Driehaus Emerging Markets Fund Market Value
| DRESX Fund | USD 20.08 0.01 0.05% |
| Symbol | Driehaus |
Driehaus Emerging '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 Driehaus Emerging'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 Driehaus Emerging.
| 01/21/2024 |
| 04/20/2024 |
If you would invest 0.00 in Driehaus Emerging on January 21, 2024 and sell it all today you would earn a total of 0.00 from holding Driehaus Emerging Markets or generate 0.0% return on investment in Driehaus Emerging over 90 days. Driehaus Emerging is related to or competes with Driehaus Emerging, Driehaus Multi, Driehaus Micro, Driehaus Small, Driehaus Emerging, Driehaus International, and Driehaus Smallmid. The fund uses a growth style of investment in equity securities, including common stocks and other equity securities of ... More
Driehaus Emerging 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 Driehaus Emerging'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 Driehaus Emerging Markets upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.6988 | |||
| Information Ratio | (0) | |||
| Maximum Drawdown | 2.96 | |||
| Value At Risk | (1.16) | |||
| Potential Upside | 1.29 |
Driehaus Emerging Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Driehaus Emerging's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Driehaus Emerging's standard deviation. In reality, there are many statistical measures that can use Driehaus Emerging historical prices to predict the future Driehaus Emerging's volatility.| Risk Adjusted Performance | 0.0759 | |||
| Jensen Alpha | 0.0601 | |||
| Total Risk Alpha | (0.01) | |||
| Sortino Ratio | (0) | |||
| Treynor Ratio | 0.4088 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Driehaus Emerging'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.
Driehaus Emerging Markets Backtested Returns
We consider Driehaus Emerging very steady. Driehaus Emerging Markets secures Sharpe Ratio (or Efficiency) of 0.12, which denotes the fund had a 0.12% return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Driehaus Emerging Markets, which you can use to evaluate the volatility of the entity. Please confirm Driehaus Emerging's Coefficient Of Variation of 817.16, mean deviation of 0.5453, and Downside Deviation of 0.6988 to check if the risk estimate we provide is consistent with the expected return of 0.0808%. The fund shows a Beta (market volatility) of 0.18, which means not very significant fluctuations relative to the market. As returns on the market increase, Driehaus Emerging's returns are expected to increase less than the market. However, during the bear market, the loss of holding Driehaus Emerging is expected to be smaller as well.
Auto-correlation | 0.23 |
Weak predictability
Driehaus Emerging Markets has weak predictability. Overlapping area represents the amount of predictability between Driehaus Emerging time series from 21st of January 2024 to 6th of March 2024 and 6th of March 2024 to 20th of April 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 Driehaus Emerging Markets price movement. The serial correlation of 0.23 indicates that over 23.0% of current Driehaus Emerging price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.23 | |
| Spearman Rank Test | 0.27 | |
| Residual Average | 0.0 | |
| Price Variance | 0.08 |
Driehaus Emerging Markets lagged returns against current returns
Autocorrelation, which is Driehaus Emerging 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 Driehaus Emerging's mutual fund expected returns. We can calculate the autocorrelation of Driehaus Emerging returns to help us make a trade decision. For example, suppose you find that Driehaus Emerging 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 |
Driehaus Emerging 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 Driehaus Emerging mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Driehaus Emerging mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Driehaus Emerging mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Driehaus Emerging Lagged Returns
When evaluating Driehaus Emerging's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Driehaus Emerging mutual fund have on its future price. Driehaus Emerging 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, Driehaus Emerging autocorrelation shows the relationship between Driehaus Emerging mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Driehaus Emerging Markets.
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 Driehaus Emerging 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, Driehaus Emerging's short interest history, or implied volatility extrapolated from Driehaus Emerging options trading.
Pair Trading with Driehaus Emerging
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Driehaus Emerging position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Driehaus Emerging will appreciate offsetting losses from the drop in the long position's value.Moving together with Driehaus Mutual Fund
| 0.98 | DIEMX | Driehaus Emerging Markets | PairCorr |
| 0.96 | DMAGX | Driehaus Multi Asset | PairCorr |
| 0.88 | DMCRX | Driehaus Micro Cap | PairCorr |
| 0.9 | DNSMX | Driehaus Small Cap | PairCorr |
The ability to find closely correlated positions to Driehaus Emerging could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Driehaus Emerging when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Driehaus Emerging - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Driehaus Emerging Markets to buy it.
The correlation of Driehaus Emerging is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Driehaus Emerging moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Driehaus Emerging Markets moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Driehaus Emerging can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Check out Driehaus Emerging Correlation, Driehaus Emerging Volatility and Driehaus Emerging Alpha and Beta module to complement your research on Driehaus Emerging. You can also try the Portfolio Center module to all portfolio management and optimization tools to improve performance of your portfolios.
Driehaus Emerging 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.