The giants among us -- or US"?

"The Giants Among Us" is an article by Tom Ewing & Robin Feldman that has recently been published at 2012 Stanford Technology Law Journal 1.  You can read it online here. Astonishingly, given that it was posted three weeks ago and covers such an important subject, no readers' comments have yet been posted in response to it.  IP Finance readers may wish to take note of its abstract:

"The patent world is undergoing a change of seismic proportions. A small number of entities have been quietly amassing vast treasuries of patents. These are not the typical patent trolls that we have come to expect. Rather, these entities have investors such as Apple, Google, Microsoft, Sony, the World Bank, and non-profit institutions. The largest and most secretive of these has accumulated a staggering 30,000-60,000 patents.

Investing thousands of hours of research and using publicly available sources, we have pieced together a detailed picture of these giants and their activities. We consider first the potential positive effects, including facilitating appropriate rewards for forgotten inventors, creating a market to connect innovators with those who can manufacture their inventions, and most important, operating as a form of insurance – something akin to an Anti-Troll defence fund.

We turn next to the potential harmful economic effects, including operating as a tax on current production and facilitating horizontal collusion as well as single firm anticompetitive gamesmanship that can raise a rival’s costs. Most important, we note that mass aggregation may not be an activity that society wants to encourage, given that the successful aggregator is likely to be the one that frightens the greatest number of companies in the most terrifying way.

We argue that mass aggregators have created a new market for monetization of patents. It is vast, rapidly growing, and largely unregulated. We conclude with some normative recommendations, including that proper monitoring and regulation will require a shift in the definition of markets as well as a different view of corporations and their agents".

Slightly mischievously, I did a word count on "Intellectual Ventures" which revealed 279 references to that remarkable business. Even more mischievously I did a word-count for "Europe", which secured just three mentions. This is an absorbing, well-reasoned and attractively-presented essay -- but it cries out for a counterpart based on European data, regulatory mechanisms and legal background with which to complement it. Is there anyone in Europe who is prepared to take up this task?

Marks and Brands in the Auto Industry II: Motorsport

It can be argued that the most valuable IP of a motorsport team is its brand: it is by allowing third parties to associate themselves – through sponsorship -- with their brand that teams earn much of their money. Similarly, it can be argued that technical IP serves merely to enhance the value of the brand by facilitating race success.

Perhaps, then, it should come as no surprise to learn that a “green” vehicle design company Set up in 2007 by Gordon Murray, former Technical Director of the successful McLaren and Brabham motorsport teams, has 13 different trade mark registrations compared with 9 patent families and two design registrations. The company also maintains a high public profile, its most recent press release announcing the development of a new electric-powered sports car, the Teewave.

In this latter respect, Gordon Murray Design seems similar to the electric sports car manufacturer TESLA founded by another high-profile figure, Elon Musk, co-founder of PayPal. Financial commentators blow hot and cold on TESLA’s prospects: it will be interesting to see how Gordon Murray Design fares.

More analysis of the IP business models of Gordon Murray Design and two other “green” UK automotive companies is available here.

Loss Leaders and Bait and Switch: Marks and Brands in the Auto Industry

I have always thought that when a car company advertises a certain model, the primary intention is to sell as many units of that model as possible. It had never occurred to me that a given model might be promoted for marketing purposes other than the goal of necessarily selling that model. "Loss leaders"?-- that is for the local pharmacy; "bait and switch"--that is for the local supermarket. Surely neither of these marketing ploys could have any relevance for the marketing and promotion of an automobile brand.My, oh my -- was I wrong!

Consider the following two items that appeared in separate December 2011 issues of The Economist. In the first article ("Difference Engine: Volt farce") here, which appeared in the 8 December issue, the focus is on the challenge facing GM in dealing with questions over the safety of the electric battery, the technological centerpiece of the highly touted Volt electric car here.

Against that background, the article stated as follows:

"For General Motors, a good deal of the company’s recovery from its brush with bankruptcy is riding on the Chevrolet Volt (Opel or Vauxhall Ampera in Europe), its plug-in hybrid electric vehicle launched a year ago. Not that GM expects the sleek four-seater to be a cash cow. Indeed, the car company loses money on every one it makes. But the $41,000 (before tax breaks) Chevy Volt is a “halo” car designed to show the world what GM is capable of, and to lure customers into dealers’ showrooms—to marvel at the vehicle’s ingenious technology and its fuel economy of 60 miles per gallon (3.9litres/100km)—and then to drive off in one or other of GM’s bread-and-butter models."

Stated otherwise, the "Volt" brand is being promoted no less for the broader message that the brand is intended to convey about the technological capabilities of a reborn General Motors than for the the direct sales potential of the model (at least for the foreseeable future, which remains uncertain). While the Volt is not exactly a loss-leader, I am sure that GM wants to make a lot of money on this vehicle, if for no other reason than the costs of bringing a new car model to market. Still, the current tribulations of the Volt car point to the fact that GE cannot really allow customer perception of the vehicle as a symbol of the company's technological prowess, even if the model itself is not directly contributing to the company's bottom line.


But this is hardly the first time that an automobile model has been used to serve purposes other than the direct sale of the model in question. This was brought home in the article in the 17/24 December issue of the same magazine ("Retail Therapy: How Ernest Dichter, an acolyte of Sigmund Freund, revolutionised marketing") here. Dichter, while today largely forgotten, was a seminal figure in the marketing revolution that took place in the 1930s and 1940s, where the focus was how to exploit irrational purchasing behaviour for better sales performance. Dichter was a committed student of Freud, and his focus was on the Freudian preoccupations of the day, emphasizing the emotional, the irrational and the sexual.

In this context, perhaps Dichter's most creative marketing ploy was his approach to the then new line of Plymouth cars. The problem was that sales of the Plymouth brand were lagging. Dichter reasoned that the problem could be found in the slogan--""different from any other one you have ever tried." Dichter reasoned that the slogan triggered an unconscious fear of the unknown in purchasers. The solution that he fashioned was ingenious. Dichter gleaned from interviews that, while only 2% of car purchasers (in 1939) owned a convertible, they (especially middle-aged men) almost all dreamed of owning one.

And so the ploy. The male would be drawn into the showroom to look at the convertible--a symbol of "youth, freedom and the secret wish for a mistress". He would then return with his wife, who had no interest in sharing her husband with a mistress, even of the four-wheeled variety. The compromise was the purchase of a sensible sedan -- of the Plymouth variety of course. It was a clever scheme to leverage one model to encourage the purchase of another.

It would be overstated to suggest that the Volt is a "loss leader" in the traditional sense, or that the Plymouth convertible was a "bait and switch" tactic. Still, there are tantalizing points of similarity. In the auto industry as well,the interrelationship among the mark, the brand and the product are at once both more and less than that which meets the eye.

Institute for Capitalising on Creativity wants knowledge transfer associate

St Andrews: a leading institution in the fields of innovation,  creativity
and saving energy by not turning on the lights when it gets dark ...

Here's an attractive position for the right bright youngster. The Institute for Capitalising on Creativity, in the School of Management at the University of St Andrews, is recruiting a Knowledge Transfer Partnership Associate. The project is with Creative Scotland and identifies successful strategies for the management, commercialization and exploitation of intellectual property in the creative industries in Scotland. It's a great opportunity to work with the creative industries and research their IP strategies.

 The position is based in Edinburgh and candidates are invited to apply if their backgrounds are in economics, management or law. The deadline for applications is 15 February and you can get more information here.

Markets -- increasingly complex dynamics over the past decade

Didier Sornette is among the most creative scientists I know, and always seems to come up with an approach to problems that is more or less orthogonal to what anyone has done before. In a paper just out (as a preprint), he and Vladimir Filimonov offer a really novel analysis on the old question about whether market movements are caused by A. external influences such as news (exogenous causes) or B. influences internal to the market itself such as emotions, avalanches of belief and opinion, etc. (endogenous causes). This matter, of course, touches directly on the infamous efficient markets hypothesis, which insists on interpretation A (all A, no B).

I've written before (here and here, for example) about various studies trying to match up news feeds with big market moves to see if the latter can be explained by the former. Generally, the evidence suggests no, implying some mixture of A and B. Sornette and Filimonov now take a very different approach, which is an attempt to use mathematics to directly measure how much of the dynamics of a time series can be attributed to endogenous, internal causes. The mathematical technique is itself interesting. If it can be trusted, then the results suggest that markets in the past decade have become much more strongly driven by internal, endogenous dynamics than they were before. As the authors point out, this could well reflect the explosion of algorithmic trading, as computers interact with one another in lots of complex feedback loops.

The authors envision their technique as a device for measuring the amount of "reflexivity" in the market, referring to the term used by George Soros to describe how human perceptions and misperceptions interact in the market to drive changes. This is a fascinating idea if it can be done. Here's how it works. Sornette and Filiminov model price time series as being generated by a statistical "point process" -- the idea is to generate price dynamics by modelling the arrival of actual buy and sell orders in the market. The simplest way to do this is to use a Poisson process, with equal probability at all times. This gives a random time series of price movements, but an unrealistic one that lacks the most interesting properties of real markets -- fat tails in the distribution of returns, and long term memory in the volatility (and also volume fluctuations). To get realistic time series, it's possible to let the arrival of buy and sell orders have strong correlations in time, as they in fact do in real markets. This technique is referred to as a "self-excited Hawkes model."

Another way to put this is as follows. In an ordinary Poisson process, the average number of events striking in an interval dt (say, 1 second) is a constant, λ. In the richer process with correlations, this will now be a function of time λ(t). The key to the analysis here is expressing this quantity (essentially, the rate of buy and sell orders hitting to book around time t) as the sum of two very different processes -- 1. a background contribution due to external events such as news, which drive the market, and 2. a feedback contribution coming from the tendency for orders now to have consequences, leading to further orders in the future. The result is eq.(1) of the paper:

Here the first term on the right is the background (which drives the exogenous dynamics) and the second term is the feedback, with h being some function that reflects the likelihood that an event at time t_i generates another one at time t later. The first term creates a steady stream of events, the second one creates events which create events which create events, a branching stream of further consequences.


Now, the task of fitting time series generated by such processes to real financial data is more involved and relies on some standard maximum likelihood techniques. The authors also assume for simplicity that the function h has an exponential form (events tend to cause others soon after, and less so with increasing time). The key parameter emerging out of such fits is n, which can be interpreted as the fraction of events of endogenous origin, or in effect, the fraction of market activity due to internal dynamics. The statistical fit also estimates μ, this being the background level of exogenous shocks, which also rises and falls with time. Sornette and Filimonov use data on E-mini futures on a second by second basis over about 12 years to run the analysis, the key results of which come out in the figure below.


The four parts going downward show volume and price, and then the estimated background and the fraction of events caused by internal dynamics, n. The most interesting feature is the general rise in n over the decade showing an increasing influence of internal dynamics, or events which causes further events through internal market mechanisms. In contrast, the background of exogenous shocks -- information driven dynamics -- remains more constant (except with a spike around the time of the Lehman Bros collapse). From this the authors offer a few comments:

The first important observation is that, since 2002, n has been consistently above 0.6 and, since 2007, between 0.7 and 0.8 with spikes at 0.9. These values translate directly into the conclusion that, since 2007, more than 70% of the price moves are endogenous in nature, i.e., are not due to exogenous news but result from positive feedbacks from past price moves. The second remarkable fact is the existence of four market regimes over the period 1998-2010:
(i) In the period from Q1-1998 to Q2-2000, the final run-up of the dotcom bubble is associated with a stationary branching ratio n fluctuation around 0.3.
(ii) From Q3-2000 to Q3-2002, n increases from 0.3 to 0.6. This regime corresponds to the succession of rallies and panics that characterized the aftermath of the burst of the dot-com bubble and an economic recession.
(iii) From Q4-2002 to Q4-2006, one can observe a slow increase of n from 0.6 to 0.7. This period corresponds to the “glorious years” of the twin real-estate bubble, financial product CDO and CDS bubbles, stock market bubble and commodity bubbles.
(iv) After Q1-2007 the branching ratio stabilized between 0.7 and 0.8 corresponding to the start of the problems of the subprime financial crisis (first alert in Feb. 2007), whose aftershocks are still resonating at the time of writing.

It should be emphasized that the analysis here is only sensitive to endogenous dynamics over timescales of only around 10 minutes or less. This stems from some assumptions necessary to deal with the highly non-stationary character of the data, as trading volume has exploded over the decade. Hence, the lower values of n earlier in the decade could reflect the failure of this analysis to detect important endogenous feedbacks operating on longer timescales (in the burst of the dot-com bubble, for example).


Now for what is perhaps the most fascinating thing coming out of this paper -- the idea that this analysis may be able to distinguish big markets movements caused by real news or other fundamental changes from those more akin to bubbles and caused purely by human behaviour (panics and the like) or algorithmic feedbacks. Sornette and Filimonov looked at two specific events, on 27 April and 6 May 2010, where markets moved suddenly and in a dramatic way. The first was caused by S&P downgrading Greece's debt rating, the second is, of course, the Flash Crash. The same analysis using their method shows strikingly different results for these two events:

 
The "branching ratio" here is just the n we've been talking about -- the fraction of market dynamics caused by internal dynamics. The most significant finding is that while the first event of 27 April showed absolutely no change in this value, expected given the apparently clear origin of this event in external information, the 6 May Flash Crash shows a sudden spike in the internal dynamics. Hence, based on this example, it appears that this parameter n acts like a flag, identifying events caused by powerful internal feedbacks. As the authors put it,

The top four panels of Fig. 3 show that the two extreme events of April 27 and May 6, 2010 have similar price drops and volume of transactions. In particular, we find that the volume was multiplied by 4.7 for April 27, 2010 and by 5.3 times for May 6, 2010 in comparison with the 95% quantile of the previous days’ volume. The main difference lies in the trading rates and in the branching ratio. Indeed, the event of April 27, 2010 can be classified according to our calibration of the Hawkes model as a pure exogenous event, since the branching ratio n (fig. 3D1) does not exhibit any statistically significant change compared with previous and later periods. In contrast, for the May 6, 2010 flash crash, one can observe a statistically significant increase of the level of endogeneity n (fig. 3D2). At the peak, n reaches 95% from a previous average level of 72%, which means that, at the peak (14:45 EST), more than 95% of the trading was due to endogenous triggering effects rather than genuine news.

Do you believe it? It sounds plausible to me. I guess the thing that would be good to see is some thorough tests of the method applied to time series for which we know the origin of the dynamics. That is, take something like a chaotic oscillator and drive it with some external noise with a controllable level and see if this method generally gives reliable results in teasing out how much of what happens is driven by the noise, and how much by the internal dynamics. Perhaps this has already been done in some of the papers describing the development of the self-excited Hawkes model. I'll try to check on this.


In any event, I think this is certainly a provocative and interesting new approach to this old question of internal vs external dynamics in markets. And I actually don't find the result surprising at all that n has increased markedly over the past decade. This is precisely what one would expect as trading moves over to algorithms that react to what other algorithms do on a sub second basis.