implies the fund had -0.12% of return per unit of price deviation over the last 3 months. Macroaxis outlook to forecasting the risk of any fund is to look at both systematic and unsystematic factors of the business, including all available market data and technical indicators. Q3 All-Weather exposes twenty-one different technical indicators, which can help you to evaluate volatility that cannot be diversified away. Please be advised to check Q3 All-Weather Sector market risk adjusted performance of (0.24), and Standard Deviation of 0.9039 to confirm the risk estimate we provide.
The entity owns a Beta (Systematic Risk) of 0.5286, which implies possible diversification benefits within a given portfolio. Let's try to break down what QAISX's beta means in this case. As returns on the market increase, Q3 All-Weather returns are expected to increase less than the market. However, during the bear market, the loss on holding Q3 All-Weather will be expected to be smaller as well. Even though it is essential to pay attention to Q3 All-Weather Sector existing price patterns, it is always good to be careful when utilizing equity price patterns. Our way in which we are forecasting any fund's future performance is to check both, its past performance charts as well as the business as a whole, including all available technical indicators. Q3 All-Weather exposes twenty-one different technical indicators, which can help you to evaluate its performance.

Auto-correlation

    
  -0.35  

Poor reverse predictability

Q3 All-Weather Sector has poor reverse predictability. Overlapping area represents the amount of predictability between Q3 All-Weather time series from 5th of February 2022 to 21st of April 2022 and 21st of April 2022 to 5th of July 2022. 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 Sector price movement. The serial correlation of -0.35 indicates that nearly 35.0% of current Q3 All-Weather price fluctuation can be explain by its past prices.
Correlation Coefficient-0.35
Spearman Rank Test-0.28
Residual Average0.0
Price Variance0.05

Q3 All-Weather Sector 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 mutual fund has exhibited high autocorrelation historically, and you observe that the stock is moving up for the past few days. In that case, you can expect the stock movement to match the lagging time series.
 Current and Lagged Values 
Share
      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 
Share
      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 
Share
      Timeline 

Q3 All-Weather Investors Sentiment

The influence of Q3 All-Weather's investor sentiment on the probability of its price appreciation or decline could be a good factor in your decision-making process regarding taking a position in QAISX. The overall investor sentiment generally increases the direction of a stock movement in a one-year investment horizon. However, the impact of investor sentiment on the entire stock markets does not have a solid backing from leading economists and market statisticians.
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 Q3 All-Weather 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, Q3 All-Weather's short interest history, or implied volatility extrapolated from Q3 All-Weather options trading.

Current Sentiment - QAISX

Q3 All-Weather Sector Investor Sentiment

Macroaxis portfolio users are evenly split in their perspective on investing in Q3 All-Weather Sector. What is your perspective on investing in Q3 All-Weather Sector? Are you bullish or bearish?
Bullish
Bearish
50% Bullish
50% Bearish

Currently Active Assets on Macroaxis

Please see Q3 All-Weather Hype Analysis, Q3 All-Weather Correlation, Portfolio Optimization, Q3 All-Weather Volatility, as well as analyze Q3 All-Weather Alpha and Beta and Q3 All-Weather Performance. Note that the Q3 All-Weather Sector information on this page should be used as a complementary analysis to other Q3 All-Weather'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 Alpha Finder module to use alpha and beta coefficients to find investment opportunities after accounting for the risk.

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When running Q3 All-Weather Sector price analysis, check to measure Q3 All-Weather's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Q3 All-Weather is operating at the current time. Most of Q3 All-Weather's value examination focuses on studying past and present price action to predict the probability of Q3 All-Weather's future price movements. You can analyze the entity against its peers and financial market as a whole to determine factors that move Q3 All-Weather's price. Additionally, you may evaluate how the addition of Q3 All-Weather to your portfolios can decrease your overall portfolio volatility.
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Q3 All-Weather 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, stock market cycles, or different charting patterns.
A focus of Q3 All-Weather technical analysis is to determine if market prices reflect all relevant information impacting that market. A technical analyst looks at the history of Q3 All-Weather trading pattern rather than external drivers such as economic, fundamental, or social events. It is believed that price action tends to repeat itself due to investors' collective, patterned behavior. Hence technical analysis focuses on identifiable price trends and conditions. More Info...