What we learned from the Ethereum flash crash

in #money7 years ago

Let me try to explain what was the flash crash and why it might happened and what it taught us about the Ethereum market. It was Wednesday of June the 22nd this summer that the price of Ethereum dropped from about $320 and was traded at a low of 10 cents in a matter of minutes at the GDAX exchange (Coinbase’s online trading platform for trading cryptocurrencies).

At first people speculated in market manipulation but the following days GDAX claimed that there was no indication of any wrongdoing when announcing: “The crash was triggered by a multi-million-dollar selling order which brought the price down, from $317.81 to $224.48, and caused the following flood of 800 stop-loss and margin funding liquidation orders, crashing the market.”

In this way this flash crash resembles other famous flash crashes, as an example fresh in memory I would point to the 2010 New York Stock Exchange flash crash which occurred during a short span of just 36 minutes where prices dropped more than 9 % in that time span! Just as with Ethereum prices reverted back up quickly. There still haven’t been formulated an exact and proven reason for this flash crash back in 2010, but many experts point to the same reason as with the Ethereum flash crash, automated trading where a bunch of stop loss orders triggers each other in a market where there are few buyers thus shifting the price downwards until real human activity is resumed.

So what are stop losses, it is a function where you automate your positions in any asset to be sold off if the price reaches a certain level, it can also be following the price up so as long as the price rises you don’t sell but if at a time price suddenly drops let’s say 5 % or 10 you sell automatically. The other automated trades are liquidation which occurs when your leveraged meaning you borrowed money in order to invest, meaning if the price falls under a certain limit you can’t cover the position you’re in with the original money you invested, thus meaning you got to deposit more money and if you can’t act in time you position will be sold because you’re out of money! These automated trades can cause a chain reaction; one automated sale can trigger the next one and so on.

In a market with low demand this can cause a big decline in a short time also called a flash crash. So now I hope everybody have an understanding for what a flash crash is and what causes them to occur from time to time.

So what did we learn? From my perspective we can see that big changes can occur even on a very liquid market such as the New York Stock Exchange but a fall of 99 % such as seen in Ethereum shows us that the market is small and a few sellers can cause big drops in a matter of seconds. The stability in the market isn’t the same as the big fiat currencies or stock indices. But what does it mean, should we worry? I don’t see a reason to worry too much after all we saw the prices reverted back almost instantly just like what happened on the New York Stock Exchange. This tells us that the market quickly reacts and returns to normal; it can’t be manipulated that easily for long-term gain. But when manipulations like the flash crash does happen (even though it might not have been intentional, it was still a manipulated market in those moments the crash occurred) it can have big ramifications for people being leveraged!

Many costumers on the exchange lost a lot of money caused by forced liquidations, so I would still be weary trading for borrowed money in cryptocurrencies because the volatility is much more extreme than we see on any other market. But the long-term trend still seems intact even though I suggest we could see a decline in prices in the short term.

My take away from this post is more to look at the flash crash as not only an instance related to cryptocurrencies, but as something that can happen on all the different financial assets being traded. Therefore don’t put too much into it, if one happens again and you’re not in the market with borrowed money or using stop losses, then do not worry.

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