BTG Pactual Fund Forecast - 8 Period Moving Average
| BTLG11 Fund | BRL 96.12 0.38 0.39% |
The 8 Period Moving Average forecasted value of BTG Pactual Logstica on the next trading day is expected to be 96.58 with a mean absolute deviation of 0.83 and the sum of the absolute errors of 43.78. BTG Fund Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast BTG Pactual stock prices and determine the direction of BTG Pactual Logstica's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of BTG Pactual's historical fundamentals, such as revenue growth or operating cash flow patterns.
BTG |
BTG Pactual 8 Period Moving Average Price Forecast For the 29th of November
Given 90 days horizon, the 8 Period Moving Average forecasted value of BTG Pactual Logstica on the next trading day is expected to be 96.58 with a mean absolute deviation of 0.83, mean absolute percentage error of 1.08, and the sum of the absolute errors of 43.78.Please note that although there have been many attempts to predict BTG 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 BTG Pactual's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
BTG Pactual Fund Forecast Pattern
| Backtest BTG Pactual | BTG Pactual Price Prediction | Buy or Sell Advice |
BTG Pactual Forecasted Value
In the context of forecasting BTG Pactual'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. BTG Pactual's downside and upside margins for the forecasting period are 95.85 and 97.32, respectively. We have considered BTG Pactual'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 BTG Pactual fund data series using in forecasting. Note that when a statistical model is used to represent BTG Pactual 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 | 103.4822 |
| Bias | Arithmetic mean of the errors | 0.4248 |
| MAD | Mean absolute deviation | 0.8261 |
| MAPE | Mean absolute percentage error | 0.0085 |
| SAE | Sum of the absolute errors | 43.7838 |
Predictive Modules for BTG Pactual
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as BTG Pactual Logstica. 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.Other Forecasting Options for BTG Pactual
For every potential investor in BTG, whether a beginner or expert, BTG Pactual's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. BTG Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in BTG. Basic forecasting techniques help filter out the noise by identifying BTG Pactual's price trends.BTG Pactual 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 BTG Pactual fund to make a market-neutral strategy. Peer analysis of BTG Pactual could also be used in its relative valuation, which is a method of valuing BTG Pactual by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
BTG Pactual Logstica 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 BTG Pactual'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 BTG Pactual's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
BTG Pactual Market Strength Events
Market strength indicators help investors to evaluate how BTG Pactual fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading BTG Pactual shares will generate the highest return on investment. By undertsting and applying BTG Pactual fund market strength indicators, traders can identify BTG Pactual Logstica entry and exit signals to maximize returns.
BTG Pactual Risk Indicators
The analysis of BTG Pactual'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 BTG Pactual's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting btg 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 | 0.518 | |||
| Standard Deviation | 0.7279 | |||
| Variance | 0.5299 |
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 BTG Fund
BTG Pactual financial ratios help investors to determine whether BTG 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 BTG with respect to the benefits of owning BTG Pactual security.
| Headlines Timeline Stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity | |
| Economic Indicators Top statistical indicators that provide insights into how an economy is performing | |
| Idea Breakdown Analyze constituents of all Macroaxis ideas. Macroaxis investment ideas are predefined, sector-focused investing themes | |
| Equity Valuation Check real value of public entities based on technical and fundamental data |