Fidelity Emerging Markets Fund Market Value
| FCEM Fund | 10.10 0.08 0.79% |
| Symbol | Fidelity |
Fidelity 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 Fidelity Emerging'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 Fidelity Emerging.
| 10/31/2024 |
| 11/30/2024 |
If you would invest 0.00 in Fidelity Emerging on October 31, 2024 and sell it all today you would earn a total of 0.00 from holding Fidelity Emerging Markets or generate 0.0% return on investment in Fidelity Emerging over 30 days.
Fidelity 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 Fidelity Emerging'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 Fidelity Emerging Markets upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.19 | |||
| Information Ratio | (0.05) | |||
| Maximum Drawdown | 7.19 | |||
| Value At Risk | (1.58) | |||
| Potential Upside | 3.21 |
Fidelity Emerging Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Fidelity Emerging's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Fidelity Emerging's standard deviation. In reality, there are many statistical measures that can use Fidelity Emerging historical prices to predict the future Fidelity Emerging's volatility.| Risk Adjusted Performance | 0.0462 | |||
| Jensen Alpha | 0.0277 | |||
| Total Risk Alpha | (0.16) | |||
| Sortino Ratio | (0.05) | |||
| Treynor Ratio | 0.2277 |
Fidelity Emerging Markets Backtested Returns
As of now, Fidelity Fund is not too volatile. Fidelity Emerging Markets secures Sharpe Ratio (or Efficiency) of 0.0513, which denotes the fund had a 0.0513% return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Fidelity Emerging Markets, which you can use to evaluate the volatility of the entity. Please confirm Fidelity Emerging's Mean Deviation of 0.8488, coefficient of variation of 1823.8, and Downside Deviation of 1.19 to check if the risk estimate we provide is consistent with the expected return of 0.0699%. The fund shows a Beta (market volatility) of 0.28, which means not very significant fluctuations relative to the market. As returns on the market increase, Fidelity Emerging's returns are expected to increase less than the market. However, during the bear market, the loss of holding Fidelity Emerging is expected to be smaller as well.
Auto-correlation | 0.32 |
Below average predictability
Fidelity Emerging Markets has below average predictability. Overlapping area represents the amount of predictability between Fidelity Emerging time series from 31st of October 2024 to 15th of November 2024 and 15th of November 2024 to 30th of November 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 Fidelity Emerging Markets price movement. The serial correlation of 0.32 indicates that nearly 32.0% of current Fidelity Emerging price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.32 | |
| Spearman Rank Test | 0.05 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Fidelity Emerging Markets lagged returns against current returns
Autocorrelation, which is Fidelity Emerging 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 Fidelity Emerging's fund expected returns. We can calculate the autocorrelation of Fidelity Emerging returns to help us make a trade decision. For example, suppose you find that Fidelity Emerging 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 |
Fidelity 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 Fidelity Emerging fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Fidelity Emerging fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Fidelity Emerging fund over time.
Current vs Lagged Prices |
| Timeline |
Fidelity Emerging Lagged Returns
When evaluating Fidelity Emerging's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Fidelity Emerging fund have on its future price. Fidelity 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, Fidelity Emerging autocorrelation shows the relationship between Fidelity Emerging fund current value and its past values and can show if there is a momentum factor associated with investing in Fidelity Emerging Markets.
Regressed Prices |
| Timeline |
Pair Trading with Fidelity 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 Fidelity 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 Fidelity Emerging will appreciate offsetting losses from the drop in the long position's value.Moving together with Fidelity Fund
| 0.66 | 0P0000706A | RBC Select Balanced | PairCorr |
| 0.68 | 0P00007069 | RBC Portefeuille | PairCorr |
The ability to find closely correlated positions to Fidelity 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 Fidelity 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 Fidelity 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 Fidelity Emerging Markets to buy it.
The correlation of Fidelity 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 Fidelity Emerging moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Fidelity 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 Fidelity 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.| Pattern Recognition Use different Pattern Recognition models to time the market across multiple global exchanges | |
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