Simulace.info - User contributions [en]

Course materials

2017-01-24T11:06:13Z

Wilv00: /* Materials online */

Please, read the article [[How to write a term paper]] for the hints for writing your semestral paper. '''Make sure''' that your assignment is really writing a course material, not a Wikipedia article! Wikipedia article is to be submitted always and exclusively directly into Wikipedia!

==Materials online==
*[[Monte Carlo method]]
**[[Pseudorandom number generators]]
**[[Randomness tests]]
**[[Probability distributions]]
**[[Variance reduction]]
**[[Monte Carlo method in simulations]]
**[[Interpretation of MC simulation results (Stochastic methods)]]
*[[Discrete event simulation]]
**[[Queueing theory]]
**[[Quality management]]
*[[Game theory]]
**[[Nash equilibrium]]
***[[Mixed strategy]]
**[[One-shot games]]
***[[Normal form]]
***[[Prisoner's dilemma]]
***[[The Chicken Game]]
**[[Repeated games]]
**[[Multistage Games]]
***[[Extensive form]]
**[[Multiplayer games]]
***[[Auctions]]
***[[N-player prisoner's dilemma]]
***[[Multiplayer cooperative games]]
*[[Multi-agent systems]]
**[[Agents]]
***[[Agent reasoning]]
****[[Markov decision process]]
**[[Agent environments|Agentn environments]]
*[[System Dynamics]]
**[[Causal loop diagram]]
**[[Stock and flow diagram]]
**[[Leverage point]]
**[[System Archetypes]]
***[[Tragedy of the commons]]
***[[Growth and Underinvestment]]
***[[Limits to Growth]]

==Required reading==
* Šalamon, T. (2011). [http://www.designofagentbasedmodels.info ''Design of Agent-Based Models : Developing Computer Simulations for a Better Understanding of Social Processes'']. Řepín, Czech Republic: Bruckner Publishing

==Recommended reading==
* Colman, A. M. (1982). ''Game theory and experimental games : the study of strategic interaction''. Oxford, UK: Pergamon
* Sterman, J. (2000). ''Business dynamics : systems thinking and modeling for a complex world''. Boston, Ma.: Irwin/McGraw-Hill
* Wooldridge, M. J. (2002). ''An introduction to multiagent systems''. Chichester, UK: John Wiley & Sons
* Polak, B. (2007) ''Game Theory'' In: Yale University: Open Yale Courses, [http://oyc.yale.edu/economics/econ-159 http://oyc.yale.edu/]

WS 2016/2017

2017-01-24T11:05:32Z

Wilv00: /* Papers */

Semestral papers from winter term 2016/2017. Please, put here links to the pages with your paper. First you need to have your [[Assignments WS 2016/2017|assignment approved]].

==Simulations==

--[[User:Kellistefl|Kellistefl]] ([[User talk:Kellistefl|talk]]) 01:23, 18 December 2016 (CET) [[Poison and Insect Population]]

-- [[User:Xushk00|Xushk00]] ([[User talk:Xushk00|talk]]) 19:29, 15 January 2017 (CET) Kateryna Ushanova [[Optimal schedule of Moscow metro]]

--[[User:Bedn00|Bedn00]] ([[User talk:Bedn00|talk]]) 13:51, 14 January 2017 (CET) Naďa Bednárová [[Phyllotaxis]]

--[[User:Xestj00|Xestj00]] ([[User talk:Xestj00|talk]]) 22:24, 14 January 2017 (CET) [[Predators & Prey]]

--[[User:Robert|Robert B.]] ([[User talk:Robert|talk]]) 09:42, 16 January 2017 (CET) [[Simulation of spreading of sexually transmitted infections]]

--[[User:Hanka|xnaph00]] ([[User talk:Hanka|talk]]) 13:42, 16 January 2017 (CET) [[The strength of tsunami]]

--[[User:xzemj34|xzemj34]] ([[User talk:xzemj34|talk]]) 17:05, 17 January 2017 (CET) [[Bank branch checkout optimalization]]

--[[User:Xvitj27|Xvitj27]] ([[User talk:Xvitj27|talk]]) 18:27, 17 January 2017 (CET)[[D1 Highway Traffic simulation]]

--[[User:Aara00|Aara00]] ([[User talk:Aara00|talk]]) 19:14, 17 January 2017 (CET) [[Spread of Disease]]

--[[User:Xvacf01|Xvacf01]] ([[User talk:Xvacf01|talk]]) 21:53, 17 January 2017 (CET) [[Spreading of a fatal epidemic in a simple society]]

--[[User:Xveds|Xveds]] ([[User talk:Xveds|talk]]) 22:54, 17 January 2017 (CET) [[Efficiency of robotic vacuums at home]]

--[[User:Wilv00|Wilv00]] ([[User talk:Wilv00|talk]]) 16:06, 18 January 2017 (CET) [[Portfolio Simulation]]

== Papers ==

--[[User:Hanka|xnaph00]] ([[User talk:Hanka|talk]]) 15:00, 22 January 2017 (CET) [[Behavioral patterns in data]]

--[[User:Wilv00|Wilv00]] ([[User talk:Wilv00|talk]]) 12:05, 24 January 2017 (CET) [[Conceptual Graphs]]

Course materials

2017-01-24T11:03:40Z

Wilv00: /* Materials online */

Please, read the article [[How to write a term paper]] for the hints for writing your semestral paper. '''Make sure''' that your assignment is really writing a course material, not a Wikipedia article! Wikipedia article is to be submitted always and exclusively directly into Wikipedia!

==Materials online==
*[[Monte Carlo method]]
**[[Pseudorandom number generators]]
**[[Randomness tests]]
**[[Probability distributions]]
**[[Variance reduction]]
**[[Monte Carlo method in simulations]]
**[[Interpretation of MC simulation results (Stochastic methods)]]
*[[Discrete event simulation]]
**[[Queueing theory]]
**[[Quality management]]
*[[Game theory]]
**[[Nash equilibrium]]
***[[Mixed strategy]]
**[[One-shot games]]
***[[Normal form]]
***[[Prisoner's dilemma]]
***[[The Chicken Game]]
**[[Repeated games]]
**[[Multistage Games]]
***[[Extensive form]]
**[[Multiplayer games]]
***[[Auctions]]
***[[N-player prisoner's dilemma]]
***[[Multiplayer cooperative games]]
*[[Multi-agent systems]]
**[[Agents]]
***[[Agent reasoning]]
****[[Markov decision process]]
**[[Agent environments|Agentn environments]]
*[[System Dynamics]]
**[[Causal loop diagram]]
**[[Stock and flow diagram]]
**[[Leverage point]]
**[[System Archetypes]]
***[[Tragedy of the commons]]
***[[Growth and Underinvestment]]
***[[Limits to Growth]]
*[[Conceptual Graphs]]

==Required reading==
* Šalamon, T. (2011). [http://www.designofagentbasedmodels.info ''Design of Agent-Based Models : Developing Computer Simulations for a Better Understanding of Social Processes'']. Řepín, Czech Republic: Bruckner Publishing

==Recommended reading==
* Colman, A. M. (1982). ''Game theory and experimental games : the study of strategic interaction''. Oxford, UK: Pergamon
* Sterman, J. (2000). ''Business dynamics : systems thinking and modeling for a complex world''. Boston, Ma.: Irwin/McGraw-Hill
* Wooldridge, M. J. (2002). ''An introduction to multiagent systems''. Chichester, UK: John Wiley & Sons
* Polak, B. (2007) ''Game Theory'' In: Yale University: Open Yale Courses, [http://oyc.yale.edu/economics/econ-159 http://oyc.yale.edu/]

Conceptual Graphs

2017-01-24T11:02:16Z

Wilv00: Created page with "= Introduction = Conceptual graphs or CG’s are graphical presentations of complex systems of logic. They visualize logic information in a way that is logically precise, huma..."

= Introduction =
Conceptual graphs or CG’s are graphical presentations of complex systems of logic. They visualize logic information in a way that is logically precise, humanly readable, and computationally tractable. They make complex systems and difficult calculations clear and readable while remaining a formal design and its own specific language. They are a combination of philosophical, psychological, mathematical and linguistic theories which makes them especially attractive for all sorts of tasks, which we will talk about later on.

= History =

Conceptual graphs were first introduced by John F. Sowa 1976 and are based on the former known existential graphs of Charles Sanders Peirce and semantic networks used in artificial presentations. Earlier in the 20th century attempts were made for graph based notation. Semantic nets, Dependency graphs and correlational nets are some examples of these graph based notations. The problem with these structures is that they could never fully express full first-order logic. There was always something missing in these structures that could be fully captured with the introduction of the conceptual graphs.

= Basic Definitions =

== Concepts and Relations ==

The most basic definitions in a conceptual graphs are the concepts and relations. The basic structure of a conceptual graph is displayed and following image:

[[File:Image1.png]]

This image tells us 3 things. There are two concepts that are connected through a certain relationship and that relationship should be read in the following way: “The relation of a Concept_1 is a Concept_2”. The reading direction is decided by the arrow. This structure shows us the immediate comfort that a conceptual graph provides. An alternative form of showing could be ‘linear’ text-based. This would look like this:

<tt>[Concept_1] -> (relation) -> [Concept_2].</tt>

This will be read in the same way as the above displayed graph but immediately looks a lot more difficult. The ‘.’ At the end of the above statement signals the end of a particular graph.
Let’s take a look at a concrete example that we will use throughout the entire explanation. It covers the topic requesting funding for new business topics within a fictitious company. Let’s work with the linear forms first. We will put them in concrete graphs later on.

<tt>[Funding_Request] -> (initiator) -> [Employee].</tt>

This reads as follows: “The initiator of a funding request is an employee.”

== Referents ==

The above statement is very broad. Any employee could be the initiator of any funding request. We make the example more particular by adding referents to the concepts. These referents refere to a particularity within the concept. This can be a person or particular instance. For example:

<tt>[Employee: Anna].</tt>

Refers to not just any employee but the employee named Anna. If there are two or more Anna’s within the system we can distinguish them more from one and another by adding a number for example.

<tt>[Employee: Anna#1].</tt>

The referent can be seen as a conformity of the specific concept or type label in which it is placed. For example Anna conforms to the type label of being an Employee. Concepts that don’t have any individual referent are called type labels with a generic referent. For our concrete example we could write the following statement:

<tt>[Employee: Anna#1] -> (initiator) -> [Funding_Request#1553].</tt>

== Hierarchy ==

Within Conceptual graphs type labels or concepts have a certain hierarchy. Linear this is explained in the following way:

<tt>Manager < Employee.</tt>

This means that every manager also an employee is or in other words: Manager is a more specialised type is of the type Employee, Manager is a subtype of Employee and Employee is a supertype of Manager. We could lead this further to the statement that an employee is for example also a person, a person is an animal, an animal is an entity and so on. This will ultimately trace back to the following statement.

<tt>Entity < T.</tt>

Where ‘T’ can be seen as the universal supertype. It has no supertypes and is therefore, by Sowa’s definition the most general type. A concept can have more than one supertypes. This means that it will inherit all the characteristics of these supertypes.

== Projection and combining graphs ==

Using referents and hierarchy can lead to more specialised conceptual graphs. More concepts, types and/or relations can be added. For example within previous example we could say that funding request is the outcome of a company policy. This will lead to following linear statement:

<tt>[Funding_Request] -
(initiator) -> [Employee]
(outcome) <- [Company_Policy]. </tt>

And to following Conceptual graph.

[[File:Image2.png]]

Subtypes can be substituted by supertypes, non-generic referents might be added to the graph…
What we can conclude is that every graph may have a more general graph from which it was derived. We define Projection as looking at a graph and trying to trace back to see if the other graph is a generalisation of it. This is important because once a graph projects into another graph we might have identified a particular pattern within these graphs. Later we will discuss the issue of Inference in Conceptual graphs and go more into detail about the above stated.
Now that we have stated the issue of projection, we can go even further and start combining different graphs. Maximal Join is the defined as the optimal method in which graphs are joined. This achieved when graphs are joined on the maximally extended, or most common, projection. Understanding example explains clearly the process of joining different graphs.

[[File:Image3.png]]
[[File:Image4.png]]

Yet when combining graphs we must be careful. It may lead to some false results. The problem is that any item will be suitable as a referent as long as it is conform the type for which it is used. An example could be that Susan is indeed a manager but works for a different company than P-H Co. (It is nowhere stated in this figure that she has to work for the company). This is where Inference comes in place.

= Inference =

Inference in Conceptual graphs is an important but complicated issue. It is based upon the existential graphs logic of Charles Sanders Pierce. We’ll start explaining Sowa’s thinking through Pierce’s logic.
Suppose 2 graphs, Graph 1 and Graph 2, some outed graphs and suppose following statement about these graphs.

“'''IF''' Graph 1 '''THEN''' Graph 2.”

Which can be read as “If Graph 1 can project into outer graphs, then Graph 2 can be reached.” This means that to reach graph 2 we must first rub out graph 1. In Pierce’s logic following sentence would be written as:

'''Not''' (Graph 1 '''and not''' Graph 2)

And would graphically look like

[[File:Image5.png]]

This visually shows that some graphs might dominate other graphs. To completely define this we say that one graph is dominated by another graph if the dominated graph is ringed by a negative context (a box) whereas the dominating graph is outside of this negative context (box). So to reach Graph 2, Graph 1 must first be deiterated. What this means is that we must find a graph in the outer graphs so that graph 1 projects into this particular graph. This would leave 2 rings around graph 2.

[[File:Image6.png]]

This results in the statement: ‘'''not''' ('''not''' Graph 2).’ This is a double negotiation which free graph 2 so that it can be asserted. Graph 2 can thus be seen as true. What this example show is the first general inference rule. Namely that a true antecedent in an ‘if-then’ rule states that its consequent will always be true. This rule is called the general inference rule of modus ponens.
In the same way we could also prove that if the consequent part (the ‘then’ part) of an ‘if-then’ rule is false then its antecedent will also be false (the ‘if’ part). This rule is called the general inference rule of modus tollens.

To conclude this means that if a graph is false, any of its specialisations will also be false. If “the company P-H Co.” is false, then “employee Anna is working for the company P-H Co.” will logically also be false. To finalise this section we will also discuss the “or” rule. If we consider the statement

Graph 1 '''or''' Graph 2.

This can be written in Pierce’s logic as: '''not''' ('''not''' (Graph 1) '''and not''' (Graph 2))
Or linear and less complex will look like:

<tt>((Graph 1) (Graph2))</tt>

Using the same logic as the above stated “if-then” rules we can say that either Graph 1 or Graph 2 might be true. If Graph 1 is true than Graph 2 will be false. If Graph 2 would be true than Graph 1 will be false. So the statement “Graph 1 or Graph 2” can also be written as “if not Graph 1 then Graph 2”
Let us now demonstrate the use of modus ponens and modus Tollens in our actual example. Following figure states this clearly:

[[File:Image7.png]]
[[File:Image8.png]]

Point (a) shows us the starting outer graphs, graph 1 and graph 2. After specialisation in (b) we can see that graph 1 can be projected in the outer graphs because the first part of the outer graphs is exactly the same as our graph 1. Thus graph 2 can be reached and the double negotiation can be rubbed out (c). What this than shows is that if a person is an experiencer of employment, he is an employee. Or this shows us that if Graph 1 is true, graph 2 is also true in this example.
To demonstrate modus Tollens we can think in the same way is stated above. Hence if Simon is not an Employee (if graph 2 is wrong) than he cannot be an experiencer of work (Graph 1 will be wrong too).
Inference is thus the attempt into reducing the context in which concepts are visually dominating other knowledge elements.

= Applications =

As mentioned before in the introduction, Conceptual graphs can be used and are used to capture knowledge as a regular person understands it. It could be information about humans playing roles in events, knowledge about the functioning within a process or method, as a means of capturing the consequences of an action or as a reasoning about general objects in the real world.
In the original paper by John F. Sowa, Conceptual Graphs were used for displaying information in a database interface. In general they are of key importance in several artificial intelligence applications. The use of models in informatics and artificial intelligence applications are of key importance to clarify the structure of an underlying problem. An architect does not start building a house and realises when it’s finished that the rooms are too small, the orientation is wrong… He starts with a model of the house to start with a basic structure which can be elaborated further and further into complex structures one step at the time. Just like the architect uses a model as a baseline structure, a database designer or in general everyone can use conceptual graphs to clarify how complex real-world problems function.

= Example =

The above stated examples were very simple and abstract and didn’t really fit within a picture of entire real-life problem. They were just used to demonstrate the elegance of Conceptual Graphs.
Underlying example is a simple application of a real-world problem and tries to demonstrate how CG is been used in daily life problems. It’s simple enough to understand it yet practical enough to demonstrate the use of Conceptual Graphs.
The example explains the use of Conceptual graphs into a company policy and comes from the paper “An introduction to Conceptual Graphs” by Simon Polovina. Suppose that a company needs to allocate budgets for funding requests made by their employees. The question now is how can they decide who gets his/her funding first? The company wants to encourage younger employees to make such requests. To support this motion, the company has decided to allocate budgets in the following order: Junior Staff, Senior Staff, Manager and last but not least Director. Understanding conceptual graph explains the seniority relationships within the company.

[[File:Image9.png]]

To be complete we also give the type hierarchy:

<tt>Junior_Employee < Employee
Senior_Employee < Employee
Director < Employee. </tt>

A more general conceptual graph shows us the general applicability of seniority.

[[File:Image10.png]]

Note that this consists of 2 graphs. If graph 1 (above stated statement) and graph 2 (the shorter statement). Using specialisation, maximal join and inference we can project graph 1 of the above standing figure with the outer graphs of the seniority relationships within the company. Let’s write this down in linear form:

<tt>[Junior_Staff: Robyn] -> (senior) -> [Senior_Staff: Simon] -> (senior) -> [Manager: Lucy].</tt>

So we can deiterate graph 1 in this figure. This means that Graph 2 is true. This means that following statement is true:

<tt>[Junior_Staff: Robyn] -> (senior) -> [Manager: Lucy].</tt>

This in turn can be maximally joined with the 3 graph from the original seniority relationships within the company. Which leads to following statement:

<tt>[Junior_Staff: Robyn] -> (senior) -> [Manager: Lucy] -> (senior) -> [Director: Richard].</tt>

In turn this than can be treated in the same way as before (using specialisation, deiteration and double negotiation) to come to the following statement:

<tt>[Junior_Staff: Robyn] -> (senior) -> [Director: Richard].</tt>

Now with this complete knowledge background we can draw a Conceptual graph for the priority of funding looking like this:

[[File:Image11.png]]

Let’s go through this graph: If a funding request is initiated by a more senior employee then that will become a priority request if there is no other request from a less senior employee. To express the simplicity of this example let us question what happens when two persons with the same level of seniority propose a funding request. A new Conceptual graph might reflect on this and for example give priority through a panel of judges, through working days in the company… This way it will come closer to the actual real-world problem it tries to solve.

= Conceptual Graph Interchange Form (CGIF) =

For clarity reasons we have used linear forms to represent the Conceptual graphs in words. For more complex problems, Sowa developed a universal language for expressing problems in CG. This was also base on the research paper of Pierce and is called Conceptual Graph Interchange Form.
Let’s say for example that we want to express following statement: “Max the dog is on the mat.” In CGIF this would look like this:

<tt>[Dog Max] [Sitting *x] [may *y] (agent ?x Max) (location ?x ?y)</tt>

This looks very complex and is difficult to read for someone who is not familiar with the syntax behind these words.

= Sources =

https://en.wikipedia.org/wiki/Conceptual_graph
http://www.jfsowa.com/pubs/cg4cs.pdf
http://www.jfsowa.com/cg/cgexampw.htm
https://wiki.eecs.yorku.ca/course_archive/2011-12/F/6339/_media/conceptual_graph_examples.pdf

File:Image5.png

2017-01-24T10:58:34Z

Wilv00:

File:Image11.png

2017-01-24T10:44:00Z

Wilv00:

File:Image10.png

2017-01-24T10:41:33Z

Wilv00:

File:Image9.png

2017-01-24T10:40:16Z

Wilv00:

File:Image8.png

2017-01-24T10:38:00Z

Wilv00:

File:Image7.png

2017-01-24T10:37:33Z

Wilv00:

File:Image6.png

2017-01-24T10:35:02Z

Wilv00:

File:Image4.png

2017-01-24T10:32:38Z

Wilv00:

File:Image3.png

2017-01-24T10:32:11Z

Wilv00:

File:Image2.png

2017-01-24T10:30:43Z

Wilv00:

File:Image1.png

2017-01-24T10:23:32Z

Wilv00:

WS 2016/2017

2017-01-18T15:06:42Z

Wilv00: /* Simulations */

Portfolio Simulation

2017-01-18T15:04:37Z

Wilv00: Created page with "= Introduction = The financial world is something unpredictable. Many economists have searched for the ideal portfolio structure. Many have searched for an “easy” way to..."

= Introduction =

The financial world is something unpredictable. Many economists have searched for the ideal portfolio structure. Many have searched for an “easy” way to get rick quickly. The truth is that there is no such thing as an easy way to get rich quickly. Prediction of stock growth and estimation of future yield are very complex problems. The goal of this simulation is to take a look into portfolio structures and find an optimal portfolio structure for different kinds of people. This means that there is no real, clear optimal solution. The goal of this simulation is to give the reader a range of solutions. Different portfolio structures will involve more or less risk. Dependent on the readers risk aversion he will find an ideal structure of his/her portfolio.

= Problem definition =

Concrete for this assignment I will make use of the Bel-20 (The Belgian stock market with the 20 largest Belgian companies), Belgian state bonds and deposits in the bank KBC (CSOB in Czech Republic). These will also affect the different risk structures since generally spoken deposits involve no risk of payback and yield and bonds only involve a low risk compared to the risk in stock investment. The stock we will use are AB-InBev (one of the largest beer producers in the world), Colruyt (warehousing company in the Belgian market), KBC-group (Bank, called CSOB in Czech Republic), Solvay (International Chemical Group), Bekaert (steel wire transformation and coatings).

= Method =

The way we will tackle this problem will be through Monte Carlo simulation. This is the ideal tool to model the randomness in the stock market. An easy and sufficient tool for tackling this simulation is excel. The simulation will take place for a 5 year period and take into account that the volatility and yield of a stock might change over this time (boom- and bust-cycle). The only thing we will simplify in this simulation is the change of interest rates over time. We will use a steady interest rate for this 5 year period. For each of the stocks we will calculate the yield and volatility over a 5 year period. We will do the same for the deposits and the government bonds. In the final model we will bring each of the instruments together in a portfolio with different compositions of volatility and yield as a result.

== Deposits ==

Like mentioned before we will use KBC-bank as our bank for deposits for this example. We could use any other bank too because the difference in interest is not that big for the moment. The current interest rate is 0.01%. KBC-bank gives just like any other bank a confidentiality fee if the money on the account was not withdrawn. This fee is 0.1%. This brings the total interest on deposit on 0.11% (0.1+0.01). If we look ahead for a period of 5 years we can conclude that the total yield will be 1.6628% (see excel file). Since the deposits are by definition without any risk of payment, we will assume the volatility as 0,00%.

== Bonds ==

Belgian government bonds over a period of 5 years give a coupon of 4,25%. This means that over a period of 5 years the holder will receive 4,25% on the initially invested amount. After 5 years the initially invested amount of money will be paid back. The risk of non-payment by the Belgian government is very small (volatility = 0.28%) and can almost be assumed zero. For the total yield of bonds we must take into account the time value of money. A formula which includes the time value of money is the “yield to maturity”:

[[File:Formule1.png]]

With
p = Price of the bond [[File:Formule2.png]]

a = nominal value of the bond

t = time variable

n = number of periods

r = yield to maturity

If we calculate r out of this formula we obtain the yield to maturity. For our case the yield to maturity is 3,79%. On secondary markets these bonds are quite unpopular for their short time period and with the current interest rate. We will not look further into this matter since it is not the objective of this simulation.

== Discussion of Stocks ==

The calculation for a 5 yearly yield and volatility is a lot more difficult than for deposits and bonds. These measures are very hard to predict, even for one year in advance. Calculating yield without inside information is impossible. We will make an estimation for each year of the yield and volatility based on historic numbers, information about the company and evolution of their sector and the economy in general. The method most used for this forecast was the method of moving averages. We must be cautious with these predicted numbers. If history told us anything is that in the financial world, no-one can predict the future.
The yield and volatility we will use to in our portfolio will be the average yield and volatility over the last 5 years. To complete this estimation the stock value of each stock was calculated for a period of 5 years using following formula:

St = St-1 + St-1 * (yield + volatility*norm.inv(random;0;1))

We calculated a monthly stock price to see the evolution of the stock. Using Monte Carlo simulation we received a clear estimation of how the stock prices will evolve over the following 5 years.

'''''AB-InBev'''''

ANHEUSER-BUSCH INBEV is one of the biggest beer brewing company in the world. Over the last years they’ve had some difficult time because there was a lot of lobbying about the take-over of/ combination with SABMiller. Because there was doubt about this take-over, shares value dropt the past few years. However, analysts predict a few more difficult years for AB-InBev with low turnovers followed by completion of the entire take-over process and high return with lower volatility. Because of their very dominant position in the beer brewing sector they do on average better than their “colleagues”. And with the take-over of SABMiller completed they will be even stronger. Yet this take-over will only bring profit in the future. On the short term however this will first lead to the drop of profit margins and high interest payments. With all this in mind we made an estimation of future yield and volatility (see excel).

'''''Colruyt'''''

Colruyt is one of Belgians biggest warehousing companies. Their activities are solely in Belgium which makes them completely dependent on the Belgian market. Lately this sector has been very competitive and characterized by mergers and acquisitions. Recently one of Colruyt’s biggest competitors, Delhaize, entered a joint venture with “Ahold Koninklijke” (A Dutch warehousing company that has been broadening its horizon across Europe). Together they now formed “Ahold Delhaize Koninklijke”. The question has been raised how Colruyt will deal with this intense competition. Over the last years Colruyt’s revenues were rising, they opened more stores in the French speaking part of Belgium, jobs were created… Colruyt’s share was blooming. Now Colruyt and many analysts believe that revenues will drop but that Colruyt’s business model still stands a chance against the power house of Ahold Delhaize Koninklijke. They’ve now started with online delivery of groceries and personal shopping of groceries which seems to have received a lot of positive attention with customers. Analysts therefor prospect a steady but smaller yield for the first years followed by a slow decrease in yield for last few years when Ahold Delhaize Koninklijke will have caught up with Colruyt. The estimation of future yield and volatility is made with all this in mind (see excel).

'''''Solvay'''''

Solvay is a Chemistry company located in Antwerp. Because of its location close to the harbour of Antwerp, Solvay has been an International player in the chemistry polymer sector. There dividend per share has been doubled over the last 10 years. However the chemistry sector is characterized by high investments which has led to high interest payback for Solvay. This has also led to high volatility for the share of Solvay. The predictions for the future of Solvay are divided. Many see a steady growth with high volatility. Others think that payback of interest and loans will lead to the absence of payment of dividends. Even more competition from China is increasing and profit margins tend to drop in the future. With all this in mind it’s very hard to calculate what Solvay’s role in the future chemistry market will be. This makes estimation of yield and volatility extremely difficult. (see excel)

'''''KBC Group'''''

KBC group has had some difficult years, as did most other banks due to the banking crisis of 2008. Slowly but steady their stock has been increasing again. They starting to gain important positions all over Europe and are now especially expanding in Central Europe (namely Bulgaria). The predictions for the banking sector are that they’re finally climbing out of the economic crisis. A small growth and positive yield can be expected for the coming years, however volatility will remain high. The estimation is made for the yield and volatility. (see excel)

'''''Bekaert'''''

Bekaert is an international player in the field of steel wire transformation and coating. They are a very unique company within their sector. They’ve established the position of monopolist even. They’ve been evolving positively for the last 10 years and are expected to keep growing at the same rate. The start-ups of factories across China and USA seemed to be having success. Yet the risk of succeeding in this markets is high. The difficulty of entering these markets has been discussed before. This is projected in future yield and volatility (see excel).

=Model=

With the above mentioned calculations and estimations we received following matrix:

[[File:Matrix1.png]]

The goal is now to construct different portfolio structures with these instruments and compare the risk and yield of these different portfolios. The total yield of such a portfolio will be:

[[File:Formule3.png]]

With
Rp = The total yield of the portfolio

Wi = The weight of a certain stock i

Ri = The yield of a certain stock i

The total volatility of a portfolio is a lot more difficult to calculate since we must take into account the correlation between the different instruments. We do this by the help of a variance covariance matrix. In portfolio theory the variance of a portfolio is given by:

[[File:Formule4.png]]

With these two formulas we can calculate the volatility and yield of each portfolio we compose. For each year we make an estimation of the future yield taken into account the projected yield and volatility of a certain portfolio. This by using random numbers in the normal distribution with the mean equal to the projected yield and the variance equal to the projected volatility. This way we receive one possible estimation of the future value of our initially invested amount in projected portfolio. Using Monte Carlo simulation we obtain multiple estimations for our problem through repetition.

= Results and conclusion =

By changing the percentage invested in each of the stocks, bonds or deposits we obtain a different estimation of what the amount will be after 5 years. The user of this program can now combine different kinds of instruments into portfolios to obtain a future projected return, the worst case scenario and the best case scenario for a certain combination of instruments. For example if one was to invest 80% in stock Bekaert and 20% into stock AB-InBev with a current budget of 20.000 euros, he can expect a most likely return around 10000 euro.

[[File:Matrix2.png]]

This way any one can decide how he will invest in stocks, bonds and/or deposits and what the future will hold for him with more certainty.

= Code =

[[File:Map1.xlsx]]

= Sources =

https://www.oblis.be/nl/school/de-waardebepaling-van-een-effect-en-een-financi%C3%ABle-portefeuille-523623
http://www.vergelijkuwvermogensbeheerder.nl/standaarddeviatie-een-essentieel-cijfer-bij-vermogenbeheer
https://aandelenkopen.nl/analyse/volatiliteit/
https://en.wikipedia.org/wiki/Stochastic_volatility
http://www.morningstar.nl/nl/news/32636/volatiliteit-standaarddeviatie-risico-en-sharpe.aspx
http://www.beursduivel.be/Koersen/Aandelen/brussel/bel20.aspx
http://www.diffen.com/difference/Bond_vs_Stock#Bond_Yields_vs._Prices
http://www.tijd.be/beurzen/euronext-brussel/bel20
http://ec.europa.eu/economy_finance/publications/eeip/pdf/ip020_en.pdf

[[User:Wilv00|Wilv00]] ([[User talk:Wilv00|talk]]) 16:01, 18 January 2017 (CET)

File:Formule4.png

2017-01-18T15:00:17Z

Wilv00:

File:Formule3.png

2017-01-18T14:59:54Z

Wilv00:

File:Formule2.png

2017-01-18T14:50:36Z

Wilv00:

File:Formule1.png

2017-01-18T14:46:21Z

Wilv00:

File:Map1.xlsx

2017-01-18T14:40:29Z

Wilv00:

File:Matrix2.png

2017-01-18T14:36:32Z

Wilv00:

File:Matrix1.png

2017-01-18T14:35:02Z

Wilv00: Wilv00 uploaded a new version of File:Matrix1.png

Assignments WS 2016/2017

2016-12-15T08:34:09Z

Wilv00: /* Brownian motion Stock simulation (Willem Van de Velde, wilv00) */

{{DISPLAYTITLE:Assignments WS 2015/2016}}

{{Ambox
| text = <div>
Please, put here your assignments. Do not forget to sign them. You can use <nowiki>~~~~</nowiki> (four tildas) for an automatic signature. Use Show preview in order to check the result before your final sumbition.
</div>
}}

{{Ambox
| text = <div>
Please, strive to formulate your assignment carefully. We expect an adequate effort to formulate the assignment as it is your semestral paper. Do not forget that your main goal is a research paper. It means your simulation model must generate the results that are specific, measurable and verifiable. Think twice how you will develop your model, which entities you will use, draw a model diagram, consider what you will measure. No sooner than when you have a good idea about the model, submit your assignment. And of course, read [[How to deal with the simulation assignment|How to deal with the simulation assignment]].
</div>
}}

{{Ambox
| type = content
| text = <div>
In order to avoid possible confusion, please, check if you have added '''approved''' in bold somewhere in our comment under your submission. If there is no '''approved''', it means the assignment was not approved yet.
</div>
}}

== Brownian motion Stock simulation (Willem Van de Velde, wilv00) ==

The simulation will contain the evolution of a portfolio of stocks. Each stock has a certain drift, volatility and initial market price.
Over time the value of a stock change dependent on a brownian motion and the time. A person wants to invest a certain amount of money in stocks.

The goal of this simulation is to see how the persons initial investment will evolve over time, what portfolio structure would be ideal for the initial investment?

Method: Monte carlo Simulation;
Program: Excel

[[User:Wilv00|Wilv00]] ([[User talk:Wilv00|talk]]) 09:52, 13 December 2016 (CET)

Hello, could you be more specific? How many stocks? what will be the options for the simulation user to setup his own portfolio? how will you implement the periodically returning depressions? I would expect that the portfolio should consist from stocks, bonds and deposits and the user would choose between the split of the portfolio among these three financial instruments, rather than choosing particular stocks (as it is done in reality). What will be the source of the data?

[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 20:48, 13 December 2016 (CET)

I would use the stock market of my home country (Belgium) so the BEL-20. I would do the simulation with the option of selecting a portfolio that consists indeed of bonds, deposits and stocks taking into account with current market intrest from Belgium and returns on these instruments. I would involve 5 different stocks from the BEL-20 and combine these into a portfolio. So the total simulation would involve a part that is invested in bonds, deposits and a portfolio of 5 stocks (i haven't looked which specific stocks i would use). The goal will than be determing which percentage of his initial investment he would have to invest in bonds, stocks and deposists to maximize his return after a certain period of years (taken into account the different risk measures associated with the different portfolio's).

I wasn't thinking about involving periodically returning depressions. This would mean that after a certain period of time I would have to change the volatility and drift of the stocks and the market intrest right?

[[User:Wilv00|Wilv00]] ([[User talk:Wilv00|talk]]) 12:09, 14 December 2016 (CET)

Yes, you have to play with it little bit as the value of the instruments/portfolios changes differently during the depression as you can see for instance in graph [http://www.diffen.com/difference/Bond_vs_Stock here]. These business cycles is what makes the portfolio value prediction so hard, so it is necessary to incorporate them in the simulation. Simulation '''approved'''.

[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 13:43, 14 December 2016 (CET)

Ok, i see. I will incorporate this in the model as well. Thank you.

[[User:Wilv00|Wilv00]] ([[User talk:Wilv00|talk]]) 09:34, 15 December 2016 (CET)

== Simulation proposal (Jakub Esterka, xestj00) ==

Simulation (in NETLOGO) will be set up as a FPS computer game (e.g. Counter Strike) with two teams and set number of players in each team (between 1 and 64). Goal of a simulation will be to find out how much more members can other team have for winning rate to be still 50 % in average. Second goal will be to find out how big advantage randomly selected player has to have for his team to dominate (after 10 games). And the third goal is to find the average rate of domination – how many games is needed for one team to start to dominate the other in every game (team members have almost maximum accuracy of 100).

- Each team can have 1 – 10 players

- Each team begins opposite of each other

- Each player moves randomly and have random accuracy (1-20)

- One player from each team can have an advantage (accuracy of 80)

- When two players from opposite teams meet, they shoot at each other with random accuracy

- If one player shoots the other one, he has its shooting accuracy increased

- When all players from one team die, game resets but players keep their accuracy (except for the first goal)

First goal is obligatory and in this research players will not keep their accuracy. If the simulation will work as planned and it will be possible for players to keep their accuracy, other goals are viable as well.

--[[User:Xestj00|Xestj00]] ([[User talk:Xestj00|talk]]) 18:42, 9 December 2016 (CET)

--- I am not generally very happy about simulations regarding video games and other entirely artificial problems, because a real benefit of such a simulation is more than questionable. But, ok... Moreover, in this case, could we be even sure that the results of the simulation really fit the game? Or in other words, how could we be sure that the parameters mentioned above and the way how you will simulate it matches how Counter Strike works? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:11, 15 December 2016 (CET)

== Software Developers (xvatj00) ==

=== Description ===
There is a small company for software development. The company takes small orders (around 3 months long) for software. The software development process consists of 3 parts - analysis, coding and testing. For each project, there is a set number of analysts, programmers and testers, who work on the given project (and no other) until it’s finished. There are 2 main types of orders - well defined and very generally defined. For well defined orders (30% of all orders), the average time of the process of analysis is shorter than in case of the generally defined order, and requires less analysts. The company knows the average times of all parts of the development as well as the average salaries of the three positions. Each part of the development also has its probability of delay and average delay (in case delay occurs). There are different scenarios in cases of delays.
Alongside specific positions, there are also “ultimate” workers, who work on the project from its beginning until the end - meaning they do all 3 parts of the development themselves. These workers have higher salaries (all are seniors), but take less time to finish the work.
Method: Simprocess

=== Goal of the Simulation ===
The goal is to see, if it’s more convenient to have specialized workers, or to hire “ultimate” workers instead, and to have an overview of the projects’ employee expenses. To reach the goal, the plan is to create 1 simulation which takes into consideration only the process with the positions divided, and a second simulation which shows the process of “ultimate” workers. In both cases, the process will be taking all the incoming orders - there will be only this one type of process.

Jana Vataščinová, [[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 20:29, 10 December 2016 (CET)

- Hi, I am missing the tool you want to use. Moreover, I hesitate a bit, whether such a "soft" process like software development should be analyzed this way. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:15, 15 December 2016 (CET)

- Good evening, I would like to use Simprocess. I was thinking that the information to the process was quite stable, so I chose the topic, because it sounds interesting to me. [[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 01:49, 15 December 2016 (CET)

== Police System (Kateryna Ushanova, xushk00) ==

This simulation will show police system and how this system will impact the crime rate of the city. Criminals will try to destroy the city's infrostructre and to make crime against civilians.
In this simulation I will use three strategies that maybe used to fight crime:

1) applying medium-sized police force

2) a strategy in which a small police force attempt to recruit civilians into the police force

3) the police react on the crime in a brief period of time

The most important factor that influence skill of the police to fight the crime is work experience. The amount of experience is propotional to the cost of fighting crime.

The criminals will be walking randomly around the visual area. During their walking there is a random chance that they will commit a crime. When they do the crime, the civilians around them become victims, and the area they occupy becomes a bad zone. Bad zone make people more likely to turn to crime.
Two main factors influence whether or not civilians will turn to crime:

1)the level of the city (user controls)

2)the simulated factors (the result of the police work; the state of the zone; the effects of random events that the user controls)

'''The goal of this simulation is:
'''

- to see how changing the work experience level effects each strategy.

- to test out different strategies and factors to see how this effects the crime rate.

- to observe possible outcomes by changing techniques and factors in a different ways.

'''Method - NetLogo

Kateryna Ushanova, [[User:Xushk00|Xushk00]] ([[User talk:Xushk00|talk]]) 13:35, 11 December 2016 (CET)

- The idea is not bad, but where are your key parameters for the simulation? How you get them (I mean the exact figures). We always prefer obtaining and working with real numbers. Sometimes, it is not possible, so it is acceptable to use secondary resources, etc. but it should be always clear, why did you use the parameters you used and why, on the other hand [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:23, 15 December 2016 (CET)

== (Poison and Insect Population, Kellianne Stefl) ==

NetLogo simulation of the steady decline in insect population in Germany from 1989 to now, also future predictions. Many other factors contribute but I will use pesticides in my visual representation.

Over the last 25 years, etymologists have set up tents all over German woodlands and meadows to observe natures insects. The average biomass of insects sampled in a 6-month period (May to October) has steadily decreased from 1.6 kilograms (3.5 pounds) (56 ounces) per trap in 1989 to just 300 grams (10.6 ounces) in 2014. 18.9% of the average biomass 25 years ago. This simulation will illuminate the devastating effects of damage to the bottom of the food chain.

-adjustable poison release

Goal:
Predict hypothetical decline of insect population: how many years until there are none left.

[[User:Kellistefl|Kellistefl]] ([[User talk:Kellistefl|talk]]) 12:47, 12 December 2016 (CET)

- Ok, we talk about entomologysts, not etymologysts, don't we? The topic is generally good, I am just not sure how exactly it will look like. Particularly, I am a bit afraid that the simulation would be pretty simple (e.g. I can see just one parameter now). Please, could you elaborate a bit? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:43, 15 December 2016 (CET)

== Phyllotaxis (Nada Bednarova, bedn00) ==

Phyllotaxis is the process of arrangement of leaves on a plant stem. While growing, leaves on a plant/flower/cone usually follow Fibonacci sequences or use golden ratio to form the most convenient angles. There are several theories on where the arrangement comes from.

Simulation in NetLogo would simulate the arrangement of leaves based on different parameters configuration (number and size of the leaves, starting angle etc.). Furthermore chemical or physiological theories about morphogenesis / meristem growth can be simulated (for example Turing's diffusion equations).

--[[User:Bedn00|Bedn00]] ([[User talk:Bedn00|talk]]) 00:07, 15 December 2016 (CET)
: This isn't an agent-based model, however the idea looks interesting, so '''accepted''' [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:45, 15 December 2016 (CET)

Assignments WS 2016/2017

2016-12-14T11:32:36Z

Wilv00: /* Brownian motion Stock simulation (Willem Van de Velde, wilv00) */

{{DISPLAYTITLE:Assignments WS 2015/2016}}

{{Ambox
| text = <div>
Please, put here your assignments. Do not forget to sign them. You can use <nowiki>~~~~</nowiki> (four tildas) for an automatic signature. Use Show preview in order to check the result before your final sumbition.
</div>
}}

{{Ambox
| text = <div>
Please, strive to formulate your assignment carefully. We expect an adequate effort to formulate the assignment as it is your semestral paper. Do not forget that your main goal is a research paper. It means your simulation model must generate the results that are specific, measurable and verifiable. Think twice how you will develop your model, which entities you will use, draw a model diagram, consider what you will measure. No sooner than when you have a good idea about the model, submit your assignment. And of course, read [[How to deal with the simulation assignment|How to deal with the simulation assignment]].
</div>
}}

{{Ambox
| type = content
| text = <div>
In order to avoid possible confusion, please, check if you have added '''approved''' in bold somewhere in our comment under your submission. If there is no '''approved''', it means the assignment was not approved yet.
</div>
}}

== Brownian motion Stock simulation (Willem Van de Velde, wilv00) ==

The simulation will contain the evolution of a portfolio of stocks. Each stock has a certain drift, volatility and initial market price.
Over time the value of a stock change dependent on a brownian motion and the time. A person wants to invest a certain amount of money in stocks.

The goal of this simulation is to see how the persons initial investment will evolve over time, what portfolio structure would be ideal for the initial investment?

Method: Monte carlo Simulation;
Program: Excel

[[User:Wilv00|Wilv00]] ([[User talk:Wilv00|talk]]) 09:52, 13 December 2016 (CET)

Hello, could you be more specific? How many stocks? what will be the options for the simulation user to setup his own portfolio? how will you implement the periodically returning depressions? I would expect that the portfolio should consist from stocks, bonds and deposits and the user would choose between the split of the portfolio among these three financial instruments, rather than choosing particular stocks (as it is done in reality). What will be the source of the data?

[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 20:48, 13 December 2016 (CET)

I would use the stock market of my home country (Belgium) so the BEL-20. I would do the simulation with the option of selecting a portfolio that consists indeed of bonds, deposits and stocks taking into account with current market intrest from Belgium and returns on these instruments. I would involve 5 different stocks from the BEL-20 and combine these into a portfolio. So the total simulation would involve a part that is invested in bonds, deposits and a portfolio of 5 stocks (i haven't looked which specific stocks i would use). The goal will than be determing which percentage of his initial investment he would have to invest in bonds, stocks and deposists to maximize his return after a certain period of years (taken into account the different risk measures associated with the different portfolio's).

I wasn't thinking about involving periodically returning depressions. This would mean that after a certain period of time I would have to change the volatility and drift of the stocks and the market intrest right?

[[User:Wilv00|Wilv00]] ([[User talk:Wilv00|talk]]) 12:09, 14 December 2016 (CET)

== Simulation proposal (Jakub Esterka, xestj00) ==

Simulation (in NETLOGO) will be set up as a FPS computer game (e.g. Counter Strike) with two teams and set number of players in each team (between 1 and 64). Goal of a simulation will be to find out how much more members can other team have for winning rate to be still 50 % in average. Second goal will be to find out how big advantage randomly selected player has to have for his team to dominate (after 10 games). And the third goal is to find the average rate of domination – how many games is needed for one team to start to dominate the other in every game (team members have almost maximum accuracy of 100).

- Each team can have 1 – 10 players

- Each team begins opposite of each other

- Each player moves randomly and have random accuracy (1-20)

- One player from each team can have an advantage (accuracy of 80)

- When two players from opposite teams meet, they shoot at each other with random accuracy

- If one player shoots the other one, he has its shooting accuracy increased

- When all players from one team die, game resets but players keep their accuracy (except for the first goal)

First goal is obligatory and in this research players will not keep their accuracy. If the simulation will work as planned and it will be possible for players to keep their accuracy, other goals are viable as well.

--[[User:Xestj00|Xestj00]] ([[User talk:Xestj00|talk]]) 18:42, 9 December 2016 (CET)

== Software Developers (xvatj00) ==

=== Description ===
There is a small company for software development. The company takes small orders (around 3 months long) for software. The software development process consists of 3 parts - analysis, coding and testing. For each project, there is a set number of analysts, programmers and testers, who work on the given project (and no other) until it’s finished. There are 2 main types of orders - well defined and very generally defined. For well defined orders (30% of all orders), the average time of the process of analysis is shorter than in case of the generally defined order, and requires less analysts. The company knows the average times of all parts of the development as well as the average salaries of the three positions. Each part of the development also has its probability of delay and average delay (in case delay occurs). There are different scenarios in cases of delays.
Alongside specific positions, there are also “ultimate” workers, who work on the project from its beginning until the end - meaning they do all 3 parts of the development themselves. These workers have higher salaries (all are seniors), but take less time to finish the work.
Method: Simprocess

=== Goal of the Simulation ===
The goal is to see, if it’s more convenient to have specialized workers, or to hire “ultimate” workers instead, and to have an overview of the projects’ employee expenses. To reach the goal, the plan is to create 1 simulation which takes into consideration only the process with the positions divided, and a second simulation which shows the process of “ultimate” workers. In both cases, the process will be taking all the incoming orders - there will be only this one type of process.

Jana Vataščinová, [[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 20:29, 10 December 2016 (CET)

== Police System (Kateryna Ushanova, xushk00) ==

This simulation will show police system and how this system will impact the crime rate of the city. Criminals will try to destroy the city's infrostructre and to make crime against civilians.
In this simulation I will use three strategies that maybe used to fight crime:

1) applying medium-sized police force

2) a strategy in which a small police force attempt to recruit civilians into the police force

3) the police react on the crime in a brief period of time

The most important factor that influence skill of the police to fight the crime is work experience. The amount of experience is propotional to the cost of fighting crime.

The criminals will be walking randomly around the visual area. During their walking there is a random chance that they will commit a crime. When they do the crime, the civilians around them become victims, and the area they occupy becomes a bad zone. Bad zone make people more likely to turn to crime.
Two main factors influence whether or not civilians will turn to crime:

1)the level of the city (user controls)

2)the simulated factors (the result of the police work; the state of the zone; the effects of random events that the user controls)

'''The goal of this simulation is:
'''

- to see how changing the work experience level effects each strategy.

- to test out different strategies and factors to see how this effects the crime rate.

- to observe possible outcomes by changing techniques and factors in a different ways.

'''Method - NetLogo

Kateryna Ushanova, [[User:Xushk00|Xushk00]] ([[User talk:Xushk00|talk]]) 13:35, 11 December 2016 (CET)

== (Poison and Insect Population, Kellianne Stefl) ==

NetLogo simulation of the steady decline in insect population in Germany from 1989 to now, also future predictions. Many other factors contribute but I will use pesticides in my visual representation.

Over the last 25 years, etymologists have set up tents all over German woodlands and meadows to observe natures insects. The average biomass of insects sampled in a 6-month period (May to October) has steadily decreased from 1.6 kilograms (3.5 pounds) (56 ounces) per trap in 1989 to just 300 grams (10.6 ounces) in 2014. 18.9% of the average biomass 25 years ago. This simulation will illuminate the devastating effects of damage to the bottom of the food chain.

-adjustable poison release

Goal:
Predict hypothetical decline of insect population: how many years until there are none left.

[[User:Kellistefl|Kellistefl]] ([[User talk:Kellistefl|talk]]) 12:47, 12 December 2016 (CET)

Assignments WS 2016/2017

2016-12-14T11:09:20Z

Wilv00: /* Brownian motion Stock simulation (Willem Van de Velde, wilv00) */

{{DISPLAYTITLE:Assignments WS 2015/2016}}

{{Ambox
| text = <div>
Please, put here your assignments. Do not forget to sign them. You can use <nowiki>~~~~</nowiki> (four tildas) for an automatic signature. Use Show preview in order to check the result before your final sumbition.
</div>
}}

{{Ambox
| text = <div>
Please, strive to formulate your assignment carefully. We expect an adequate effort to formulate the assignment as it is your semestral paper. Do not forget that your main goal is a research paper. It means your simulation model must generate the results that are specific, measurable and verifiable. Think twice how you will develop your model, which entities you will use, draw a model diagram, consider what you will measure. No sooner than when you have a good idea about the model, submit your assignment. And of course, read [[How to deal with the simulation assignment|How to deal with the simulation assignment]].
</div>
}}

{{Ambox
| type = content
| text = <div>
In order to avoid possible confusion, please, check if you have added '''approved''' in bold somewhere in our comment under your submission. If there is no '''approved''', it means the assignment was not approved yet.
</div>
}}

== Brownian motion Stock simulation (Willem Van de Velde, wilv00) ==

The simulation will contain the evolution of a portfolio of stocks. Each stock has a certain drift, volatility and initial market price.
Over time the value of a stock change dependent on a brownian motion and the time. A person wants to invest a certain amount of money in stocks.

The goal of this simulation is to see how the persons initial investment will evolve over time, what portfolio structure would be ideal for the initial investment?

Method: Monte carlo Simulation;
Program: Excel

[[User:Wilv00|Wilv00]] ([[User talk:Wilv00|talk]]) 09:52, 13 December 2016 (CET)

Hello, could you be more specific? How many stocks? what will be the options for the simulation user to setup his own portfolio? how will you implement the periodically returning depressions? I would expect that the portfolio should consist from stocks, bonds and deposits and the user would choose between the split of the portfolio among these three financial instruments, rather than choosing particular stocks (as it is done in reality). What will be the source of the data?

[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 20:48, 13 December 2016 (CET)

I would use the stock market of my home country (Belgium) so the BEL-20. I would do the simulation with the option of selecting a portfolio that consists indeed of bonds, deposits and stocks taking into account with current market intrest from Belgium and returns on these instruments. I would involve 5 different stocks from the BEL-20 and combine these into a portfolio. So the total simulation would involve a part that is invested in bonds, deposits and a portfolio of 5 stocks (i haven't looked which specific stocks i would use). The goal will than be determing which percentage of his initial investment he would have to invest in bonds, stocks and deposists to maximize his return after a certain period of years.

I wasn't thinking about involving periodically returning depressions. This would mean that after a certain period of time I would have to change the volatility and drift of the stocks and the market intrest right?

[[User:Wilv00|Wilv00]] ([[User talk:Wilv00|talk]]) 12:09, 14 December 2016 (CET)

== Simulation proposal (Jakub Esterka, xestj00) ==

Simulation (in NETLOGO) will be set up as a FPS computer game (e.g. Counter Strike) with two teams and set number of players in each team (between 1 and 64). Goal of a simulation will be to find out how much more members can other team have for winning rate to be still 50 % in average. Second goal will be to find out how big advantage randomly selected player has to have for his team to dominate (after 10 games). And the third goal is to find the average rate of domination – how many games is needed for one team to start to dominate the other in every game (team members have almost maximum accuracy of 100).

- Each team can have 1 – 10 players

- Each team begins opposite of each other

- Each player moves randomly and have random accuracy (1-20)

- One player from each team can have an advantage (accuracy of 80)

- When two players from opposite teams meet, they shoot at each other with random accuracy

- If one player shoots the other one, he has its shooting accuracy increased

- When all players from one team die, game resets but players keep their accuracy (except for the first goal)

First goal is obligatory and in this research players will not keep their accuracy. If the simulation will work as planned and it will be possible for players to keep their accuracy, other goals are viable as well.

--[[User:Xestj00|Xestj00]] ([[User talk:Xestj00|talk]]) 18:42, 9 December 2016 (CET)

== Software Developers (xvatj00) ==

=== Description ===
There is a small company for software development. The company takes small orders (around 3 months long) for software. The software development process consists of 3 parts - analysis, coding and testing. For each project, there is a set number of analysts, programmers and testers, who work on the given project (and no other) until it’s finished. There are 2 main types of orders - well defined and very generally defined. For well defined orders (30% of all orders), the average time of the process of analysis is shorter than in case of the generally defined order, and requires less analysts. The company knows the average times of all parts of the development as well as the average salaries of the three positions. Each part of the development also has its probability of delay and average delay (in case delay occurs). There are different scenarios in cases of delays.
Alongside specific positions, there are also “ultimate” workers, who work on the project from its beginning until the end - meaning they do all 3 parts of the development themselves. These workers have higher salaries (all are seniors), but take less time to finish the work.
Method: Simprocess

=== Goal of the Simulation ===
The goal is to see, if it’s more convenient to have specialized workers, or to hire “ultimate” workers instead, and to have an overview of the projects’ employee expenses. To reach the goal, the plan is to create 1 simulation which takes into consideration only the process with the positions divided, and a second simulation which shows the process of “ultimate” workers. In both cases, the process will be taking all the incoming orders - there will be only this one type of process.

Jana Vataščinová, [[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 20:29, 10 December 2016 (CET)

== Police System (Kateryna Ushanova, xushk00) ==

This simulation will show police system and how this system will impact the crime rate of the city. Criminals will try to destroy the city's infrostructre and to make crime against civilians.
In this simulation I will use three strategies that maybe used to fight crime:

1) applying medium-sized police force

2) a strategy in which a small police force attempt to recruit civilians into the police force

3) the police react on the crime in a brief period of time

The most important factor that influence skill of the police to fight the crime is work experience. The amount of experience is propotional to the cost of fighting crime.

The criminals will be walking randomly around the visual area. During their walking there is a random chance that they will commit a crime. When they do the crime, the civilians around them become victims, and the area they occupy becomes a bad zone. Bad zone make people more likely to turn to crime.
Two main factors influence whether or not civilians will turn to crime:

1)the level of the city (user controls)

2)the simulated factors (the result of the police work; the state of the zone; the effects of random events that the user controls)

'''The goal of this simulation is:
'''

- to see how changing the work experience level effects each strategy.

- to test out different strategies and factors to see how this effects the crime rate.

- to observe possible outcomes by changing techniques and factors in a different ways.

'''Method - NetLogo

Kateryna Ushanova, [[User:Xushk00|Xushk00]] ([[User talk:Xushk00|talk]]) 13:35, 11 December 2016 (CET)

== (Poison and Insect Population, Kellianne Stefl) ==

NetLogo simulation of the steady decline in insect population in Germany from 1989 to now, also future predictions. Many other factors contribute but I will use pesticides in my visual representation.

Over the last 25 years, etymologists have set up tents all over German woodlands and meadows to observe natures insects. The average biomass of insects sampled in a 6-month period (May to October) has steadily decreased from 1.6 kilograms (3.5 pounds) (56 ounces) per trap in 1989 to just 300 grams (10.6 ounces) in 2014. 18.9% of the average biomass 25 years ago. This simulation will illuminate the devastating effects of damage to the bottom of the food chain.

-adjustable poison release

Goal:
Predict hypothetical decline of insect population: how many years until there are none left.

[[User:Kellistefl|Kellistefl]] ([[User talk:Kellistefl|talk]]) 12:47, 12 December 2016 (CET)

Assignments WS 2016/2017

2016-12-13T08:52:51Z

Wilv00: