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Posts categorized "Automated Trading"
The Volcker Rule - aka one man's trade is another man's hedge
One of the PRMIA folks in New York kindly recommended this paper on the Volcker Rule, in which Darrell Duffie criticises the proposed this new US regulation design to drastically reduce proprietary ("own account") trading at banks.
As with all complex systems like financial markets, the more prescriptive the regulations become the harder it is "lock down" the principles that were originally intended. In this case the rules (due July 2012) make an exception to the proprietary trading ban where the bank is involved in "market-making", but Darrell suggests that the basis for what types of trades are "market-making" and what types of trades are more pure "proprietary trading" are problematic in this case, as there will always be trades that are part of "market-making" process (i.e. providing immediacy of execution to customers) that are not directly and immediately associated with actual customer trading requests.
He suggests that the consequences of the Volcker Rule as it is currently drafted will be higher bid-offer spreads, higher financing costs and reduced liquidity in the short-term, and a movement of liquidity to unregulated entities in the medium term possibly further increasing systemic risk rather than reducing it. Seems like another example of "one man's trade is another man's hedge" combined with "the law of unintended consequences". The latter law doesn't give me a lot of confidence about the Dodd-Frank regulations (of which the Volcker Rule forms part), 2319 pages of regulation probably have a lot more unintended consequences to come.
Posted by Brian Sentance | 20 January 2012 | 3:47 pm
Analytics Management by Sybase and Platform
I went along to a good event at Sybase New York this morning, put on by Sybase and Platform Computing (the grid/cluster/HPC people, see an old article for some background). As much as some of Sybase's ideas in this space are competitive to Xenomorph's, some are very complimentary and I like their overall technical and marketing direction in focussing on the issue of managing of data and analytics within financial markets (given that direction I would, wouldn't I?...). Specifically, I think their marketing pitch based on moving away from batch to intraday risk management is a good one, but one that many financial institutions are unfortunately (?) a long way away from.
The event started with a decent breakfast, a wonderful sunny window view of Manhattan and then proceeded with the expected corporate marketing pitch for Sybase and Platform - this was ok but to be critical (even of some of my own speeches) there is only so much you can say about the financial crisis. The presenters described two reference architectures that combined Platform's grid computing technology with Sybase RAP and the Aleri CEP Engine, and from these two architectures they outlined four usage cases.
The first use case was for strategy back testing. The architecture for this looked fine but some questions were raised from the audience about the need for distributed data cacheing within the proposed architecture to ensure that data did not become the bottleneck. One of the presenters said that distributed cacheing was one option, although data cacheing (involving "binning" of data) can limit the computational flexibility of a grid solution. The audience member also added that when market data changes, this can cause temporary but significant issues of cache consistency across a grid as the change cascades from one node to another.
Apparently a cache could be implemented in the Aleri CEP engine on each grid node, or the Platform guy said that it was also possible to hook in a client's own C/C++ solution into Platform to achieve this, and that their "Data Affinity" offering was designed to assist with this type of issue. In summary their presentation would have looked better with the distributed cacheing illustrated in my view, and it begged the question as to why they did not have an offering or partner in this technical space. To be fair, when asked whether the architecture had any performance issues in this way, they said for the usage case they had then no it didn't - so on that simple and fundamental aspect they were covered.
They had three usage cases for the second architecture, one was intraday market risk, one was counterparty risk exposure and one was intraday option pricing. On the option pricing case, there was some debated about whether the architecture could "share" real-time objects such as zero curves, volatility surfaces etc. Apparently this is possible, but again would have benefitted by being illustrated first as an explicit part of the architecture.
There was one question about the usage of the architecture applied to transactional problems, and as usual for an event full of database specialists there was some confusion as to whether we were talking about database "transactions" or financial transactions. I think it was the latter, but this wasn't answered too clearly but neither was the question asked clearly I guess - maybe they could have explained the counterparty exposure usage case a bit more to see if this met some of the audience member's needs.
The latter question on transactions above got a conversation going on about resilliancy within the architecture, given that the Sybase ASE database engine is held in-memory for real-time updates whilst the historic data resides on shared disk in Sybase IQ, their column-based database offering. Again full resilience is possible across the whole architecture (Sybase ASE, IQ, Aleri and the Symphony Grid from Platform) but this was not illustrated this time round.
Overall good event with some decent questions and interaction.
Posted by Brian Sentance | 20 October 2010 | 7:40 pm
When is a trade, not a trade?...
...er, when it is a hedge? Adding to my current confusion over just how the Obama administration is going to define just what is and is not "proprietary trading", Gillian Tett of the FT today has put together a good article on some of unexpected effects that such a ban may have - my advice is don't mess with the all-powerful "Law of Unintended Consequencies"...
Posted by Brian Sentance | 19 February 2010 | 2:58 pm
More CEP Events
Sybase have acquired Aleri according to Finextra. It was less than a year ago when the complex event processing (“CEP”) vendors Aleri and Coral8 announced their merger (see press release); there was also a big buzz when Sybase announced a CEP capability based on Coral8 and Streambase decided to offer an Amnesty Program for Aleri-Coral8 Customers (see earlier post 'Merging in public is difficult...). And only a few months later, Microsoft announced that their CEP Orinoco (now integrated with SQL Server 2008 as StreamInsight) was heading to market (see post 'Microsoft CEP surfaces as 'Orinoco').
Another sign that CEP is moving more mainstream and that real-time everything is becoming more important? Or a good market for acquisitions?
Posted by Sara Verri | 4 February 2010 | 6:00 pm
Maths to Money - Quantitative Investment
I attended the Quant Invest 2009 event for the first time last week in Paris. The event is unsurprisingly about quantitative investment strategies, but with an institutional asset manager and hedge fund focus - so not so much about ultra-high frequency trading (although some present) but more about using quantitative techniques to manage medium/longer-term investment decisions and applied portfolio theory. A few highlights below that I found interesting:
- Pierre Guilleman of Swiss Life Asset Management gave an interesting 1/2 day workshop entitled "A random walk through models":
- He is a strong supporter of the need to understand more about the data and statistical assumptions upon which any quant investment model is based and how these fit with the desired investment objectives (similar to the Modeler's Manifesto)
- He made the point that good models can sometimes be almost annoyingly simple, and cited the example by a Professor Fair of Yale who had determined that US elections were predictable based on simple parameters such as past results, inflation and gdp and that policy did not seem to be a key factor at all - annoying for the politicians anyway!
- Pierre seems very concerned that the Solvency II regulation applied to Life Institutions will negatively influence the investment policies of many institutions - applying sell-side risk measures like VAR to the insurance industry will drive a more short-term approach to investment. He strongly believes that VAR applied to his industry should have an expected return parameter introduced to fit with longer term investment horizons of 10 to 25 years.
- Bob Litterman of Goldman Sachs Asset Management opened the first "official" day of the conference:
- Bob put forward his "scientific" approach to investment modelling going through the stages of hypothesis, test and implement. He warned against overconfidence in investment (apparently 70% of us think we are "above average"...) and impulsiveness (quick impulsiveness test: "if a bat costs $1 more than the ball, and the bat and ball together cost $1.10 then how much does the bat cost?...")
- He said that the failure of quantitative investment models in 2007 needed to be understood given the success of quant models over past decades. In particular he thought that quant investment became the "crowded trade" of 2007 with every hedge fund having a quant investment strategy. In terms of why this became a "crowded trade" Bob thinks that the barriers to entry into quant investment (particularly technology) have lowered significantly recently.
- He noted that factor-based investment opportunities decay quicker than they used to due to increased competition - implying the need for a more dynamic and opportunistic investment approach.
- GSAM are now looking at new markets and new investment instruments, trying to find areas of market disruption but without following what others are doing in the market.
- He pointed out the conflict between investors wanting more transparency over what is done for them, against the need to be more proprietary about the investment models developed.
- Next there was a talk on regulation from the French regulator that was dull, dull, dull both in terms of content and presentation style (when will regulators actually prepare well for the talks they give?)
- Panel debate was also pretty average, with the word "alpha" being used too much in my view - asset managers of a certain type seem to hide behind this word as an opaque "magic wand" to justify what they do.
- Jean-Phillippe Bouchard of Capital Fund Management did a great talk called "Why do Prices Move?". Some points from the talk:
- He started off with a reminder about the Efficient Markets Hypothesis (EMH) and how it says that crashes and market movements are caused by events outside (endogenous to) the market such as news, events etc.
- He then said this was not born out in the data, where extreme jumps in prices were only related to news only 5% of the time.
- Volatility looks like a long memory process with clustering of vol over time - similar to behaviour in complex systems
- The sign of order flow is predictable but the price movement is not, with only 1% of daily order volume accounting for price movements over 5%
- Even very liquid stocks have low immediate liquidity, meaning that price movements can play out over many hours and days as liquidity is sought to "play-out" some change in fundamental price levels.
- Joseph Masri of the Canadian Pension Plan Investment Board then did a good talk on Risk Management:
- Jo said that sell-side risk was easier to deal with in some ways since it involved fewer strategies in high volumes, and hence could be better resourced.
- Buy-side quantitative risk was harder due to its reliance onsell-side research and risk tools, the outsourcing of credit assessment to the credit rating agencies, the loss of Bear and Lehman's having caused the buy-side to have to do more risk management itself (and through third parties) rather than rely on the sell side risk management tools.
- He said that sell-side risk models are a good start for an asset manager, but need to be adapted to give both absolute and relative risk (to a benchmark fund for instance). All models are no substitute for risk governance.
- He described the cross over from risk methods: VAR, stress testing, factor-based and their applicability to market risk, credit and counterparty risk.
- Like Pierre he was not a fan of 1 or 10 day trading VAR being applied to investment managers since this risk measure was not suitable for long term investment in his view.
- On stress testing he said this needed to be top down (using historical events etc) as well as bottom up from knowing the detail of strategy/portfolio.
- In terms of challenges in risk management he said that VAR needed more stress testing to cope with the fat tails effect in markets, that liquidity risk both of counterparties and of illiquid products was vital and the importance of stress testing (he mentioned reverse stress testing) plus also the feedback (crowding effects) of having similar investment strategies to others in the market.
- Dale Gray of the IMF gave a very interesting talk on how he and Bob Merton have been applying the contingent claims model of a company (looking at equity in terms of option payoffs for shareholders and bondholders) to whole economies:
- He said that some of his work was being applied to produce a model for the pricing of the implicit guarantees offered by governments to banks
- He said these models were also applicable to macro-prudential risk
- Very interesting talk, and if he really has something of macro-level risk then this is great relative to the wooly approach by the regulators so far
There were some other good talks from Danielle Bernardi on Behavioural Finance, Martin Martens on Fixed Income Quant Investment, Vassilios Papathanakos on Stochastic Portfolio Theory (seemed to be a "holy grail" of investment model, giving good returns even in the crisis - begs the question why he is telling everyone about it?), Claudio Albanese on unified derivative pricing/calibration across all markets (again another "holy grail" worth more investigation) and Terry Lyons on speeding up monte carlo simulations.
Overall a good conference although the quality of the asset managers present seemed very digital from those who really seemed to know what they talking about to those who plainly did not (in my limited view!). Along this line of thought, I think it be good to test whether there is an inverse relationship between the quality of the asset manager and the amount of times they use the word "alpha" to explain what they are doing...
Posted by Brian Sentance | 5 December 2009 | 2:08 pm
It's in the hormones...
Taking the discussion on behavioural finance and news analytics a scientific step further, then this article in the FT today on how increased testorone equals an increased appetite for risk taking is interesting. Apparently experience of trading is also a big help in increasing a trader's Sharpe ratio, from which the authors suggest that markets are not efficient and the EMH does not hold. Now if only they could find a hormone that was correlated with increased returns, then I think they'd really have something...
Posted by Brian Sentance | 25 November 2009 | 7:12 pm
It's in the news...
I went along to the Forum on News Analytics over in Canary Wharf on Monday evening, organised by Professor Gautam Mitra from OptiRisk / Carisma at Brunel University. We seem to be in the early days of transforming news articles into quantifiable/machine-readable data so that it can be processed automatically/systematically in trading and risk management. It was a good event with both vendors and practititioners attending so was reasonably balanced between vendor hype and the current state of market practice.
As background on what is meant by news analytics data, then for example you might count the number of news articles about a particular company and look at whether the quantity of news articles might be a predictor of some change in the company's stock price or volatility. Moving on from this simple approach (assuming that you are clever enough to be certain about what news is about what company), then you can then move towards assessing whether the news is negative, neutral or positive in sentiment about a company/stock.
The context here is about having the capability to automatically process/analyse any kind of text-based news story, not just those from research analysts that might be nicely tagged with such quantifiers of sentiment (see http://www.rixml.org/ on xml standards for analyst data). The way in which the meaning of the text is "quantified" uses some form of Natural Language Processing.
The event started with a brief talk by Dan di Bartolemeo of Northfield Information Services. I hadn't heard of him or his company before (maybe I should pay more attention!) but he seemed a very solid speaker with strong academic and practical background in investment management and modelling. He referenced a few academic papers (available via their web site) on news analytics, and how news analytics and implied volatility could provide better estimates of future volatility than implied volatility alone. He also made some good points about how investment "models" are calibrated to history and how such models need to adapt to "today" - he put it as "how are things different now from the past?" and put forward the idea of a framework for assessing and potentially modifying a model to respond to the "now" situation. He also suggested that the market can react very differently to "expected news" (having a range of investment "what ifs" planned for a known earnings announcement) as opposed to unexpected information (we are back into the realms of the Black Swan and the ultimate in uncertainty wisdom from Donald Runsfeld)
Armando Gonzalez of RavenPack then began by explaining how RavenPack had become involved in applying text analysis to finance (it seems the subject has its origins, like a lot of things, in the military). RavenPack seem to be highest profile quantified news vendor at the moment, and whilst Armando is obviously biassed towards pushing the concept that money can be made by adding quantified news data to trading models, he said that not many firms are as yet systematically processing news and most people are relying upon manual interpretation of the news they buy/use. Some of the studies Ravenpack have on market news and prices are very interesting, showing how a news event can take up to 20 mins before the market settles on a new "fair" price level for a stock. Additionally, and maybe an interesting reflection on human behaviour, was that in bull markets there are usually twice as many positive stories about companies than negative, but strikingly in a bear market there was still almost equal amounts of positive and negative news - so humans are basically optimists! (or delusional, or just plain greedy...take your pick!)
Mark Vreijling of Semlab followed Armando and suggested that a lot of their sales prospects understandably desire "proof" of the benefits of adding quantified news to trading, but this was a little ironic since most financial institutions have been paying to receive "raw" news for years, presumably because they perceive beneift from it. Mark also mentioned that the application of quantified news to risk management was a new but growing area for him and his colleagues.
Gurvinder Brar of Macquarie then went into some of the practicallities of quantifying and using news in automated trading. He suggested that you need to understand what is really "news" (containing information on something that has just happened) and what is merely an news "article" (like a "feature" in a magazine etc). Assessing relevance of news was also difficult and he added that setting a hierarchy of what kind of events are important to your trading was a key step in dealing with news data. Fundamentally he suggested that why wait for five days for analysts to publish their assessment of a market or company-specific event when you could react to the event in near real-time.
The event then went into "panel" mode where the following points came out:
- Dan thought that a real challenge was integrating quantified news with all of the other relevant datasets (market data, but also reference data etc)
- Armando picked up on Dan's point by giving the example news about Gillette which at one point was about Gillette the company but then on acquisition became news about the Gillette "brand" which became a part of Proctor and Gamble.
- Dan said that a key problem with processing news was also understanding what news was simply ignored by the news wires i.e. we know what is being talked about, but what could have been talked about, why was it ignored and is it (even so) relevant to trading?
- Mark and Armando said that the "context" for the news story was vital and that market expectations can turn many "negative" news stories into positive outcomes for trading e.g. the market likes bad news when it is not as "bad" as everyone thought.
- Dan made a very interesting point about trading in terms of categorising trades as "want to" trades and "have to" trades. He gave the example of a trade being observed that seemingly has no news associated/prompting it - so does this mean the trade is occuring because somebody "has to" make the trade (a fund facing an welcome client redemption for example?) or because there has been some information leak to a market participant and such a participant "wants to" make a trade before the news becomes available to the market as a whole.
- I think all of the panel members then collectively hesitated before answering the next question from the audience, with Microsoft having one of their "text search" R&D team (think Bing...) asking about news categorisation and quantification.
- Dan also mentioned something that I have only recently become more aware of, which is that apart from major markets in the US, most exchanges world-wide do not publish whether a trade was a "buy" or "sell" trade (they just publish the price and transaction size). Obviously knowing the direction of the trade would be useful to any trading model, and Dan referred to this as wanting to know the "signed volume".
- A member of the audience then asked whether most quantified news had been based on just the English language and the concensus was that most was based on English, but Natural Language Processing can be trained in other languages relatively easily. A few members of the panel pointed out that all languages change, even English, requiring constant retraining, and also that certain languages, countries and cultures added further complication to the recognition process.
- The next question asked was whether the panel could outline the major areas that quantified news is applied in - the answer included intraday (but not quite real-time) trading, algorithmic execution, lower frequency portofolio rebalancing and in compliance/risk/market abuse detection.
- A good debate ensued about whether "news" was provided by the official newswires or by the web itself. The panel (and audience) concensus seemed to favour the premise the news wires are the source of news and the web is a reflection/regurgitation of this news. That said, Gurvinder of Macquarie gave the nice counter example of the analysts/news wires not making much of the new Apple iPod, when looking at the web it was possible to see that the public were in contrast very enthusiastic about it.
Overall an interesting event. I think the application of "quantified news" to risk management is interesting - maths and financial theory is very interesting but markets are driven by people's behaviour and if "quantified news" can help us understand this better it has to help in avoiding (some!) of the future problems to be faced in the market.
Posted by Brian Sentance | 12 November 2009 | 12:06 am
High Frequency Trading vs Flash Trading
Economist Tim Worstall has an distinction to make on the differences between high frequency trading and flash trading in a recent article.
Essentially it is the difference between getting your orders in quicker than every one else, and having a peek at what everyone else is doing before putting your money down. The SEC appears to be conflating the two and has concerns.
With the world condition in banking, could we see some poorly thought out legislation rushed through so that regulators can be seen "doing something"? Or would it level the playing field a little so that those trading operations that cannot afford the overhead of super fast computers and networks are not excluded?
Posted by Dean K | 2 October 2009 | 2:51 pm
Tick Size Harmony...
...in a rare show of co-operation (I wonder what is the carrot or (regulatory) stick here to motivate this?) European exchanges and MTFs seem to have agreed on standardising tick sizes (or at least to have two standards rather than twenty five!). Extract from article on AutomatedTrader:
"From the perspective of each trading venue, strong incentives exist to undercut others in terms of tick sizes, which is not in the interest of market efficiency or the users and end investors. This might, in turn, lead to excessively reduced tick sizes in the market. Excessively granular tick sizes in securities can have a detrimental effect to market depth (i.e. to liquidity). An excessive granularity of tick sizes could lead to significantly increased costs for the many users of each exchange throughout the value chain; and have spillover costs for the derivatives exchanges' clients."
Posted by Brian Sentance | 9 July 2009 | 8:11 am
Best execution 2009 - July 1st 2009
A few summary points I took from the Best Execution Europe 2009 event courtesy of Incisive Media that I attended yesterday morning.
The event started with a presentation by Michael Fridrich, Legal and Policy Affairs Officer of the European Commission:
So in summary it was a civil servant PR exercise with few surprises, other than we are going to regulate anything that moves. On to a panel debate on "build vs. buy" for execution management software. I will try and put my obvious vendor bias to one side in summarising this one: The debate on this was pretty standard, but the guy from Majedie was at least controvertial in what he was saying, (including at one point that "investment management does not scale"). I assume he is trading simple products and as such is able to outsource more than the JPMorgan manager. My own slant is that more vendor products need to be designed to integrate easily with the IPR of a financial institution i.e. less black box. Tom Middleton of Citi then did a presentation on (equity) market liquidity and market fragmentation: Tom's presentation was then followed by a panel debate on Smart Order Routing: And finally (at least before I had to leave) there was a presentation by Richard Semark of UBS on Transaction Cost Analysis (TCA): Not sure who the TCA providers he refers to are, but maybe I should find out to see what they offer...
Posted by Brian Sentance | 2 July 2009 | 8:17 am
Twittering the Wisdom of Crowds
Deserving an award for title alliteration, an article on Finextra has announced that Streambase Systems have connected their system to Twitter, the fashionable microblogging site. Regardless of the intent, it is an excellent marketing exercise by Streambase (er, maybe one that I should remember for the future!...).
Reasonable comments from Finextra at the end of the article, saying that Twitter is a notoriously bad source of information, very open to (designed for?) rumour, and as such it would be difficult to see what real information traders could extract from the noise. At one level, then rumour and counter-rumour are the basis of markets, although the recent financial crisis has illustrated how powerful rumours can be. I would suggest it begs the question as to when rumour and counter-rumour is part of the price formation process, and when it becomes market manipulation.
On a related note, the Efficient Market Hypothesis (EMH), the financial theory that all information (including rumours) is reflected in current prices, has been coming under some attack in the press recently. With a fund-management and Monty-Pythonesque slant, James Montier of Société Générale takes EMH to task in his recent article in the FT (see Pablo Triana for an alternative view).
My opinion is that EMH has still got some legs in it as a model, but behavioural finance probably has a lot more to explain (or rationalise?) about this theory and others in light of recent events. Anyone got a different opinion, or do I need to open a Twitter account to find out?...
Posted by Brian Sentance | 25 June 2009 | 10:16 pm
Alternatives Need a Bigger Umbrella?
Interesting article in the FT today about why the US exodus from traditional exchanges might not be repeated here in Europe, which is contrary to the recent marketing mantra of the alternative trading venues such as Chi-X, Turquoise and Equiduct. If correct, the economics outlined in the article look justifiably prohibitive: "Merely to break even, an alternative platform with a cost base of about €10m would need to do 100m trades a year. Quite a task, given that the 208-year-old London Stock Exchange, which reports full-year figures on Wednesday, said in March it was on course for about 190m in its UK orderbook." The article points out the difficulty of starting an alternative trading venue against a dire economic background and emphasises this by ending with: “Xavier Rolet, the LSE’s new chief executive, should be praying for rain.”
Posted by Brian Sentance | 19 May 2009 | 1:16 pm
Microsoft CEP Surfaces as "Orinoco"
Seems like Microsoft have now gone public on the Microsoft TechEd site that they have a Complex Event Processing (CEP) engine that will be coming to market shortly (see MagmaSystems blog post ). One of my colleagues Mark Woodgate attended a briefing event at Microsoft for this technology back in February this year - here's an extract from some internal notes that Mark made back then:
"Microsoft CEP is very similar to StreamBase conceptually (and not unsurprisingly), in the sense that there are adapters and streams and how you merge and split them via some kind of query language is the same. However, StreamBase uses the StreamSQL which as we have seen is SQL-like in syntax but Microsoft CEP uses LINQ and .NET and although conceptually it is doing the same thing, it does not look the same. StreamBase’s argument was you can be an SQL programmer to use it and don’t need lower-level like .NET; however, it’s not SQL really as it has all these ‘extensions’ you have to learn so using .NET might look more tricky but in fact it makes sense. They don’t have a sexy GUI yet for designing CEP applications like StreamBase but it will be done in Visual Studio 2008.
Currently, you build various assemblies (I/O adapters, queries and functions) and then bolt them all together, called ‘binding’ by command line tool. You then deploy the application onto one or more machines using another tool so it’s a manual process right now. They are aware this needs to be made easier and more visual. They are allowing other libraries to be bolted in via the various SDKs so it’s pretty open and flexible. It works well with HPC and clusters/grids (or so they say) and of course can be used with SQL Server. The CEP engine also has a web interface based on SOAP so at least non-Windows based systems can talk to it"
The release of this technology will be an interesting addition to the CEP market and to the Microsoft technology stack in general. Assuming performance is at credible levels (i.e. not necessarily leading but not appalling either) it will certainly bring both technical and commercial pressure to bare on existing CEP vendors (see earlier post on Aleri/Coral8) and has the potential to broaden the usage of CEP. Obviously Linux-Lovers (sorry, I didn't mean to be personal...) will not agree with this, but Microsoft is putting together an interesting stack of technology when you see this CEP engine, Microsoft HPC and Microsoft Velocity coming together under .NET.
Posted by Brian Sentance | 14 May 2009 | 4:13 pm