科伟's profile生活是最好的老师：kevin kewei tan...PhotosBlogListsMore  |  Tools Help |
|
生活是最好的老师：kevin kewei tangSeptember 30 六项基本生存技能 in Quantitative Finance World<One>. Probability and Stochastic Process:
Key Words: Probability Space, Sigma Field, Borel-Cantelli, Characteristic Function, Radon-Nikodym, Conditional Expectation, Convergence Mode, Limiting Theorem, Point Process, Markov Chain in Discrete Time and Continuous Time, Martingale, Brownian Motion, Diffusion Process, First Passage, Hitting Times, Optional Stopping,
Main Reference:
1). A Probability Path by Resnick
2).Adventures in Stochastic Processes by Resnick
3).Introduction to Probability Models by Ross
4).Basic Stochastic Process by Brzezniak and Zastawniak
5). A First Course in Stochastic Processes by Karlin Taylor
<Two>. Statistics, Signal Processing and Time Series:
Key Words: Testing, Estimation, Bayesian, ARMA, Kalman Filter, GARCH, High Frequency, Unit Root, VAR, Cointegration
Main Reference:
1. Lecture Notes on Statsitcal Inference
2. Various Time Series Books and Exercises
3. Introduction to high Frequency Finance
4. The Econometrics of Financial Markets
5. Kalman Filtering in Theory and Practice using Matlab
6. Kalman-Bucy Filters by Brammer and Siffling
<Three>. Stochastic Calculus and Derivatives
Key Words: ITO Formula, Black-Scholes, Credit Derivatives, Interest Rate Models
Main Reference:
1. Options, Futures and Other Derivatives by John Hull
2. Stochastic Calculus for finance by Steven Shreve
3. Stochastic Differential Equations by Oksendal
4. Introduction to Stochastic Calculus with Applications by Klebaner
5. Arbitrage Theory in Continuous Time by Bjork
6. Concepts and Practice in Mathematical Finance by MJ
7. Risk-Neutral Valuation by Bingham and Kiesel
<Four>. Analytical Solution of Differencial Equations
Key Words: Series Solution, Fourier Series, Methods of Characteristics, Bessel Function, Green Function, Initial Value Problem, Boundary Value Problem,
Main Reference:
1. Lecture Notes
2. Various Books
<Five>. Numerical Methods
Key Words: Monte Carlo, Bootstrap, Computational Linear Algbra, Approximation Methods, Numerical Integration, Finite Difference, Finite Element
Main Reference:
1. Lecture Notes
2. Various Books
3. Simulation by Sheldon Ross
4. Statistical computing with R by Rizzo
5. Monte Carlo Methods in Financial engineering by Glassman
6. Monte Carlo simulation and finance by McLeish
7. Introduction to Numerical analysis by Suli etc
8. Numerical Analysis by Burden and Faires
<Six>. Programming and Algorithms
Key Words: Objected Orieted, Class and Inheritance, Vitual Function, Handle Class, Overload, Initialization, Vitual Destructor, Reference and Pointer, Template, Sorting, Search, R Language,
Main Reference:
1. Thinking in C++
2. Accelerated C++
3. Effective C++
4. Schaum's Outlines
5. R Introduction
6. C++ Design Pattern and Derivative Pricing September 09 两位女性CEO谈到目前亚洲的情况关于目前大陆市场的红火情况，这位来自上海的大姐在鼓励大家继续制造泡沫。视频连接如下：
Sep. 5 - The CEO of China International Fund Management says despite the recent run-up in the Chinese stock market, corporate fundamentals are 'still very good.' Mandy Wang, speaking at the Reuters China Century Summit in Shanghai on Wednesday, says Asian markets are "still the most attractive area in the world." Wang says one reason for being bullish on Asia is that over the "next two decades China and India will stimulate domestic consumption" and provide a great deal of opportunities for companies doing business in the region. Speaker: 这位来自香港的英语好很多的大姐则用了一些摆事实讲道理的手法说了不少更让人信服的话语： http://www.reuters.com/news/video/videoStory?videoId=65619&feedType=RSS Sep. 5 - China's domestic stock market is likely to rise a further 10 percent by the end of the year, according to Yang Liu, the top China fund manager at Atlantis Investment Management. Liu says China's robust economy is decoupling from other major markets such as the United States. Strong Chinese corporate earnings should help fuel stock market growth. Speaker:
关于目前的金融危机和矿工的情况第一篇：How Market Turmoil Waylaid the 'Quants'Morgan Stanley Star Is
Among Those Battered; No Time for Music Now By SCOTT PATTERSON and ANITA RAGHAVAN
September 7, 2007; Page A1 Peter Muller, a 43-year-old trader at Morgan Stanley, is used to markets behaving more or less as he expects. But in late July, some unusual patterns perplexed him. Certain investing strategies that historically had posted steady gains started faltering for no evident reason. Soon, the unusual trading spread from U.S. to Japanese and European markets as well. Mr. Muller picked up rumors that one or more unknown investors were buying and selling giant positions similar to the ones he held, according to someone familiar with the matter. The next two weeks proved one of the biggest convulsions ever faced by a breed of market players that includes Mr. Muller: quantitative investors, known as "quants." These traders use complex mathematical models to invest in markets around the globe. Their computers track a wide range of data and variables, such as how cyclical stocks do when a particular currency rises or falls. Formulas programmed into their computers spit out prices at which stocks or other instruments are to be bought and sold. In fact, the computers themselves often do the trading. Quant strategies have been around for decades, but in recent years they have really come into their own, thanks in part to technology that has lowered the costs of their trading-intensive methods. Whereas investors like Warren Buffett and Peter Lynch defined an era of common-sense "value" investing in the 1980s -- and swashbuckling hedge funds betting on everything from metals to the British pound typified the 1990s -- quants have scaled the heights of the investing world in the past decade. Quants' avoidance of the limelight has only amplified the aura of stars like James Simons of Renaissance Technologies Corp. and David Shaw of D.E. Shaw Group. Large investors such as pension funds seek the steady returns these funds have produced. Assets in just two common types of quant funds -- known as "statistical arbitrage" and "market neutral" funds -- have risen nearly 60% in two years, to $96 billion as of June 30, according to research group Hedgefund.net. The rise reflects both investment gains and new money. Against this backdrop, quant funds' turmoil in late July and early August was all the more disconcerting. The broader U.S. stock market fell about 4% in that stretch. But Renaissance Institutional Equities slid 8.7%. Another big quant fund, AQR Capital Management, lost 13%. A Goldman Sachs Group Inc. quant fund called Global Equity Opportunities fell about 30%. Tykhe Capital LLC saw losses of roughly 20%. And Mr. Muller suffered along with them. KEEPING COUNT
• The Landscape: Quantitative trading driven by computers has become highly popular for its reliable returns.
• Market Jolt: In late July and early August, 'quant' portfolios, including one that manages some of Morgan Stanley's money, took heavy losses.
• Situation Now: The drop exposed problems quant traders are still reckoning with. They say the fall will be forgotten as their strategies continue to churn out steady profits. Though few on Wall Street know about it, his group at Morgan Stanley has been among the investment bank's most profitable operations in recent years. Known as PDT, for Process Driven Trading, it produced profits of roughly $3.5 billion in the 10 years through 2006, people familiar with it say. They add that PDT, which now contains about $6 billion of Morgan Stanley's money, accounted for 7.2% of the bank's net income last year by producing $540 million in profits. But between the last week of July and Aug. 9, PDT lost approximately $500 million, according to traders. Neither Morgan Stanley nor Mr. Muller would comment on the losses or on PDT's trading strategy. Morgan Stanley said it is fully committed to the quantitative trading business. "It's a very humbling event for [quants] to take these kinds of losses. These guys think of themselves as masters of the universe," said Lee Maclin, manager of Pragma Financial Systems, a New York "fund of funds," or hedge fund that invests in other hedge funds. The quants' summer woes remind some of the near-meltdown almost a decade ago of high-flying hedge fund Long-Term Capital Management. Like quant funds, LTCM was steered by brainy academics who made money exploiting out-of-kilter relationships between different securities. Unlike LTCM, though, today's quant funds are far less leveraged and thus unlikely to sustain huge losses as LTCM did. Quants say their bad patch will be forgotten as their strategies continue to churn out steady profits. Most of the funds, including Mr. Muller's, have recouped some of the losses. By the end of August, AQR had bounced back by roughly 10% from its lows, and the Goldman fund by 12%, according to people familiar with these funds. Even so, the outsize drops could dim the luster of the quant approach -- especially since quants themselves still don't know for certain what triggered the carnage. A common theory is that one or more large funds was forced, possibly because of losses on subprime mortgages in other parts of its business, to rapidly dump stock to raise cash, and this set off a ripple effect among quant traders. Others say that stocks that were expected to fall began rising when traders who had borrowed shares and sold them were forced to start buying shares back. Meanwhile, the proliferation of quant funds holding a lot of the same positions may have been a recipe for magnifying the losses. Mathematical, computer-driven trading was an arcane corner of the financial industry when Mr. Muller joined Morgan Stanley in 1992. He had been exposed to it, however, for several years at Barra Inc., a risk-analysis firm in Berkeley, Calif.
A 1985 math graduate of Princeton, Mr. Muller impressed some investment elders early on. Jeremy Grantham, chairman of the big money-management firm GMO LLC, recalls seeing a youthful Mr. Muller as a panelist at a conference 20 years ago. "I caught both super-quants [on the panel] in a logical fallacy," Mr. Grantham says. "The first one kind of choked on it, but Peter danced around the minefield like a tap dancer. I thought, 'That guy can really think on his feet.' " Restless after Barra went public in the early 1990s, Mr. Muller interviewed for a job at Morgan Stanley. He told executives there that he didn't really think any amount of money could get him to leave his laid-back California life for Wall Street. But he accepted when the bank offered to let him set up a group that would invest some of its own money using a quantitative strategy. Morgan Stanley -- which eventually bought Barra -- wasn't new to such techniques. Years earlier, it had employed Nunzio Tartaglia, a onetime astrophysicist and Jesuit seminarian who was an early practitioner of a particular quant strategy. And one of Mr. Tartaglia's underlings in the 1980s was Mr. Shaw, now the proprietor of one of the largest quant funds, D.E. Shaw. The strategy Mr. Tartaglia used gives an idea of how quants operate. Called "pairs trading," it involves betting on two stocks that have a strong historical relationship. Suppose that General Motors and Ford Motor stocks usually move more or less together. If they aren't doing so at a particular time, and there is no clear reason why, there's a good chance the past relationship will reassert itself. So if Ford has risen while GM languished, a quant might buy GM shares and sell Ford short, betting on it to decline. The "pairs trade" will pay off if the historic correlation returns. Quants play the game on a massive scale -- betting on many different securities and using borrowed money to magnify the effect of any market anomalies detected by their computers. So although they expect to lose on many trades, the gains tend to outweigh the losses, thanks to their formulas and computing power. Ideas like pairs trading have blossomed into others such as "statistical arbitrage," a more complex version that is one of Mr. Muller's specialties at PDT. By the late 1990s, PDT group had become so successful it commanded the biggest chunk of Morgan Stanley's stock trading for its own account. Mr. Muller let members of the group dress down when their returns were up -- and forced them to dress up when their returns were down -- so everyone else at the firm knew how they were doing. But according to a short biography on Mr. Muller's Web site, he "woke up 6 years ago and realized that he can no longer find happiness in the corporate world." He had already taken a one-year 1999 sabbatical. In 2001, he left full-time work again, though he remained an adviser. Friends say Mr. Muller felt he had already accomplished more than he expected, and the intense money focus and social-climbing side of New York left him wishing for a more balanced life. He also had broken up with a longtime girlfriend. So over the next several years, Mr. Muller traveled to Bhutan, New Zealand and Hawaii, and kayaked in the Grand Canyon. He spent time in California and took up yoga. He began writing crossword puzzles, several of which appeared in the New York Times. He also became more serious about his music. He had taken up the piano as a child and joined a jazz band in California. In 2002 and 2004 he recorded albums on his own label, Dog and Hammock Productions. During his time away from Morgan Stanley early this decade, he could be seen playing on the streets of Barcelona, Spain, and in New York City subways. Mr. Maclin of Pragma Financial recalls seeing Mr. Muller playing on a subway platform: "People were dropping change in his [keyboard case] not realizing the guy is worth millions." Late last year, Mr. Muller returned to Morgan Stanley full time, encouraged by Chief Executive John Mack's push toward more aggressive risk-taking at the investment bank. The trader also felt that in what was becoming an increasingly competitive quant field, PDT could benefit from more hands-on guidance. Though secretive about their formulas, quants like him are often seen together at social gatherings. Poker is a favorite pastime. Mr. Muller is the ace of the group. While away from Morgan Stanley, he briefly joined the World Poker Tour and pocketed nearly $100,000 in a tournament in 2004. In March 2006, at a charity event called Math for America held at New York's St. Regis Hotel, several quants squared off in "Wall Street Poker" night. Looking on, according to people who were there, was a murderers' row of hedge-fund managers: Citadel Investment Group's Kenneth Griffin, Renaissance Capital's Mr. Simons and David Einhorn of Greenlight Capital Inc. In the final round, Clifford Asness, who runs AQR Capital, faced off against Mr. Muller, who took the title with a pair of kings to his foe's ace and 10. This summer was less fun. Mr. Muller had retaken the helm of PDT just in time for the biggest test of his career, as the subprime-mortgage meltdown broadened into a more-general credit squeeze. Among the unusual results was that stocks many investors considered low-quality -- and had bet against -- began to outperform the market, says Diane Garnick, investment strategist at Invesco PLC. She attributes much of this to "short covering": Investors who had borrowed shares and sold them had to buy them back when their brokers reined in their credit lines. In contrast to the "flight to quality" often seen during a crunch, she says, the anomalous result was a "flight to non-quality." The phenomenon may have been magnified by the similarity of quants' portfolios. Their world is one of shared theories. "Everybody has read the same academic literature and knows what's in the air," says Richard Bookstaber, a portfolio manager at FrontPoint Partners. Mr. Asness, in a letter to his investors at AQR, wrote that the early-August jolt "is about a strategy getting too crowded." Mr. Muller has been playing detective to avoid repeating past mistakes, peppering friends with questions about the performance of his peers, asking pointedly which funds got in trouble and which did better, says a person familiar with the situation. He has talked several times with Mr. Asness. Though computers execute quant trades, real people are constantly at the switch during the trading day, monitoring portfolios to make sure the programs are operating according to plan. If a computer accumulates too much of a single stock, a trader may intervene. And quants are always tweaking their models. Mr. Muller has told friends that the August swoon presents opportunities for experienced managers like him. Then there's his music. Songs on his first two albums reflected what was going on his life, including one song with the lyrics "I almost made my escape, I almost got away.... So hard to quit when you're good at the game." But Mr. Muller's Wall Street career is getting in the way again. Since returning to PDT, he hasn't written a new song all year. As he recently wrote on his Web site, "one of my other passions, mathematical finance, has taken a lot of my time this year." 第二篇 How the Playbook Failed for ‘Quant' Hedge Funds
By JUSTIN LAHART | The Wall Street Journal The managers of "quantitative" hedge funds that got roiled in this summer's stock-market selloff didn't gather after work to drink beer and swap trading ideas. But they might as well have. A number of quant funds, which use statistical models to find winning trading strategies, reported heavy losses this month. In many cases, the managers pointed their fingers at other quantitative hedge funds, essentially saying they all owned many of the same stocks and their models told them all to sell at the same time, driving down the share prices, hurting everyone in the process. In a letter to investors, Jim Simons of the hedge fund Renaissance Technologies wrote the quantitative funds behind the selling "undoubtedly share some signals in common with our own, and the result has been losses." It didn't help that quant funds are among the fastest expanding categories of hedge funds. Filings with the Securities and Exchange Commission show that as of the end of June, quantitative hedge funds often shared large positions in the same stocks. Renaissance held 1.1 percent of the shares outstanding of NVR Inc., a Virginia construction and home-building company. AQR Capital Management, another quant fund, held 0.9 percent of the company's shares and quant fund Numeric Investors had a 1.6 percent stake. NVR stock, which closed Thursday at $571 a share, trades less than most companies of its size. The shares have bounced higher since the selloff, but they are off 8.4 percent over the past month. The overlap in quant funds' positions wasn't limited to NVR. Satya Pradhuman, director of research at Cirrus Research, which analyzes small and midsize stocks, found 148 other companies with market capitalizations between $2 billion and $10 billion where large quant funds owned 5 percent or more of the shares outstanding. As a whole, those companies' shares underperformed the shares of other midcap stocks during the selloff. Mr. Pradhuman found 473 small-cap stocks, with market capitalizations of $250 million to $2 billion, where the quant funds owned 5 percent or more of the shares outstanding. These stocks also performed worse than other similar stocks. The midcap companies where quant funds held big stakes included packaging company Pactiv Corp., toy maker Hasbro Inc. and managed care provider WellCare Health Plans Inc. Small caps included printer Deluxe Corp., consumer-products company Russ Berrie & Co. and health-care equipment maker Zoll Medical Corp. Academics, notably Eugene Fama at the University of Chicago with Kenneth French at Dartmouth, have documented how, over time, stocks with smaller market capitalizations and lower valuations tend to do better than the overall stock market. The reason for the outperformance, Mr. Pradhuman said, is both smaller companies and companies with low valuations are more likely to go bust if the economy sours, so they are riskier. Since the U.S. economy has been highly successful, taking the risk of buying the shares of such companies has paid off. Since history had shown that buying small and low multiple companies was a good idea, many quant models screened for them. When stocks started getting rattled last month after credit markets seized up, worries about business risk rose sharply and the shares of those companies bore the brunt of the selling. Other investors had bid up the share prices of some of these companies in the belief that leveraged-buyout firms would snap them up at healthy premiums. When credit tightened, takeover prospects dimmed. The combined effect of some quant funds and other investors cutting positions in the stocks sent them lower still. Mr. Pradhuman said quantitative investing still makes sense, and indeed many of quant funds that got hurt in the selloff have already made back the money they lost. "Quant strategies may be getting broad-brushed," he said. "In the long term, these are disciplined approaches that are doing things at every tick to look for value." The risks to quantitative investing may be rising. Even if they don't share the same statistical models, quant funds share similar approaches to the market. They are schooled in the same statistical methods, pore over the same academic papers and use the same historical data. As a result, they can easily come to similar conclusions about how best to invest. What doesn't exist in the data that the quant funds comb through, however, are the quant funds themselves. Scientists talk about the "observer effect," where the very act of observing a phenomenon, such as the behavior of animals, can change the phenomenon. For the quant funds, this effect is magnified, because they aren't merely observing the market, but using what they learned to take part in it. That effect was amplified by the rapid growth of these funds. AQR, one of the most successful quant fund managers, has about $35 billion under management, up from less than $7 billion nine years ago, though not all of the money is in these specific strategies. University of Rochester finance professor William Schwert has found that after academic papers come out highlighting opportunities to outperform the market, those opportunities tend to diminish or outright disappear. The popularity of quantitative strategies in recent years may mean that the opportunities to make money are getting whittled away more quickly than ever, according to Invesco PLC investment strategist Diane Garnick. "You have this inflow of dollars into quantitative strategy and this inflow of intellect," she said. "It's becoming more difficult to capture outperformance." To stay ahead of the game, quant managers need to be more aware of what their peers are doing, said Massachusetts Institute of Technology finance professor Andrew Lo, who is also a principal at asset manager AlphaSimplex Group LLC. By the same token, if the losses this summer drive some investors out of quantitative strategies, it could be good for the quants that are still in the game. June 12 just for fun－a story from DominicAt P&D we don't even have a list of "leading universities", the notion is bogus. Some are better than others of course, but actually what "leading" seems to mean is "the recruiter has heard of it". At one firm who shall remain nameless, the head of HR was asked why they didn't see any CVs from Southampton, which is probably on few "leading" lists. The meeting was about why the quality of newbies they had interviewed was so low. "Oh that place, terrible, the calibre of graduates is simply appalling..." said the HR who didn't have a degree in anything. "Really ?" said the senior manager (himself a graduate of that awful place) "Yes said HR, we reject anyone who sends their CV without even reading it, we only do Oxbridge" "Won't you miss some good people ?", says other senior manager who's from Oxbridge, but who's father is a Dean of a Southampton faculty. "They're a waste of space..." contiuned the HR manager who quite coincidentally no longer works for that firm... On the other hand I do know that GS was so unhappy with the newbies it was seeing last year, that they told HR to go through the database and retry everyone from a "top" university from the previous year. Was quite funny in it's own way. May 09 关于 financial mathematics and levy process1. Bibliography on Levy processes in financial modeling
|
|
||||
|
|
