Federal Agricultural Mortgage Stock Market Value
| AGM-A Stock | USD 165.01 5.01 3.13% |
| Symbol | Federal |
Federal Agricultural Price To Book Ratio
Federal Agricultural '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 Federal Agricultural's stock 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 Federal Agricultural.
| 09/02/2024 |
| 12/01/2024 |
If you would invest 0.00 in Federal Agricultural on September 2, 2024 and sell it all today you would earn a total of 0.00 from holding Federal Agricultural Mortgage or generate 0.0% return on investment in Federal Agricultural over 90 days. Federal Agricultural is related to or competes with Federal Agricultural, Federal Agricultural, Federal Agricultural, Federal Agricultural, Orix Corp, Atlanticus Holdings, and Nelnet. Federal Agricultural Mortgage Corporation provides a secondary market for various loans made to borrowers in the United ... More
Federal Agricultural 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 Federal Agricultural's stock 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 Federal Agricultural Mortgage upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.4 | |||
| Information Ratio | 0.1164 | |||
| Maximum Drawdown | 12.97 | |||
| Value At Risk | (1.81) | |||
| Potential Upside | 3.43 |
Federal Agricultural Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Federal Agricultural's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Federal Agricultural's standard deviation. In reality, there are many statistical measures that can use Federal Agricultural historical prices to predict the future Federal Agricultural's volatility.| Risk Adjusted Performance | 0.1499 | |||
| Jensen Alpha | 0.3466 | |||
| Total Risk Alpha | 0.0308 | |||
| Sortino Ratio | 0.1599 | |||
| Treynor Ratio | 10.57 |
Federal Agricultural Backtested Returns
Federal Agricultural is out of control given 3 months investment horizon. Federal Agricultural secures Sharpe Ratio (or Efficiency) of 0.12, which denotes the company had a 0.12% return per unit of risk over the last 3 months. We were able to interpolate twenty-eight different technical indicators, which can help you to evaluate if expected returns of 17.01% are justified by taking the suggested risk. Use Federal Agricultural Mean Deviation of 1.17, coefficient of variation of 531.4, and Downside Deviation of 1.4 to evaluate company specific risk that cannot be diversified away. Federal Agricultural holds a performance score of 9 on a scale of zero to a hundred. The firm shows a Beta (market volatility) of 0.0332, which means not very significant fluctuations relative to the market. As returns on the market increase, Federal Agricultural's returns are expected to increase less than the market. However, during the bear market, the loss of holding Federal Agricultural is expected to be smaller as well. Use Federal Agricultural downside deviation, information ratio, and the relationship between the semi deviation and coefficient of variation , to analyze future returns on Federal Agricultural.
Auto-correlation | 0.25 |
Poor predictability
Federal Agricultural Mortgage has poor predictability. Overlapping area represents the amount of predictability between Federal Agricultural time series from 2nd of September 2024 to 17th of October 2024 and 17th of October 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 Federal Agricultural price movement. The serial correlation of 0.25 indicates that over 25.0% of current Federal Agricultural price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.25 | |
| Spearman Rank Test | -0.04 | |
| Residual Average | 0.0 | |
| Price Variance | 72.78 |
Federal Agricultural lagged returns against current returns
Autocorrelation, which is Federal Agricultural stock'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 Federal Agricultural's stock expected returns. We can calculate the autocorrelation of Federal Agricultural returns to help us make a trade decision. For example, suppose you find that Federal Agricultural 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 price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Federal Agricultural 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 Federal Agricultural stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Federal Agricultural stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Federal Agricultural stock over time.
Current vs Lagged Prices |
| Timeline |
Federal Agricultural Lagged Returns
When evaluating Federal Agricultural's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Federal Agricultural stock have on its future price. Federal Agricultural 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, Federal Agricultural autocorrelation shows the relationship between Federal Agricultural stock current value and its past values and can show if there is a momentum factor associated with investing in Federal Agricultural Mortgage.
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.When determining whether Federal Agricultural is a strong investment it is important to analyze Federal Agricultural's competitive position within its industry, examining market share, product or service uniqueness, and competitive advantages. Beyond financials and market position, potential investors should also consider broader economic conditions, industry trends, and any regulatory or geopolitical factors that may impact Federal Agricultural's future performance. For an informed investment choice regarding Federal Stock, refer to the following important reports:Check out Federal Agricultural Correlation, Federal Agricultural Volatility and Federal Agricultural Alpha and Beta module to complement your research on Federal Agricultural. You can also try the Portfolio Diagnostics module to use generated alerts and portfolio events aggregator to diagnose current holdings.
Federal Agricultural technical stock 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.