Catalyst Dynamic Alpha Fund Market Value
| CPEIX Fund | USD 23.01 0.12 0.52% |
| Symbol | Catalyst |
Catalyst Dynamic '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 Catalyst Dynamic'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 Catalyst Dynamic.
| 04/25/2023 |
| 04/19/2024 |
If you would invest 0.00 in Catalyst Dynamic on April 25, 2023 and sell it all today you would earn a total of 0.00 from holding Catalyst Dynamic Alpha or generate 0.0% return on investment in Catalyst Dynamic over 360 days. Catalyst Dynamic is related to or competes with Nasdaq 100, Nasdaq 100, and Nasdaq 100. The fund seeks to achieve its investment objective by investing primarily in common stocks of U.S More
Catalyst Dynamic 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 Catalyst Dynamic'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 Catalyst Dynamic Alpha upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.8283 | |||
| Information Ratio | 0.0736 | |||
| Maximum Drawdown | 4.65 | |||
| Value At Risk | (1.31) | |||
| Potential Upside | 1.46 |
Catalyst Dynamic Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Catalyst Dynamic's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Catalyst Dynamic's standard deviation. In reality, there are many statistical measures that can use Catalyst Dynamic historical prices to predict the future Catalyst Dynamic's volatility.| Risk Adjusted Performance | 0.0935 | |||
| Jensen Alpha | 0.0564 | |||
| Total Risk Alpha | 0.0384 | |||
| Sortino Ratio | 0.0847 | |||
| Treynor Ratio | 0.1043 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Catalyst Dynamic'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.
Catalyst Dynamic Alpha Backtested Returns
We consider Catalyst Dynamic very steady. Catalyst Dynamic Alpha secures Sharpe Ratio (or Efficiency) of 0.1, which signifies that the fund had a 0.1% return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Catalyst Dynamic Alpha, which you can use to evaluate the volatility of the entity. Please confirm Catalyst Dynamic's Risk Adjusted Performance of 0.0935, downside deviation of 0.8283, and Mean Deviation of 0.7831 to double-check if the risk estimate we provide is consistent with the expected return of 0.0982%. The fund shows a Beta (market volatility) of 1.23, which signifies a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, Catalyst Dynamic will likely underperform.
Auto-correlation | 0.12 |
Insignificant predictability
Catalyst Dynamic Alpha has insignificant predictability. Overlapping area represents the amount of predictability between Catalyst Dynamic time series from 25th of April 2023 to 22nd of October 2023 and 22nd of October 2023 to 19th 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 Catalyst Dynamic Alpha price movement. The serial correlation of 0.12 indicates that less than 12.0% of current Catalyst Dynamic price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.12 | |
| Spearman Rank Test | 0.07 | |
| Residual Average | 0.0 | |
| Price Variance | 3.92 |
Catalyst Dynamic Alpha lagged returns against current returns
Autocorrelation, which is Catalyst Dynamic 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 Catalyst Dynamic's mutual fund expected returns. We can calculate the autocorrelation of Catalyst Dynamic returns to help us make a trade decision. For example, suppose you find that Catalyst Dynamic 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 |
Catalyst Dynamic 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 Catalyst Dynamic mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Catalyst Dynamic mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Catalyst Dynamic mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Catalyst Dynamic Lagged Returns
When evaluating Catalyst Dynamic's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Catalyst Dynamic mutual fund have on its future price. Catalyst Dynamic 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, Catalyst Dynamic autocorrelation shows the relationship between Catalyst Dynamic mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Catalyst Dynamic Alpha.
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 Catalyst Dynamic 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, Catalyst Dynamic's short interest history, or implied volatility extrapolated from Catalyst Dynamic options trading.
Pair Trading with Catalyst Dynamic
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 Catalyst Dynamic 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 Catalyst Dynamic will appreciate offsetting losses from the drop in the long position's value.Moving together with Catalyst Mutual Fund
| 0.73 | HIICX | Catalystsmh High | PairCorr |
| 0.78 | HIIFX | Catalystsmh High | PairCorr |
| 0.74 | HIIIX | Catalystsmh High | PairCorr |
| 0.81 | MLXCX | Catalyst Mlp Infrast | PairCorr |
| 0.84 | MLXAX | Catalyst Mlp Infrast | PairCorr |
Moving against Catalyst Mutual Fund
| 0.55 | CWXCX | Catalystwarrington | PairCorr |
The ability to find closely correlated positions to Catalyst Dynamic could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Catalyst Dynamic 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 Catalyst Dynamic - 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 Catalyst Dynamic Alpha to buy it.
The correlation of Catalyst Dynamic 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 Catalyst Dynamic moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Catalyst Dynamic Alpha 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 Catalyst Dynamic 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 Catalyst Dynamic Correlation, Catalyst Dynamic Volatility and Catalyst Dynamic Alpha and Beta module to complement your research on Catalyst Dynamic. You can also try the ETF Categories module to list of ETF categories grouped based on various criteria, such as the investment strategy or type of investments.
Catalyst Dynamic 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.