Amongst other things, the fourth week of the Crypto Academy Season 3 taught us how to exploit market reversals to our advantage with the use of the commodity channel index (CCI). The course was geared towards the practical aspect of trading cryptocurrencies via demo accounts.
We reviewed a total of 26 entries in the intermediate course which is 67.5% lesser than last time. Although we hoped to see more participants perform the exercise, it appears the course wasn't quite as easy for most. Moving forward, we will dilute the level of practical exercises to foster increased participation.
On the bright side, we had no case of plagiarism last week. We appreciate the time and effort of all those who participated in the course. We thank you all for making this possible. For those who weren't able to participate, we look forward to seeing you in the next class. Also, thanks to the Steemit Team for organizing an enabling environment for users to learn more about the crypto world.
What I Noticed
First of all, the number of unique entries caught my attention whilst reviewing the homework task. 100% of the total submissions were unique. That's unbelievable! It seems the practicality of the course made it difficult to cheat. That said, the battle against plagiarism continues and we hope to get 100% unique content continually.
Participants displayed their understanding of market reversals and how the psychology of traders affects the direction of trends. The commodity channel index (CCI) was the oscillator used to monitor the change in the trading behaviour of people in the crypto market.
To add to that, the participants were also able to filter the signals of CCI with the use of other indicators, such as; Moving Average Convergence Divergence (MACD), Bollinger Bands, and so on.
Average Score
The scatter diagram below reveals an increase in the average score of submissions:
The simple average score for submissions on #asaj-s3week4 tag stands at 6.27
The average score of participants has risen by 10% when compared to the previous time. There are three possible reasons for this.
Firstly, it appears most persons who performed the last task have some experience in the crypto space.
Secondly, it can be observed in the scatter diagram above that there are no entries in the zero territories which means that the level of high-quality contents had increased.
Thirdly, the tasks were constructed in such a way that no two persons can have the same answer. So, it would be easy to spot plagiarised content.
Talking about the exercise, we tried to assess how participants understood the course using the following task:
Open a demo account on any trading broker and select five cryptocurrency pairs
Create a market entry and exit strategy
Use the signals of the Commodity Channel Index (CCI) to buy and sell the coins you have selected
Declare your profit or loss
Explain your trade management technique
To make the course easy, we started by explaining the meaning of market reversal and demonstrated how to use CCI to identify the reversals of market trends.
Generally, participants completed the tasks.
Homework Statistics (S03 • W04)
Before we delve into the statistics of submissions let us take a quick look at how they are categorized.
Quality Scale
The homework task is grouped using the following scale:
- Distinction: 8 to 10
- Good: 6.6 to 7.9
- Average: 5 to 6.5
- Below Average: 0 to 4.9
With that in mind, let's analyse the grades of entries.
Grade Analysis
Of the 26 entries, 6 participants made a distinction, 4 did a good job, 12 had an average performance, 4 did below average, and we had no plagiarism case. Here is a bar chart that shows this:
Furthermore, the doughnut chart below presents the data in percentage.
| Distinction | ||
| Good | ||
| Average | ||
| Below Average | ||
| Plagiarism | ||
Post of the Week
It took some mental gymnastics to select three out of the series of quality articles that were submitted. Remember the academy promotes healthy competition that seeks to improve the quality of submissions.
Know this: As far as you participated in the assignment you are a winner. Maybe not today, but someday you will be. We hope this encourages you to work harder in order to earn a spot in the post of the week. Now, here are the homework posts of the week (July 9th to 24th):
 |
| Provided unique answers using two Exponential Moving Averages in conjunction with the CCI oscillator to identify reversals in market trends. Chirag Bitoni's submission was properly formatted and his work clearly reveals his attention to detail. |
 |
| Brief but succinct. Atul Pathak's work exudes remarkable mastery of the commodity channel index (CCI) signals. With the combination of a momentum-based indicator and a trend-based indicator, Atul got some of the best signals. |
 |
| Demonstrated a clear understanding of the topic by presenting practical steps on how to use CCI to monitor changes in the trend direction of five cryptocurrencies. Chimaobi Nwaeze's work is also a practical guide on how to open a demo account on Paper Trading. |
We had a good time reading all your quality content and it is a pleasure to share our knowledge in the Crypto Academy. We look forward to seeing all your quality posts in the coming weeks.
Final Words
At the end of the day, it isn’t all about what you know but how well you express yourself. The mode of delivery is just as important as the knowledge you choose to deliver. Using complicated words often does not yield the best results. The primary purpose of communication is to express, not impress.
Hence, we encourage you to organize your work in a logical format and use simple terms to express yourself. You do not have to copy anyone. Be yourself! Don’t say that because one user answered a question in a certain way so you must do the same. No! Be yourself and your work will stand out.
We are building a community that fosters engagement through educative content. Like every successful community, it takes collective effort and cooperation. Remember that no one is perfect, we all need correction (myself included) to become better. So let us learn together.
Thank you so much professor @asaj for recognizing my work, Looking forward for your upcoming lectures.
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Thank you professor @Asaj for recognizing my work. This is a good motivation to me. I will do my best from now henceforth. Thank you #steemit community.
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Nice post please send me a woot
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