LevelUp^ Earnings Line - Quarterly EPSThe LevelUp Earnings Line plots quarterly earning per share (EPS) data providing a visual representation of the earnings trend over time.
Earnings are a foundational concept that can have a significant impact on a stock's longer term performance. With the option to view earnings as a plot versus a table of statistics, you can quickly identify earnings acceleration or deceleration. A steep line upwards from one earnings release to another, or a series of progressively higher EPS values, indicates a strong earnings trajectory. The more pronounced the acceleration, the more likely the company is to outperform the market.
At each quarterly earnings release you can view the details for Reported (non-GAAP), Diluted and Basic EPS by hovering over the plotted symbols on the earnings line.
This indicator uses TradingView's financial functions to request the following EPS data:
▪ Reported (non-GAAP) : this is one of the most popular ways to view earnings information. With non-GAAP, companies often exclude nonrecurring charges such as acquisitions and restructuring costs as these items are often not indicative of a companies overall performance.
▪ Basic : net income minus preferred dividends divided by the average number of common shares outstanding.
▪ Diluted : net income minus preferred dividends divided by the average number of common shares outstanding & convertible preferred shares such as convertible debt, equity options and warrants.
Although the quarterly earnings data is the same across all timeframes, viewing the longer term trend versus the shorter term trend is relevant based on the objectives of the investor. For example, the earnings growth on a monthly chart provides the big picture view, which may span years. This can be helpful for investors interested in more of a buy and hold approach.
The earnings trend on weekly and daily charts has fewer data points simply based on the shorter timeframe. This information is helpful for investors who are more focused on trades that may be weeks or months in length. The momentum and direction of the current earnings trend is of great importance for those looking to ride the current trend.
Summary:
Historical models have shown the best-performing companies have consistent earnings growth. Whether you are looking short or long term, understanding the earnings trend is a key factor in determining the potential price direction.
Key Features:
▪ Choose the EPS to plot: Reported (non-GAAP), Basic or Diluted.
▪ View stats for all EPS types.
▪ Plot on daily, weekly and monthly timeframes.
Move Earnings Line To Main Chart
▪ Click on the indicator name on left side of the chart.
▪ Select the "..." option.
▪ Use the "Move-to" option to change the location of the earnings line.
▪ To hide the EPS scale on the left, select the "..." option.
▪ In "Pin to scale" select the "No scale (fullscreen)" option.
The LevelUp Earnings Line is included the LevelUp Tools suite of TradingView indicators for trend followers.
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The Z-score The Z-score, also known as the standard score, is a statistical measurement that describes a value's relationship to the mean of a group of values. It's measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean.
The concept of Z-score was introduced by statistician Carl Friedrich Gauss as part of his "method of the least squares," which was an important step in the development of the normal distribution and Z-score tables. It's a key concept in statistics and is used in various statistical tests.
In financial analysis, Z-scores are used to determine whether a data point is usual or unusual. You can think of it as a measure of how many standard deviations an element is from the mean. For instance, a Z-score of 1.0 would denote a value that is one standard deviation from the mean. Z-scores are also used to predict probabilities, with Z-scores having a distribution that is expected to be normal.
In trading, a Z-score is used to determine how often a trading system may produce a string of winners or losers. It can help a trader to understand whether the losses or profits they see are something that the system would most likely produce, or if it's a once in a blue moon situation. This helps traders make decisions about when to start or stop a system.
I just wanted to play a bit with the Z-score I guess.
Feel free to share your findings if you discover additional applications for this strategy or identify timeframes where it appears to perform more optimally.
How it works:
This strategy is based on a statistical concept called Z-score, which measures the number of standard deviations a data point is from the mean. In other words, it helps determine how unusual or usual a data point is.
In the context of this strategy, Z-score is applied to a 10-period EMA (Exponential Moving Average) of Heikin-Ashi candlestick close prices. The Z-score is calculated over a look-back period of 25 bars.
The EMA of the Z-score is then calculated over a 20-bar period, and the upper and lower thresholds (bounds for buy and sell signals) are defined using the 90th and 10th percentiles of this EMA score.
Long positions are taken when the Z-score crosses above the lower threshold or crosses above the mid-line (50th percentile). An additional long entry is made when the Z-score crosses above the highest value the EMA has been in the past 100 periods.
Short positions are initiated when the EMA crosses below the upper threshold, lower threshold or the highest value the EMA has been in the past 100 periods.
Positions are closed when opposing entry conditions are met, for example, a long position is closed when the short entry condition is true, and vice versa.
Set your desired start date for the strategy. This can be modified in the timestamp("YYYY MM DD") function at the top of the script.
