Seasonality refers to the phenomenon where there is a repeatable pattern (or trend) in the market.
When there is a clear seasonal pattern in a market or product, it can be used as an additional piece of insight to form a more reliable trade decision,
With this understanding, let's do a seasonal analysis on FTSE4Good Bursa Malaysia (F4GBM) Index and find out what we can learn from this!
What is FTSE4Good Bursa Malaysia (F4GBM) Index?
The F4GBM index represents the performance of more than 100 public-listed companies in Malaysia that demonstrates strong ESG practices.
These companies are selected from the FTSE Bursa Malaysia EMAS Index, which comprises small, medium, or large market capitalization companies.
Traders that are interested to gain exposure in F4GBM index can do so through the FTSE4Good Bursa Malaysia Index Futures (F4GM), Malaysia's first ESG-based futures contract.
How to conduct seasonal Analysis on F4GBM Index?
With more online tools and solutions available these days, it is easy to do seasonal analysis on most financial instruments like index and stocks.
One of those tools is the latest 'Seasonality' indicator on TradingView:
By applying the Seasonality indicator on the chart of F4GBM Index on TradingView, we'll be able to spot some interesting seasonal pattern.
The Seasonality indicator shows seasonal trend/pattern from 2015 to present day. Let me share with you what I got:
Seasonal Analysis on F4GBM Index
#1 Which months are the most seasonally-positive months?
There are 2 ways to spot this. Firstly, we can do it vertically by spotting the months with the most green (ie. bullish month) in the heatmap.
With this approach, we will be able to spot the month of October and December being two of the most bullish months since 2015.
Another way to do this is by looking at the 'Pos %' horizontal row. 'Pos %' refers to % of positive months. From this row, we can observe that:
December is the most seasonally bullish month for F4GBM Index with Pos % being 100% positive every year.
This is followed by October, with Pos % being 78% positive.
With this insight, traders could:
Potentially build their bias to be more bullish than bearish in these more seasonally bullish months, and;
Be more mindful with risk should there is a bearish trade opportunity as it goes against the overall historical seasonal pattern.
#2 Which months are the most seasonally-bearish months?
Reversing our approach from #1, we will be able to spot the seasonally bearish month for the F4GBM Index:
Firstly, we can do it vertically by spotting the months with the most red (ie. bearish month) in the heatmap.
With this approach, we will be able to spot the month of May and September being two of the most bearish months since 2015.
Another way to do this is by looking at the 'Pos %' horizontal row. 'Pos %' refers to % of positive months. From this row, we can observe that:
September is the most seasonally bearish month for F4GBM Index with Pos % at only 11% positive as a whole.
This is followed by June, with Pos % being 33% positive.
With this insight, traders could:
Potentially build their bias to be more bearish than bullish in these more seasonally bearish months, and;
Be more mindful with risk should there is a bullish trade opportunity as it goes against the overall historical seasonal pattern.
#3 Which month is seasonally more volatile than others?
Standard deviation is a measure of how big (or small) the dispersion of a measurement is around their mean. Analyzing this metric can help traders determine whether a month's changes tend to vary or remain more stable over successive years.
In our context, the larger the value of 'StDev' (Standard Deviation), the more volatile a particular month is from its average ('Avgs).
In this case, the month of July and August have a Standard Deviation value of 3.88 and 3.77 respectively, which is larger than the other months.
This also indicates that these months tend to have performance that deviates further from their average. For instance, in average, the month of July returned +1.87%. However, in reality, the actual performance from each individual years from 2015 - 2023 showed a big discrepancy from the average (eg. +6,27% and +7.04% in 2018 and 2020 respectively & -2.62% in 2021).
With this insight, traders could:
Avoid relying on average return figure too much for more volatile months as they tend to be less reliable.
#4 Which month is seasonally less volatile than others?
On the flip side, a lower Standard Deviation (StDev) would indicate that the performance of a particular month does not deviate as much from the average return figure.
In this example, both month of April and December displayed a Standard Deviation value of 1.86 and 1.92 respectively, which are lower than the other months.
This also imply that these months tend to have performance that deviates less from their average performance. For instance, in average, the month of December returned +2.20%. In comparison, the actual performance from each individual years from 2015 - 2023 showed a less discrepancy from the average compared to months with larger Standard Deviation value. .
With this insight, traders could:
Use average return figure as a reference while making trading decisions.
#5 Be cautious of 'Average' (when there are outliers)
While 'Average' performance could be a reference while making trade decision, it is not the most reliable when there is a rare outlier in the calculation.
For instance, the average performance of F4GBM from 2015 - 2023 for the month of September is -1.95%. However, while other years had displayed return that closely resembles the average, there is an outlier of -7.37% in 2022.
In this scenario, having an larger negative % outlier could deviate the average figure further towards negative.
For some instances, traders may find it helpful to exclude the outlier figure from the calculation of average performance.
This can be done by excluding specific months from the Seasonality indicator's calculations. To exclude a month in TradingView, write it in the "YYYY-MM" format.
Let's look at the difference after we exclude September from the average performance for year 2022:
The result: A lower average performance figure of -1.27% (vs -1.95%) and a lower Standard Deviation of 1.13 (vs 2.29).
With this insight, traders could:
Identify and remove a rare outlier figure from average performance calculation to give a better picture of performance under normal circumstances.
Verdict: Use seasonal tools to help you make better trade decisions
In this post, we've learned to use Seasonal tools like the Seasonal Indicator on TradingView to do a detailed seasonal analysis for F4GBM Index, which can be applied on the F4GM futures.
I hope this is helpful in giving you a new perspective, and in return helping you make better trade decisions!
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Disclaimers
Any of the information above is produced with my own best effort and research.
This post is produced purely for sharing purposes and should not be taken as a buy/sell recommendation. Past return is not indicative of future performance. Please seek advice from a licensed financial planner before making any financial decisions.
Leverage is a financial tool that comes with its advantages and risks. Please learn and understand both the upsides and downsides of leverage before using it for trading.
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