Market Plunge Baffles Wall Street
online.wsj.com
online.wsj.com
Trader 1 puts in a order to sell everything if the market goes down by 4% in 1 hour.
Trader 2 knows that and wants to get out of the market before trader 1 does in a crash, so he puts in a order to sell everything if the market goes down by 3.9% in 1 hour.
Trader 3, Trader 4, etc. continue this process.
Then you have a day like yesterday when the market goes down by 2 percent and there is a lot of uncertainty about Europe, causing more people to put in stop-loss orders. The one automatic order triggers hundreds more.
Now they are going to rollback some of these trades because it was an "Trading Error". When Investors on Wall St. have trades that make money it is because of their skill and they get bonuses. But when their own stop-loss program sells for a 70% loss they get a do over.There has to be a mechanism to undo cascade mistakes because, if someone figures out a way (and that's rather easy) to induce mistakes and to profit from them, it will shortly become the prevalent form of trading. We want exchanges to foster investment on productive companies.
If algorithmic trading causes vulnerability to mistakes, they need to revise their algorithms or factor in the risk of this type of loss; that's the way free markets work. The externalities of a sudden crash suck, but other than as a one-time emergency measure, rolling back all the trades isn't a good solution. Wall Street firms should've learned something since 1987.
That sounds contrary to what Goldman Sachs is saying why they shouldn't be sued. They are using the "big boys" defense.
http://www.cbsnews.com/stories/2010/04/21/politics/washingto...
This isn't necessarily everything that happened -- there's a ton of other rumors flying around about the yen carry trade and a lot of other random stuff.
"With Accenture, for example, 20,365 shares changed hands at around $39.98 during the minute of 2:46 p.m., then another 68,516 shares were traded at $38 per share during the minute of 2:47. But then in the 2:49 p.m. minute, 66,277 shares traded at one cent. By 2:50 p.m., the stock was back up to $39.51."
The trade at 2:50 pm is the is the one that intrigues me , i can understand how the other ones can be blamed/attributed to HFT algorithms , but how does one explain the bounce-back at 2:50 from one cent to 39.51 ?
Yes i might believe it is worth $40 but when i am getting something for much cheaper than that surely i would just buy and wait for it to go up, in which case the price rise should also be in stages, which it is not.
My take away from my experience in that industry was that you can't actually trust banks or other financial institutions to follow the rules; the best thing you can do is to make sure you're lost in the crowd. Don't stand out, and you won't get hammered down. These trades and this whole episode stood out, so of course they're going to retroactively change it to the detriment of anyone for whom it was a good thing.
1) Short DJIA.
2) Pick some stocks and place buy orders at $0.01.
3) Get a friend to fill those orders for you at $0.01, taking the loss. Call it a trader error.
4) A lot of poorly written algorithms, which take into account the last traded price, start selling to cover their stoploss orders (sell if the price < X).
5) Havoc ensues. DJIA is down. Cover your DJIA short and take the rest of the day off.
Assume the stocks you are manipulating are bid at 99.99, ask at 100.
3 - Your friend's first few sell orders at $0.01 or better are filled at about $99.99.
Your buy orders go unfilled.
4 - If your friend sold enough shares, the algorithms notice someone aggressively selling. They may undercut and sell at 99.99 or even 99.98.
The algorithms also place a few buy orders at 99.96-99.97.
5 - Your friend's trades (assuming he is placing multiple orders, and is selling a lot) execute and drive the price down to 99.96-99.97 or so.
6 - The algorithm's buy orders at 99.96-99.97, are filled by your friend's sell orders.
7 - Price back up to 99.99.
8 - Algorithms eventually sell the shares they bought at 99.96 at 99.99.
Sum total: the algorithms made a few pennies off your friend. Your DJIA short does pretty much whatever it would already have done.
Also, except in the case of certain rare events which cause high latency (e.g., yesterday), it is also illegal to play games like this. For instance, if the bid is 99 on BATS and only 50 on ARCA, and I want to sell, I can't sell on ARCA. (I'm grossly oversimplifying, of course, but my simplifications don't exclude the case of selling at $0.01 to fool the markets.)
If the market is 99.99-100.00 you cannot trade even at 99.98
As I understood you, algorithms notice someone dumping stock and they pick it up. Then they hope you were selling for cheaper than market value because you were in a hurry, not because you thought said stock was overvalued, and they try to pass off the stock later on.
Is this what "providing liquidity" means? It seems like a good thing, iff people generally do high-frequency trading far more than actual investment. What's providing that confidence? Experience?
Most liquidity providers would love to be in the market when it's panicking, because this is a great time to make a lot of money, but can't be there if their data is bad and they're at risk of enormous losses.
Similarly, any person who doesn't put their retirement fund into junk bonds and penny stocks is also a con artist. After all, they are avoiding risky markets!
Do you really think that it's of benefit to society for some people to show up to work every day and take home Wal-Mart wages, instead of having real alternatives?
A large share of this government waste goes to military contractors employed in completely unnecessary wars such as the multi-trillion-dollar mess in Iraq.
Also, please cite your "on average double" statistic. If my memory serves me, the discrepancy is about 30% on average, mainly because private-sector pay is far more recession-sensitive. (The discrepancy would shrink, if not reverse, in a growing economy with a healthy private sector.) For the record, low-level government employees do make more while upper-level people make considerably less than they do in the private sector.
Given the prevalence of unemployment, yes Walmart jobs are better than at least one real alternative.
Arbitrage and market-making are legitimate businesses that provide liquidity to markets, making it easier for other traders to get fair trades. (Whenever you trade, the fair value is assumed to be somewhere between the bid and ask, so you're paying about half the spread on every share you trade.)
Of course, many hedge funds out there are scams that exist to take fees while taking ridiculous (and poorly-disclosed) risks with others' money, but not all of them are.
The exchanges are breaking a whole bunch of trades and algorithms can't predict which trades will be broken. So imagine an algorithm bought at the bottom and sold halfway up the recover of yesterday's spike. Their buy orders at the bottom get broken. Their sells halfway up do not.
To meet their obligations, the algorithm must buy again at fully recovered prices. The process of breaking trades has turned a big profit into a big loss.
Market orders (sell at any price) are handled first, and then, limit orders are. You can only guarantee one thing: either execution, or a price level. And when you're dealing with stop losses, you want to guarantee the execution in most cases.
This US equity rally was driven by technically oriented buying from the Banks and the hedge funds. There was and still is a lack of legitimate institutional buying at these price levels. This was machine driven speculation enabled by the lack of reform in a system riddled with corruption, from the bottom to the top."
Translation: there's no real buyers in the market at the current price, so when panic came, there were no buys to prop up the free falling
link: http://jessescrossroadscafe.blogspot.com/2010/05/plunge-1000...
The problem was the NYSE paused trading for many of the stocks in question for 90 secs because of heavy sell pressure, driving those trades to other markets which had little to no liquidity for a few minutes (and are solely electronic). Compound that with a possible trading error, and HFT algorithms, and you had a short period of time where there were no bids for those stocks on those electronic markets.
When liquidity for those stocks returned to the market, the proper forces brought the stocks back to their bid/ask prices in a liquid market.