Inverse Emerging Markets Fund Market Value
| RYWWX Fund | USD 8.57 0.03 0.35% |
| Symbol | Inverse |
Inverse 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 Inverse 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 Inverse Emerging.
| 01/29/2023 |
| 01/18/2025 |
If you would invest 0.00 in Inverse Emerging on January 29, 2023 and sell it all today you would earn a total of 0.00 from holding Inverse Emerging Markets or generate 0.0% return on investment in Inverse Emerging over 720 days. Inverse Emerging is related to or competes with Fidelity Flex, Transamerica Short-term, Touchstone Ultra, Leader Short-term, Delaware Investments, Prudential Short, and Lord Abbett. The fund invests at least 80 percent of its net assets in financial instruments with economic characteristics that shoul... More
Inverse 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 Inverse 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 Inverse Emerging Markets upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 2.13 | |||
| Information Ratio | 0.1186 | |||
| Maximum Drawdown | 11.6 | |||
| Value At Risk | (3.69) | |||
| Potential Upside | 4.51 |
Inverse Emerging Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Inverse Emerging's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Inverse Emerging's standard deviation. In reality, there are many statistical measures that can use Inverse Emerging historical prices to predict the future Inverse Emerging's volatility.| Risk Adjusted Performance | 0.1078 | |||
| Jensen Alpha | 0.2562 | |||
| Total Risk Alpha | 0.2661 | |||
| Sortino Ratio | 0.1225 | |||
| Treynor Ratio | (1.13) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Inverse 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.
Inverse Emerging Markets Backtested Returns
Inverse Emerging appears to be somewhat reliable, given 3 months investment horizon. Inverse Emerging Markets holds Efficiency (Sharpe) Ratio of 0.12, which attests that the entity had a 0.12% return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Inverse Emerging Markets, which you can use to evaluate the volatility of the entity. Please utilize Inverse Emerging's Market Risk Adjusted Performance of (1.12), risk adjusted performance of 0.1078, and Downside Deviation of 2.13 to validate if our risk estimates are consistent with your expectations. The fund retains a Market Volatility (i.e., Beta) of -0.23, which attests to not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Inverse Emerging are expected to decrease at a much lower rate. During the bear market, Inverse Emerging is likely to outperform the market.
Auto-correlation | 0.10 |
Insignificant predictability
Inverse Emerging Markets has insignificant predictability. Overlapping area represents the amount of predictability between Inverse Emerging time series from 29th of January 2023 to 24th of January 2024 and 24th of January 2024 to 18th of January 2025. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Inverse Emerging Markets price movement. The serial correlation of 0.1 indicates that less than 10.0% of current Inverse Emerging price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.1 | |
| Spearman Rank Test | 0.24 | |
| Residual Average | 0.0 | |
| Price Variance | 1.03 |
Inverse Emerging Markets lagged returns against current returns
Autocorrelation, which is Inverse 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 Inverse Emerging's mutual fund expected returns. We can calculate the autocorrelation of Inverse Emerging returns to help us make a trade decision. For example, suppose you find that Inverse 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 |
Inverse 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 Inverse Emerging mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Inverse 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 Inverse Emerging mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Inverse Emerging Lagged Returns
When evaluating Inverse Emerging's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Inverse Emerging mutual fund have on its future price. Inverse 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, Inverse Emerging autocorrelation shows the relationship between Inverse Emerging mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Inverse Emerging Markets.
Regressed Prices |
| Timeline |
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Other Information on Investing in Inverse Mutual Fund
Inverse Emerging financial ratios help investors to determine whether Inverse 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 Inverse with respect to the benefits of owning Inverse Emerging security.
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