bocca dello squalo

 

  By: GZ on Domenica 21 Ottobre 2007 01:54

"....One trader I spoke with at a $10 billion hedge fund based in New York said that his computer executed 1,000 to 1,500 trades daily..." !!!!!!!!!!!!!!!!!!!! -------------------------------------- Technologyreview ha un reportage affascinante sul mondo del ^trading altamente computerizzato e scientifico#http://www.technologyreview.com/Biztech/19529/?a=f^, dove PHD in fisica, astronomia e matematica con dozzine di computers analizzano secondo per secondo 24 ore al giorno ogni titolo o strumento finanziario del mondo ed eseguono anche 1.000 o 2.000 operazioni giornaliere sullo stesso strumento. Si stima che intorno al 40% delle transazioni totali in borsa, cambi, derivati, bonds e commodities sia totalmente computerizzata, creata da gente che non legge bilanci e notizie, ma analizza solo numeri ------------------ ..One trader I spoke with at a $10 billion hedge fund based in New York said that his computer executed 1,000 to 1,500 trades daily (although he noted that they were not what he called "intra-day" trades). His inch-thick employment contract precluded my using his name, but he did talk a little bit about his approach. "Our system has a touch of genetic theory and a touch of physics," he said. By genetic theory, he meant that his computer generates algorithms randomly, in the same way that genes randomly mutate. He then tests the algorithms against historical data to see if they work. He loves the challenge of cracking the behavior of something as complex as a market; as he put it, "It's like I'm trying to compute the universe." Like most quants, the trader professed disdain for the "sixth sense" of the traditional trader, as well as for old-fashioned analysts who spent time interviewing executives and evaluating a company's "story." High-frequency trading is likely to become more common as the New York Stock Exchange gets closer and closer to a fully automated system. Already, 1,500 trades a day is conservative; the computers of some high-frequency traders execute hundreds of thousands of trades every day. Computers also underlie another developing frontier, high-frequency trading, which is a fantastically exaggerated form of day trading. The computer looks for patterns and inefficiencies over minutes or seconds rather than hours or days. An algorithm, for instance, might look for patterns in trading while the Japanese are at lunch, or in the moments before an important announcement. There is a massive amount of such data to crunch. Olsen Financial Technolo­gies, a Zürich-based firm that offers data for sale, says it collects as many as a million price updates per day. Linked with high-frequency trading is the developing science of event processing, in which the computer reads, interprets, and acts upon the news. A trade in response to an FDA announcement, for example, could be made in milliseconds. Capitalizing on this trend, Reuters recently introduced a service called Reuters NewsScope Archive, which tags Reuters-issued articles with digital IDs so that an article can be downloaded, analyzed for useful information, and acted upon almost instantly. I did manage to speak with some current traders, who gave me a general idea of their approach, and with some ex-traders, who were slightly more specific. One common method that quants use to identify market opportunities is pairs trading. Pairs trading involves trying to find securities that rise in tandem, or that tend to go in opposite directions. If that relationship falters--if, say, the values of two stocks that travel together suddenly diverge--it's likely to indicate that one stock is undervalued or overvalued. Which stock is which is irrelevant: a trader who simultaneously bets that one will go up and the other one down will probably make money. It's a strategy that lends itself to the use of computers, which can sort through huge numbers of price correlations over many years of stored data--although the final decision to speculate on the relative pricing of paired stocks generally rests with a fund's managers. Quants have also been pursuing a strategy known as "capi­tal structure arbitrage," which seeks to exploit inefficient pricing of a company's bonds versus its stocks. Again, computers do the searching, looking for instances where, for one reason or another, the securities are slightly misaligned. In a similar technique, Max Kogler, a principal at the newly launched MM Capital in New York, uses computers to look for inconsistencies in value between the option on an index fund and the options on the stocks that compose that index. Kogler has a master's from the University of Cambridge in pure mathematics with a focus on statistics. He says his algorithms look for "baskets of options that are not doing what they're supposed to be doing." When his computers find such a basket, he and his partners discuss whether or not to buy. Kogler runs his algorithms on "one Linux box." "Part of the allure of our algorithm," he said in an e-mail, "is that it cuts down computational requirements dramatically. Nonetheless, you'll want to have a ^speedy machine with pretty decent clock speed and a couple of parallel CPUs..#http://www.technologyreview.com/Biztech/19529/?a=f^, ^

 

  By: gianlini on Mercoledì 15 Agosto 2007 14:27

ad occhio e croce non è quanto hanno preso di bonus in 2-3 anni i partners??? allora non si lamentino e stiano buoni

 

  By: GZ on Mercoledì 15 Agosto 2007 13:48

perdere il -30% su dei miliardi di dollari quando le borse sono su del +15% significa fallire per un fondo hedge tanto è vero che Goldman Sachs ha annunciato che gli mette 3 miliardi di denaro suo per salvarlo Goldman giù da 235$ a 169$

 

  By: gianlini on Mercoledì 15 Agosto 2007 13:24

resta il fatto che mi stupisco perdere il 30 % in un anno su un singolo fondo, ora che tutti spingono sulla totale diversificazione e allocazione su decine se non centinaia di fondi, mi sembra una cosa del tutto normale (sarà che avendo perso il 70 % quest'anno, mi farebbe assai piacere aver limitato al 30 % la perdita) invece questi qua appena li si tocca anche per un solo centesimo nel portafoglio scattano subito come delle molle

un evento a 25 deviazioni standard - gz  

  By: GZ on Mercoledì 15 Agosto 2007 12:41

Nell'agosto 1998 il modello computerizzato per il trading del reddito fisso di un singolo mega-iper fondo hedge, Long Term Capital, creò da solo una crisi perchè non aveva previsto che la Russia potesse non pagare i suoi bonds Il risultato è che il fondo perse un -10% circa sulle posizioni in quanto tale, ma avendo una leva di 1 a 20 perdeva il 200% e fu spazzato via. Le banche centrali tagliarono i tassi a ottobre per impedire che le banche che gli prestavano i soldi andassero sotto e tenere su i mercati. I premi Nobel e matematici che vi lavoravano dissero che si era verificato "un evento che teoricamente accade ogni 10mila anni". Ieri Goldam Sachsche ha un fondo che perde il -30% in 12 mesi (cone le borse mondiali ancora in attivo del +12%) ha scritto agli investitori: "..“We are seeing things that were 25-standard deviation events, several days in a row,” said David Viniar, Goldman’s chief financial officer. “There have been some issues [before] in some of the other quantitative spaces, but nothing like what we saw last week.” a “25-standard deviation event” – something that only happens once every 100,000 years or more. ... ("..un evento a 25 deviazioni standard, qualcosa che accade ogni 100 mila secondo il modello del computer...") Oggi hai che i il modello computerizzato per il trading del reddito fisso, delle azioni, dei derivati, dei bonds immobiliari di decine di mega hedge fund da quelli di Goldman Sachs, Barclay's, Lehman, ARQ, Renaissance, D.E. Shaw (e tanti altri che non avete mai sentito nominare perchè sono nell isole vergini e non fanno pubblicità) sta creando una crisi perchè non aveva previsto che i derivati sui mutui immobiliari crollassero in alcuni casi del -60% Il problema è che questi PHD in fisica e matematica che lavorano per le banche e creano i modelli computerizzati usano algoritmi basati su dati in un periodo in cui c'era liquidità e li estrapolano. Poi avendo successo da cinque fondi che usano questi modelli nei hai cinquanta, poi cinquecento e alla fine tutti hanno su le stesse posizioni e quando liquidano si massacrano a vicenda e mandano giù i mercati. Ma i loro modelli non contemplano il caso in cui manca la liquidità, il denaro e lettera e il casi in cui tanti fondi usano tutti lo stesso modello alterando da soli il mercato... -------------------------- Limitations of computer models By Gillian Tett and Anuj Gangahar August 14 2007 19:28 In recent years, Goldman Sachs has become renowned as one of the savviest players on Wall Street. This week, however, the mighty US bank was forced into an embarrassing admission. In a rare unplanned investor call, the bank revealed that a flagship global equity fund had lost over 30 per cent of its value in a week because of problems with its trading strategies created by computer models. In particular, the computers had failed to foresee recent market movements to such a degree that they labelled them a “25-standard deviation event” – something that only happens once every 100,000 years or more. “We are seeing things that were 25-standard deviation events, several days in a row,” said David Viniar, Goldman’s chief financial officer. “There have been some issues [before] in some of the other quantitative spaces, but nothing like what we saw last week.” By any standards, it is a striking admission, given that these losses at the Goldman fund could top $1.5bn (£750m, €1.1bn). But what is more startling still is that Goldman Sachs is not alone in seeing its models go haywire. On the contrary, in recent days a host of other funds have experienced similar difficulties, including highly renowned funds at Renaissance Technologies. James Simons, founder of Renaissance and one of the most respected quantitative fund managers, last week wrote a letter to investors saying losses were about 9 per cent in the first few days of August (the funds have since recovered at least some of the losses). He also tellingly wrote that “we cannot predict the duration of the current environment,” highlighting the fact that even a group such as Renaissance – whose flagship fund, Medallion, has had an annual return of 30 per cent since 1988 – is suffering badly from recent movements. Other big-name funds that have been hit include Highbridge Capital (controlled by JPMorgan), DE Shaw, AQR Capital and Barclays Global Investors – as well as funds run by groups such as Lehman Brothers. “Models (ours including) are behaving in the opposite way we would predict and have seen and tested for over very long time periods,” said Lehman Brothers last week. A glance at recent financial history shows that this type of “rare” event is not so unusual at all. Back in 1998, for example, a key reason for the near-implosion of Long Term Capital Management was that the fund’s economic whizzkids – who included some Nobel prize-winning economists – had devised model-based trading strategies that turned sour when markets moved in unforeseen ways. Similarly, two years ago the financial industry received a shock when General Motors, the US car group, was downgraded – a move that left the price of financial assets gyrating in relation to each other in ways computers had not predicted. The question now being asked by some bankers – and regulators – is whether this week’s events show that the modern financial industry is foolish to be placing so much faith in these complex computer-driven models. “People say these are one-in-a-100,000-years events but they seem to happen every year,” says Satyajit Das, a consultant to hedge funds and investment banks. “This episode should make people ask questions about models – I think it could lead to a real reassessment.” Any such reassessment could have far-reaching consequences. The spread of financial models is at the heart of the growth of modern banking. Indeed, were it not for modern computing power, this decade’s remarkable explosion in finance would not have occurred at all. The roots of this revolution go back to the 1970s, when computers became small and flexible enough to be easily used by bankers – and bright minds in the world of economics started to move into finance. Initially, their techniques were mostly used to help asset managers decide which equities to buy. But in the 1980s, bankers started to use these tools to analyse complex debt securities, a development that later enabled them to create, price and trade instruments such as derivatives. This decade, the use of models has moved on to a whole new plane. As computing capabilities increased and global markets became more closely integrated, asset managers started relying on models to track asset prices and detect tiny anomalies that a human eye might struggle to see. Initially, people then traded on these anomalies; but soon they started using computers not just to spot anomalies but to execute trades too. Computers are thus now using models to make trades – and often trading with other computers – with barely any human intervention. This shift has delivered many powerful benefits for finance. Trading by computer is cheaper than using humans and can be quickly expanded in scale. It tends to be more consistent, since machines – unlike people – never get tired. More important still, computers can trade faster than humans, which is crucial when investment groups are racing one other to exploit tiny price differentials. As a result, computer-driven trading has proliferated, particularly in markets such as equities that tend to be readily accessed and highly liquid. In many cases, these strategies have delivered excellent investor results, as highlighted in Mr Simons’ letter. But while computers are often able to operate better than humans in “normal” markets, this month’s events demonstrate that during times of stress they have some crucial flaws. One problem is that models typically predict the future on the basis of past data. This can lead to distortions, given the speed at which the financial industry is currently evolving. Indeed, many of the instruments at the heart of the current credit storm barely existed before this decade – which means that computers can only model these markets based on the benign conditions of the past few years. Another big problem is that computer models do not always take account of the way that their own behaviour is affecting markets. The essential danger, as Donald Mackenzie, a British finance professor, points out, is a tendency to view models as “cameras”, snapping pictures of market movements. However, models are now so widely used that they often drive markets as well, Mr Mackenzie says, which means they are probably better viewed as an “engine”. “The emergence of modern economic theories of finance [have] affected markets in fundamental ways . . . models are not simply external analyses but intrinsic parts of economic processes,” he notes. In practical terms, this means that when models evaluate markets, they often fail to recognise how their own behaviour is distorting prices. Take the case of Amaranth, the hedge fund that imploded with $6bn of losses last year. Before this collapse, Amaranth was so dominant in the natural gas market that when it bought it tended to push up prices. These prices were then used in models that calculated Amaranth’s trading risk. But when Amaranth was forced to sell, gas prices collapsed much faster than any model might have predicted. Although Amaranth itself was not trading on the basis of models, this pattern of events can be doubly dangerous for asset managers using computer-driven programmes, for these computers have a nasty habit of all using similar strategies – partly because they are created by humans who have studied at the same institutions. Thus they can all dash for the exits at the same time. The issue of computer “herding” appears to be a key factor behind this month’s problems at the Goldman Sachs funds and others. Although aspects of this saga are still unknown, it appears to have started a few weeks ago when some large investment managers suffered losses on subprime securities. This prompted investment banks to demand that hedge funds post more cash against their trades – which in turn forced these funds to sell assets. However, since subprime securities were hard to trade, the forced sales occurred in other, more liquid markets such as equities. The consequence was a wave of triggered price movements that seemed utterly “irrational”, according to models. Last week, for example, the stock price of some highly valued companies suffered in relation to lowly-rated stocks such as US homebuilders. This appears to have been particularly devastating for the computer strategies used by Goldman’s fund, since such programmes typically assume that low-rated stocks will perform badly in a credit crunch. Since then, many of these extreme market swings have corrected themselves. Consequently, many of the so called “quants” (experts in quantitative models) who work in the financial industry insist that it is premature to criticise all these strategies. After all, they point out, the vast majority of models that are used in the markets work perfectly well. Moreover, efforts are under way to address problems such as the “feedback loop”, or danger of computer herding. One key focus of some banks, for example, is the search for ways to apply research in the field of artificial intelligence, or neural networking, to financial models. This, they hope, will enable them to “learn” from mistakes and bouts of irrationality – and thus perform better at times of market stress. “Academic research has been shifting to some degree from a focus on ‘efficient market’ theories to focus more on ‘inefficient market’ theories [and] there is an increased recognition of inefficient market trading strategies,” says Colm Fitzgerald, head of quantitative trading at the Bank of Ireland. “Investors in funds with strategies based on the latter models are not likely to be currently facing any trouble.” Nevertheless, whether these new “super-intelligent” models will do better remains to be seen. “Bankers talk about self-learning models, with neural networks and things, but a lot of that is hogwash,” says Mr Das. ..

 

  By: GZ on Martedì 26 Giugno 2007 01:00

Cosa sono i CDO ? Una cosa nuova intanto, nel 2002 se ne emettevano per 80 miliardi e nel 2006 per 500 miliardi Questi due hedge funds che ora vengono salvati prestandogli sembra 3.2 miliardi erano pieni di CDO e se li devono salvare evidentemente hanno perdite tipo del -30% e avendo 900 milioni di capitale e 6 miliardi investiti... beh... vuole dire che anche un cedimento piccolo dei mutui immobiliari possono creare velocemente perdite nei CDO Insomma ci sono in giro almeno 1.000 miliardi di questi derivati, CDO, creati tutti dopo il 2002, basati su dei rischi di credito per mutui immobiliari e altri prestiti e che sono trattati a prezzi teorici, quelli veri nessuno sa esattamente quali siano... ad esempio questi due fondi un mese fa pensavano di avere perdite minime e ora li devono salvare ----------------------- Although CDOs have been around for about 20 years, their use soared in recent years. Investment banks in 2006 issued about $500 billion in CDOs, compared with about $84 billion in 2002, according to research by Morgan Stanley. The popularity of CDOs grew as low interest rates caused investors to embrace products that offered the promise of higher yields. Fans argue that CDOs allow investors to buy into higher-yielding securities while taking on the same risk as they would with safe, lower-yielding securities. They also say that CDOs are another tool that allow financial markets to further spread risk so it isn't concentrated in the hands of a few players. But some investors think CDOs are an example of financial engineering gone haywire. CDOs are "more sleight of hand" than a sound way to generate diversified returns, said Brad Alford, founder of Alpha Capital Management, an Atlanta-based investment advisory firm that caters to wealthy families. "They're a method for Wall Street to repackage securities as a way to make more money." Indeed, Wall Street has made millions of dollars in fees in recent years by creating CDOs, selling them, servicing them and helping investors trade them. The vehicles are generally used by institutional investors, such as pension funds or hedge funds, not individual investors. CDOs have generated debate because they are complex, and pose a risk because they are several steps removed from the actual asset, or debt, that is being packaged. Consider a mortgage. Jane Sixpack borrows $100,000 from a bank to buy a house. The bank then pools Jane's loan with thousands of other mortgages. It then issues securities backed by this pool and sells those to investors. Jane keeps making her payments to the bank, but her mortgage is now owned by investors. An investment bank creates a CDO, which is really just a company. The CDO then buys some mortgage-backed securities, one of which holds Jane's loan. The CDO then pools these with other mortgage-backed securities and maybe some corporate bonds, slicing them up based on investor preferences for yield versus risk. The CDO manager sells portions of the package to other investors. In some cases, other CDOs are the buyers. There are even CDOs comprised of CDOs that have invested in CDOs. The bundling of different debts, along with the fact that the CDOs are a few steps removed from the debts they include, give rise to another risk. It's tough to get an accurate price for CDOs, which don't trade in active markets. When markets sour, the lack of available prices can make it even more difficult to value a holding, or to get out of it without taking a big haircut. So investors often have to estimate the value of a CDO and have a lot of leeway in how they do it. That's a worry for investors in hedge funds, big buyers of CDOs. Hedge-fund managers make most of their money through performance fees. This gives them added incentive to use price estimates that work in their favor, even if they might not reflect the price at which they could actually trade the CDO. Or it could mean that the managers themselves don't know exactly what their holdings are worth, because they are so far removed from the underlying investment. In the case of Jane's loan, that means the CDO buyer will have a tough time gauging whether she's a good risk or not. And if she defaults, it may take a while before that affects the value of the CDO, even though market conditions overall might have already changed.

Questo è il vero motore dei mercati - gz  

  By: GZ on Lunedì 07 Novembre 2005 11:32

C'è un settimanale nuovo che si occupa di quello che fanno i traders e pubblica la classifica di reddito dei ^30 top operatori europei che guadagnano da 20 milioni di dollari in su#http://www.traderdaily.com/magazine/article/1595.html^ Non si tratta di istituzioni o banche, ma singoli individui che una volta magari lavoravano per una banca, ora si sono messi in proprio e sono quasi tutti basati a Londra più qualcuno in Svizzera (ovviamente poi esiste una classifica simile e molto più ampia negli Stati Uniti, qui parliamo solo degli europei) Questa gente opera con cifre dai 300 milioni fino ai 5 o al massimo 10 miliardi nei casi più di successo, quindi come dimensione hanno gestioni molto più piccole di Banca Intesa o S. Paolo Imi con le loro gestioni e fondi, ma dato che usano la leva finanziaria e sono molto aggressivi il loro impatto è quello che muove i mercati nel corso della settimana A parte quindi istituzioni come Deutsche Bank che oggi ottengono il 75% dei profitti dalla pura speculazione hai quindi oggi in Europa trenta "privati" che coi loro hedge funds hanno rendimenti tali da guadagnare dai 200 milioni di dollari annui di Louis Bacon ai 20 milioni dell'ultimo della lista (la classifica è in sterline e ho traslato) Ogni mese devono quindi inventarsi qualcosa sui cambi o gli indici o certe azioni per fare il loro 30 o anche 40% annuale su cui prendono "2+20" (2% fisso e 20% dell'utile) o anche "3+25". Questo è il vero motore dei mercati, perchè a differenza dei fondi comuni questa gente è in grado di mettersi in tasca personalmente utili pari a quelli di un grande industriale. Quindi non investono un portafoglio e poi vanno a casa alle 17:30, ma si muovono 24 ore su 24 con derivati per spingere con ogni pretesto i mercati europei agli estremi (^il resto della classifica#http://www.traderdaily.com/magazine/article/1595.html^)

 

  By: gianlini on Martedì 20 Maggio 2003 22:25

Luigi io l'apprezzamento dei bond proprio non l'ho capito... se la gente si indebita sempre più e così anche gli stati, con i debiti e deficit ormai fuori controllo, come cavolo fanno i tassi a scendere e soprattutto l'inflazione a non crescere?

 

  By: Luigi Luccarini on Martedì 20 Maggio 2003 15:22

... perchè naturalmente il calo delle borse di ieri e l'apprezzamento dei bonds che dura da un anno ed il crollo del dollaro che dura da sei mesi dipende dagli attentati, ovvio che sia così. Continuiamo a farci del male, boys.

 

  By: DOTT JOSE on Martedì 20 Maggio 2003 13:22

gianlini fai lo stesso ragionemento dei pacifisti.. "se han fatto la guerra all iraq ..allora anche tanti altri paesi devono essere disarmati..pakistan per esempio..."

 

  By: gianlini on Domenica 18 Maggio 2003 16:39

noto soprattutto il proliferare di manifestazioni dei pacifisti contro questi attentati alla pace.....

 

  By: Leofab on Domenica 18 Maggio 2003 16:04

Sembra che appena la situazione economica, del mondo capitalistico, stia per segnare una svolta, l' organizzazione terroristica dell' altro pianeta si scatena. Successe con le due torri, adesso cercano di eguagliare in diffusione il clamore. La tempistica perfetta in certi momenti storici dei mercati finanziari rende chiarissimo il giudizio su questi eventi: sono pianificati da una mente al di sopra dei singoli gruppi di straccioni o di Bin Laden. Interi stati sono responsabili. Quelli che contano, che non fanno parte del sistema. Gli interventi vittoriosi in Afghanistan e Iraq, non sono nient'altro che preparazioni aeroportuali per il vero contrasto a simili organizzazioni. Così sembra. Comunque adesso stiamo rigiocando una nuova partita. Se l' occidente riuscirà a contenere i danni di quest'altra ondata terroristica vile e sciagurata, i mercati premieranno con un ciclo diverso da quelli visti negli ultimi anni. Le carte si scopriranno entro un paio di settimane.

 

  By: gianlini on Domenica 18 Maggio 2003 14:45

Larry ne parlerebbe senza mezzi termini nè paure da verginella: tra CRB e T-Bond c'è una bocca da squalo bianco incredibile tra T-Bond e Azionario c'è una bocca da squaletto fastidioso il US-Dollar contro Euro sta crollando ad una velocità raggiunta neanche nei veloci ritracciamenti del trend al rialzo fra 1999 e 2001... O sta per scoppiare la terza guerra mondiale (e gli attentati degli ultimi giorni non sembrano ben auguranti) oppure siamo di fronte ad occasioni di trading pazzesche!