ltrd Profile picture
May 7 18 tweets 6 min read Twitter logo Read on Twitter
[1] The hottest topic in the crypto universe last couple of days was $PEPE - a meme coin that went to top 40 coins and was the biggest meme surprise since SHIB in October 2021. How did the market look in the HFT data? Let’s see! 🧵🧵

#pepe #cryptocurrency #trading Image
[2] I focus on CEX trading because there were more analyses related to the $PEPE and trading on DEXes, such as the great thread by @thiccythot_ which can bring you a lot of value in terms of understanding what happened on $PEPE. Highly recommended thread.
[3] What is important in terms of the analysis of $PEPE is that we should divide our analysis into two periods: The first move with only a couple of exchanges that had $PEPE listed with really small liquidity and the second move with other exchanges in the game such as OKX. Image
[4] The first move was dominated by MEXC and GATE IO exchanges which collected almost all (except DEXes) volume in the first phase. The next phase was dominated by OKX with a huge volume there. Relatively slow in terms of listing was KuCoin and Binance with listing on May 5th.
[5] Let’s dive into the first phase of the move and focus on what was happening on the GATE IO exchanges. This first move should base on low liquidity, sharp moves with big market impact, and pretty big spreads. Image
[6] On the left y-axis, we have CVD (Cumulative Volume Delta) in USDT for Gate.io spot exchange. You can clearly see that we had big sell pressure - there was no sign of accumulation during the April 26-29 period, which we could anticipate.
[7] Especially from April 30th, we can see huge (probably) take profits and sell pressure. Even with such big sell pressure, there was so much bid liquidity in the orderbook that the price still was going parabolic.
[8] Spread in such times when the market is not full of market makers is pretty big and market impacts are huge, especially on those sharp moves where we can a lot of bad factors combined: fewer MMs, less liquidity, more FOMOers, and bigger latency.
[9] We see similar sell pressure on perps which means that big players were looking for a way to hedge their on-chain positions. It was probably the first perp for PEPE, so it was a great place to use the leverage in order to TP on their previously accumulated positions. Image
[10] As I said before - the first phase of the market is always related to the low liquidity and huge market impacts. This time was NOT different - we could see more than 10% of the market impact on the trades on PEPEUSDT. Image
[11] One of the trades filled over 340 levels in the orderbook and there were 51 trades that filled more than 50 levels.
[12] In the second phase on $PEPE, OKX exchange (both spot and perps) dominated the market in terms of volume. The CVD is much different and we can see sell pressure after the peak around .45 price of $PEPE. We see that market impacts are not as big as it was in the first phase. Image
[13] Here, we have OKX Perps. I checked it a few times and I can promise you that I have never seen such a chart before where the CVD and Price have such similar shapes. I cannot tell you how it is possible and I will definitely think about it more in the next few days. Image
[14] Let’s look at the market after the Binance Futures listing. BFUT is the exchange that can (on average) absorb the most market orders, so the market always changes a lot after a BFUT listing. This time was no different.
[15] We can see that right after the Binance Futures listing, OKX lost its dominance in the market, although, before the listing, OKX highly dominated the $PEPE market. From that point, spreads are much lower and liquidity is much better in the orderbooks. Image
[16] As you can see, there is still a big sell pressure both on the spot and perp. A similar situation was in the first half of 2021 where CVD on all of the pumped coins was highly negative. Those who could - hedged their position left retail in a trap. IS THIS TIME DIFFERENT?
[17] Listing policy is much more aggressive now than it was before and it makes the game much tougher for smaller market makers. Markets are much more efficient and the propagation of signals is faster than it was before - even on such illiquid coins as $PEPE.
[18 - the end] That's all for now - if you enjoyed it, please share it and comment.

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More from @ltrd_

Mar 26
A couple of days ago we had probably the most important listing this year - $ARB. It is the best possibility to understand the market because of the lack of perpetual swaps, withdrawals, and liquidity. Let’s take a look at it through the eyes of an HFT player.

#Arbitrum
In the first minutes of the trading, there is absolutely Wild West in terms of the market microstructure. You do not have perps and withdrawals, so the capability of HFT players is limited and then you can see the purest form of trading.
One of the first exchanges that listed $ARB was Kucoin. How different and strange is the market in the first minutes can be proved by the fact that although the possible price consensus for ARB was $1.3-$1.5, buy orders for over $200k were created over the price of $10.
Read 13 tweets
Jan 30
A lot of (probably most) the crypto exchanges produce fake trades that count into the overall turnover in order to move the exchange up in volume rankings. How really famous exchanges do it? How we can see it?

🧵🧵🧵

#trading #cryptocurrency Image
What do I mean by fake trade? It is a trade that you, as an other player in the market, cannot participate in, because it is an exchange's trade with itself. If you are not able to participate with this trade, it should not be included in the overall turnover.
Unfortunately, it is how a lot of exchanges promote themselves in rankings where they fight with tons of other exchanges. How can we spot it?
Read 8 tweets
Jan 26
Recently, I watch @LomahCrypto videos. What is visible, is that he almost always trades hot coins + BTC/ETH. What I wanted to check is if staying with top performers is typically good for you or not as a trader.
🧵I think the results with be insightful for everybody.🧵

#trading
I divided my data into two periods:

- First 10 days of 2023
- Rest of 2023

Data consists of all the Binance Spot instruments with quote currency in USDT and BUSD.
Firstly, I wanted to check the relation between price change in the first and second periods. You can see that the relation is good for us - better coins in period 1 are better in period 2. Unfortunately, we have 2 outliers that make our model bad (GALA and LDO) Image
Read 9 tweets
Jan 24
🧵🧵Why it is more important to know when to trade than what to trade?

Recently, I heard from @LomahCrypto during his live that one of the greatest mistakes is to trade when you should not. I would like to prove statistically and by visualization, that it is truth.

#trading
I created a simple portfolio:
- Choose one instrument randomly
- Choose when to open a position randomly
- Choose when to close the position randomly.

By doing that, I want to make sure that I do not interfere in choosing what I trade. We do not do anything special.
We have 100 buy trades, so we repeat the process from the previous tweet 100 times. Everything in random. What is not random is that I create this strategy for 3 different periods:
- The year 2023
- May 14th to June 9th (after LUNA collapse)
- Second half of 2022
Read 11 tweets
Jan 22
Last time my book recommendation had pretty good feedback. Today, I would like to encourage you to read probably the best book that I have ever read. It is Think Like A Rocket Scientist written by Ozan Varol.
Even the first two words on the cover sentence (Simple Strategies...) resonated with me. It is the book for everybody, from traders, through entrepreneurs to researchers. Everybody can take a lot from reading this position.
This book can tell you how to think about processes, how to gain the most from failures, and how to be comfortable with uncomfortable but necessary things in your life. I cannot stress out how good this book is.
Read 12 tweets
Jan 19
Crypto influencers persuade people to invest in low marketcap coins. Here I would like to show you what happens when tweets like this show up on your timeline. It can be a disaster for you and the market. Do not let anybody be his exit liquidity. $FIDA

🧵🧵🧵
Firstly, I would like to say that I would not like to be anybody's enemy. I just spot strange things on the market and try to analyze them. I am here to educate you as well and make you a better trader. These behaviors are not appropriate, unfortunately.
This tweet showed up at 01:35:40 p.m. on a Twitter account with over 155k followers. It pushed the market by almost 30% on really low liquidity. Let's see what exactly happened.
Read 10 tweets

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