Symphony Floating Fund Forecast - 4 Period Moving Average
| SSF-UN Fund | CAD 7.07 0.05 0.71% |
The 4 Period Moving Average forecasted value of Symphony Floating Rate on the next trading day is expected to be 7.05 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.19. Symphony Fund Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Symphony Floating stock prices and determine the direction of Symphony Floating Rate's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Symphony Floating's historical fundamentals, such as revenue growth or operating cash flow patterns.
Symphony |
Symphony Floating 4 Period Moving Average Price Forecast For the 27th of November
Given 90 days horizon, the 4 Period Moving Average forecasted value of Symphony Floating Rate on the next trading day is expected to be 7.05 with a mean absolute deviation of 0.02, mean absolute percentage error of 0.0007, and the sum of the absolute errors of 1.19.Please note that although there have been many attempts to predict Symphony Fund prices using its time series forecasting, we generally do not recommend using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Symphony Floating's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Symphony Floating Fund Forecast Pattern
Symphony Floating Forecasted Value
In the context of forecasting Symphony Floating's Fund value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. Symphony Floating's downside and upside margins for the forecasting period are 6.62 and 7.49, respectively. We have considered Symphony Floating's daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the 4 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of Symphony Floating fund data series using in forecasting. Note that when a statistical model is used to represent Symphony Floating fund, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.| AIC | Akaike Information Criteria | 103.4714 |
| Bias | Arithmetic mean of the errors | -0.0067 |
| MAD | Mean absolute deviation | 0.021 |
| MAPE | Mean absolute percentage error | 0.003 |
| SAE | Sum of the absolute errors | 1.195 |
Predictive Modules for Symphony Floating
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Symphony Floating Rate. Regardless of method or technology, however, to accurately forecast the fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the fund market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Symphony Floating'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.
Other Forecasting Options for Symphony Floating
For every potential investor in Symphony, whether a beginner or expert, Symphony Floating's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Symphony Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Symphony. Basic forecasting techniques help filter out the noise by identifying Symphony Floating's price trends.Symphony Floating Related Equities
One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with Symphony Floating fund to make a market-neutral strategy. Peer analysis of Symphony Floating could also be used in its relative valuation, which is a method of valuing Symphony Floating by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Symphony Floating Rate Technical and Predictive Analytics
The fund market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Symphony Floating's price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of Symphony Floating's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Symphony Floating Market Strength Events
Market strength indicators help investors to evaluate how Symphony Floating fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Symphony Floating shares will generate the highest return on investment. By undertsting and applying Symphony Floating fund market strength indicators, traders can identify Symphony Floating Rate entry and exit signals to maximize returns.
| Accumulation Distribution | 11.46 | |||
| Daily Balance Of Power | 1.666667 | |||
| Rate Of Daily Change | 1.01 | |||
| Day Median Price | 7.06 | |||
| Day Typical Price | 7.06 | |||
| Price Action Indicator | 0.04 | |||
| Period Momentum Indicator | 0.05 |
Symphony Floating Risk Indicators
The analysis of Symphony Floating's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in Symphony Floating's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting symphony fund prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
| Mean Deviation | 0.3257 | |||
| Semi Deviation | 0.2835 | |||
| Standard Deviation | 0.4317 | |||
| Variance | 0.1863 | |||
| Downside Variance | 0.2386 | |||
| Semi Variance | 0.0803 | |||
| Expected Short fall | (0.46) |
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.
Pair Trading with Symphony Floating
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 Symphony Floating 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 Symphony Floating will appreciate offsetting losses from the drop in the long position's value.Moving together with Symphony Fund
| 0.83 | 0P0000706A | RBC Select Balanced | PairCorr |
| 0.83 | 0P00007069 | RBC Portefeuille | PairCorr |
| 0.75 | 0P0001FAU8 | TD Comfort Balanced | PairCorr |
| 0.88 | 0P00012UCU | RBC Global Equity | PairCorr |
The ability to find closely correlated positions to Symphony Floating could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Symphony Floating 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 Symphony Floating - 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 Symphony Floating Rate to buy it.
The correlation of Symphony Floating 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 Symphony Floating moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Symphony Floating Rate 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 Symphony Floating 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.Other Information on Investing in Symphony Fund
Symphony Floating financial ratios help investors to determine whether Symphony 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 Symphony with respect to the benefits of owning Symphony Floating security.
| Risk-Return Analysis View associations between returns expected from investment and the risk you assume | |
| Equity Forecasting Use basic forecasting models to generate price predictions and determine price momentum | |
| Funds Screener Find actively-traded funds from around the world traded on over 30 global exchanges | |
| Insider Screener Find insiders across different sectors to evaluate their impact on performance |