But starting today you can get interactive, embeddable WikiCharts like the one below from Wikinvest
. Hold the mouse down over the chart and you can pan it from left to right. Hover over the line and you will get date, price, and volume, information.
Several years ago, Shaw stepped down from the day-to-day management of his derivatives firm, D.E. Shaw and Company—which in June 2008 was managing upwards of $39 billion in investments.
Roger Brent, director of the Molecular Sciences Institute in Berkeley, California, suggested in the Times article that scientists may not know what such a powerful computer is capable of until they use it.
Remember Julian Robertson’s curve steepener? At the end of January, it seemed very smart.
As a result, the difference between the two, at 130bp, is 20bp lower than it was at the end of January, and financial institutions who put on steepeners this year have lost as much as $5 billion, according to the WSJ. I wonder if Robertson is among them.
A smart idea from AOL founder Steve Case’s Revolution Money: Send and request money to/from people on AOL Instant Messenger, instantly, for free, via a new AIM plug-in.
Goldman Sachs and Credit Suisse were way ahead of their peers in recognizing the potential of developing their electronic reserves of anonymous orders, or dark pools, to divert business from exchange floors and electronic stock markets. In terms of volume, they dominate the growing dark-pool area.
In June, Goldman’s Sigma X had a 26% market share among dark pools and alternative trading systems, according to Tabb Group’s Liquidity Matrix, with Credit Suisse’s CrossFinder second at 16%. None of the roughly 40 other dark pools come close; the next largest is Knight Capital Group’s 9% slice of the pie.
Given the popularity of individuals speculating on the foreign exchange (currency) markets, this seems inevitable… Social media firm Tradual has raised $2.6 million of a $4 million round led by North Bridge Venture Partners, according to peHUB, citing a regulatory filing. The Boston-based company doesn’t have a working website yet, so it’s not totally clear what they’re building, but it’s something having to do with Forex and social media. Money meets social networking has been a big trend, with sites like MyTrades, Stockpickr and several others attacking this area.
Interestingly, because veteran traders are running these training programs, they recognize the importance of both teaching skills and instilling proper trading psychology. In my opinion, this makes the training programs far more “real world” than many of the “trading education” offerings from self-anointed gurus.
As an example of this new breed of prop firm and the kind of skills and information they teach, check out the blog for SMB Capital.Perhaps the most interesting part of what they’re doing is that they’ve opened up their training programs to traders who can’t join their New York firm. This enables independent traders to receive the same education/training/support that would be available in a professional firm, thanks to the online medium.
Keep your eyes open; a number of proprietary trading firms–several of which have been in touch with me–will be entering this space:
http://traderfeed.blogspot.com/2008/07/training-successful-traders-new-breed.html
In truth, any attempt to analyse the hedge-fund industry as a whole runs into the problem that it is not an asset class but a style of fund management.
Now hedge funds are trying to market themselves to pension funds and endowments. What those clients want is a controlled balance between risk and reward, and a return that is not correlated with conventional stockmarkets.
That helps explain two trends in the industry. The first is concentration: the assets of the 100 largest funds rose from 47% of the industry in 2002 to 66% in 2007, according to GAM, an asset manager.
The second is a reliance on funds-of-funds.
http://www.economist.com/finance/displaystory.cfm?story_id=11793069
Mint, the popular personal finance site that won TechCrunch 40, has further expanded its services by introducing support for mortgage and loan tracking. Users will now be able to keep tabs on their loans from over 1,000 supported institutions. In addition to the mortgage and loan tracking, Mint also monitors users’ savings accounts, credit cards, and investments.
Mint doesn’t deal with any actual fund transfers. Instead, it monitors users’ spending habits, producing coherent graphs that are designed to help people save their money (or at least know where it’s all going). Users can also elect to receive SMS and email alerts when bills are due or their balance drops below a certain level.
We consider the problem of learning the ranking function that maximizes a generalization of the Wilcoxon-Mann-Whitney statistic on the training data. Relying on an $\epsilon$-accurate approximation for the error-function, we reduce the computational complexity of each iteration of a conjugate gradient algorithm for learning ranking functions from $\mathcal{O}(m^2)$, to $\mathcal{O}(m)$, where $m$ is the number of training samples. Experiments on public benchmarks for ordinal regression and collaborative filtering indicate that the proposed algorithm is as accurate as the best available methods in terms of ranking accuracy, when the algorithms are trained on the same data. However, since it is several orders of magnitude faster than the current state-of-the-art approaches, it is able to leverage much larger training datasets.