A stock operator's thoughts and ideas about market principles
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Economy Student
J.P. Janssen's website.The purpose of the site is to discuss ideas and principles about markets. More |
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Sections Empirical Tests Market Models Cycles Practical Trading Mathematical Psychology Biology Philosophy Personal Development The Importance of ... Poetry Global Warming Complete Archive |
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The Special Sections Relative Sizes Quotes The Domino Effect |
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Recommended Books The Edu. of a Speculator 
Practical Speculation 
The Black Swan 
Fooled by Randomness 
Market Wizards 
Reminis. of a Stock Operator 
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Recommended Websites Daily Speculations Science Daily CIA World Factbook Project Gutenberg LibriVox |
Oct/09/2006
The Cycles in Micro Economics
Based on the article below.
The idea of periodic mass extinctions is from the basic fact that those ignoring risks are better off as long as what they are ignoring don’t happen.
In microeconomics it is stated that competition forces zero economic profits so that
π = TR – TC = 0
TR = TC
where
π = Profits
TR = Total Revenue
TC = Total Cost
The cost
The cost a firm faces can be divided into the real costs RC it faces and insurance costs IC so that if
TC = RC + IC
those ignoring the IC will either make a profit or have a loss depending on whether the costs occurred or not. Whether the expected cost EC was larger than the IC doesn’t matter in retrospect.
Say that there are i uncertain costs c, each happening with a probability pi during a period
EC = ∑cipi
The paradox
Let’s assume perfect competition, but not perfect knowledge.
Divide the otherwise identical firms into two groups, one that sets IC1 = EC, and the second with IC2 < EC.
Competition forces
P = (RC + IC2) / Q
This leaves group one with three choices;
1. Halt production, and face any stand-by costs that may occur
2. Change business or go bankrupt
3. Reduce the IC to the level of IC2
Say each firm has a reserve r it can use before being forced to option 2 or 3.
A group one firm will survive if the negative profit from the n periods of IC1 > IC2 is within the reserves
-πn ≤ r
Group two firms will go bankrupt the period they face an uninsured cost that is greater than the reserve.
c > r
An example
There are two kinds of restaurants. Group one takes hygiene seriously, whereas the kitchens of the second group are something the customers wished they had seen beforehand but should be happy they didn’t see after the meal.
Group two can offer a meal for a price 5, but the first group has to charge 7 to break even. The reason is that group one has to hire more people to keep the cleanliness.
If a person gets sick each dirty restaurant has to pay 1,000 in fines as the investigation afterwards reveals the cheating. The chance for this happening is only 10% during one period though.
Competition forces even the dirty restaurants into zero profit, but the expectancy is negative;
-1,000 * 0.1 = -100
A number one firm has a negative profit -10 each period. A firm with reserves 50 can then survive 5 periods, and its outcome depends on whether the cheating is revealed in the sixth period or not. The probability of surviving is then
p(survive) = 1 - 0.96 = 47%
A lousy comfort is though that a group two firm has a chance of zero for survival in the long run.
Oct/09/2006
Increased Efficiency causes a Domino Effect
An improvement of the model from May 15th 2006
If the market price always was perfect, there would be no incentives to trade. But if no one traded as new information was revealed, the price would be wrong. This is the essence of the Grossman-Stiglitz paradox.
The traders doing the research should get compensated for their work. They’ll expect to receive
(PSell – PBuy)Q / T = L
where
P = Price per unit at time of selling and buying
Q = Number of units traded
T = Time from buying once to buying again
L = Labour cost in period T
Note that this is the expected return, and not what they really make in each round.
This minimum inefficiency L in the market has then three components; (PSell – PBuy), Q and T. Some time goes between the time of buying and selling, and in this period the participants are vulnerable. Every participant has a point where a move in the wrong direction will squeeze him out. This will further be a factor in the wrong direction, and so a domino is possible.
The smaller PSell – PBuy gets, the more likely is such a domino of occurring. This will happen if LT /Q decreases, which will happen when:
* Q increases as the participants accumulate wealth, as if L > their expenses plus the profit they change to other businesses
* T decreases as of the market fluctuating faster, so that the traders can go in and out and in again faster
* L decreases if the traders will receive lower alternative pay
Some reasons why this actually will happen in real life:
* If there is cheating, the cheaters will thrive until they are detected, which may all ready have forced others out of business
* If risk is underestimated, as with the black swan effect, the over optimistic ones will survive until the law of large numbers catches up with them
Generally, one can say that if there is a risk of something negative happening and there is a cost of insuring against it, those who ignore the risk will be better off until it happens.
In the stock market the cost of a trade is the average inefficiency. This causes the cost to be too low, until the domino occurs and the cost will temporarily larger than it would have been without the cheaters or risk ignorers. This is the same for every business where there are risks that can temporarily be ignored.
Examples
* A street has several restaurants. A few of them sell illegally imported meat. No customer can tell this. The cheaters will grow faster, and may sell at prices which force the other restaurants out of business. This will go on until there is a health inspection or customers get sick
* Entrepreneurs ignores earth quake safety
* I guess this can be seen in physiology; the immune system
* Evolution of the species
Graphs
A computer simulation shows how the increased competition from those benefiting from the inefficiencies lead to increased efficiency followed by mass extinction and a new cycle.
The black-greenish area shows the difference between market price and perfect price.
Smoothed out, with two dominos, the inefficiency would be under the blue lines like this:
The probability of a domino occurring is like this:
May/19/2006
Increased Efficiency causes a Domino Effect
This model can maybe explain the huge volatility seen this week. Competition will increase efficiency, but under a certain circumstance those who were increasing the efficiency will actually decrease it:
If the market were efficient there would be no incentives to trade. But if no one traded on the new information the markets would not reflect it and therefore not be efficient. This is the essence of the Grossman-Stiglitz paradox.
I wonder if this can be illustrated by a wave. Let’s first define these letters for use in mathematical formulas:
L – Labour cost
P* – The efficient price which includes all present information
P – The market price
∆P – | P* – P |
Q – Quantum, number of shares
W – Wealth accumulated
n – Number of trades
π – Expected profit (from inefficiency)
t – Time
T – Period on the wave
x – Vulnerability factor
For the informed trader the expected profit should compensate the constant labour costs associated with getting informed.
π = ∆PQ = L
Every time a trade is done the profit is added to the wealth.
W = nπ = n∆PQ
As the traders accumulate more wealth competition will force more efficient markets.
W = PQ = nπ
Q = nπ / P
Since π and P are independent from n and Q, Q will grow as n increases. From π = ∆PQ we see that the price inefficiencies diminish.
A wave illustrating the price inefficiencies can be written as:
P = P* + ∆P * sin(2Pi * t / T)
= P* + π * sin(2Pi * t / T) / Q
= P* + W * sin(2Pi * t / T) / nQ
However, here I have only used the expected profit. P* will most likely change in any direction between the entry and the exit of a trade (T / 4). If the trader can only handle a loss of x∆P, there is no guarantee P* will not change, pushing P as well, while the trader still holds an open position. In such a case the trader who is covering will push the price further away in the wrong direction. If this forces yet another trader to cover, a chain reaction may have started, which can be described as the niche’s x∆P Mass death is the result and only the very strongest ones are left when the cycle starts all over again.
I think this wave can illustrate one specific niche. Mass death in one niche might influence another niche, causing a collapse. The shorter the amplitudes, the more fragile the market is. I believe this also can be used to explain how species die out (genetic variability as the amplitude?), as well as to be used in politics, maybe psychology and also other areas where evolution is present.
Blue line = efficient price P*
Green line = market price P
Red and dark red dots = the vulnerable price x∆P where the domino effect starts
This model will be further developed, and applied to other areas as well. Please do not hesitate to mail me with suggestions.
I have clarified the assumptions:
With the efficient price I mean a theoretical price which reflects all current information. Even a perfectly priced stock will fluctuate as new information occurs. Random walk in other words.
I have assumed that the price (that is actually traded at) most of the time will be different from this. Very simplified a sinus curve is used to illustrate.
Put the sinus curve aside and imagine the market existing of two groups; the ignorant and the informed. The ignorant will, if they are the only participants, push the price in a random walk which is totally independent of the theoretically correct efficient price’s random walk. When the difference is large enough the informed ones will exploit this and correct the price.
The profit I referred to were not the actual profit they will make, but the expected profit. As the informed traders are vulnerable because random news will affect the price between the entry and the exit, even a perfectly informed trader will risk a huge loss. If he is forced to cover, he will not correct the price, but actually push it in the wrong direction. This is extremely dangerous as it may start a domino effect of informed traders being forced out of the market.
The informed trader who can make money during normal times AND survive the domino (corrections, crashes and so on) is the king of the market.
May/26/2006
The Domino Effect in Ecology
During the last two weeks the domino has been seen around the global markets. As always when too much wealth is accumulated, vulnerability increases, and participants will be squeezed out. It is fascinating too see what nature has done in order to reduce this problem in the natural evolution.
Just like competition reduces the inefficiencies in the markets, competition will select the fittest individuals for survival and reproducing in the nature. When the environment changes the definition of the fittest will change as well. Species with low genetic variability will be very vulnerable for changes. The paradox is that survival of the fittest refers to the current environment, which means the individuals the closest to genetic ideal will reproduce, thus reduce the genetic variability.
Mother Nature’s solution to this problem is found in the double set of chromosomes. The evolution of the evolutionary unit has obviously found a double pair of genes to be the best. This enables mutations and other kind of unfit genes to stay around, and is in this sense not very smart. But it’s just the best way of keeping a genetic variability and so avoiding the domino effect.
Some may claim the double set of genes is a mechanism to protect against bad genes (the best of the two is selected), and for the individual sure this is correct. But I think the most adequate is to say the double pairs’ role is to save bad genes. This is because what are bad genes today may be good genes in tomorrow’s environment. Let’s say some 99.99% of the genes will remain bad, but it’s the remaining .01% that makes tigers, bumble bees, and humans today.
The classic survival of the fittest is an extremely slow process which I think involves becoming the most efficient given the current environment, i.e. perfecting an equilibrium where all species are in balance.
When there is not a balance, however, evolution will be extremely fast. It is during this circumstance the “bad” genes get a chance to show they really are good, for example genes for larger brains or opposite thumbs. During a situation of mass death some other characteristics than during normal times will be essential.
If the mass death within one species is so harsh it dies out, the environment will be changed for other species because everything is connected. If this makes other species extinct as well, we will see an ecological domino disaster.
Jun/02/2006
More on the Domino Effect in Ecology
I assume there is an ideal adaptation to the environment and the further a gene is away from this ideal, the less common it will be. A bell curve will be a suitable way of illustrating this. Because of a double set of chromosomes the individuals fit enough to reproduce will hold genes which are not fit. This means fit animals will sporadically give birth to unfit offspring. Although evolution will force a narrower bell curve, loss of genetic variability will increase inbreeding, so a balance is found. This is due to the double chromosomes.
If there is a sudden change in the ideal to the right, some of the previous fit on the left will die and some of the previous unfit will thrive. As the new ideal settles, so will the population and a small, but fast, evolutionary change has taken place.
If there is a large enough change of the ideal to extinct all the fit ones within one generation, the potential fit genes aren’t of much use and the species extents. This will further move the ideal for other species further away and an ecological domino disaster may be the result, like the domino we saw in the markets this May.
“It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is the most adaptable to change.”
Charles Darwin
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