What is the seasonality?
The seasonality of a financial instrument is the average behaviour of its price in the previous years. In certain months of the year, a commodity or a stock, can be subjected to influences that produce recursive movements in the price.
The influences can derive from climatics factors (e.g. the temperature that influences the demand for a commodity used to heat) or calendar events (e.g. the release of the quarterly financial statements) etc.
The key is to understand how strong is the impact of a seasonal influence on the price. A stronger influence can produce, more likely, similar behaviour of the price in the future.
What is the difference between seasonality and cyclical analysis?
Seasonal cycles are observed within one calendar year, while cyclical effects, such as boosted sales due to low unemployment rates, can span time periods shorter or longer than one calendar year, such as 3-6 months or 5-10-15 or more years.
How is the seasonality calculated?
Seasonality is calculated by cumulating the average performances of each single trading day in a year, from January 1st to December 31th.
What are the lines that I see in the seasonal charts?
The default chart has 2 lines:
- the blue line is the seasonality
- the red line is the performance of the financial instrument on the current year
It is possible to add and/or edit the lines of the chart in every way you want. For instance, it is possible to add in the same chart more than one seasonalities or more years of performance.
What do the 6 charts show?
Following, there is a list of textual explanation of the 6 charts and the relative video-pill extracted from the Video 2.
The classic seasonality shows the average yearly performance of the symbol in the selected years. It is simply what we call seasonality: “the seasonality of Apple”, “the seasonality of Gold” etc.
The detrended seasonality is built from the classic seasonality and that line has been detrended through linear regression. This type of seasonality is useful to see better the major turning point of the market during the solar year, so in which timespan it is more reasonable to see an high or a low on that market.
Percentage of Positive Month
The percentage of positive month chart shows for each month the frequency in which a financial symbol has closed positively: closing price of the month > opening price of the month.
For instance, Goldman Sachs from 1999 to 2019:
- has closed negatively 65% of the times in May,
- has closed positively 80% of the times in October.
Monthly Average Performance
The monthly average performance chart is the historical performance of the financial instrument (or ratio) in each month of the year.
For example, the average performance of Facebook from 2012 to 2019 has been:
- + 11.49% in January,
- - 1.40% in February and March.
Monthly Average Volatility
The monthly average volatility chart shows the average volatility of the financial instrument in each month. It is calculated by averaging the distance between the monthly lowest low and the monthly highest high. It can represent an useful information for option traders or for a directional trader who want to decide the width of the stop loss for a trade in that month.
Equity Line Backtest
The equity line backtest shows the historical result of a simple strategy that, starting from an initial capital of 10,000:
- buy at the opening of the month,
- close the position at the closing price of the same month.
The chart is useful to see how stable is, during the whole historical series, the strength or the weakness of a financial instrument in a particular month.
TDW is an acronym for Trading Day of the Week. These graphs show the historical performance of the financial instrument on each day of the week, from Monday to Friday.
These graphs are useful to know if a financial instrument has an exceptional strength or weakness in one or more trading days of the week. This information can be used, for example, to build or improve a trading strategy.
DOM stands for Day Of Month. These graphs show the historical performance of the financial instrument on each day of the month, from the 1st to the 31st.
The histogram chart, above the others, is a summary of all the single DOM charts. All these charts can help a trader to understand better how the financial instrument has moved on average in his history, on a monthly basis.
For instance, this information can be used as an additional filter for a trading strategy:
- by buying a financial instrument only in the most bullish days of the month ,
- or by excluding long trades in the most bearish days of the month.
Interactive chart (technical analysis)
In this special chart it is possible to analyze a financial instrument (using ForecastCycles's historical data) with all the technical analysis tools offered by TradingView, including:
- draw trend lines, supports, resistances, etc.
- insert indicators (such as RSI, MACD, boolinger bands etc.)
- comparing the performance of multiple financial instruments in the same chart
- ... and much, much more
What does the algorithmic rank section show?
This section shows a rank, computed through a score assigned to every indication by our seasonal algorithm. An example of indication is “long Amazon from March 1st to March 31th”.
The score is attributed to an indication taking in consideration statistics such as average monthly performance, percentage of positive months, etc.
In this section, updated daily, you will see ranked by strength, the financial instruments with the greatest potential to generate a rise in price (in case of long indication) or a decline in price (in case of short indication) from the current day until the end of that month.
How to read Algorithmic Rank?
In this video Andrea explains how to read the algorithmic rank table.
Tutorial: Using Algorithmic Rank to buy Microsoft stock
In this video Andrea use an Algorithmic Rank indication to buy Microsoft stock in a demo account, to show beginners how to make a trade.
This video doesn’t want to represent a push to trade with real money, but a tutorial on how you can start gaining confidence and experience in trading through a demo account with virtual money.
What does the best seasonality section show?
This section shows a rank, order by the linear correlation coefficient computed between:
- the performance of the last year of a financial instrument (the last 250 days),
- its best seasonality. The best seasonality is the seasonal line that is more correlated to the last year of performances. For instance, the best seasonality can be the one computed on the last 5 years of data, or the one computed on the last 20 years of data.
In other words, in this section, we use the correlation coefficient to measure the grade of the similarity between the last 250 trading days of a financial instrument and its best seasonality.
The correlation coefficient can assume values between -1 (perfect inverse correlation) and +1 (perfect direct correlation).
More the correlation of the ‘best seasonality’ is near to 1:
- greater is the similarity between the last year of performance and the seasonal pattern of that financial instrument, and
- more likely that financial instrument could continue following its seasonal pattern.
What's a ticker?
A ticker is a term to describe a generic financial instrument.
How can I search and filter tickers?
To search for a financial instrument use the search bar. To have instruction about how to filter them, check the video.
Are stocks dividend and splits back-adjusted?
Yes, every stock is back-adjusted for dividends and split to avoid jumps in the historical series that would invalidate seasonal analysis of a financial instrument.
Are some historical series continuous futures data?
Yes, the historical series of the following asset classes are continuous futures data, to avoid that contango or backwardation would invalidate the seasonal analysis of a financial instrument:
- government bond prices
- stock indices
I can’t find a financial instrument that I would like to analyze.
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