Boosting Alpha trading-Bots performance per May 2021

Boosting Alpha May 2021

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And again our end-of-month overview of all our trading bots.
The month of May turned out to be a very bad month for the crypto market with the Bitcoin declining with 35% and most other coins declining even more.

The average result of our trading bots was -8,31%. This was definitely the most negative month for our bots since we went live in January 2020 (the Corona crash from March 2020 did not have any impact on the 2 bots that we had live back then).

Among the negative performers were a lot of the HODL trading bots which look at the long-term only and only rebalance once every 2 weeks. If we look at the return in EUR, the EUR decline was higher with -16,51%, which was obviously higher because of the bots which have a BTC basecoin (Dagobert Buck bots + Hirundo).

Interesting to see is that there were also some bots which still had a very positive month of May as well with Roar of the Tiger at the top.

Roy Lenders, Boosting Alpha

 

How crash-proof are Bots?

“How crash-proof are Bots?
How will RevenYOU BOTS behave in a Bear-market?”

On the social media this was a  frequently asked question. The problem is that it needs time to draw such conclusions. Now curiously,  during exactly the first anniversary week of BOTS, we can now begin answer this question.
Why? Because during the first year of existence of the BOTS-Platform all went relatively smoothly, bullish or stable. Actually often with extreme yields.

Bots 1st anniversary week 2021

On the 19 May 2021  there was  a crash of BitcoinBitcoin and subsequently the whole crypto market.
How did the Bots survive, perform and recover?

We have created a Poll to rank individual Bots Creators for their crash-proof level. At this Creator level, because we already have a Bots Popularity Polls at the Bot level. Depending on how important you judge this aspect of performance-security, it can be a determining factor in this Poll.

Especially investors and traders who entered the market only recently, say this year, were shocked to see the volatility of Bitcoin (BTC) and many altcoins. Value and prices crashed by 50% or even more. This was a good opportunity to see how Bots behave specifically at the Creator level.  Was the damage limited or not, and how went performance recovery. This of course is valuable information for investors, new and experienced.

How crash-proof,  that is safe or secure are Bots produced by the diverse Bot Creators. This is where the Poll is all about. Some Bots have performed very well some even extremely well. However this is the time to prove if they are crash-proof or not at all. And how important is that to you and your cryptocurrency portfolio.

The first crash-proof Poll on 28 May 2021 has now some meat on the bone, with 53 voters and 104 choices, and can now be used to draw workable conclusions.

Total of 104 recorded votes by 53 voters for this poll on 28 May 2021

Of the 28 Bot Creators the top 5 have almost all the votes. The remaining developers or producers have only one or no votes.

  • The number 1 is Agga Team Bots (AB), by far the best reputation with regard being crash-proof.
  • The number 2 and 3 being one of the oldest producers is  Boosting Alpha (BA) and the BA trademark The Noogleman (TN).
  • The number 4 is Atmos (AM) and is one of the new Creators with currently  6 Bots. Three dated before the crash and 3 after the crash date.
  • Altrady (AT), also an “older” producers, with many non-USDT basecoin Bots.

Depending on your portfolio involvement, passive and even defensive, average or active and even aggressive, the Creator choice is important. Apart of the Risk Classification (RC) per Bot, this poll may be useful for you and other investors, in combination with the Bots Popularity Polls.

 

Why is my bot making less profit than the underlying coin?

Dear botbuilder, Crypto.bot trading in ETH only and took 10% while Ethereum went up by 20%!  Explain yourself!

This type of question comes on a daily base in a variety of flavors, one being more polite than the other. In both bear and bull markets our precious bot heroes are spending a lot of time justifying themselves, while in almost all cases the answer is straight forward. The bot acted rationally, the crypto market did not.
Very often these questions do not come from a lack of trust but more an attempt to better understand how these algorithms works. Therefore, I decided to use an example from the recent past to illustrate how bots behave and why it perfectly makes sense these things happen.

Let’s head into a real-life example.

For demonstration purposes I cut a few corners and use round numbers to ease the math. In reality it is far more complex but irrelevant for this illustration.

We go back to the beginning of May 2021. I have Crypto.bot running with 2850 USDT. Exactly 1 ETH at that time. What a coincidence.

Crypto.bot is in ETH for 100%.  On May the 2nd ETH hit the symbolic 3K. The so called “all time high” (ATH). While every vein in my body was shouting “To the moon!”, Crypto.bot started to see some orange flags. Its logic told him the risk of a correction became higher than the chance of continuing this steep upwards line. In an attempt to secure the profit it pro-actively traded 25% of in USDT.  The upwards trend continued and at 3.1K it secured another 25%.

While my emotions kept on shouting to buy more, my bot rationally decided to secure another 25% at 3.3K.

At that point I have 2350 USDT and 0.25 ETH in my portfolio. Against all odds, ETH kept on booming and went almost straight to 4K. On May the 6th Crypto.bot realized it was missing out too much and decided to buy again 50% of ETH at 3.5K.

The log file showed the below trades. I skipped a few and the actual numbers are slightly different but as mentioned before, for easy illustration purposes I simplified. In movie terms we would speak of “based on true events”.

Why is my bot making less profit
BOT performance: +11%
Ethereum performance: +19%

Conclusion

At certain thresholds, the algorithm decided to prioritize securing profit.  Would you really bet all your money that Ethereum would hit the 4K at that time?
Probably not. Crypto.bot did not either and unfortunately it missed some of the gain in his effort to secure some profit.

But then, would you have done better?

PS: If you want to know how it acted on the recent drop, keep an eye for my next post: “Lessons learned”.

 

How to Classify and typify BOTS?

Classification and typification of BOTS is an interesting  subject. In the blog post: Newcomer, Beginner approach to (RevenYOU) BOTS, it is described how to go about to purchase your first few Bots.
From experience we know that this is often the way the knowledge develops, based on growing interest end investments.  You want to know more about Bots and Cryptocurrency-Markets, behavior and the impact to your yield and risc.
While building a growing Bots-portfolio more and more question popup and need to be answered.

This was the reason to create a new page: Classes, Types of BOTS on the Bots Institute website. Although the text starts with: “Quick overview… ” these are many complexities involved in selecting the best bot for your purpose. The “Classes and types” table is structured with a matrix, in such way that it tries to trigger your interest and directs you into the required information sources available on the BI-website.

In addition being structured it includes many links and some footnotes. In this way it is simply a matter of clicking the link of your keyword to get to the relevant information, and back into the table.

Classes and types of bots table-matrix
Part of Classes and types of bots table-matrix
Classes and categories

At the highest level the Bots have been classified in two classes:
Trading Bots and Hodl Bots.
These two classes have there own very specific  and distinguishing characteristics.

These two classes can be divided into categories as follows:
• Class: Trading: Category:  1, 2, 3.
• Class: Hodl:  Category:  A, B.

In the first table-matrix the most important five characteristics are listed the left side. Then, at the right site of the matrix, it shows the respective values for particular categories of bots. Notice the differences between the two classes but even more between the two Hodl categories.

The Dumbbots need special care. While, the so called, “genuine bots”, act as your personal portfolio manager, the Dumbbots do not. These bots just buy a cryptocoin at the start and hold the coin as long as you do not sale (=stop) the bot. Meaning it just follows the marked, up or down, high or low. That means that trading, or not, is your own responsibility.

For instance, with regard to the Basecoin the matrix  value=”All” means all cryptocoins. In practice this is currently limited to  Binance BNB (Binance Coin), Bitcoin BTC (Bitcoin), EtheriumETH (Etherium), Tether USDT (Tether) and a single Uwezocoin UWC (Uwezocoin) bot.

Properties and Attributes matrix

The bottom part of the table contains the Properties and Attributes matrix.

In this second matrix the most noticeable properties and attributes are listed.  This shows a diversity of values with very different implications and impact. All keywords and their value may, or may not or more or less, influence your decision to buy, keep or sell a bot in your portfolio.

As an example the Bot Creator (®, ™, Label), may deem highly important to some person while others couldn’t care less.
In particular the combination of Bots Popularity Polls and the Creator name is a key property for some (potential) investors.

To view the full table see page: Classes, Types of BOTS.
Remember on the page, click the link of keywords, properties or attributes, to get to the related information.

 

Popularity Poll: Bots Top-15, Q2-2021, 350 ratings by 100 users

Our first Bots Top-10 in two Risk Classifications is dated 28 December 2020.  The second was:  Popularity Polls Bots Top-15, with over 200 user-ratings.

This is the third post about bots “popularity”.
The approach for these polls has been reconsidered. The most important reason for this is the Risk Classifications (RC).
The division in Risk Classifications is no longer used.
The reason is two fold:

  • The Bots Risk Classification is dynamic and can change over time, dramatically. For the purpose of Polls the RC is just one of the many aspects to be considered.
    So far there are no Bots available in the 3rd RC, Low (1-4) category. Due to these dynamics the value is limited.
  • How useful is the RC division for popularity ratings. Not only is the value limited, it is also under discussion with regard to cryptocurrency in general.

And yes, it is a long list of BOTS-Names and growing.
At this point in time we can draw conclusions about the Bot popularity and how the selected bots are valued by the investors. The investor may be you but new-comers in bots valuable the input even more.

On the poll-page users can indicate there experience and satisfaction with bots. The bot-strategy should be an important aspects, because this is important to all users. Aspects to take into consideration are: Overall performance, risk versus yield, stability vs volatility, Bots Creator score, availability (=to start) etc.
Do not forget that you can re-issue you votes at any time.  In principle the “Poll” is always actual. This with exception of the archive or historic polls.

Popularity Polls Bots Top-15, 8 May 2021
Popularity Polls Bots Top-15 of 350 recorded votes by 100 voters  on 8 May 2021.

The Top-15 Bots by 5 BOTS-Creators:

7 x (AB) Agga Team Bots,
3 x (DE) Dembots,
2 x (BA) Boosting Alpha,
2 x (AT) Altrady,
1 x (TO) TTO, Track This Out.

Interesting to notice that the recently new series “HODL the bottle top 35” and – 40  by Boosting Alpha,  hold the 1st and 2nd position.
In total the 7 out of 15 Agga Team Bots are in favour of our voters, both older but mostly relatively new Bots.  Dembots (aka DemaTrading.ai ) also have a solid position.

Thanks on behalf of all readers.
The BI-Team.

Blog post: How crash-proof are Bots?