Simulating Hyperinflation for 3650 days.  If private bond holdings are going down and the government is running a big deficit then the central bank has to monetize bonds equal to the deficit plus the decrease in private bond holdings.  We don't show the details of the central bank buying bonds here,
Simulating Hyperinflation for 3650 days.

If private bond holdings are going down and the government is running a big deficit then the central bank has to monetize bonds equal to the deficit plus the decrease in private bond holdings.  We don't show the details of the central bank buying bonds here, just the net results.

See blog at http://howfiatdies.blogspot.com for more on hyperinflation, including a hyperinflation FAQ.
 ​Dieses Modell soll aufzeigen, wie sich ein neues Produkt auf das Kundenverhalten auswirkt. Vorteil von Paketen für z.B. eine Bank ist es, dass die Kunden egal welche Produkte sie haben, immer gleich viel bezahlen und somit die Kosten einfacher Berechnet werden können.  Im Weiteren ist die Administ

​Dieses Modell soll aufzeigen, wie sich ein neues Produkt auf das Kundenverhalten auswirkt. Vorteil von Paketen für z.B. eine Bank ist es, dass die Kunden egal welche Produkte sie haben, immer gleich viel bezahlen und somit die Kosten einfacher Berechnet werden können.

Im Weiteren ist die Administration von einem standarisierten Paket einfacher und günstiger, als die Administration der einzelnen Produkte.

Im Modell kann berechnet werden, wie sich die Attraktivität des Paketes gegenüber den Einzelprodukten (in diesem einfachen Modell nur über den Preis definiert) auf das Wechselverhalten der Kunden auswirkt.

The simulation integrates or sums (INTEG) the Nj population, with a change of Delta N in each generation, starting with an initial value of 5. The equation for DeltaN is a version of  Nj+1 = Nj  + mu (1- Nj / Nmax ) Nj  the maximum population is set to be one million, and the growth rate constant mu
The simulation integrates or sums (INTEG) the Nj population, with a change of Delta N in each generation, starting with an initial value of 5.
The equation for DeltaN is a version of 
Nj+1 = Nj  + mu (1- Nj / Nmax ) Nj
the maximum population is set to be one million, and the growth rate constant mu = 3.
 
Nj: is the “number of items” in our current generation.

Delta Nj: is the “change in number of items” as we go from the present generation into the next generation. This is just the number of items born minus the number of items who have died.

mu: is the growth or birth rate parameter, similar to that in the exponential growth and decay model. However, as we extend our model it will no longer be the actual growth rate, but rather just a constant that tends to control the actual growth rate without being directly proportional to it.

F(Nj) = mu(1‐Nj/Nmax): is our model for the effective “growth rate”, a rate that decreases as the number of items approaches the maximum allowed by external factors such as food supply, disease or predation. (You can think of mu as the growth or birth rate in the absence of population pressure from other items.) We write this rate as F(Nj), which is a mathematical way of saying F is affected by the number of items, i.e., “F is a function of Nj”. It combines both growth and all the various environmental constraints on growth into a single function. This is a good approach to modeling; start with something that works (exponential growth) and then modify it incrementally, while still incorporating the working model.

Nj+1 = Nj + Delta Nj : This is a mathematical way to say, “The new number of items equals the old number of items plus the change in number of items”.

Nj/Nmax: is what fraction a population has reached of the maximum "carrying capacity" allowed by the external environment. We use this fraction to change the overall growth rate of the population. In the real world, as well as in our model, it is possible for a population to be greater than the maximum population (which is usually an average of many years), at least for a short period of time. This means that we can expect fluctuations in which Nj/Nmax is greater than 1.

This equation is a form of what is known as the logistic map or equation. It is a map because it "maps'' the population in one year into the population of the next year. It is "logistic'' in the military sense of supplying a population with its needs. It a nonlinear equation because it contains a term proportional to Nj^2 and not just Nj. The logistic map equation is also an example of discrete mathematics. It is discrete because the time variable j assumes just integer values, and consequently the variables Nj+1 and Nj do not change continuously into each other, as would a function N(t). In addition to the variables Nj and j, the equation also contains the two parameters mu, the growth rate, and Nmax, the maximum population. You can think of these as "constants'' whose values are determined from external sources and remain fixed as one year of items gets mapped into the next year. However, as part of viewing the computer as a laboratory in which to experiment, and as part of the scientific process, you should vary the parameters in order to explore how the model reacts to changes in them.
 ​Dieses Modell soll aufzeigen, wie sich ein neues Produkt auf das Kundenverhalten auswirkt. Vorteil von Paketen für z.B. eine Bank ist es, dass die Kunden egal welche Produkte sie haben, immer gleich viel bezahlen und somit die Kosten einfacher Berechnet werden können.  Im Weiteren ist die Administ

​Dieses Modell soll aufzeigen, wie sich ein neues Produkt auf das Kundenverhalten auswirkt. Vorteil von Paketen für z.B. eine Bank ist es, dass die Kunden egal welche Produkte sie haben, immer gleich viel bezahlen und somit die Kosten einfacher Berechnet werden können.

Im Weiteren ist die Administration von einem standarisierten Paket einfacher und günstiger, als die Administration der einzelnen Produkte.

Im Modell kann berechnet werden, wie sich die Attraktivität des Paketes gegenüber den Einzelprodukten (in diesem einfachen Modell nur über den Preis definiert) auf das Wechselverhalten der Kunden auswirkt.

In this model, we look at "human resource" supply chains and how quickly and unpredictably an organization can enter long periods of being either overstaffed or understaffed.
In this model, we look at "human resource" supply chains and how quickly and unpredictably an organization can enter long periods of being either overstaffed or understaffed.
In this model, we look at "human resource" supply chains and how quickly and unpredictably an organization can enter long periods of being either overstaffed or understaffed.
In this model, we look at "human resource" supply chains and how quickly and unpredictably an organization can enter long periods of being either overstaffed or understaffed.
We are modeling future cash flows in the system consisting of three interacting parties, one of which secures deals between the two others which do not trust each other.
We are modeling future cash flows in the system consisting of three interacting parties, one of which secures deals between the two others which do not trust each other.
Irving Fisher's Debt Deflation Theory from Michael Joffe Fig. 3.4 p54  Ch3 Feedback Economics Book  with Private Credit Inflation boom added to the  bust cycles
Irving Fisher's Debt Deflation Theory from Michael Joffe Fig. 3.4 p54 Ch3 Feedback Economics Book with Private Credit Inflation boom added to the  bust cycles
Simulation compares Bitcoin cloud mining opportunity (hashflare.io) to HODL. The model does not calculate with mining difficulty, pool's efficiency and changes in fees. Using monthly cloud fees as of the end of November 2017.  Used https://www.coinwarz.com/calculators/bitcoin-mining-calculator for m
Simulation compares Bitcoin cloud mining opportunity (hashflare.io) to HODL.
The model does not calculate with mining difficulty, pool's efficiency and changes in fees. Using monthly cloud fees as of the end of November 2017.
Used https://www.coinwarz.com/calculators/bitcoin-mining-calculator for mining calculations.

 *scroll to bottom for user inputs*     FIRE_simulation  v1.0  20200618     A personal finance simulation to predict retirement date.       with some adjustable variables, and some probabilistic variables, you can run a simulation of 500 clones of yourself pre->post FIRE and see how many clones r
*scroll to bottom for user inputs*

FIRE_simulation
v1.0
20200618

A personal finance simulation to predict retirement date. 

with some adjustable variables, and some probabilistic variables, you can run a simulation of 500 clones of yourself pre->post FIRE and see how many clones retire at what years.

Some clones get lucky with the market and eg low child costs -> retire early.
Some clones get bad luck and take a few more years to retire!

can also track a clones assets, income, savings rate over time.

Also can use to stress-test (eg poor market returns), and goal seek (assets go to zero when i die. to retire earlier)

Top right are variables about me.
Top left are market variables.
bottom right are simulant/clone (output) info.

Middle 'folder' represents a clone of me.

some vars arent fixed, rather probabilities eg child costs being unknown, i have normally distributed it (my half of costs) around $12k pa and each clone of me gets a random cost on the dist for the simulation. I will add and update in next version

Sign up to insightmaker, click "clone insight" and build/adjust your own modelling. Or send feedback to phillip.balding@gmail.com


programming notes:
-market return years running consecutively not random.
-future years return FIRE rule
-cap_gains and pay_super flows can now be neg
-intro of super still seems too high, grows too much after 60
-rearrange user input variables

To do:
-get actual historical dividends
-goalseek to die with 0 assets -> minimise retirement age.
-year begin not integer?
-auto interpolation seems good.
-tidy the fucking model map mess
-fix child costs at initial random dist.
Simulating Hyperinflation for 3650 days.  If private bond holdings are going down and the government is running a big deficit then the central bank has to monetize bonds equal to the deficit plus the decrease in private bond holdings.  We don't show the details of the central bank buying bonds here,
Simulating Hyperinflation for 3650 days.

If private bond holdings are going down and the government is running a big deficit then the central bank has to monetize bonds equal to the deficit plus the decrease in private bond holdings.  We don't show the details of the central bank buying bonds here, just the net results.

See blog at http://howfiatdies.blogspot.com for more on hyperinflation, including a hyperinflation FAQ.
Stock-flow consistent model with private debt provided by the financial sector. Growth in model is predicated on Business sector growth in the wage bill which is funded by internal finance if available, while the remainder is financed by credit, i.e., external finance (an exogenous variable in the m
Stock-flow consistent model with private debt provided by the financial sector. Growth in model is predicated on Business sector growth in the wage bill which is funded by internal finance if available, while the remainder is financed by credit, i.e., external finance (an exogenous variable in the model). Business equity is the difference of the Business's current account and business debt (i.e., capital account). Firms are passive in this model--they do not save and pass all revenue, and external financing, to households minus repayments on debt--which is an exogenous variable in the model.
10 months ago
Simple causal loop diagram of a compound interest savings account.
Simple causal loop diagram of a compound interest savings account.
WIP replication of Khalid Saeed's draft paper presented by the Economics chapter of the SD Society in Sept 2019  youtube video
WIP replication of Khalid Saeed's draft paper presented by the Economics chapter of the SD Society in Sept 2019 youtube video
A causal loop diagram illustrating a subset of variables influencing business problems related to the transitioning of the Social Assistance Management System (SAMS) from initial production deployment to steady state.    Inherent in the diagram is a representation of two well-known system dynamics a
A causal loop diagram illustrating a subset of variables influencing business problems related to the transitioning of the Social Assistance Management System (SAMS) from initial production deployment to steady state.

Inherent in the diagram is a representation of two well-known system dynamics archetypes:

  • Shifting the Burden, represented in the interplay between the B1, B2, and R3 loops, and
  • Limits to Success, represented in the interplay between the B1 and R5 loops.
Extremely basic stock-flow diagram of compound interest with table and graph output in interest and savings development per year. Initial deposit, interest rate, yearly deposit and withdrawal can all be modified in Dutch.
Extremely basic stock-flow diagram of compound interest with table and graph output in interest and savings development per year. Initial deposit, interest rate, yearly deposit and withdrawal can all be modified in Dutch.
Nastiňuje vlivy financí a školních výsledků na školáka
Nastiňuje vlivy financí a školních výsledků na školáka
 Důchodová kalkulačka po reformě, pro narozené mezi lety 1972 a 2005   Autor: Viktor Vojtko (www.viktorvojtko.cz)     Verze je zatím určená k testování, průběžně ji aktualizuji a může obsahovat chyby.     Výsledky při základním nastavení představují vizi hnutí Starostové a nezávislí o tom, jak by se
Důchodová kalkulačka po reformě, pro narozené mezi lety 1972 a 2005
Autor: Viktor Vojtko (www.viktorvojtko.cz)

Verze je zatím určená k testování, průběžně ji aktualizuji a může obsahovat chyby.

Výsledky při základním nastavení představují vizi hnutí Starostové a nezávislí o tom, jak by se do budoucna měly generovat příjmy v důchodu. Nejedná se tedy ani o investiční radu ani o garanci skutečných příjmů.
7 months ago
Problemas  de Ratios  de   custos  fixos  diversos  multiprodutos
Problemas  de Ratios  de   custos  fixos  diversos  multiprodutos