QACTX Mutual Fund Market Value

QACTX
 Fund
  

USD 8.10  0.04  0.49%   

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 Tactical 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 Tactical and determine expected loss or profit from investing in Q3 All-Weather over a given investment horizon. Please see Q3 All-Weather Correlation, Q3 All-Weather Volatility and Q3 All-Weather Alpha and Beta module to complement your research on Q3 All-Weather.
Symbol

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
09/05/2022
No Change 0.00  0.0 
In 3 months and 1 day
12/04/2022
0.00
If you would invest  0.00  in Q3 All-Weather on September 5, 2022 and sell it all today you would earn a total of 0.00 from holding Q3 All-Weather Tactical or generate 0.0% return on investment in Q3 All-Weather over 90 days. Q3 All-Weather is related to or competes with JPMorgan Chase, Scheid Vineyards, Bondbloxx ETF, Galxe, FT Cboe, SECOM, and VANGUARD SMALL-CAP. The investment seeks a positive rate of return over a calendar year regardless of market conditions 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 Tactical 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
7.468.108.74
Details
Intrinsic
Valuation
LowReal ValueHigh
7.558.198.83
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 Tactical.

Q3 All-Weather Tactical Backtested Returns

Q3 All-Weather Tactical retains Efficiency (Sharpe Ratio) of -0.2, which implies the fund had -0.2% 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 Tactical standard deviation of 0.6328, and Market Risk Adjusted Performance of (1.14) to confirm the risk estimate we provide.
The entity owns a Beta (Systematic Risk) of 0.125, which implies not very significant fluctuations relative to the market. Let's try to break down what QACTX'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 Tactical 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

    
  0.20  

Weak predictability

Q3 All-Weather Tactical has weak predictability. Overlapping area represents the amount of predictability between Q3 All-Weather time series from 5th of September 2022 to 20th of October 2022 and 20th of October 2022 to 4th of December 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 Tactical price movement. The serial correlation of 0.2 indicates that over 20.0% of current Q3 All-Weather price fluctuation can be explain by its past prices.
Correlation Coefficient0.2
Spearman Rank Test0.07
Residual Average0.0
Price Variance0.03

Q3 All-Weather Tactical 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   
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       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   
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       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 Tactical.
   Regressed Prices   
Share
       Timeline  

Be your own money manager

Our tools can tell you how much better you can do entering a position in Q3 All-Weather without increasing your portfolio risk or giving up the expected return. As an individual investor, you need to find a reliable way to track all your investment portfolios. However, your requirements will often be based on how much of the process you decide to do yourself. In addition to allowing all investors analytical transparency into all their portfolios, our tools can evaluate risk-adjusted returns of your individual positions relative to your overall portfolio.

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Currently Active Assets on Macroaxis

Please see Q3 All-Weather Correlation, Q3 All-Weather Volatility and Q3 All-Weather Alpha and Beta module to complement your research on Q3 All-Weather. You can also try Positions Ratings module to determine portfolio positions ratings based on digital equity recommendations. Macroaxis instant position ratings are based on combination of fundamental analysis and risk-adjusted market performance.

Complementary Tools for analysis

When running Q3 All-Weather Tactical 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, fund 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...