Sei Institutional Mutual Fund Forecast - Triple Exponential Smoothing

LLOBX Fund   10.17  0.01  0.1%   
The Triple Exponential Smoothing forecasted value of Sei Institutional Managed on the next trading day is expected to be 10.15 with a mean absolute deviation of 0.05 and the sum of the absolute errors of 2.67. Sei Mutual Fund Forecast is based on your current time horizon.
  
Triple exponential smoothing for Sei Institutional - also known as the Winters method - is a refinement of the popular double exponential smoothing model with the addition of periodicity (seasonality) component. Simple exponential smoothing technique works best with data where there are no trend or seasonality components to the data. When Sei Institutional prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any trend in Sei Institutional price movement. However, neither of these exponential smoothing models address any seasonality of Sei Institutional Managed.

Sei Institutional Triple Exponential Smoothing Price Forecast For the 8th of January

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Sei Institutional Managed on the next trading day is expected to be 10.15 with a mean absolute deviation of 0.05, mean absolute percentage error of 0.01, and the sum of the absolute errors of 2.67.
Please note that although there have been many attempts to predict Sei 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 Sei Institutional's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Sei Institutional Mutual Fund Forecast Pattern

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Sei Institutional Forecasted Value

In the context of forecasting Sei Institutional'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. Sei Institutional's downside and upside margins for the forecasting period are 9.47 and 10.82, respectively. We have considered Sei Institutional'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.
Market Value
10.17
10.15
Expected Value
10.82
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Sei Institutional mutual fund data series using in forecasting. Note that when a statistical model is used to represent Sei Institutional 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.
AICAkaike Information CriteriaHuge
BiasArithmetic mean of the errors 0.0134
MADMean absolute deviation0.0453
MAPEMean absolute percentage error0.0043
SAESum of the absolute errors2.6707
As with simple exponential smoothing, in triple exponential smoothing models past Sei Institutional observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older Sei Institutional Managed observations.

Predictive Modules for Sei Institutional

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Sei Institutional Managed. 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.
Hype
Prediction
LowEstimatedHigh
9.5110.1810.85
Details
Intrinsic
Valuation
LowRealHigh
9.5810.2510.92
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Sei Institutional. Your research has to be compared to or analyzed against Sei Institutional's peers to derive any actionable benefits. When done correctly, Sei Institutional's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in Sei Institutional Managed.

Other Forecasting Options for Sei Institutional

For every potential investor in Sei, whether a beginner or expert, Sei Institutional's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Sei Mutual Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Sei. Basic forecasting techniques help filter out the noise by identifying Sei Institutional's price trends.

Sei Institutional 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 Sei Institutional mutual fund to make a market-neutral strategy. Peer analysis of Sei Institutional could also be used in its relative valuation, which is a method of valuing Sei Institutional by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Sei Institutional Managed Technical and Predictive Analytics

The mutual fund market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Sei Institutional'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 Sei Institutional's current price.

Sei Institutional Market Strength Events

Market strength indicators help investors to evaluate how Sei Institutional 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 Sei Institutional shares will generate the highest return on investment. By undertsting and applying Sei Institutional mutual fund market strength indicators, traders can identify Sei Institutional Managed entry and exit signals to maximize returns.

Sei Institutional Risk Indicators

The analysis of Sei Institutional'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 Sei Institutional's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting sei 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.
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.

Other Information on Investing in Sei Mutual Fund

Sei Institutional financial ratios help investors to determine whether Sei 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 Sei with respect to the benefits of owning Sei Institutional security.
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