"The point is that in fast moving markets, one needs something a little better than simple historical moving averages of daily closing prices. This is better, and extending the idea of 'volume time' vs. 'chronological time' is an intriguing direction. But one can also look at bid-ask spreads directly, or the VIX futures, or its etf, the VXX, and combinations, to gauge intraday volatility as well. Further, one can better estimate 'buy volume' using the transaction price relative to the then extant bid-ask spread, rather than if the price was weakly increasing, though this then involves syncing the trade information with quote information, and for academics such data are often hard to come by (further, quote information is often 10 times as large)."

"Oil just doesn't fall by 10 percent in the course of a normal day, though. In commodities markets, oil is king, and its daily contract turnover, typically around $200 billion, is usually able to absorb even large inflows or outflows of investment.

The rare moves of $10 a barrel usually are set off by dramatic events -- the outbreak of the first Gulf War in 1991, or the collapse in 2008 of Lehman Bros bank, which both led to recessions.

Of course, there was major news last week. But the daring Pakistan raid that killed Osama bin Laden had done little to shift the balance of oil markets on Monday.

In interviews with more than two dozen fund managers, bankers and traders, no clear cause emerged for the plunge in price. Market players were unable to identify any single bank or fund orchestrating a massive sale to liquidate positions, not even an errant trade that triggered panic selling, as seen in the equities flash crash last May."

"Our results show that the marginal effect of financial development on output growth becomes negative when credit to the private sector surpasses 110% of GDP. This result is surprisingly consistent across different types of estimators (simple regressions and semi-parametric estimations) and data (country-level and industry-level). The threshold at which we find that financial development starts having a negative effect on growth is similar to the threshold at which Easterly et al. 2000 find that financial development starts increasing volatility."

What follows is very much a field report of one particular DIY Masters in Financial Engineering. That brings drawbacks (like idiosyncrasy and personal narrative) — and advantages (I’ve actually read the stuff I’m going to tell you about). The report is half why-I-didn’t-get-an-MFE and half what-I-did-instead.

Masters in financial engineering

"…This phenomenon is self-healing. This is the important part, but it's not as complicated as it sounds. As we've established, shares can only be redeemed when they are actually delivered into the trust. If everyone wants to redeem their shares, then the shorts need to cover their positions - we have also already discussed this above.…"

Andrew Lo and Mark Meuller have has a recent paper that addresses the issue of physics envy. They focus on the applicability of the tools of physics as the type of uncertainty becomes more profound, pointing out that while physics can generate useful models if there is well-parameterized uncertainty, where we know the distribution of the randomness, it becomes less useful if the uncertainty is fuzzy and ill-defined, what is called Knightian uncertainty.
I think it is useful to go one step further, and ask where this fuzzy, ill-defined uncertainty comes from. It is not all inevitable, it is not just that this is the way the world works. It is also the creation of those in the market, created because that is how those in the market make their money. That is, the markets are difficult to model, whether with the methods of physics or anything else, because those in the market make their money by having it difficult to model, or, more generally, difficult for others to anticipate and do as

"To define oscillatory movements of securities market, we put in the non-local extension of Ito- equation for wavelet-images of random processes. It is proposed an algorithm of creation of evolutionary equation and a model of prediction of the most probable price movement path. It is carried out experimental validation of findings."

"As we continue to monitor the markets for evidence of Quote Stuffing and Strange Sequences (Crop Circles), we find that there are dozens if not hundreds of examples to choose from on any given day. As such, this page will be updated often with charts demonstrating this activity.

The common theme with the charts shown on this page is they are obviously all generated in code and are algorithmic. Some demonstrate bizarre price or size cycling, some demonstrate large burst of quotes in extremely short time frames and some will demonstrate both. In most cases these sequences are from a single exchange with no other exchange quoting in the same time frame."

"Select the historical market data products below
Here you can select the products you are interested in. Click on the product's name to find out more about it. Press the Continue button to place an order or to get a quote."

"I'll start by highlighting that while all the software in this post is indeed free (true to FOSS), an account with Interactive Brokers is needed to make use of it. For those not familiar with IB, they offer a trading platform that excels on numerous fronts but is most appealing to those of us who trade algorithmically. IB makes available a rather comprehensive API that makes data access and trade execution entirely possible programmatically via a handful of "supported" languages. These include Java (the language of the platform), C#, VBA and even Excel. The also have a POSIX compliant C++ version for those who enjoy C++ but dislike Windows.

For those who dislike Windows and C++, the community of IB users have a few "non-official" options. They include some nice implementations in C, Python (2), Matlab, and something even more abstracted in the trading-shim. While all well and good, there was one missing: R.…"

"… Our methods use simple ideas from signal processing and statistics, which are sometimes overlooked in the empirical financial literature. The two approaches are evaluated against benchmark allocation techniques using 4 real datasets. Our methods outperform the benchmark allocation techniques in these datasets, in terms of both computational demand and financial performance."

"Might there be more to last week's crash than a "fat fingered" trade, or someone mistakenly entering a "billion" instead of a "million?" An online stock trader has a video showing an unusual spike in trading volume, followed by a very quick sell-off, by funds at large investment firms BlackRock and Vanguard and some other funds 30 to 15 minutes before the big crash. Prescience? Watch the video, check the logs, and decide for yourself."

"In this case, the computers kicked in their sell programs and there were no buy programs engaged - and so there was no market - and stocks wound up selling for a penny a share.

Now already known as the “flash crash,” this remarkable event will almost surely put a whole generation of young math whizzes out of business as Congress and the SEC crawl all over these operations and limit this kind of insane action.

I’m all for it because, and you can call me old fashioned, I don’t think the global equities markets should be an online gambling casino which is what they’ve become with the rise of the “quants” and their hyperactive supercomputers."

"… It avoids most of the shortcomings encountered with the now classic Black-Scholes-Merton framework. Several convincing computer simulations are presented. Some of them are dealing with abrupt changes, i.e., jumps."

Links to paper on "Financial Innovation and Financial Fragility" by Nicola Gennaioli, Andrei Shleifer, and Robert Vishny