ETHUSD Seasonality Forecast, 1st WOTY 2022

Seasonality helps us identify how price over a set period of time in the year typically performs. Not every year should seasonal behavior be expected, and some periods have strong or weak seasonal effects.

In these three charts I have Wayne's Pivots Pro and Pivot Probabilities applied, and combining the two we can get a trading strategy for seasonal effects.

While these percentage odds may sound good, in reality because the sample count is so low on ETHUSD , only 7 years so only 7 samples; it's difficult to say until there's more data with certainty if there is a true seasonal pattern to be analyzed. That being said, understanding the current limitations of the data, readers should take these historical probabilities and this analysis with a grain of salt.

Notes:

• All pivot points in these charts are on a weekly resolution.
  
• The orange dotted line is a weighted mean, taking pivot point levels and weighting historical probabilities against them to create a single probability weighted pivot point level. It acts like a mean of our visual histogram.
  

Chart 1

• Over the last 7 years, 71.42% or 5/7 closes on ETHUSD in the first week of the year were above the central pivot, CP ($3,848.04).
  
• Only 2 times before have we close below CP.
  
• Closing above R1 ($4,111.28) has occurred only once before.
  
• For these three reasons we will use a Bullish Range trade setup as it best fits the historical distribution of closes between any two pivot points.
  

Chart 2

• In the last 7 years, 57.17% (4 occurrences), of tops occurred between CP and R1.
  
• Three highs have occurred above R1 historically, 42.86% of the time.
  
• Because of the low sample count, it is safer to assume the odds are in reality closer to 50/50 whether or not we get a high above or below R1.
  
• The total, historical probability of a high above the Bullish Range target of H1 ($3979.66) is 71.43%, or 5/7.
  

Chart 3

• In the last 7 years, 57.17% (4 occurrences), of bottoms occurred between CP and S1 ($3567.65).
  
• Again, because of the low sample count, it is safer to assume the odds are in reality closer to 50/50 whether or not we get a low below or above S1.
  
• The total, historical probability of a low below the Bullish Range stop loss of L2 ($3436.03) is 28.58%, or 2/7.
  

Trade closed: stop reached:

In the following 12 hours, ETHUSD had a -6.69% (-$253.53) move; which was a high volatility move that reached the stop loss.

When you have a very small sample size for testing seasonal data, you run the risk of not being able to make statistically significant interpretations. It's exactly unpredictable events like these that, even if the odds look decent, you never bet more than you can afford to lose an any one given trade.

My interpretation for Chart 3 turned out to be very reasonable. It was safer to assume that the odds were in reality closer to 50/50, on if we got our low above or below S1 since we had a lack of significant historical occurrences. This is more-so an example of the importance of statistical interpretation, and how it can save you from taking trades with odds closer to a coinflip.