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QuoteActually, price instability fails to reveal supply and demand because the tactic has two key assumptions. First, it assumes that the volume of purchasing of a product is equivalent to the volume of demand for the product. If a grocery store cuts the price of diapers in half, it will sell a ton of diapers in a short period of time but that's not because parents decided they can put their babies on high-fiber diets. Instead, the parents are speculating that the price of diapers will revert and they are increasing their household inventories of diapers in advance of the price increase when the grocer ends the sale. Second, the tactic assumes that genuine producers and users are risk-neutral. If a potential cookie factory owner sees volatile prices for flour, sugar, food oils, etc., then they might decide not to build a new cookie factory because the chance of the volatility accumulating to high ingredient prices (making cookies too expensive) would be too high.Small price excursions do strengthen those exposed to them but only if training matches reality and only if downstream players understand what's happening. If primary participants learn that someone is injecting 1% to 5% flashcrashes as artificial training, they will soon adapt their systems as if a 5.001% event cannot happen. And if secondary participants aren't aware that the primary participants are buffering the volatility (so that secondary players don't see any of the 1%-5% blips), then any shock bigger than 5% will wreck havoc on everyone. I think you are saying two things about volatility. You kind of say twice that within "normal" regime of volatility it gets faded, either by diapers buyers or by "primary participants". Once volatility is "abnormal" something else happens, like some sort of crash. I have no problem with these observations. However, i disagree with your assessment that milk and cookies are not produced when prices for grain and sugar are volatile. Production just requires more reserves, more capital to be sustainable -- higher volatility of inputs leads not just to higher volatility of outputs but also to higher prices for the outputs, milk and cookies. If, however, everyone observes artificially non-volatile prices, production becomes possible with little capital -- that's how these banks pre crisis got to have leverage of 100 to 1. Then any revelation of actual volatility on the downside is "abnormal" and it "wrecks havoc" as those with little capital have to dump everything and depress prices further. Although i didn't read Taleb, i think it's kind of what he is saying.

QuoteOriginally posted by: zerdnaQuoteActually, price instability fails to reveal supply and demand because the tactic has two key assumptions. First, it assumes that the volume of purchasing of a product is equivalent to the volume of demand for the product. If a grocery store cuts the price of diapers in half, it will sell a ton of diapers in a short period of time but that's not because parents decided they can put their babies on high-fiber diets. Instead, the parents are speculating that the price of diapers will revert and they are increasing their household inventories of diapers in advance of the price increase when the grocer ends the sale. Second, the tactic assumes that genuine producers and users are risk-neutral. If a potential cookie factory owner sees volatile prices for flour, sugar, food oils, etc., then they might decide not to build a new cookie factory because the chance of the volatility accumulating to high ingredient prices (making cookies too expensive) would be too high.Small price excursions do strengthen those exposed to them but only if training matches reality and only if downstream players understand what's happening. If primary participants learn that someone is injecting 1% to 5% flashcrashes as artificial training, they will soon adapt their systems as if a 5.001% event cannot happen. And if secondary participants aren't aware that the primary participants are buffering the volatility (so that secondary players don't see any of the 1%-5% blips), then any shock bigger than 5% will wreck havoc on everyone. I think you are saying two things about volatility. You kind of say twice is that within "normal" regime of volatility it gets faded, either by diapers buyers or by "primary participants". Once volatility is "abnormal" something else happens, like some sort of crash. I have no problem with these observations. However, i disagree with your assessment that milk and cookies are not produced when prices for grain and sugar are volatile. Production just requires more reserves, more capital to be sustainable -- higher volatility of inputs leads not just to higher volatility of outputs but also to higher prices for the outputs, milk and cookies. If, however, everyone observes artificially non-volatile prices, production becomes possible with little capital -- that's how these banks pre crisis got to have leverage of 100 to 1. Then any revelation of actual volatility on the downside is "abnormal" and it "wrecks havoc" as those with little capital have to dump everything and depress prices further. Although i didn't read Taleb, i think it's kind of what he is saying.On the short end of the volatility time horizon, the empirical demand elasticity (i.e., the relationship between short-term price fluctuations and short-term retail unit sales volume fluctuations) will be higher than the true value due to speculative activities by customers (e.g., stocking up when prices are low, waiting for discounts when prices are high). For example, if diaper prices decrease (or increase) over the short-term, people buy greater (or fewer) numbers of diapers but don't change their use of diapers by as much as the sales volatility would suggest. This effect seems independent of the scale and shape parameters of the distribution of the volatility: "normal" vs. "abnormal."Volatility certainly affects the viability of large, long-term capital projects. The long-term return on a capacity-adding investment seems extremely sensitivity to the volatility. To a first approximation, the return on investing in new capacity for an elastic good is negatively-linear in the double-integral of the price shocks or the single integral of the price level curve over the investment horizon. The reserves required to avoid bankruptcy are a function of the extrema over the integral of the quarterly profit curve. Worse, not only do high prices for raw materials reduce the profit margins (causing losses in some periods), but those same high prices are likely to suppress demand. For very long-term projects, price volatility contingencies can actually induce irreversible substitution effects (e.g., if the price spikes, customers find other products/processes, and demand does NOT revert to pre-spike levels even if the prices revert to pre-spike levels). Exxon, for example, definitely worries about price volatility when building large petrochemical facilities that cost billions up front and take years or decades to pay-off.

In general, replacing h(x) with N * h(x / N) (p. 165) assumes that the system is Markovian (has no memory - the harm function effect takes place in infinitesimally short time, if you get what I'm trying to say). It is a popular assumption in physics (and other sciences), simplifying mathematical analysis, but it is a good approximation only for systems with a large number of modes/very high entropy. In the context of financial markets it means assuming that the market is fully efficient, which we know to be false. Isn't it a problem?I think that in reality small stresses, occurring quickly in succession in the same place (there's always some memory/nonzero relaxation time/imperfect dissipation in most systems), would have a cumulative effect stronger than N * h(x/N). E.g. a strong wave could break a dam, but small streams erode down whole mountains.