What the equity herd might look like

… aka, equity market agents and non-linear dynamic behaviour
[updated to account for Steve’s comment]

Inspired by reading Professor Steve Keen’s book on ‘Debunking Economics’, this is a first pass at quantifying what many call the ‘herd’. Understanding herd mentality/crowds/group behaviour is a cornerstone to successful investing. In my (slow and winding) path of development of a better toolset for analysing price history for investment decisions, I have a string of projects that are effectively Engineering applications to the field of economics.

Not many books can be picked up and read that leave you with an appreciation of the subject, it’s power, limitations, history and the subjects internal professional biases. Steve’s book is all that for non-economists such as myself. It isn’t hate mail – it is a qualified professional taking stock of his life’s study. In doing so, Steve does a nice job giving the reader every opportunity to research and verify for themselves his own expert opinions on why mainstream economics can be, and is often, dangerous. Better yet, his book provides practical solutions that better describe day to day economic observations, at least to this Engineer.

I come to this point not from browsing news-stands, but having spent the past 2 years completing my own hands on full time private trading education having scoured libraries and universities for material that helped explain what was reportedly ‘unprecedented, unforeseeable, unexpected and unpredictable’ market volatility not seen since the Great Depression of the 1930’s. What I have since discovered for myself is completely the opposite. What we are living through is normal volatility that has existed in the markets for over 100 years that is not unprecedented and most certainly IS foreseeable, expected and (to a large extent) predictable. Volatility is inherent, innate and natural behaviour of dynamic systems and should be expected, and thus planned for. Many days were spent in libraries perusing journals of popular brand name economists searching for that elusive being who could explain dynamic disequilibrium to a simpleton. None qualified, so I have since developed an effective way to monitor, analyse, trend and model the dynamics of prices with using only an Engineering toolset. The success of this approach filters all the noise of misleading and costly distractions brought about by false explanations.

Professor Steve Keen’s book ties in all the important economic themes necessary for non-economists to make sense of what main stream ‘bookstand’ economists fail dismally at i.e. modelling instability and disequilibrium. His consideration of the history of economics and the major unorthodox contributors of past leave the reader with an appreciation that Steve cares about his profession and is determined to contribute to a better understanding of the subject matter.

Hence, a good application of my newfound knowledge would be explaining the periodic volatility that has existed in 100 years of Dow Jones Industrial Average since 1896 and most likely since it’s inception. In an attempt to quantify the equity market herd/crowd, I extracted the top listed shareholders of the 45 largest public listed US equities in NYSE, NASDAQ and AMEX exchanges. The top shareholders were simply the public listed top 5 individuals (persons), top 10 institutions, and top 10 mutual funds. APPL, XOM, MSFT, WMT etc and down the list ranked by market cap. I stopped at 45 for no particular reason. The results –

45 stocks, $6.65Trillion current market cap; top shareholders are –
140 unique individuals (persons), holding 2.4% of this market cap
97 unique institutions, holding 18.4% of this market cap
139 unique mutual funds, holding 6.2% of this market cap
– all told, 386 unique stock holders with different strategies, objectives, expectations and preferences hold just 27% of $6.65Trillion held in just 45 stocks.

According to the World Federation of Exchanges, the US equity market cap is of the order of $17Trillion (in round numbers) in several thousand listed equities. Extrapolating by crude approximation only – given the expanding number of smaller stocks to remaining and more numerous smaller holdings, it is not a stretch to estimate an additional 3x the above numbers for the remaining US equity market. Remember the above are considered only the major shareholders.

[Edit – thanks to comments from Steve shaking his head muttering ‘Econ101 buddy. Power law.’] I know my quick and dirty extrapolation was linear, so roughly 386×4 = 1544 holding 100% is not correct due to the statistical reality of Guassian or exponential decay in size of holdings. In assessing those most likely to trade actively in contributing to the much coveted ‘liquidity’ then only some fraction of the total needs to be modelled in any case.

So using a power law non-linear extrapolation, if 27% is 386, then 100% would be 1887 agents. Ignoring the lowest 25% holders (on account of small size, likely trading inactivity and lumping some portion of private individuals who wouldn’t actively trade their holding) then perhaps a more realistic number of active agents would be 75% being 1297, say 1300. Still, 1000 of these are likely to be more active to represent the lions share of volume – but this is unfounded speculation on my part.

Something of the order of 1,300 unique entities (representing the largest 75%) actively and continuously control the lions share of $17Trillion in US equities on a day to day basis. Economists call these ‘agents’, traders call them ‘the herd’ or the ‘crowd’. Volume is the crowd, the price is the common language. The price history of an asset accurately reflects the movement of the crowd – whether you happen to agree with it or not.

“Debunking Economics’ proposes a more accurate reality in the aggregation of multiple supply/demand curves (expectation curves I call them) to be non-linear. This non-linearity is modelled on a daily basis in technical analysis of asset prices, and is evidenced in over 100 years of the DJIA price history. So it stands to reason herd behaviour is in fact the real form of Steve’s non-linear aggregation.

Aggregating 1,300 unique investment expectations (agents) is no easy task. However ‘herd mentality’ permits some crude approximations in probably 6 groupings of tactical strategies linking similar behaviours (by my estimations). These are value/growth investors (buy and hold types), pensions/endowments, institutions, individuals/private equity, speculative traders and algorithmic/high frequency (millisecond) trading.

I am enthralled in reading Keen’s book ‘Debunking Economics’, as it is well written, and provides sufficient introductory and supporting material to help non-economists come to terms with a difficult and misunderstood subject. It joins the list of few reference manuals to be kept within arms length. It should be a text book for anyone interested in reading economic theory.

The reading of ‘Debunking Economics’ better enlightens me on what market effects agents like Bernanke, Summers and Lagarde et al might like to think they can impose. In the end, these players live in hope to influence the crowd, for the dynamics are well and truly baked into the equity cake. QE1 and QE2 has been crowd control, full stop.

Regards,

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About atradersrant

Self-employed private trader of equities, commodities and FX for income and investment; Follow me at your own risk! I provide analysis of major market & economic trends .. with too much commentary on fraud and corruption that is rife in the open market.
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3 Responses to What the equity herd might look like

  1. Martin Green says:

    I am curious why “Engineer” and “Engineering” have first letter capitalisation, but “economics” not so?

  2. Pingback: What the equity herd might look like « naked capitalism

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