Crédit Agricole Pink Sheet Forecast - Triple Exponential Smoothing
| CRARF Stock | USD 15.95 0.45 2.90% |
The Triple Exponential Smoothing forecasted value of Crdit Agricole SA on the next trading day is expected to be 15.98 with a mean absolute deviation of 0.14 and the sum of the absolute errors of 8.45. Crédit Pink Sheet Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Crédit Agricole stock prices and determine the direction of Crdit Agricole SA's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Crédit Agricole's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Crédit Agricole to cross-verify your projections. Crédit |
Most investors in Crédit Agricole cannot accurately predict what will happen the next trading day because, historically, stock markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the Crédit Agricole's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Crédit Agricole's price structures and extracts relationships that further increase the generated results' accuracy.
Triple exponential smoothing for Crédit Agricole - 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 Crédit Agricole 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 Crédit Agricole price movement. However, neither of these exponential smoothing models address any seasonality of Crdit Agricole SA. Crédit Agricole Triple Exponential Smoothing Price Forecast For the 6th of May
Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Crdit Agricole SA on the next trading day is expected to be 15.98 with a mean absolute deviation of 0.14, mean absolute percentage error of 0.05, and the sum of the absolute errors of 8.45.Please note that although there have been many attempts to predict Crédit Pink Sheet 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 Crédit Agricole's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Crédit Agricole Pink Sheet Forecast Pattern
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Crédit Agricole Forecasted Value
In the context of forecasting Crédit Agricole's Pink Sheet 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. Crédit Agricole's downside and upside margins for the forecasting period are 14.36 and 17.61, respectively. We have considered Crédit Agricole'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 Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Crédit Agricole pink sheet data series using in forecasting. Note that when a statistical model is used to represent Crédit Agricole pink sheet, 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 | Huge |
| Bias | Arithmetic mean of the errors | -0.0354 |
| MAD | Mean absolute deviation | 0.1432 |
| MAPE | Mean absolute percentage error | 0.0098 |
| SAE | Sum of the absolute errors | 8.4493 |
Predictive Modules for Crédit Agricole
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Crdit Agricole SA. Regardless of method or technology, however, to accurately forecast the pink sheet market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the pink sheet 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 Crédit Agricole'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 Crédit Agricole
For every potential investor in Crédit, whether a beginner or expert, Crédit Agricole's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Crédit Pink Sheet price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Crédit. Basic forecasting techniques help filter out the noise by identifying Crédit Agricole's price trends.Crédit Agricole 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 Crédit Agricole pink sheet to make a market-neutral strategy. Peer analysis of Crédit Agricole could also be used in its relative valuation, which is a method of valuing Crédit Agricole by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Crdit Agricole SA Technical and Predictive Analytics
The pink sheet market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Crédit Agricole'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 Crédit Agricole's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Crédit Agricole Market Strength Events
Market strength indicators help investors to evaluate how Crédit Agricole pink sheet reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Crédit Agricole shares will generate the highest return on investment. By undertsting and applying Crédit Agricole pink sheet market strength indicators, traders can identify Crdit Agricole SA entry and exit signals to maximize returns.
| Daily Balance Of Power | 9.2 T | |||
| Rate Of Daily Change | 1.03 | |||
| Day Median Price | 15.95 | |||
| Day Typical Price | 15.95 | |||
| Price Action Indicator | 0.22 | |||
| Period Momentum Indicator | 0.45 | |||
| Relative Strength Index | 75.28 |
Crédit Agricole Risk Indicators
The analysis of Crédit Agricole'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 Crédit Agricole's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting crédit pink sheet 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 | 1.03 | |||
| Semi Deviation | 1.21 | |||
| Standard Deviation | 1.66 | |||
| Variance | 2.76 | |||
| Downside Variance | 5.89 | |||
| Semi Variance | 1.46 | |||
| Expected Short fall | (2.05) |
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.
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Crédit Agricole in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Crédit Agricole's short interest history, or implied volatility extrapolated from Crédit Agricole options trading.
Pair Trading with Crédit Agricole
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 Crédit Agricole 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 Crédit Agricole will appreciate offsetting losses from the drop in the long position's value.Moving together with Crédit Pink Sheet
| 0.85 | HDB | HDFC Bank Limited Financial Report 15th of July 2024 | PairCorr |
| 0.63 | CIHKY | China Merchants Bank | PairCorr |
| 0.68 | CIHHF | China Merchants Bank | PairCorr |
Moving against Crédit Pink Sheet
| 0.88 | BPTS | Biophytis | PairCorr |
| 0.78 | RBGPF | Reckitt Benckiser | PairCorr |
| 0.7 | AULT | Ault Alliance | PairCorr |
| 0.7 | ITCL | Banco Ita Chile | PairCorr |
| 0.47 | FITBP | Fifth Third Bancorp | PairCorr |
The ability to find closely correlated positions to Crédit Agricole could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Crédit Agricole 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 Crédit Agricole - 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 Crdit Agricole SA to buy it.
The correlation of Crédit Agricole 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 Crédit Agricole moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Crdit Agricole SA 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 Crédit Agricole 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.Check out Historical Fundamental Analysis of Crédit Agricole to cross-verify your projections. You can also try the Equity Analysis module to research over 250,000 global equities including funds, stocks and ETFs to find investment opportunities.
Complementary Tools for Crédit Pink Sheet analysis
When running Crédit Agricole's price analysis, check to measure Crédit Agricole's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Crédit Agricole is operating at the current time. Most of Crédit Agricole's value examination focuses on studying past and present price action to predict the probability of Crédit Agricole's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Crédit Agricole's price. Additionally, you may evaluate how the addition of Crédit Agricole to your portfolios can decrease your overall portfolio volatility.
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