SRN Crypto Coin Forecast - 8 Period Moving Average
| SRN Crypto | USD 0.000087 0.000001 1.14% |
The 8 Period Moving Average forecasted value of SRN on the next trading day is expected to be 0.000087 with a mean absolute deviation of 0.00000339 and the sum of the absolute errors of 0.0002. SRN Crypto Coin Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast SRN crypto prices and determine the direction of SRN's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of SRN's historical fundamentals, such as revenue growth or operating cash flow patterns.
SRN |
SRN 8 Period Moving Average Price Forecast For the 2nd of December
Given 90 days horizon, the 8 Period Moving Average forecasted value of SRN on the next trading day is expected to be 0.000087 with a mean absolute deviation of 0.00000339, mean absolute percentage error of 0, and the sum of the absolute errors of 0.0002.Please note that although there have been many attempts to predict SRN Crypto Coin 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 SRN's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
SRN Crypto Coin Forecast Pattern
SRN Forecasted Value
In the context of forecasting SRN's Crypto Coin 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. SRN's downside and upside margins for the forecasting period are 0.000001 and 3.22, respectively. We have considered SRN'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 8 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of SRN crypto coin data series using in forecasting. Note that when a statistical model is used to represent SRN crypto coin, 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 | 78.8502 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0 |
| MAPE | Mean absolute percentage error | 0.048 |
| SAE | Sum of the absolute errors | 2.0E-4 |
Predictive Modules for SRN
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as SRN. Regardless of method or technology, however, to accurately forecast the crypto coin market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the crypto coin 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.Other Forecasting Options for SRN
For every potential investor in SRN, whether a beginner or expert, SRN's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. SRN Crypto Coin price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in SRN. Basic forecasting techniques help filter out the noise by identifying SRN's price trends.SRN 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 SRN crypto coin to make a market-neutral strategy. Peer analysis of SRN could also be used in its relative valuation, which is a method of valuing SRN by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
SRN Technical and Predictive Analytics
The crypto coin market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of SRN'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 SRN's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
SRN Market Strength Events
Market strength indicators help investors to evaluate how SRN crypto coin reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading SRN shares will generate the highest return on investment. By undertsting and applying SRN crypto coin market strength indicators, traders can identify SRN entry and exit signals to maximize returns.
| Accumulation Distribution | 0.0114 | |||
| Daily Balance Of Power | (1.00) | |||
| Rate Of Daily Change | 0.99 | |||
| Day Median Price | 1.0E-4 | |||
| Day Typical Price | 1.0E-4 | |||
| Price Action Indicator | (0.000001) | |||
| Period Momentum Indicator | (0.000001) | |||
| Relative Strength Index | 89.09 |
SRN Risk Indicators
The analysis of SRN'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 SRN's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting srn crypto coin 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 | 2.23 | |||
| Semi Deviation | 1.6 | |||
| Standard Deviation | 3.24 | |||
| Variance | 10.48 | |||
| Downside Variance | 9.26 | |||
| Semi Variance | 2.57 | |||
| Expected Short fall | (3.87) |
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.
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.When determining whether SRN offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of SRN's financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Srn Crypto.Check out Historical Fundamental Analysis of SRN to cross-verify your projections. You can also try the Piotroski F Score module to get Piotroski F Score based on the binary analysis strategy of nine different fundamentals.