What do these have in common? . Why is it that zero inventory levels cannot be accounted for in the money system except by bankruptcy? If economic change is asymmetric, then why to holiday traditions occur on regular intervals?
The invention of finance relies on the relatively fast adaption time of money. Yet there are many economic activities in which inventory changes occur faster than money can adapt. Money has never completely conquered the seasonal output of agriculture. Not has the pricing system eliminated criminal activity.
When inventory goes to zero, the ratio of lot sizes (in QM Theory) determines price. Inventory coherency becomes unstable as we get a zero in the denominator. Seasonal changes in agriculture, the sudden arrival of winter cause periodic events of inventory changes happening faster than money can adapt. During these periods the pricing system fails and the economy reverts to pre-monetary, culturally enforced coherency.
A bankruptcy is priced by arbitrary rule, Christmas is a period of non-monetary giving, as his Halloween a traditional form of non-monetary taking. Herding mammals do have to maintain coherency even in the absence of money.
Saturday, May 30, 2009
Stock market manipulation
As reported in the Baltimore Chronicle and Sentinel. Read at your own risk, basically pointing out the natural monopolies don't go away, they just get government's help in stock manipulation.
HT Zero Hedge
HT Zero Hedge
Queuing transaction rates and the yield curve
Rather than use transaction rates to map to the yield curve, use inter arrival times. The optimization problem is, How can one minimize variance on queue size with the most idle time. So, 30 year term structures are things that happen on 30 year intervals, like building a highway or establishing a family neighborhood.
Sample period is the average inter arrival period, so we convert to sample periods. The question becomes, How many sample frequencies do we need to estimate queue sizes? Well, we are restricted to computing equilibrium moments, then the question becomes, How many sampling frequencies do I need to sample gaussian noise. And the the distribution of sampling frequencies becomes the Fourier transform of that, which is again Gaussian. So, we pick sampling frequencies along the yield curve, which is Gaussian at stability. Use the constant measurement error to limit the dimensionality. Do one of a number of decompositions of NGDP, in time, and pick the top five modes. They should be distributed to minimize inter nodal errors due to measurement uncertainty, which one can check against the actual real yield curves.
In the multi-stage queue model, all distribution chains will adapt to these sampling rates, dividing up production and lot sizes to meet a specific production structure, with capital investment decisions agglomerating about the sample period. So, in the queuing model, introduce lot size, again getting back to price theory as lot size ratios.
So, when a yield curve is steep, there is a tendency for long term capital investments to hold, for a long time; and variations from planned output will be managed by lower lever, shorter term queues. Our curve is steep, whatever we have decided long term can be changed by a double dip recession and restart (asymmetry) ; or it can be made to work.
Sample period is the average inter arrival period, so we convert to sample periods. The question becomes, How many sample frequencies do we need to estimate queue sizes? Well, we are restricted to computing equilibrium moments, then the question becomes, How many sampling frequencies do I need to sample gaussian noise. And the the distribution of sampling frequencies becomes the Fourier transform of that, which is again Gaussian. So, we pick sampling frequencies along the yield curve, which is Gaussian at stability. Use the constant measurement error to limit the dimensionality. Do one of a number of decompositions of NGDP, in time, and pick the top five modes. They should be distributed to minimize inter nodal errors due to measurement uncertainty, which one can check against the actual real yield curves.
In the multi-stage queue model, all distribution chains will adapt to these sampling rates, dividing up production and lot sizes to meet a specific production structure, with capital investment decisions agglomerating about the sample period. So, in the queuing model, introduce lot size, again getting back to price theory as lot size ratios.
So, when a yield curve is steep, there is a tendency for long term capital investments to hold, for a long time; and variations from planned output will be managed by lower lever, shorter term queues. Our curve is steep, whatever we have decided long term can be changed by a double dip recession and restart (asymmetry) ; or it can be made to work.
Money Velocity and government spending
DeLong is at it again, trying to determine the determinants of money velocity.
Money velocity theory ultimately boils down to inventory management and the yield curve measures inventory shortages and gluts at the various term scales. Brad thinks part of our solution is more stimulus. Then Brad believes that, right now, the set of government goods and services are a better balance in terms of inventory management. To the extent that government offers a mix of production to better balance inventory then the higher the multipliers; and visa versa. Increase the government deficit if the inventory chain becomes better managed, decrease the deficit other wise.
Friday, May 29, 2009
Maximize inter arrival times.
makes the bet objective function. Maximize the length of time before I have to go collect inventory. Using that in place of velocity of money for some one of a few equilibrium points. Then the yield curve makes better sense, expecting the longer to shorter estimate how often a transaction needs to take place, on the average, to maintain coherency.
Then, at any given mode of the curve, there is an average lot size and typical queue size, the price ratio between lot sizes for both money and any other good.
If you recall, I work the multi-stage queue model, finite span.
Then, at any given mode of the curve, there is an average lot size and typical queue size, the price ratio between lot sizes for both money and any other good.
If you recall, I work the multi-stage queue model, finite span.
When was the pending recession first observed?
Macro and Other Musings discussed the issue. So I go back to my Universal Economic Calculator and following David Beckworth's argument, I see the spot precisely as March 10, 2006. At that point, there was a rush to buy long term treasuries. The financial market correctly predicted the recession and the subsequent drop in long term rates. Going to my oil charts, (second chart) , I discover that oil at just peaked past $60, setting a new record since 1983. By late 2006, the yield curve was fully inverted.
Niall Ferguson hits back at Paul Krugment for the Econ 101 lecture when Naill pointed out that large deficits would cause inflation expectations.
The correct answer? The recent run up in rates after the Treasury auctions is caused by the financial markets indicating the deficits cannot hold with the severe oil constraint still on the docket. It is the deficit in comparison to the constraint that matters. Financial markets are testing whether the "stimulus" is actually solving the constraint. It is not. The stimulus is trying to solve problems not related to the cause of the recession.
Niall Ferguson hits back at Paul Krugment for the Econ 101 lecture when Naill pointed out that large deficits would cause inflation expectations.
The correct answer? The recent run up in rates after the Treasury auctions is caused by the financial markets indicating the deficits cannot hold with the severe oil constraint still on the docket. It is the deficit in comparison to the constraint that matters. Financial markets are testing whether the "stimulus" is actually solving the constraint. It is not. The stimulus is trying to solve problems not related to the cause of the recession.
Thursday, May 28, 2009
Let them mix, Podcar revisited
Podcars and pedestrians mix, I am convinced. Let the Podcar know how to stop and say excuse me, and the human pedestrian will treat the Podcar with respect.
These Podcars can move as slow as pedestrians, or as fast. Podcars can go up and down a straight line on Broadway, in the middle of pedestrian traffic. Podcars are courteous and safe. They can group and move together like a bus. Podcars hang out in parks, shopping centers, factories, and busy streets.
Some Podcars carry boxes of groceries. Bicyclists should not surprise the Podcar.
These Podcars can move as slow as pedestrians, or as fast. Podcars can go up and down a straight line on Broadway, in the middle of pedestrian traffic. Podcars are courteous and safe. They can group and move together like a bus. Podcars hang out in parks, shopping centers, factories, and busy streets.
Some Podcars carry boxes of groceries. Bicyclists should not surprise the Podcar.
Profits first, financial adjustment second
Free Exchange asks a question, Can output recover before investment does?
The answer, according to Quantum Economics, is yes, output always must give a signal that it meets economies of scale before credit can transmit that information. In a multiple good model, in which money is just one of many goods, then money distribution relies on its ability to react fast with its own inventory adjustments, faster than other of goods. The job of money is to give a coherent account of inventory adjustments in other goods, so it must see them before it reports.
Within observability, most sectors see money adapting as fast, or faster than other goods, but this is the Money Illusion. Generally one systematic goods constraint is much harder than constraints to other inventory systems. The one constrained good reaches a satisfactory solution, and the happy news is transmitted to other goods as fast as finance can adapt.
The answer, according to Quantum Economics, is yes, output always must give a signal that it meets economies of scale before credit can transmit that information. In a multiple good model, in which money is just one of many goods, then money distribution relies on its ability to react fast with its own inventory adjustments, faster than other of goods. The job of money is to give a coherent account of inventory adjustments in other goods, so it must see them before it reports.
Within observability, most sectors see money adapting as fast, or faster than other goods, but this is the Money Illusion. Generally one systematic goods constraint is much harder than constraints to other inventory systems. The one constrained good reaches a satisfactory solution, and the happy news is transmitted to other goods as fast as finance can adapt.
Tyler Cohen asks a question and I answer
In this post he asks:
"But if you can explain to me exactly why oil prices rose as they did during the first part of 2008, despite the slowing global economy"
The answer is that some technology shift allowed important parts of the economy to uses oil more efficiently. There has been some positive productivity shock to the economy.
"But if you can explain to me exactly why oil prices rose as they did during the first part of 2008, despite the slowing global economy"
The answer is that some technology shift allowed important parts of the economy to uses oil more efficiently. There has been some positive productivity shock to the economy.
MV=PQ, modified to fit Quantum Economics
The orrect would be:
For some finite N, which seems to be in the range of 5-7, tyhe the equation becomes.
Vi becomes Transaction rate for equilibrium point i
Qi becomes average lot size for for equilibrium point i
Pis the ratio between Qi for this equilibrium point to the average Q overall.
Then for each i, Vi = PQi
Vi (or Qi)?? would follow the Hamiltonian and be normal, independent; thus the 1/Vi (or Q1??)trace the yield curve of the economy, long term purchases occur less frequently. This part needs some thught, maybe later.
The sum of Vi over all i is the minimum transaction rate required to meet the Hamitonian, and should minimize total measurement error. The end result is a Krugman agglomeration.
But we still can break Qi down to its subcomponents within an equilibrium point and talk about price just for that equilibrium point.
For some finite N, which seems to be in the range of 5-7, tyhe the equation becomes.
Vi becomes Transaction rate for equilibrium point i
Qi becomes average lot size for for equilibrium point i
Pis the ratio between Qi for this equilibrium point to the average Q overall.
Then for each i, Vi = PQi
Vi (or Qi)?? would follow the Hamiltonian and be normal, independent; thus the 1/Vi (or Q1??)trace the yield curve of the economy, long term purchases occur less frequently. This part needs some thught, maybe later.
The sum of Vi over all i is the minimum transaction rate required to meet the Hamitonian, and should minimize total measurement error. The end result is a Krugman agglomeration.
But we still can break Qi down to its subcomponents within an equilibrium point and talk about price just for that equilibrium point.
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