Segall Bryant Hamill Fund Market Value
SBEMX Fund | USD 8.94 0.02 0.22% |
Symbol | Segall |
Segall Bryant '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 Segall Bryant'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 Segall Bryant.
02/27/2024 |
| 03/28/2024 |
If you would invest 0.00 in Segall Bryant on February 27, 2024 and sell it all today you would earn a total of 0.00 from holding Segall Bryant Hamill or generate 0.0% return on investment in Segall Bryant over 30 days. Segall Bryant is related to or competes with Westcore Orado, Westcore Plus, Westcore Global, Westcore Flexible, Westcore Small, Westcore Municipal, and Segall Bryant. The fund will invest at least 80 percent of its net assets in equity securities, primarily common stock, of companies ti... More
Segall Bryant 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 Segall Bryant'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 Segall Bryant Hamill upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 1.15 | |||
Information Ratio | 0.0158 | |||
Maximum Drawdown | 10.42 | |||
Value At Risk | (0.92) | |||
Potential Upside | 1.29 |
Segall Bryant Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Segall Bryant's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Segall Bryant's standard deviation. In reality, there are many statistical measures that can use Segall Bryant historical prices to predict the future Segall Bryant's volatility.Risk Adjusted Performance | 0.0798 | |||
Jensen Alpha | 0.111 | |||
Total Risk Alpha | (0.11) | |||
Sortino Ratio | 0.0155 | |||
Treynor Ratio | 0.5677 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Segall Bryant'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.
Segall Bryant Hamill Backtested Returns
We consider Segall Bryant very steady. Segall Bryant Hamill owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.15, which indicates the fund had a 0.15% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Segall Bryant Hamill, which you can use to evaluate the volatility of the fund. Please validate Segall Bryant's Semi Deviation of 0.9059, coefficient of variation of 743.54, and Risk Adjusted Performance of 0.0798 to confirm if the risk estimate we provide is consistent with the expected return of 0.1%. The entity has a beta of 0.25, which indicates not very significant fluctuations relative to the market. As returns on the market increase, Segall Bryant's returns are expected to increase less than the market. However, during the bear market, the loss of holding Segall Bryant is expected to be smaller as well.
Auto-correlation | 0.33 |
Below average predictability
Segall Bryant Hamill has below average predictability. Overlapping area represents the amount of predictability between Segall Bryant time series from 27th of February 2024 to 13th of March 2024 and 13th of March 2024 to 28th of March 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 Segall Bryant Hamill price movement. The serial correlation of 0.33 indicates that nearly 33.0% of current Segall Bryant price fluctuation can be explain by its past prices.
Correlation Coefficient | 0.33 | |
Spearman Rank Test | 0.33 | |
Residual Average | 0.0 | |
Price Variance | 0.0 |
Segall Bryant Hamill lagged returns against current returns
Autocorrelation, which is Segall Bryant 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 Segall Bryant's mutual fund expected returns. We can calculate the autocorrelation of Segall Bryant returns to help us make a trade decision. For example, suppose you find that Segall Bryant 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 |
Segall Bryant 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 Segall Bryant mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Segall Bryant mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Segall Bryant mutual fund over time.
Current vs Lagged Prices |
Timeline |
Segall Bryant Lagged Returns
When evaluating Segall Bryant's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Segall Bryant mutual fund have on its future price. Segall Bryant 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, Segall Bryant autocorrelation shows the relationship between Segall Bryant mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Segall Bryant Hamill.
Regressed Prices |
Timeline |
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 Segall Bryant 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, Segall Bryant's short interest history, or implied volatility extrapolated from Segall Bryant options trading.
Currently Active Assets on Macroaxis
Check out Segall Bryant Correlation, Segall Bryant Volatility and Segall Bryant Alpha and Beta module to complement your research on Segall Bryant. You can also try the Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
Complementary Tools for Segall Mutual Fund analysis
When running Segall Bryant's price analysis, check to measure Segall Bryant'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 Segall Bryant is operating at the current time. Most of Segall Bryant's value examination focuses on studying past and present price action to predict the probability of Segall Bryant's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Segall Bryant's price. Additionally, you may evaluate how the addition of Segall Bryant to your portfolios can decrease your overall portfolio volatility.
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Segall Bryant 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.