Real Estate Fund Market Value

RYHRX Fund  USD 42.01  0.34  0.80%   
Real Estate's market value is the price at which a share of Real Estate trades on a public exchange. It measures the collective expectations of Real Estate Fund investors about its performance. Real Estate is trading at 42.01 as of the 22nd of November 2024; that is 0.8 percent decrease since the beginning of the trading day. The fund's open price was 42.35.
With this module, you can estimate the performance of a buy and hold strategy of Real Estate Fund and determine expected loss or profit from investing in Real Estate over a given investment horizon. Check out Real Estate Correlation, Real Estate Volatility and Real Estate Alpha and Beta module to complement your research on Real Estate.
Symbol

Please note, there is a significant difference between Real Estate's value and its price as these two are different measures arrived at by different means. Investors typically determine if Real Estate is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Real Estate'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.

Real Estate '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 Real Estate'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 Real Estate.
0.00
10/29/2023
No Change 0.00  0.0 
In 1 year and 26 days
11/22/2024
0.00
If you would invest  0.00  in Real Estate on October 29, 2023 and sell it all today you would earn a total of 0.00 from holding Real Estate Fund or generate 0.0% return on investment in Real Estate over 390 days. Real Estate is related to or competes with Utilities Fund, Emerging Markets, Heritage Fund, and Value Fund. Under normal circumstances, the fund invests substantially all of its net assets in equity securities of Real Estate Com... More

Real Estate 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 Real Estate'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 Real Estate Fund upside and downside potential and time the market with a certain degree of confidence.

Real Estate Market Risk Indicators

Today, many novice investors tend to focus exclusively on investment returns with little concern for Real Estate's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Real Estate's standard deviation. In reality, there are many statistical measures that can use Real Estate historical prices to predict the future Real Estate's volatility.
Hype
Prediction
LowEstimatedHigh
41.2142.0142.81
Details
Intrinsic
Valuation
LowRealHigh
41.2942.0942.89
Details
Naive
Forecast
LowNextHigh
41.3242.1242.93
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
41.2442.1943.13
Details

Real Estate Fund Backtested Returns

At this stage we consider Real Mutual Fund to be very steady. Real Estate Fund maintains Sharpe Ratio (i.e., Efficiency) of 0.0253, which implies the entity had a 0.0253% return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Real Estate Fund, which you can use to evaluate the volatility of the fund. Please check Real Estate's Risk Adjusted Performance of 0.0621, coefficient of variation of 1243.95, and Semi Deviation of 0.763 to confirm if the risk estimate we provide is consistent with the expected return of 0.0204%. The fund holds a Beta of 0.14, which implies not very significant fluctuations relative to the market. As returns on the market increase, Real Estate's returns are expected to increase less than the market. However, during the bear market, the loss of holding Real Estate is expected to be smaller as well.

Auto-correlation

    
  0.45  

Average predictability

Real Estate Fund has average predictability. Overlapping area represents the amount of predictability between Real Estate time series from 29th of October 2023 to 11th of May 2024 and 11th of May 2024 to 22nd 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 Real Estate Fund price movement. The serial correlation of 0.45 indicates that just about 45.0% of current Real Estate price fluctuation can be explain by its past prices.
Correlation Coefficient0.45
Spearman Rank Test0.22
Residual Average0.0
Price Variance6.79

Real Estate Fund lagged returns against current returns

Autocorrelation, which is Real Estate 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 Real Estate's mutual fund expected returns. We can calculate the autocorrelation of Real Estate returns to help us make a trade decision. For example, suppose you find that Real Estate 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  

Real Estate 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 Real Estate mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Real Estate mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Real Estate mutual fund over time.
   Current vs Lagged Prices   
       Timeline  

Real Estate Lagged Returns

When evaluating Real Estate's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Real Estate mutual fund have on its future price. Real Estate 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, Real Estate autocorrelation shows the relationship between Real Estate mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Real Estate Fund.
   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 Real Mutual Fund

Real Estate financial ratios help investors to determine whether Real 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 Real with respect to the benefits of owning Real Estate security.
Equity Search
Search for actively traded equities including funds and ETFs from over 30 global markets
FinTech Suite
Use AI to screen and filter profitable investment opportunities
Content Syndication
Quickly integrate customizable finance content to your own investment portal
Watchlist Optimization
Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm