ALM ES (Germany) Market Value

0P0001NBQF   130.01  0.58  0.44%   
ALM ES's market value is the price at which a share of ALM ES trades on a public exchange. It measures the collective expectations of ALM ES Actions investors about its performance. ALM ES is selling at 130.01 as of the 1st of December 2024; that is 0.44% down since the beginning of the trading day. The fund's open price was 130.59.
With this module, you can estimate the performance of a buy and hold strategy of ALM ES Actions and determine expected loss or profit from investing in ALM ES over a given investment horizon. Check out Trending Equities to better understand how to build diversified portfolios. Also, note that the market value of any fund could be closely tied with the direction of predictive economic indicators such as signals in board of governors.
Symbol

ALM ES '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 ALM ES's 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 ALM ES.
0.00
06/10/2023
No Change 0.00  0.0 
In 1 year 5 months and 24 days
12/01/2024
0.00
If you would invest  0.00  in ALM ES on June 10, 2023 and sell it all today you would earn a total of 0.00 from holding ALM ES Actions or generate 0.0% return on investment in ALM ES over 540 days.

ALM ES 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 ALM ES's 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 ALM ES Actions upside and downside potential and time the market with a certain degree of confidence.

ALM ES Market Risk Indicators

Today, many novice investors tend to focus exclusively on investment returns with little concern for ALM ES's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as ALM ES's standard deviation. In reality, there are many statistical measures that can use ALM ES historical prices to predict the future ALM ES's volatility.

ALM ES Actions Backtested Returns

As of now, ALM Fund is very steady. ALM ES Actions secures Sharpe Ratio (or Efficiency) of 0.0993, which signifies that the fund had a 0.0993% return per unit of return volatility over the last 3 months. We have found twenty-eight technical indicators for ALM ES Actions, which you can use to evaluate the volatility of the entity. Please confirm ALM ES's Semi Deviation of 0.5409, mean deviation of 0.5386, and Risk Adjusted Performance of 0.0939 to double-check if the risk estimate we provide is consistent with the expected return of 0.0745%. The fund shows a Beta (market volatility) of 0.0873, which signifies not very significant fluctuations relative to the market. As returns on the market increase, ALM ES's returns are expected to increase less than the market. However, during the bear market, the loss of holding ALM ES is expected to be smaller as well.

Auto-correlation

    
  0.68  

Good predictability

ALM ES Actions has good predictability. Overlapping area represents the amount of predictability between ALM ES time series from 10th of June 2023 to 6th of March 2024 and 6th of March 2024 to 1st of December 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 ALM ES Actions price movement. The serial correlation of 0.68 indicates that around 68.0% of current ALM ES price fluctuation can be explain by its past prices.
Correlation Coefficient0.68
Spearman Rank Test0.59
Residual Average0.0
Price Variance11.82

ALM ES Actions lagged returns against current returns

Autocorrelation, which is ALM ES 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 ALM ES's fund expected returns. We can calculate the autocorrelation of ALM ES returns to help us make a trade decision. For example, suppose you find that ALM ES has exhibited high autocorrelation historically, and you observe that the 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  

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

ALM ES Lagged Returns

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

Currently Active Assets on Macroaxis

ETFs
Find actively traded Exchange Traded Funds (ETF) from around the world
Efficient Frontier
Plot and analyze your portfolio and positions against risk-return landscape of the market.