Putnam Convertible Mutual Fund Forecast - Simple Exponential Smoothing
| PRCCX Fund | USD 27.84 0.06 0.22% |
The Simple Exponential Smoothing forecasted value of Putnam Convertible Incm Gwth on the next trading day is expected to be 27.84 with a mean absolute deviation of 0.20 and the sum of the absolute errors of 12.12. Putnam Mutual Fund Forecast is based on your current time horizon.
The relative strength index (RSI) of Putnam Convertible's mutual fund price is slightly above 62 indicating that the mutual fund is rather overbought by investors at this time. The main point of the Relative Strength Index (RSI) is to track how fast people are buying or selling Putnam, making its price go up or down. Momentum 62
Buy Extended
Oversold | Overbought |
Using Putnam Convertible hype-based prediction, you can estimate the value of Putnam Convertible Incm Gwth from the perspective of Putnam Convertible response to recently generated media hype and the effects of current headlines on its competitors.
The Simple Exponential Smoothing forecasted value of Putnam Convertible Incm Gwth on the next trading day is expected to be 27.84 with a mean absolute deviation of 0.20 and the sum of the absolute errors of 12.12. Putnam Convertible after-hype prediction price | USD 0.0 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as fund price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Putnam |
Putnam Convertible Additional Predictive Modules
Most predictive techniques to examine Putnam price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Putnam using various technical indicators. When you analyze Putnam charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Putnam Convertible Simple Exponential Smoothing Price Forecast For the 24th of January
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Putnam Convertible Incm Gwth on the next trading day is expected to be 27.84 with a mean absolute deviation of 0.20, mean absolute percentage error of 0.08, and the sum of the absolute errors of 12.12.Please note that although there have been many attempts to predict Putnam Mutual 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 Putnam Convertible's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Putnam Convertible Mutual Fund Forecast Pattern
| Backtest Putnam Convertible | Putnam Convertible Price Prediction | Buy or Sell Advice |
Putnam Convertible Forecasted Value
In the context of forecasting Putnam Convertible's Mutual 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. Putnam Convertible's downside and upside margins for the forecasting period are 26.76 and 28.92, respectively. We have considered Putnam Convertible'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 Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Putnam Convertible mutual fund data series using in forecasting. Note that when a statistical model is used to represent Putnam Convertible mutual 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 | 115.5298 |
| Bias | Arithmetic mean of the errors | -0.0289 |
| MAD | Mean absolute deviation | 0.1987 |
| MAPE | Mean absolute percentage error | 0.0076 |
| SAE | Sum of the absolute errors | 12.12 |
Predictive Modules for Putnam Convertible
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Putnam Convertible Incm. Regardless of method or technology, however, to accurately forecast the mutual fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the mutual 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 Putnam Convertible'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.
Putnam Convertible After-Hype Price Prediction Density Analysis
As far as predicting the price of Putnam Convertible at your current risk attitude, this probability distribution graph shows the chance that the prediction will fall between or within a specific range. We use this chart to confirm that your returns on investing in Putnam Convertible or, for that matter, your successful expectations of its future price, cannot be replicated consistently. Please note, a large amount of money has been lost over the years by many investors who confused the symmetrical distributions of Mutual Fund prices, such as prices of Putnam Convertible, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
Putnam Convertible Estimiated After-Hype Price Volatility
In the context of predicting Putnam Convertible's mutual fund value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on Putnam Convertible's historical news coverage. Putnam Convertible's after-hype downside and upside margins for the prediction period are 0.00 and 1.07, respectively. We have considered Putnam Convertible's daily market price in relation to the headlines to evaluate this method's predictive performance. Remember, however, there is no scientific proof or empirical evidence that news-based prediction models outperform traditional linear, nonlinear models or artificial intelligence models to provide accurate predictions consistently.
Current Value
Putnam Convertible is somewhat reliable at this time. Analysis and calculation of next after-hype price of Putnam Convertible Incm is based on 3 months time horizon.
Putnam Convertible Mutual Fund Price Prediction Analysis
Have you ever been surprised when a price of a Mutual Fund such as Putnam Convertible is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Putnam Convertible backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Fund price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with Putnam Convertible, there might be something going there, and it might present an excellent short sale opportunity.
| Expected Return | Period Volatility | Hype Elasticity | Related Elasticity | News Density | Related Density | Expected Hype |
0.11 | 1.08 | 0.00 | 0.29 | 0 Events / Month | 1 Events / Month | Within a week |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | ||
27.84 | 0.00 | 0.00 |
|
Putnam Convertible Hype Timeline
Putnam Convertible Incm is at this time traded for 27.84. The entity stock is not elastic to its hype. The average elasticity to hype of competition is -0.29. Putnam is forecasted not to react to the next headline, with the price staying at about the same level, and average media hype impact volatility is insignificant. The immediate return on the next news is forecasted to be very small, whereas the daily expected return is at this time at 0.11%. %. The volatility of related hype on Putnam Convertible is about 41.2%, with the expected price after the next announcement by competition of 27.55. The company last dividend was issued on the 26th of March 2020. Assuming the 90 days horizon the next forecasted press release will be within a week. Check out Historical Fundamental Analysis of Putnam Convertible to cross-verify your projections.Putnam Convertible Related Hype Analysis
Having access to credible news sources related to Putnam Convertible's direct competition is more important than ever and may enhance your ability to predict Putnam Convertible's future price movements. Getting to know how Putnam Convertible's peers react to changing market sentiment, related social signals, and mainstream news is a great way to find investing opportunities and time the market. The summary table below summarizes the essential lagging indicators that can help you analyze how Putnam Convertible may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| QCELX | Aqr Large Cap | 19.01 | 4 per month | 0.45 | 0.12 | 1.31 | (1.46) | 15.30 | |
| ALCEX | Avantis Large Cap | 0.26 | 1 per month | 0.51 | 0.13 | 1.66 | (1.33) | 3.75 | |
| PAFDX | T Rowe Price | (29.39) | 2 per month | 0.43 | 0.05 | 1.49 | (1.00) | 3.17 | |
| FCLKX | Fidelity Large Cap | 0.00 | 0 per month | 0.59 | 0.04 | 1.28 | (1.32) | 3.76 | |
| VAAGX | Virtus Nfj Large Cap | (18.02) | 4 per month | 0.56 | 0.08 | 1.73 | (1.44) | 11.75 | |
| DLQIX | Dreyfus Large Cap | 7.16 | 2 per month | 0.18 | 0.11 | 1.19 | (1.30) | 20.87 | |
| AMFFX | American Mutual Fund | 0.00 | 0 per month | 0.50 | 0.05 | 0.87 | (1.03) | 7.65 | |
| CMIFX | Calvert Large Cap | 0.01 | 1 per month | 0.00 | (1.55) | 0.10 | (0.10) | 0.21 |
Other Forecasting Options for Putnam Convertible
For every potential investor in Putnam, whether a beginner or expert, Putnam Convertible's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Putnam Mutual Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Putnam. Basic forecasting techniques help filter out the noise by identifying Putnam Convertible's price trends.Putnam Convertible 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 Putnam Convertible mutual fund to make a market-neutral strategy. Peer analysis of Putnam Convertible could also be used in its relative valuation, which is a method of valuing Putnam Convertible by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Putnam Convertible Market Strength Events
Market strength indicators help investors to evaluate how Putnam Convertible mutual fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Putnam Convertible shares will generate the highest return on investment. By undertsting and applying Putnam Convertible mutual fund market strength indicators, traders can identify Putnam Convertible Incm Gwth entry and exit signals to maximize returns.
| Daily Balance Of Power | 9.2 T | |||
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 27.84 | |||
| Day Typical Price | 27.84 | |||
| Price Action Indicator | 0.03 | |||
| Period Momentum Indicator | 0.06 | |||
| Relative Strength Index | 62.71 |
Putnam Convertible Risk Indicators
The analysis of Putnam Convertible'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 Putnam Convertible's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting putnam mutual 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 | 0.7591 | |||
| Semi Deviation | 0.8615 | |||
| Standard Deviation | 1.07 | |||
| Variance | 1.14 | |||
| Downside Variance | 0.9956 | |||
| Semi Variance | 0.7422 | |||
| Expected Short fall | (0.81) |
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.
Story Coverage note for Putnam Convertible
The number of cover stories for Putnam Convertible depends on current market conditions and Putnam Convertible's risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that Putnam Convertible is classified under. However, while its typical story may have numerous social followers, the rapid visibility can also attract short-sellers, who usually are skeptical about Putnam Convertible's long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
Other Macroaxis Stories
Our audience includes start-ups and big corporations as well as marketing, public relation firms, and advertising agencies, including technology and finance journalists. Our platform and its news and story outlet are popular among finance students, amateur traders, self-guided investors, entrepreneurs, retirees and baby boomers, academic researchers, financial advisers, as well as professional money managers - a very diverse and influential demographic landscape united by one goal - build optimal investment portfolios
Story Categories
Currently Trending Categories
Other Information on Investing in Putnam Mutual Fund
Putnam Convertible financial ratios help investors to determine whether Putnam 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 Putnam with respect to the benefits of owning Putnam Convertible security.
| Equity Analysis Research over 250,000 global equities including funds, stocks and ETFs to find investment opportunities | |
| Portfolio Suggestion Get suggestions outside of your existing asset allocation including your own model portfolios |