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THERRAMUS 18 January 2009


A cause for the financial crisis of 2008 is described that differs from the conventional wisdom. It is proposed that a fundamental shift in interest occurred in the 2000s that profoundly altered incentives for the global financial industry. The underlying reason for this shift is suggested to be volatility in the price of oil and its downstream effects on investment risk.

Novel data is provided to demonstrate that a distinct series of spikes in oil price volatility initiated in the early 2000s (see Figure 9). These volatility spikes resulted from either sharp rises or falls in price. The oil shock of 2008, when the cost of oil doubled in less than a year (peaking at ~ $140 a barrel), is shown not to be an isolated event. Instead, the oil shock of 2008 caused what is presently the largest of 7 prominent spikes in oil price variance. This now nearly decade long pattern of spiking instability  in oil price appears to be unprecedented, is ongoing and may be a natural process that results from starting or being on the down-slope from "Peak Oil".

Importantly, the individual spikes in oil price variance since 2000 each precede (i.e. are upstream of) corresponding spikes in volatility in the inflation rate, the S&P 500 index and the price of gold - indices strongly tied to the confidence of financial professionals to make informed assessments of investment risk. It is proposed that as evidence consolidated that growing unpredictability in oil price was causing increasing uncertainty in investment outcomes, the necessary and sufficient conditions emerged for:

1) Expansion of the "shadow banking system" and

2) Unregulated value extraction (i.e. looting) from this sequestered pool of capital.

Finally, it is shown that all six recessions and stock market crashes since 1970 have been preceded by spikes in the volatility of oil price. Most notably the "Black Monday" stock market plunge of October 1987 was foreshadowed by an unexpected price shock in 1986 caused by a temporary failure of the OPEC oil cartel. "Black Monday" may have provided a salutory demonstration to the financial markets that a spike in oil price volatility was sufficient in its own right to induce a sudden increase in investment risk (see Figure 14).

Lessons learned on the consequences of oil price instability from "Black Monday" may have been a factor guiding the behavior of the financial industry in the lead up to the crisis of 2008.




Oil-price net logog.jpg




Oil-price net logog.jpg



The former chairman of the US Federal Reserve Alan Greenspan provided the following response during questioning about his “ideology” before a committee of the US congress on the 23rd Oct 2008:

Greenspan said: "I have found a flaw. I don't know how significant or permanent it is. But I have been very distressed by that fact...."

A reflexive media and commentators jumped on a bowed Greenspan for the usual depressing reasons. However, was it possible that Mr Greenspan had let his mask slip for a moment ? The attention grabbing part of his sentence was “…how significant or permanent…”. Could it have been that Mr Greenspan was not saying he’d been wrong ? Instead, was he implying that conditions in the economy had changed unexpectedly and fundamentally in a manner that now made his old way of thinking flawed ?

This idea explores the possible causes for Mr Greenspan’s distress. In short, it proposes the outline of a mechanism for how volatility in the price of oil might have contributed to the apparently irrational actions of the financial industry. In particular, it speculates how recognition of the implications of this volatility might have rationally and quickly changed the incentives of  global finance. The idea also proposes that in coming years, unpredictability resulting from sudden movements up or down in the price of oil will become understood to be one of the most serious and pressing threats to our economy and democracy.

Consider the following hypothetical sequence of events:

1. Global oil production begins to peak around the yr 2000 as predicted by Hubbert.

2. A new pattern of volatility in oil prices emerges shortly thereafter and this pattern continues to build through the present (and into the future).

3. This type of volatility is in the nature of being on the production down slope of a finite resource in great demand (i.e., oil). Variance and occasional very large movements were certainly evident in the upslope of the production curve. However, the frequency and severity of oil price movements that characterize the new pattern on the downhill side of the production curve are envisaged to be of a different pattern and order of magnitude.

4. Owing to the singular role of oil in the economy, volatility in its price begins to propagate in variable degrees into the volatility of the price of nearly everything else.

5. A general increasing volatility in prices translates into increases in risk of investment - indeed, due to unknowns in future prices and most especially of oil itself, real financial risks across the board are probably rising exponentially relative to price volatilities.

6. A smart, knowledgeable and initially small number of insiders anticipate and confirm the implications (as outlined broadly in 1 through 5) of being on the down slope of the global oil production 4-8 yrs earlier than the rest of us. These people don't need to know each other, but do need to have specialized knowledge and be capable of uncommon insight.

7. With financial risk increasing, and a still small, but growing number coming to understand what is going on, the incentives within markets shifted rather quickly from protecting the interests of shareholders, to figuring out how to “cash out” quickly. This shift in incentive is the fundamental change (of uncertain permanence) that may be the real cause of Mr Greenspan's distress.

8. The behavior of the primary few spreads within the global financial industry and perhaps beyond. Most secondarily affected individuals are probably oblivious to the ultimate cause (i.e., oil price volatility) of their choices and actions. A fin-de-siecle ethos becomes pervasive. There is an unspoken, or perhaps even quietly discussed urgency, that time is running out to make your “nut” (i.e., sufficient money to retire wealthy) and get out. Greed, fear and/or the survival instinct does the rest. An asymmetric herding behavior takes hold as individuals within the financial industry overwhelmingly place self-interest above the interests of their clients, shareholders and society at large.

How the "cashing out" occurred is a matter of some complexity. But this part of the story does seem to conclude with tens and perhaps hundreds of trillions dollars in  worthless ("toxic") assets in the "shadow banking system". It is speculated that the primary mechanisms of "cashing out" did not directly involve the accumulation wealth in the "shadow banking system" per se. Instead, the evidence suggests that extraction of value involved the taking of fees, salaries, bonuses, stock options and other mechanisms leveraged against the "toxic assets" by the exclusive group that have access to this pool of capital. Government bailouts of "systemically important institutions" is possibly the last gasp of this use of leverage against the "shadow banking system" by insiders. Whatever the specifics of the mechanism - we know the rest - credit crisis, stock and housing market crashes, job losses and the deepest recession of the last 50 years.

The Limits of Conventional Wisdom and the Causes of the Financial Crisis

The hypothetical sequence of 1 through 8 imagines a cause for the financial crisis beyond human failings such as greed and selfishness. Human frailty is a necessary, but not sufficient factor. Speculating on the cause of this economic collapse is a weakness of this idea... as it is not so hard to be off track when there are so many unknowns. On the one hand, the workings of complex systems are ineffable....and well...complex. But, even in the most ephemeral of cases, the proverbial butterfly in South East Asia still has to beat its wings to provoke that storm two years later in North Carolina. Some causes are cryptic, but turn out not so hard to be resolve with the right perspective. For example, though not evident until Jared Diamond pointed it out, how the axial geography of Eurasia conspired to give a leg up to certain technological civilizations now seems obvious to any thinking person.

The above being said, the cause tagged here is more robust than a wing beat and though in plain sight, we have been curiously blind to it. At its most essential, this narrative is about the primacy of the laws of physics and the sad consequences of magical thinking. It has taken time to piece my story together as it has many intricacies and moving parts. Insights arrived over time, sometimes from unexpected directions. Occasionally startling patterns came sharply into focus. Hopefully, the reader will persist as they are taken through the case step-by-step. But first, put aside the belief that what many call  "human weaknesses" had the axial role. Foibles such as hubris, greed, and ambition are recognized as key and necessary factors, but it is suggested that they are not the ultimate determinant of our current unpleasant circumstances.

Another much talked about causal factor is the sub-prime mortgage industry. However, because "experts" keep telling us that sub-prime is the root or ultimate cause of the present difficulties does not necessarily make it so. The workings of oil markets fall outside the experience of most people, but many understand the mechanics of financing a mortgage. Sometimes, familiarity with a subject matter can hinder understanding. The Indian tale of the blind men and the elephant provides a classic fable on the treacherousness of narrowed perspective and half-truths. The fact is that securitization of sub-prime mortgages was just one of the more lucrative facets of a huge and labyrinthine shadow banking system. More on the secondary, but nonetheless key role played by mortgage financing and the SBS in this crisis will be provided later.

Sadly, the ultimate mechanisms guiding many events are lost to the past - owing to various factors including acceptance of the conventional ignorance (i.e, wisdom), the tendency of victors to write the history and so on. Nicholas Nassim Taleb has written beautifully on this topic. Also, as alluded to above, how does one read the thoughts of minds from the past as collective actions were prompted and choices made that determined the course of events. No insider is going to admit, or perhaps even care to remember a point in the early to mid 2000s that they came to deduce or intuit that the financial system was "going to hell in a hand basket" and that the rational option was to make off like a bandit. Wall Street even has a coded acronym that describes this mind-set   "IBGYBG" - I'll be gone, you'll be gone. For an industry subscribing to IBGYBG as an operating principle, the realization that risks associated with investment in the normal economy were quantifiably increasing was probably deeply unsettling. Given the culture of Wall Street and the wholesale failure of our Government to carry out its regulatory duties, the expansion and  looting of the shadow banking system perhaps became all but inevitable.

It is perhaps worth emphasizing that the hypothesis posed here does NOT require an organized conspiracy to work. Those caught up in the fin-de-siecle mentality that lubricated this crisis do not have to know each other or openly share their concerns. Given the right seed bed, timely ideas propagate like weeds. Simply put, the idea proposes that anticipation of the economic disruptions that would be wrought by instability in the price of oil following its global peak in production provides a key to understanding the current financial crisis. The pricing unpredictability in this most fundamental of energy sources is proposed to be the sole factor that is both necessary and sufficient to explain the present debacle - and perhaps future debacles as well. All else, bad behavior of the Wall Street included, is suggested to self-organize and flow downstream from the effects of volatility in the price of oil on investment risk.


Events 1 through 8 of the “hypothetical sequence” outline propositions for which a certain amount of data can be derived. For example, the “hypothetical sequence” suggests the following:

1. Volatility in the price of oil will increase after Hubbert's peak in global oil production (i.e, "Peak Oil").

2. This increase in the volatility of the price of oil will propagate volatility into the price of other goods and services.

3. Increasing volatility in the price of oil and the prices of things general will result in increases in investment risk.

4. And that information was in place prior to the crisis enabling anticipation that peak-oil-induced volatility would increase investment risk to levels unacceptable to the financial industry.

The author refers to these as the four propositions of the apocalypse - a sad attempt at playfulness and definitely in poor taste. Nonetheless, data will be provided to support each of the propositions. It is probably fair to point out that although propositions propose mechanistic linkages, the actual data presented will be correlative. This is one step better than an opinion not backed up by facts. Nonetheless, one can not infer causation from correlation.

Many commentators have fixated on the pernicious effects to the economy of oil prices hitting new highs. However, this is only half the story. A meaningful index of volatility reflects the magnitude of sharp movements in either a positive or negative direction. Financial unpredictability wrought by a sharp decrease in oil price is likely to be just as economically destablizing as that resulting from sudden increase. The reader should bear this important subtlety in mind as the case in this essay is developed.

The fourth proposition will explore how anticipation may have occurred, paying special attention to what could have been learned from the peak in US oil production in the 1970s and the stock market crash of October 1987 called "Black Monday". Indeed, it is suggested that the mysterious "Black Monday" crash is a key to understanding the present crisis. It is proposed that on this day over 20 years ago, the market learned that spikes in oil price variance are a standalone determinant of investment risk in their own right.

There is one more thing that needs to be written before moving onto the data supporting these four propositions - a look into a possible future. In this essay it will be shown that distinctive series of spikes in oil price variance have recurred as transient phenomena since 2000. Moreover, evidence will be outlined as to how these spikes in volatility propagate their effects downstream  into the economy over time. Unfortunately, since these 'variance transients' have now established a repeating pattern, it is likely that economic disruption of the type we have just experienced will occur again (and again) until a new equilibrium is reached.

PROPOSITION 1. Volatility in the Price of Oil Increased after Hubbert's Predicted Peak in Global Oil Production

Getting hold of a free source of historical oil pricing data on the internet is surprisingly difficult. There appeared to be packages that could be purchased, but eventually what seemed to be a reliable and free data base was identified at the Illinois Oil & Gas Association website.

Historical oil prices

This site provides complete monthly data from the mid-1980s up until the present on the “HISTORY OF ILLINOIS BASIN POSTED CRUDE OIL PRICES”. Not perfect, but a start.

The chart in Figure 1 is a simple plot of monthly crude “oil price” over a period from 1986 to 2009.

Figure 1 - Monthly oil price 1986-2009

Figure 1

The sharp rise (and fall !) in oil at the tail of Figure 1 (i.e., the oil shock of 2008) is a part of this story that is all to familiar to motorists.

The next problem was how to calculate an index in the volatility of oil price based on the monthly data. It was reasoned that this index of volatility should reflect the spread or variability in price over successive months. To acheive this a straightforward approach based on parametric statistics together with Microsoft Excel was used. The index was calculated as follows. The monthly oil prices for Jan, Feb and Mar of 1986 were $22.50, $16.00 and $14.00 respectively. First the standard deviation (SD) of the first 2 numbers (i.e., $22.50 for Jan 1986 and $16.00 for Feb 1986) was calculated as an index of their spread. This SD was 4.60. Next, the standard deviation of the 2nd and 3rd numbers for (i.e., $16.00 for Feb 1986 and $14.00 for Mar 1986) was estimated to give an SD of 1.41. These calculations were carried out for successive pairs of months for all 276 months from Jan 1986 down to Dec 2008.

The chart in Figure 2 plots the index of “Oil Price Volatility” in red in the left-hand Y-axis along with the monthly oil price plotted in blue (now in the right-hand Y-axis). Eyeballing the "seismograph-like twitchings" on this chart suggests that volatility has been increasing, particularly since 2002. Something that is particularly intriguing about this chart is a progression of increasingly larger "peak twitches" that appear to rise notably above a lower background of variance in the volatility index (see small arrows on Figure 2). This could be noise, but these higher amplitude pulses do seem to have pattern which looks as though it may be meaningful. More on this later.

Figure 2 - Oil price volatility has risen since 2000 - A

Figure 2

A few notes on Figure 2 and its underlying assumptions. First, one has to worry about deviance from normality etc. The approach used is not perfect. However, the aim was not to clear the forest, but to cut a narrow path through it. For this purpose, using SD as a proxy for spread seemed sufficient for now. Second, it is understood that variance (i.e., SD squared) is the preferred method by statisticians for estimating the spread of a sample population. Variances were calculated for the list of SDs and these calculations tended to accentuate the trend seen in red in figure 2. However, it was decided that the simpler SD calculation did the job, so it was stuck with. Third, calculating SD for 3 or 5 successive months was also carried out. The same overall pattern resulted from these calculations as was found for the 2-monthly calculations in figure 2. Fourth, it would have been great to get one's hands on daily, rather than monthly, oil price data to do the calculations – but as mentioned, such data is hard find on the internet. Finally, coefficient of variance (i.e., average for the 2 monthly numbers over their SD x 100) was considered as another parametrically based index of volatility. However, on reflection it was decided that an SD-based index would be better as it reflected absolute, rather than mean normalized, variability in the price of oil.

Qualitatively, the underlying trend in oil price volatility over time in Figure 2 appeared non-linear. Microsoft Excel was used to calculate a 3-factor polynomial fit to the scatter plot. This trend as represented in the pink non-linear regression line overlaid the “red” price volatility data in Figure 3. The R squared of the regression line is statistically significant and so on as provided in the chart. Interesting features of the pink regression line include that it starts to move notably from around year 2000 (i.e., Hubbert’s predicted production peak as in the "hypothetical sequence"). It also climbs in what appears to be an exponential manner from this time to the present (i.e., Jan 2009).

Figure 3 - Oil price volatility has risen since 2000 - B

Figure 3

The trend in oil price volatility is isolated in Figure 4. From this it can be seen that volatility based on the calculation approximately doubled between yrs 2000 and 2004 and then approximately doubled again between 2004 and 2006. What happens next is an interesting question ? A clue to this might come from a smaller bump in volatility occurring during the 1990s (see Figure 4). Based on this pattern it is speculated that the current exponential rise will flatten as time proceeds and eventually becoming a second bump, albeit of higher amplitude than that occurring during the 1990s. After completion of the current bump, one imagines that a large rise and fall in volatility has the prospect to occur all over again, if and when economic recovery occurs. With tightening supply, cycling variance in the price of oil on the downside of Hubbert's peak will be a stomach churning ride. Policy makers trying to force a recovery by flooding the economy with "stimulus" might consider this unwelcome possibility. The fruit of their efforts may simply be to prematurely spark the next waiting surge in oil price!

Figure 4 - Regression of oil price volatility trend 1986-2009

Figure 4

The regression line in figure 4 was recalculated for different time frames in an attempt to figure out when in the past the trend line would have indicated a significant uptick in oil price volatility. This was done to test a speculation in point 6 of the “hypothetical sequence” in which it was posed that data on rising oil price volatility and its implications on investment risk may have been available to financial insiders 4-5 yrs ago. This was achieved by removing yr 2008 and then calculating the regression line, and then doing the same with yrs 2008 and 2007 removed from the regression and and so on. Doing this, it emerged that the signal for the rising trend in oil price volatility was faintly evident (in an empirical sense) from the end of 2003 and continued to build over successive years from that time. Prior to 2003 it would have been very tough to pick up the rising trend signal from the approach taken here.

In conclusion, looking back from 2008 there is quantitative evidence for a rising trend in the volatility of the price of oil that commenced from around year 2000 coinciding with Hubbert's predicted global peak in oil production. The signal confirming the start of this upward trend in volatility would have been evident 4 to 5 years ago from around the end of 2003.

PROPOSITION 2. Increases in Oil Price Volatility is Propagating Instabilities into the Price of Other Goods and Services

As a first step, the monthly year-to-year inflation rates between 1986 and 2009 were used to derive an index of general price volatility in goods and services.

Monthly numbers on historical inflation rate (calculated from the so-called CPI-U) were obtained from:

Historical official inflation rate

Figure 5 shows a co-plot of monthly inflation (orange as calculated from the consumer price index - CPI-U), the index of inflation volatility based on bimonthly SD (green), and the trend in the inflation volatility index (light green line) over the period between Jan 1986 and Jan 2009. Bimonthly SD was calculated as an index of volatility of CPI-U/inflation exactly as was described above for the index of oil price volatility. As was the case for oil price volatility, a trend line was also calculated by Microsoft Excel as a 3-factor polynomial fit to the CPI-U/inflation volatility data (equation and R square value are provided on the chart).

Figure 5- Volatility in the Govt. consumer price index (CPI-inflation) has risen since 2000

Figure 5

The pattern for CPI-U/inflation volatility is different in subtle ways from that of oil price volatility. Nonetheless, a commonality of increasing volatility from the late 90s rising until the present is evident. The dark green line indicating the CPI-U/inflation SD switches with increasingly greater amplitude over this period. The lighter green regression line confirms the trend.

Figure 6- Trends in volatilities of oil price and Govt. inflation appear not to coincide

Figure 6

In Figure 6 the trends in monthly oil price and inflation (CPI-U) volatility are plotted together on the same time scale (i.e., Jan 1986-Jan 2009). A rise from the late 1990s to the early 2000s in the trends for both indices is apparent. However, an important problem is that the inflation SD trend appears to reach it lowest point in 1997, slightly earlier than the oil price SD trend (which as discussed above bottoms around 2000). This feature is referred to as a "non-coincident bottom" on the plot. This lack of coincidence in the lowest trough of the two plots is problematic for the "hypothetical sequence" in which it is implied that oil price variance should causally underlie inflation volatility . It is also an issue from the point of view of suggesting that some sort of coincidence occurs between the timing of Hubbert's prediction of global peak oil (i.e., yr 2000) and inflation volatility kicking off. One can perhaps account for this "non-coincidence" as a statistical error, the effects of more than one time-dependent factor on inflation, the result of government manipulation and so on. Nonetheless, this discrepancy is a concern and further clarification is required.

What happens with if "honest" numbers on inflation rate are used ?

There is much question as to whether the "official" US inflation figures reflect the actual rate of inflation in this economy. An interesting website that provides alternate calculations of inflation is "John Williams Shadow Government Statistics":

Historical shadow inflation rate

At this site, inflation numbers are calculated using methodologies that were utlized in 1980s. A site newsletter indicates that this "Alternate Consumer Inflation measure, reverses the methodological gimmicks of the last 25 years". In other words, the site suggests that Government "cheating" on inflation has been removed from estimates so that the true variance in inflation over time can be seen. Interestingly, a strong advocate for the current official inflation calculation was none other than Mr Alan Greenspan of the current distress. Unfortunately, does not provide its numbers free, and as there was no money or desire to purchase said data, the numbers were interpolated from a plot helpfully provided at the website. I might add that if I been caught by my partner paying just under $200 "for just some numbers off the web!"... there would have been serious repurcussions. Though the coming "the end of the world as we know it" is being reflected upon here, the author has no wish to sleep alone with the cats during the interim. The plot below in Figure 7 provides the fruits of the effort to (re)generate data on "honest" inflation and inflation volatility from publicly available information.

Figure 7 "Honest" inflation rate and inflation volatility since 2000

Figure 7

What we see from the "honest" numbers in Figure 7 is that volatility is now picking up slightly later into the 2000s than calculated from the official Govt. stats. Indeed, it appears that shadow inflation rate volatility does not start a new pattern of more vigoruous "twitching" until after 2000. The light green plot of the volatility trend confirms a low point for the shadow numbers occurs from around the year 2000. Figure 8 co-plots the trend for oil price volatility and shadow inflation (CPI-U) volatility and from this it can be ascertained that the pattern of variance of the two indices since the mid 1990s is very similar. The non-linear exponential rise in the inflation volatility curve is now apparently lagging a little behind the rise in oil price volatility. Most importantly, the low point of the two trends curves now share a "coincident bottom" and coincident bottoms are a lovely thing.

Figure 8 The trends in oil price and "honest" inflation rate volatilities coincide

Figure 8

A feature of the plot for inflation are larger twitches or pulses of volatility (Figure 7). Similar, though somewhat less distinctive pulses were noted earlier on the plot of oil price volatility (Figure 2). To improve resolution of these larger twitches by reducing noise, 3-month moving averages of the inflation and oil price were calculated (Figure 9), and then the volatility indices for inflation and oil price were re-calculated based on these moving averages. These plots reveal fascinating patterns. Prior to 2000, spiking in the two "smoothed" indices occurs, but it is rather irregular. However, after 2000 the spiked pulses of volatility appear to assume an organization. In particular, 6 distinct pulses in inflation volatility are evident in the period (green arrows on top panel) between 2004 and 2009, the most recent of the 6 occurring ~December 2008, being particularly large. An early seventh uptick in inflation rate instability is also marked on the chart that peaks in 2001-2002. Although a possible harbinger, it is not clear whether this 2001-2002 peak is truly part of the 2004 to 2009 series, as it is not as sharp as the subsequent 6 pulses or primary volatility events. There seems to be regularity to the pulses - and thus a temptation to assume that the sequence is an oscillating wave.

Figure 9 A series of spiked pulses in inflation and oil volatility emerged after yr 2000

Figure 9

Now... if one looks at the "smoothened" oil price volatility index over the period between 2004 and 2009, almost the same pattern is seen (lower panel Figure 9). A distinct series of pulsed spikes (red arrows), each spike being separated by increasingly shorter intervals of time. It should be noted that the words "almost the same" are used in the prior sentence. The reason for this becomes apparent when the plots for the oil and inflation indices are overlaid between 2000 and 2009 (Figure 10). Although the two patterns are very similar, individual "pulse" peaks for inflation and oil price do NOT show precise alignment in time. Instead, in 5 out of 6 of the spikes in the series between 2004 and 2009, a pulse in inflation volatility lags slightly behind a leading pulse in oil price volatility. The exception being the first inflation spike in the sequence occurring at the beginning of 2005, which precedes (albeit by a hair), rather than follows, a pulse in oil price volatility. A further notable feature of the plots is that the amplitude of the volatility spikes, and in particular those of oil, show progressive increase over time.

A coincident bottom is one thing, but agreement at six points ? If this were a crime scene finger print, one would reasonably assume that a match was likely. Moreover, inflation pulses tend to be downstream, from the spikes in oil price volatility. This would be consistent with, although not confirmatory of, oil price variance determining inflation rate variability, and not vice versa. And not to be boring about it, but these curiously well-organized and co-related patterns, spring up ~3 years after 2000, Hubbert's predicted year for peak oil.

Pulse 2 in oil price volatility is interesting. Its initiation toward the end of 2005 corresponds roughly to Hurricane Katrina. Many in the US will remember the sharp rise in oil prices at the time and how conventional wisdom noisily focused on the hurricane as the primary causal factor in the sharp ascent of gas prices. However, the big picture view provided in Figure 9 indicates that the "Katrina-induced" spike in oil price is actually part of a larger pattern of volatility pulses, including one that preceded it by a year and the third pulse in the sequence that followed roughly a year later. As with 2005, 2004 also had an active hurricane season. However, 2006 was comparatively quiet. The point is that while events such as Hurricane Katrina may act as triggers, they are certainly can not be the ultimate cause of , multi-year instabilities of the type illustrated in Figure 9. To believe otherwise would be a classic "missing of the wood for the trees". Or is it trees for the wood ? - never can get that one straight.

A further point regarding future volatility spikes. The triggers for volatility spikes on the downside from Peak-Oil may increasing come not only from familiar past sources of unpredictability such as hurricanes or insurrections in the Niger river delta, but new and as yet unimagined origins. This will occur as the search for new reserves progressively moves to places where the extraction of oil becomes a riskier, tougher and more expensive . One example, of this is in the Middle East. With the decline in Saudi feilds, the US has allocated growing resources to Iraq - a country rich in oil reserves, but possessed of very tricky politics. The growing expansion of deep sea exploration is another example of a new and risky frontier. Iraq and deep under the sea are examples of places that are rich spawning grounds for the type of unexpected event (i.e. triggers) that could lead to rapid swings in the price of oil.

The volatility index developed here is what is called a positive definitive index. It provides a measure of the level of fluctuation in a variable such as monthly oil price, without regard to whether the changes are positive or negative i.e., increase or decrease over time in oil price. The presumption is that our index provides an empirical means of outlining the pattern of unpredictability faced by the financial industry and in turn, a guide to the forces determining their collective behavior. This being said, how does one create a mental or intuitive picture of what is going on. Grasping the underlying concept of volatility is itself unfamiliar territory for most. Imagine a flag gently fluttering in a steady breeze, a single volatility event could be pictured as the flag suddenly being flapped vigorously back and forth by a strong gust of wind. Or how about a running tap plumbed into an artesian well ? When the well head is high, water runs smoothly from the tap. But when the well is running dry, air gets into the water line causing flow to splutter and choke.

How about a mental model of the correlation in time between the behavior of variance in oil price and inflation ? One analogy could be the relationship between bioelectricity and the heart beat. The heart beat literally results from a traveling electrical impulse (think oil volatility spike) that triggers a reactive twitch in the muscle of the heart (think inflation rate spike ). Taking the analogy a little deeper, the electrical impulse originates from instabilities (i.e., volatility) in the bioelectrical properties of the heart's pacemaking cells which coalesce at regular intervals to form the impulse. Astute readers will be thinking, but the heart beat is regular. Well, yes it is - except just before a heart attack. The pattern of variance shown in Figure 9 has a scary resemblance to an electrogram trace of a beating heart becoming chaotic and entering ventricular fibrillation !

Figure 10 Volatility spikes in oil price precede pulses of volatility in inflation

Figure 10

The findings so far are gratifying in the sense that a case can now be made from the data that the pattern of volatility in general pricing (as reflected by the shadow inflation (CPI-U) volatility plots) is plausibly downstream from oil price volatility, at least since peak oil. However, there are caveats that must be born in mind. First, close and convenient correlations in the timing and shape of the two patterns of variance is not proof of causality. Second, by accepting the shadow statistics inflation over those of the Government, multiple errors are possible. For example, the mistake of confirming one's own preconceived ideas has to be watched for. When building a story from a tableau of similar, but subtly differing facts it is all to easy to assume that the data variant that best seems to fit the narrative is the data that must be right.

In conclusion, it is cautiously proposed that there is evidence of a correlative link between volatility in the price of goods and services, as reflected in the shadow CPI-U, that coincides with increasing volatility in the price of oil from year 2000. The strongest support for this link comes from a distinct and unprecedented series of pulses in oil price instability that occurs over the period between 2004 and 2009. Each pulse in this series is matched by a coincident or downstream twitch in volatility in the inflation rate

PROPOSITION 3. Increasing Volatility in the Price of Oil Is Causing Increased Investment Risk

Deriving an accurate measure of investment risk is hard. How does one get at such an intangible ? Certainly not in real time or in the future - otherwise one would be wealthy. To look back at how investment risk may have varied over the last decade or so a leaf was taken from the preceding sections. It seems silly to say it, but first let's accept that stock markets reflect investment activity. One of the broadest and deepest stock indices is the US S&P 500. A measure of risk of investment risk based on the S&P 500 would be its volatility over time. Certain readers are now thinking. There he goes again - on and on about volatility. To a hammer, everything looks like a nail (such an irksome cliche) and so on. But stick with it, if you can.

Imagine that the S&P had been on a gently rising trend with very few ups and downs over an extended period of months. With such a pattern in place, most investors could safely bet that tomorrow the index would still be on this same unwavering trend. In this environment the day-to-day risk of investment, if a number could put on it, would assumed to be low . By contrast, if there were a great deal of turbulence in the S&P 500, then one would be much less certain that an investment made today would look wise tomorrow. This would be a high risk environment, a situation that unfortunately reflects the current reality of the S&P 500. Since October 2008 the S&P 500 has been in enormous flux, building and melting over time intervals of weeks and months. Any reader who transferred 401k monies away from stock-based mutuals in October 2008 and returned in December 2008/January 2009 only to be battered again in February 2009 appreciates the unique perils of an unpredictable market .

Figure 11 Volatility spikes in oil price generally precede pulses of volatility in the S&P 500

Figure 11

Figure 11 is a co-plot of the "smoothened" volatility of the S&P 500 stock index (calculated as for inflation and oil in Figure 9) and oil price volatility over the period from 2000 to the present. It has to be said that the correlation in the peaks of volatility is not as nice as that seen between oil price and inflation volatility over the same period (e.g., Figure 10). Between 2000 and 2004, there is turbulent "froth" in the S&P that presumably corresponds to the recession in the aftermath of the tech boom of the late 1990s. However, between the all important 2004 and 2009 period, the same general pattern observed previously applies. There are coincident spikes in volatility in the S&P 500 (blue) and oil price (red) between 2004 and 2009, with pulses in the oil-based index generally leading surges of volatility in the stock index. There are exceptions. A spike in the S&P occurs between pulses 3 and 4 that appears to have no matching spike in oil price change (indicated by a question mark on Figure 11). Perhaps there is an abortive uptick at the base of the "question-marked" spike. Also, pulse 5 in the S&P is more a shoulder on pulse 6, than a distinct spike in its own right. So, on the basis of Figure 11, squinting a little and using one's imagination - you may convince yourself that the idea has not quite fallen apart.

An analysis of the subsequent Figure (12) provides a more persuasive case for a tie between the rate of oil price change and investment risk. This plot shows the "smoothened" volatility of the price of gold (as measured from Historical gold price USD ) over the period from 2000 to 2009 (gold line). The gold index is co-plotted with the trusty, jagged plot of "smoothened" oil price volatility (red line). Gold is an interesting commodity. In days gone by it provided the foundation of the means of exchange i.e., it was regarded as money. Gold may well return to this status. However, for the moment, and over the last 60 or so years, evidence is strong that oil supplanted gold as the primary guarantor of value around the world. Many professional economists point to the Bretton Woods conference or President Nixon, as fixed events or personalities that occasioned the decoupling of gold and paper currency. However, it seems that such these were may have been mere "anchor" events that acknowledged a changing reality where oil had supplanted gold as the new king. King oil may be spluttering and dying, but king it remains.

The above being said, reading the economic literature, one comes across charts of the inflation-adjusted price of gold which suggest that over the last 150 to 200 years gold has continued to hold its value. By contrast, owing to the acidic affects of inflation, a dollar in 2009 retains only a tiny fraction of its purchasing power to a dollar spent at the turn of the 20th century. For this reason gold is treated as a safe haven by investors wishing to protect against inflation. For example, financial advice websites are presently full of exhortations by various "experts" to buy gold as a hedge against the inflationary and potentially dollar-debasing policies of the Bush and Obama administrations. The perception that gold acts as a store of value confers an interesting property on fluctuations in its price. The vigorousness of its movements up and down reveal the sentiment of people of means who are able to buy gold to offset investment risk. In other words, volatility in the price gold provides an index of how safe or risky sophisticated investors judge the investment environment to be - a measure of the level of uncertainty perceived by investors.

Figure 12 Volatility spikes in oil price precede pulses of volatility in gold

Figure 12

As with oil price volatility, fluctuations in the price of gold show a general rising trend over the period between 2000 and the present. Looking at the detailed geometry of the ups and downs within this trend, it can be seen that Pulse 1 in oil price volatility is matched by a downstream peak in the gold index. What comes next is a shocker. BANG ! Pulse 2 in oil price volatility (the Hurricane Katrina pulse) appears to ignite a huge surge in gold price variance. Its almost as if the pulse 1 was a warning shot and then a second confirmatory slug of oil price turbulence convinces a bunch of savvy investors to run for cover - big time. Pulse 3 in oil occurs and there follows a modest surge in gold price variance. Then the more dramatic pattern repeats. With the rise of pulse 4 in oil volatility, there is second a dramatic and sharp run up in variance associated with gold price. This huge spike in the gold index coincides with the first swallows (vultures ?) of the credit crisis: Bear Stearns collapse, Bernanke assuring us that the sub-prime market is contained and so on. The cycling pulses in oil price volatility 5 and 6 follow, with all too predictable downstream spikes in gold volatility.

The patterns in Figure 12 are astonishing. Volatility in the price of oil genuinely appears to be leading investor sentiment - each pulse heralding large changes in fluidity in the gold market. Again, it must be reiterated that it can not be concluded that actual investment risk is rising based on Figure 12. This gets back to the "through a glass darkly" problem in measuring investment risk in real time alluded to at the opening of proposition 3. But what we can say is that the type of people with resources and knowledge to "play" the precious metal markets, "the gold bugs", are certainly acting as if they believe that investment risk has risen over the last 5 years. It should also be noted that if one eyeballs the area under the curve of the gold plot, around 50 % of total activity occurred prior to early 2007. This strongly suggests that there was a cohort of smart people who were expecting BIG TROUBLE long before the rest of us had ever heard of a credit default swap or indeed AIG. This needs to be reflected on for those who hold the position that continues to be promulgated by our nearly useless news media that, "No one saw this coming".... or (Imagine comely female news anchor) "Nouriel Roubini. You are one of the few people that predicted this...blah..blah...blah". Well, the gold data suggests that a whole bunch of savvy people anticipated what was coming and many of these individuals are probably now doing very nicely, thank you.

Figure 13 Volatility of gold, the S&P 500, inflation and oil are on upward trends

Figure 13

The data analysis section initially focused on comparison of volatility regression trends. However, as we have gotten deeper in, the multi-pulse pattern in oil price volatility and downstream fluctuations in gold, inflation and the S&P 500 have taken precedent. The theory, as we elaborate in the paragraphs above, is that the pulses or spikes provide reference markers in time, that enables interpretation of relationships between different variables in greater temporal detail. For example, pairwise analysis of the "smoothened" volatility plot for oil indicates 6 pulses of variance between 2004 and 2009. Each pulse in the oil plot stands as a staging post for a subsequent unitary spike of heightened fluidity in inflation rate, the S&P 500 stock index and gold price.

The trend analysis nonetheless remains a valuable tool. Figure 13 plots regression lines for the trends in volatility of oil, gold, the S&P and inflation indices between 2000 and 2009. The Y axis values for each variable was normalized (highest measurement to 1) to enable plotting on the same graph. The most striking and obvious feature that can be drawn from Figure 13 is that volatility in all 4 indices display exponentially rising trends. The non-linear trend in "honest" inflation rate bottoms coincidently, or perhaps even a little after that of oil (as indicated previously). In turn, the S&P 500 demonstrates a recent nadir that occurs subsequent to both inflation and oil price volatility.

So far, so good. The trend data for oil, inflation and stock prices concur with the hypothetical sequence. The exception is the gold volatility index. The regression trend for variance in gold price genuinely seems to bottom out around yr 2001, a time preceding the other 3 indices, including oil. However, to reiterate, the "pulse" analysis governs. When volatility is examined at higher resolution (e.g., as in Figure 12), it is seen unequivocally that over the last 5 years individual pulses in oil price fluctuation precede those of gold.

One interpretation of what is going on here harks back to the special status of gold as a safe haven. The early rise in fluidity of the gold market after yr 2000 perhaps reflects the anticipation of the coming age of turbulence by a number of keyed-in individuals. It suggests the existence of prescient actors who despite the Himalayan up and downs of the gold market and the existence of manifold lucrative and less risky opportunities for investment elsewhere (at least prior to 2007), were systematically hedging wealth with gold in increasing amounts. A second consideration is the destablizing or shock effect of large transient variances in key economic per se. The central role of volatility spikes or variance transients to the unfolding events will be examined further in the following section of this essay.

A final word and a return to caveats associated with estimating investment risk. The most damnable thing is that the further into the future one goes, the less accurate the estimate of risk becomes. Anyone who has ever extrapolated a regression trend understands how error bounds bloom the longer the line goes into uncharted territory. Its not only a vexing problem for this analysis, but also generates a paradox that unsettles the advise given by "investment advisors". Namely that such-and-such an investment is good for the long-term. Putting aside well-meaning,self-serving, or just plain dumb "professional advice", the testimony of real-word experience is clear The further one goes into the future, the likelihood that something completely unexpected will wipe out a specific investment increases. Indeed, over long enough time frames (e.g. generations) it becomes almost certain that most individual investments will go to zero value.

A limitation of the approach used so far in proposition 3 is that it is restricted to estimates of short-term variation over monthly sequences. Obviously, it may help the robustness of the analysis that the S&P is comprised of many opportunities rather, than a single investment. However, if there is one thing that the financial crisis has taught us, the assumed protections of portfolio diversity can rapidly evaporate when nearly everything starts moving in the same direction i.e., precipitously down. One approach that may be worth exploring is to use the historical data to generate what is imagined as 3D surface of risk volatility trends between investments separated by varying lengths of time ... but, exploring the alchemy of risk topology will be for another day.

In summary, evidence is provided for a correlative link between volatility in the price oil and two indices of investment risk. Fluctuations in the S&P 500 stock index and the price of gold. Again, six pulses in oil price instability are seen to be matched by unitary twitches of volatility in the stock index and gold price over period between 2004 and 2009. The detailed correspondence between the oil and gold indices is particularly striking. It is concluded the environment for investment over the last 5 to 9 years has been marked by risk that is increasing in a non-linear, perhaps even exponential manner.

PROPOSITION 4. Information in Place Prior to the Crisis Enabled Anticipation that Oil Volatility would Increase Investment Risk.

When Black Monday Came

Occam's Razor - Of several acceptable explanations for a phenomenon, the simplest is preferable.

Figure 12 provides evidence that massive hedging in gold was occurring in waves prior to the onset of the financial crisis in spite of the short-term unpredictability of gold as an investment. One reason for this paradoxical phenomenon is that gold is a barometer of perceived investment risk. Proposition 4 examines how it came to be understood that oil volatility was adding unprecedented levels of uncertainty to investment outcomes through the 2000s - as reflected in indices such as the price of gold. Here, the question posed is ...whether specific information was available that could have led to a change in incentive within the financial industry from protecting shareholders to unregulated "cashing out" ?

Exhibit A in Proposition 4 is Figure 14. It may take a while to study and verify this complex chart. However, once you have familiarized yourself with its implications, your view of how economic events in the modern world are shaped may be changed - perhaps not in a happy way. In a nutshell Figure 14 shows that unitary spikes in volatility of the price of oil have occurred immediately downstream to almost all US recessions and stock market crashes since 1966.

Put aside for a moment the explanations trotted out by experts on the vagaries and fortunes of the US economy -- sub-prime, the Fed, interests rates, the business cycle etc etc etc. Figure 14 teaches the single factor common to virtually every US recession and market crash for nearly half a century is that each has been preceded by a prominent transient spike of instability in the price of oil. The one exception with no preceding variance pulse is the shortest recession of this period, which occurred in 2001 in the wake of the so-called bubble in technology stocks. There is debate as to whether dot com actually met the formal definition of a recession, as it did not comprise 2 successive quarters of negative GDP growth. Semantics aside, it is notable that a volatility spike was coincident with this recession, so the 2001 downturn might be considered as not inconsistent with the general pattern brought to light in figure 14.

Figure 14 - Geopolitical and Economic History of Oil Price Volatility

Figure 14

Looking at Figure 14 in detail, the now familiar recent 6-7 volatility spikes of 2000 to 2008 can be seen at the far right of the plot. Each of these transients in price variance are asterisked and referred to as "primary volatility spikes" on the plot. A new, more recent pulse can be observed to be building in 2009. While this upstroke shows signs of flattening, it has already risen to the point where it is currently the 5th largest spike in oil volatility of the last 50 years.

The left hand of Figure 14 covering the period between 1966 and 1980 provides new food for thought. Against the background of the turbulence of the last 10 years the volatility transients (again asterisked) in this era are almost imperceptible. However, by expanding the Y axis (right hand inset Figure 14) we can see the definite nubs of variance that coincide with the oil shocks of the early 1970s. And these are indeed primary volatility spikes in the context of their era, as they rise above a background which maintained at near-zero levels until ~1980.

It should be noted that the oil markets were heavily regulated by commercial and government interests during this period. Hence, although squelched, volatility appeared to squeak out in spurts when it could no longer be constrained. All the same, two official recessions and a stock market crash can be recognized proximal to and downstream of notable volatility spikes between 1966 and 1979.

The period between 1980 and the early 1990s is fascinating. Within this time, frame three recessions and one stock market crash occurred. Again the "one on one" and upstream relationship of primary volatility spikes to economic events is maintained. Perhaps the most interesting event of this period is the stock market crash known as "Black Monday". The crash that began on Tuesday the 19th of October 1987 appeared to come out of nowhere, occurring during a period of steady gains in growth in the US economy. While "Black Monday" remains the greatest single-day loss that Wall Street has ever experienced, no convincing answer to what caused it has ever been forthcoming. There are speculations on the role of computer trading, herd behavior by market players and derivatives.

In the historical perspective provided by Figure 14 it can be seen that an overlooked factor is a large oil volatility transient that peaked shortly prior to this market crash. This spike was caused by a failure of OPEC to stabilize prices owing to "cheating" by cartel members on production quotas. The honorable Saudi's tired of their role as a production "buffer" to counter misbehavior by OPEC siblings and temporary chaos (and hence volatility) ensued in the oil markets.

"Black Monday" may turn out to be one of the most significant lessons in the dark arts of the markets ever. It came as if a meteor in a time before telescopes or knowledge of heavenly bodies. Its singularity and inexplicably is just the "exception that proves the rule" that good scientists are always on the look out for. The unexpectedness of this stock market crash spared it a tidy accounting by the press and the mendacities of conventional wisdom. In the context provided by Figure 14, that "Black Monday" was the immediate downstream product of an unusually large spike in oil volatility now becomes a totally reasonable proposition. Indeed, it may be the only explanation that makes any sense. A precipitous induction of investment risk by an oil variance pulse in the absence of an economic downtown. In other words, OPEC gave us an experiment on the effects of a primary volatility spike controlled for the confounding influence of declines in US quarterly GDP (US quarterly GDP).Sweet. No need to invoke the God's of randomness to explain "Black Monday" then - ergo Occam's razor.

It is speculated that inquiring minds watching the events that unfolded over 20 years ago on October 19th 1987 may have become early adopters of the conclusions regarding transient instablities in oil price and investment risk outlined in this essay. The insights provided by the oil shock's of 1970s probably laid out the principle for anyone awake and motivated enough to recognize the pattern. Similarly, oil volatility pulses at the beginning of the 1980s and the 1990s provided further confirmation of the correlation. But in these latter cases, one could still have argued that the poor investment environment resulted from the economy being in bad shape. But "Black Monday" sealed the deal, by showing that a primary spike in oil price variance was sufficient, in it own right, to inject uncertainty into investment markets, even during a period of steady growth in GDP. Students of "Black Monday" likely now hold some of the most senior and influential positions in the Global Financial Industry.

Here another curious thing. The arrow hanging over "Black Monday" on the chart proper is actually an error. It got accidentally left there whilst Figure 14 was being prepared in Photoshop. But I'm going to leave the "hanging" arrow there as in the "The Omen". You know...there were those creepy blurred lines that hovered over pictures taken of the doomed priest.

Figure 15 - Primary Oil Price Volatility Spikes 1966-2009

Figure 15

In the penultimate step of the data section of this essay, an attempt will be made to "drag the beast" into the "light of day" as fully as possible. The root cause of our economic woes is postulated as to what the essay now refers to as primary volatility spikes - large, transient variances in the price of oil. It is suggested that primary volatility spikes can be thought of as a class of discontinuous phenomena in their own right within the broader category of volatility. The focus here is on oil, but as has already demonstrated, other economic variables (e.g., inflation) over the last 6-7 years have also displayed similar discrete spikes.

The ability of large variance transients in oil price to cause economic shock appears to some extent to be dependent on the era in which they occurred. For example, relative to those of the last decade, the absolute magnitude of spikes in the early 1970s were small (e.g., inset Figure 14) - nonetheless the dire economic ramifications of these shocks are all too well remembered by anyone over the age of 45. In the following paragraphs, a simple arithmetic device will be used to provide a visual representation of the relative impact and frequency of primary volatility spikes over the last half century.

The top panel of Figure 15 again shows the plot of oil price volatility (darker red line) from 1966 through to 2009, though this time with a 60-month moving average (thick pink line) co-plotted on the same axes. This pink line provides the mean level of volatility within rolling 5 year time frames as a backdrop to appreciate individual peaks in oil price variance against. We can take this a step further, by expressing each time point along the darker red line as a function of the moving average at that same time. This is called normalization and a plot of normalized volatility can be seen in the lower panel of Figure 15.

"Normalization" brings into the "light of day" some 30 primary volatility spikes. For the first time we now are able to gain a sense of the magnitude and unitary nature of spikes in oil price variance from era to era - albeit imperfectly. The spikes within the 43 year time span are clustered into 5 groups (Figure 15). The first cluster of spikes is in the early 1970s, corresponding to the period in which US "Peak oil" occurred, the second, third and fourth clusters are centered on the 1986 "Black Monday" spike and the fifth is the largest and most recent group that has been the main focus of this essay.

One surprise outcome of "normalization" is that it provides evidence that the latest (i.e.,fifth) cluster of instability in oil pricing may have initiated in the mid 1990s, rather than in the early 2000s as was indicated from earlier charts in this essay. If this earlier onset is the case, it has interesting implications. For example, if the new pattern of volatility seen in cluster 5 is diagnostic of the aftermath of Hubbert's peak, then it could infer that the worldwide crest in oil production occurred prior to 2004.

The actual timing of Hubbert's peak will only be settled by a future economic historian with retrospective data in hand. All the same, if one were hedging bets, a safe-ish guess is that "Peak oil" probably got under way sometime between 1997 and 2007. It would certainly have been a remarkable piece of prognostication if Dr Hubbert turns out to have hit the mark both times in in his 1956 prediction that 1970 and turn of the millenium would correspond to when the US and world reached their respective maxima in crude oil production.

Figure 16 - Primary Oil Price Volatility Spikes and Gold Price Movements 1966-2009

Figure 16

Figure 16 returns us to the theme of this essay. Namely, the effect of volatility in the price of oil on investment risk. Gold was fingered earlier on as both a store of value and an extremely sensitive indicator of perceived market risk by sophisticated investors. Figure 16 provides a beautiful illustration of how primary volatility spikes presage and accompany surges in the price of gold. Using this chart it is straightforward to guess which is the "horse" (Theramus suggests the volatility spikes) and which is the "cart" (gold) of the pair. Interestingly, a small upward blip in gold price (yellow arrow, Figure 16) can even be seen to occur toward the end of 1986, prior to the "Black Monday" stock market crash. But consistent with the hypothesis outlined in this essay, this small surge in gold price and the large market crash of the following October, both occurred after the initiation of the 3rd cluster of oil price variance spikes .

Finally, note how the start of the fifth and most recent cluster of volatility in the late 1990s precedes the kick-off of a relentless climb in the value of gold over most of the 2000s. If you're curious about what happened to money lost during the financial crisis, then one perhaps does not have to look too much further than this veritable mountain of gold with its foothills nestling in the year 2000. If you wish to recover the money back from your dropping house value or evaporating 401k plan, one place to turn your attention too would be the vast amount of wealth that has been accumulated in gold over the last 5 or so years by certain individuals. Good luck with that, by the way : >)

In summary, based on the data of this and preceding sections, the concept of a "primary volatility spike" or "variance transient" is introduced. It is shown that primary volatility spikes in the price of oil show an uncanny proximal and upstream correlation with all major US recessions and stock market crashes since 1966. Of specific interest, the stock market crash of "Black Monday" may have provided a controlled experiment demonstrating that a primary volatility spike was sufficient to cause a major induction in investment risk independent of other factors. Lessons learned over the last 40 years on the effect of oil variance transients on investment risk are suggested to have guided the response of the global financial industry to the present crisis. In particular, this information may have provided the rationale for shifts in incentive that led to:

1) the uncoupling of the interests of the financial industry from the broader economy,

2) the expansion and looting the shadow banking system and

3) the aggregation of wealth by prescient actors in "value stores" such as gold.


About Therramus

Therramus is a neutered Tom. He resides with his family in Charleston, South Carolina.

Tom Therramus is the pen name of Robert Gourdie. .....................................................................IMG 1781 b.jpg.....................................................................


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