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Assignment 3 - Ryan Salvaggio 43668070

Ryan Salvaggio

Assignment 3 – Complex Systems

 Ryan Salvaggio - 43668070

 

The Model

This model conceptualizes the effects on a real-estate market-model utilizing agent based modelling. This model utilizes basic economic principles of supply and demand.

The model bases itself on two Agents - one being ‘Customers’ of the real estate market model, whilst the other being the Real estate itself, coined 'Houses'.

Consumers (Demand)

The Agent population, ‘Consumers’ specifies the total amount of people whom can potentially become buyers within the market. This is limited to 30 for conceptual purposes. The Agent ‘Consumer’ exists in two states, either being an ‘Active Customer’ (Active) or an ‘Inactive Customer’ (Inactive).  The transition from Inactive to Active occurs upon the basis that the ‘Budget’ of the Consumer meets the desired price of the marketplace, this is specified through the variable ‘Budget’ defining the probability that this transition will occur – this is adjustable by the user indicating a highly resistive or by accepting the market. ‘Budget’s probability in a real life scenario would be based upon numerous factors however conceptually utilizing the slider can present many of these various situations.

Upon transitioning into an active state an ‘Active consumer’ will attempt to find the closest ‘For sale household’, this is represented and carried out through the ‘Enter’ action.  Upon finding a household the consumer and house will both return to their respected inactive state thus repeating the process.

Demand – ‘Count of active customers – demand’ is then calculated by a count of Consumers transitioned and currently in the Active state. A high demand would be indicative through a high ‘Budget’ responsiveness whilst a low demand would be indicative of a low ‘Budget’ responsiveness. The increase in Price and hence supply of household thus reduces demand and vise versa.  

House (Supply)

The Agent population, ‘Houses’ specifies the total amount of households that can potentially become for sale within the market. This is limited to 112 for conceptual purposes. The Agent ‘House’ exists in two states, either being ‘For Sale’ (Active) or ‘Not for Sale’ (Inactive).  The transition from Inactive to Active occurs upon the basis that the ‘Motivation to Sell’ of the House is satisfied, this satisfaction is specified by a set probability that this transition will occur – this is adjustable by the user indicating a highly responsive or restricted house market. ‘Motivation to sell’ probability in a real life scenario would be based upon numerous factors however conceptually utilizing the slider can present many of these various situations.

Upon transitioning into an active state a ‘For Sale’ house will wait for an ‘Active Customer’ ‘this is represented and carried out through the ‘Search’ action. Upon completion of the action both states become inactive and the process continues.

Supply – ‘Count of houses for sale –supply’ is then calculated by a count of Houses ‘For Sale’ that are currently in the active state. Ultimately a high Motivation to sell would sharply increase supply, whilst a low motivation would have the adverse effects.  

Movement Speed

Movement speed – describes the base movement rate of Consumers. This variable describes the transition into the ‘Inactive’ state of a consumer, ultimately when a household is found and purchased. Movement speed affects both demand and supply in the sense that the transitioning of stages is quickened and more responsive. (Indicated by a more rigid demand and supply curve).

Market Price

In economics Price is a linear function (straight line) of the proportion of houses for sale (positive slope), and also a linear function of the proportion of buyers (negative slope).Therefore , the variable ‘Market Price’ is calculated by 10 * the portion of ‘House’ in the active state (which is the supply) over the portion of ‘Consumers’ in the active state (which is the demand) Ultimately this presents the economic principles  that as Supply is directly related to Price and demand is inversely related to Price.

Note

Each simulation (with the same settings) will present a different and unique simulation. I have set a Random Boolean to the active component that randomizes the amount of Customers or houses that begin in their active state. The probability is only 0.008 but is useful in describing the effects on the market from various position’s and seeing unique models.  

References

https://www.youtube.com/watch?v=ynuoZQbqeUg - Your First ABM/Part II

https://insightmaker.com/insight/35714/Foraging-Model

Real Estate Agent Based Model MGMT220 Business Analytics Ryan Salvaggio 43668070

  • 4 years 1 week ago

William Pale 42877083 (Assignment 3)

William Pale
The real estate market is heavily influenced by social and economical factors that effect the price of dwellings. Two of the main factors that contribute to not only the housing market but most consumables are supply and demand.
Supply is the amount of one good or service in that market. A market driven economy could utilize supply to regulate price. Generally, if the supply is higher than the demand for that good the price will be lower. If the supply is lower than the demand, the price will tend to increase.
Demand is the amount of consumers that want/need that good or service. Price is also influenced by demand. Generally, if the demand is higher than the supply the price will increase. If the demand is lower than the supply, the price tends to decrease.
Price can be derived from demand and supply.

The following model depicts how the changes in supply and demand of Households effect pricing. The sliders replicate how each of the variables interact with price.
Secondary factors, such as interest rate, foreign investors and government policies also all weigh in on determining a price for a dwelling. 

Real Estate Housing Demand Supply

  • 4 years 2 weeks ago

Property Market

Massimo Rinaldi
​This insight demonstrates the effects of both supply and demand directly relating to price in conjunction with the change in interest rate. This system represents a 5 year period broken into monthly periods.
The number of buyers and sellers are both demonstrated as stocks which in turn are affected by the number of houses purchased and indirectly related to new investors and a growth in housing per period.
There is a 20% growth rate of new housing with a investor growth rate proportional to the current interest rate as well as being affected by the current number of potential buyers. All other initial values are either predefined or generated in relation to its links to other stocks/variables.
Price can be understood to be directly related to the ratio of both buyers and sellers and in turn loop to affect the change in the numbers of Houses For Sale and Potential Buyers. It is also directly related to the number of people looking to purchase as a ratio of those looking to purchase and houses for sale.
Sales are generated when a purchase is made therefore modifying the number of buyers and sellers in the market at time the sale is generated.
Setting only the Interest Rate as a changing variable, the slider can be used to understand that an increase in interest rate lowers the number of potential buyers, whilst a decrease in interest rate increases the likelihood for investors and new home buyers to enter the market.

Real Estate Assignment3

  • 4 years 1 week ago

Complex Systems - 43036317

Dileesha Sigera
The following is a complex system depicting the nature of real estate and showing the deciding factors of its activities.
House supply and house prices have a direct relationship (linear - positive)​. Buyers and house prices have an indirect relationship (linear - negative). Interest rate and desire are directly related (linear - positive).

Real Estate Housing

  • 4 years 1 month ago

MGMT220 - Assignment 3 - 43808719 - Chris Houston

Chris Houston
This simulation shows the relation ship between the number of houses for sale (Supply), the amount of people searching for home (Demand) and how these factors affect the prices within the real estate market, with the purpose of forecasting when the best time to buy and sell property is. It is assumed in this model that the number of houses are a constant, as we are looking at existing housing infrastructure rather than an emerging market or apartment buildings.
This model spans over 20 years, showing the long-term flow of the real estate market within this time frame. Price is a linear function of the number of houses for sale (positive) and also a liner function of the number of people searching for homes (negative).
Demand Elasticity Of price, Price Elasticity of Demand, Price elasticity of Supply, Supply Elasticity of Price and Interest rates can all be adjusted through the use of the sliders to create different scenarios with supply, demand and interest rates. The sales variable passes information into both the buying and sold variables upon completion of a relevant transaction.
While demand is low, the price is typically low too, however the supply of houses is high. While the demand is high the price is driven up and the supply of houses is lower than the demand.

Property Real Estate Supply

  • 4 years 1 week ago

Real Estate Market - Raymund Paradeza 43626491

Raymund Paradeza
The following model shows a real estate market created by a web-based modelling and simulation tool; Insight Maker. This model shows the relationships and links between many different players within the real estate market and how some changes are able to change the marketplace overall. 
Information from ModelThe information generated from this model includes "Wanting to Buy", "Houses for Sale" and "Price". "Wanting to Buy" refers to the players who demand or wish to buy houses, "Houses for Sale" refers to the total supply of houses within this marketplace whilst "Price" refers to the price an individual bought a house at a certain point in time.
Variables IncludedAll variables on the model are shown as ovals and are either fixed or can be adjusted. The fixed variables are shown in yellow, where fixed refers to not being able to be changed by non-editors viewing this model. These variables can not be adjusted as these variables are directly related from the information produced within the model. For example, the variable "Price" can not be adjusted as it would produce incorrect information when the model is simulated
All other variables shown in orange can be adjusted by moving the respective sliders. These variables are able to be adjusted according to what the view wishes. 
Interesting ParametersOne adjusted that the user can make is to increase the "Demand Elasticity of Price" from 100 to 200. This increase in demand elasticity means a greater amount of individuals would be willing to purchases a house. As with the laws of supply and demand, an increase in demand will lead to a increase in price. Once simulated, this model shows that over time the price for a house increases.
One other interesting parameter that the user could do is to increase the level of "Destroy Houses" from 0.05 to 0.1. This increase would lead to a fall in the total amount of houses as the level of houses being destroyed (0.1) is greater than the level of houses being build (0.05). As shown in the simulation, this would lead to a fall in the total houses available in the marketplace.

Housing Real Estate

  • 4 years 1 month ago

42928575 Winston Shi-Chung Real estate

winston shi-chung
The following model depicts the effects of supply, demand and its price on the real estate market. This model will try to demonstrate how growth, supply and pricing correlate with each other.  All three have been represented by stocks where the inflow shows the increase amount while out flow shows the decrease amount. All three variables affect each other in certain ways.

For example if supply is higher than demand or if demand is not that high to begin with than the price will drop accordingly and vice versa. If there are less willing buyers than unwilling buyers then the demand will go down. The supply and demand relatable to each other.

According to the simulation if price is fairly low supply and demand will steadily increase however at a certain point it starts to sky rocket and supply and demand gradually declines.

Real Estate

  • 4 years 1 month ago

42928575 Winston Shi-Chung Real estate

winston shi-chung
The following model depicts the effects of supply, demand and its price on the real estate market. This model will try to demonstrate how growth, supply and pricing correlate with each other.  All three have been represented by stocks where the inflow shows the increase amount while out flow shows the decrease amount. All three variables affect each other in certain ways.

For example if supply is higher than demand or if demand is not that high to begin with than the price will drop accordingly and vice versa. If there are less willing buyers than unwilling buyers then the demand will go down. The supply and demand relatable to each other.

According to the simulation if price is fairly low supply and demand will steadily increase however at a certain point it starts to sky rocket and supply and demand gradually declines.

Real Estate

  • 4 years 2 weeks ago

Clone of Assignment 3 - Ryan Salvaggio 43668070

Fons Wijnhoven

Assignment 3 – Complex Systems

 Ryan Salvaggio - 43668070

 

The Model

This model conceptualizes the effects on a real-estate market-model utilizing agent based modelling. This model utilizes basic economic principles of supply and demand.

The model bases itself on two Agents - one being ‘Customers’ of the real estate market model, whilst the other being the Real estate itself, coined 'Houses'.

Consumers (Demand)

The Agent population, ‘Consumers’ specifies the total amount of people whom can potentially become buyers within the market. This is limited to 30 for conceptual purposes. The Agent ‘Consumer’ exists in two states, either being an ‘Active Customer’ (Active) or an ‘Inactive Customer’ (Inactive).  The transition from Inactive to Active occurs upon the basis that the ‘Budget’ of the Consumer meets the desired price of the marketplace, this is specified through the variable ‘Budget’ defining the probability that this transition will occur – this is adjustable by the user indicating a highly resistive or by accepting the market. ‘Budget’s probability in a real life scenario would be based upon numerous factors however conceptually utilizing the slider can present many of these various situations.

Upon transitioning into an active state an ‘Active consumer’ will attempt to find the closest ‘For sale household’, this is represented and carried out through the ‘Enter’ action.  Upon finding a household the consumer and house will both return to their respected inactive state thus repeating the process.

Demand – ‘Count of active customers – demand’ is then calculated by a count of Consumers transitioned and currently in the Active state. A high demand would be indicative through a high ‘Budget’ responsiveness whilst a low demand would be indicative of a low ‘Budget’ responsiveness. The increase in Price and hence supply of household thus reduces demand and vise versa.  

House (Supply)

The Agent population, ‘Houses’ specifies the total amount of households that can potentially become for sale within the market. This is limited to 112 for conceptual purposes. The Agent ‘House’ exists in two states, either being ‘For Sale’ (Active) or ‘Not for Sale’ (Inactive).  The transition from Inactive to Active occurs upon the basis that the ‘Motivation to Sell’ of the House is satisfied, this satisfaction is specified by a set probability that this transition will occur – this is adjustable by the user indicating a highly responsive or restricted house market. ‘Motivation to sell’ probability in a real life scenario would be based upon numerous factors however conceptually utilizing the slider can present many of these various situations.

Upon transitioning into an active state a ‘For Sale’ house will wait for an ‘Active Customer’ ‘this is represented and carried out through the ‘Search’ action. Upon completion of the action both states become inactive and the process continues.

Supply – ‘Count of houses for sale –supply’ is then calculated by a count of Houses ‘For Sale’ that are currently in the active state. Ultimately a high Motivation to sell would sharply increase supply, whilst a low motivation would have the adverse effects.  

Movement Speed

Movement speed – describes the base movement rate of Consumers. This variable describes the transition into the ‘Inactive’ state of a consumer, ultimately when a household is found and purchased. Movement speed affects both demand and supply in the sense that the transitioning of stages is quickened and more responsive. (Indicated by a more rigid demand and supply curve).

Market Price

In economics Price is a linear function (straight line) of the proportion of houses for sale (positive slope), and also a linear function of the proportion of buyers (negative slope).Therefore , the variable ‘Market Price’ is calculated by 10 * the portion of ‘House’ in the active state (which is the supply) over the portion of ‘Consumers’ in the active state (which is the demand) Ultimately this presents the economic principles  that as Supply is directly related to Price and demand is inversely related to Price.

Note

Each simulation (with the same settings) will present a different and unique simulation. I have set a Random Boolean to the active component that randomizes the amount of Customers or houses that begin in their active state. The probability is only 0.008 but is useful in describing the effects on the market from various position’s and seeing unique models.  

References

https://www.youtube.com/watch?v=ynuoZQbqeUg - Your First ABM/Part II

https://insightmaker.com/insight/35714/Foraging-Model

Real Estate Agent Based Model MGMT220 Business Analytics Ryan Salvaggio 43668070

  • 1 month 3 weeks ago

Clone of Assignment 3 - Ryan Salvaggio 43668070

Natty Gur

Assignment 3 – Complex Systems

 Ryan Salvaggio - 43668070

 

The Model

This model conceptualizes the effects on a real-estate market-model utilizing agent based modelling. This model utilizes basic economic principles of supply and demand.

The model bases itself on two Agents - one being ‘Customers’ of the real estate market model, whilst the other being the Real estate itself, coined 'Houses'.

Consumers (Demand)

The Agent population, ‘Consumers’ specifies the total amount of people whom can potentially become buyers within the market. This is limited to 30 for conceptual purposes. The Agent ‘Consumer’ exists in two states, either being an ‘Active Customer’ (Active) or an ‘Inactive Customer’ (Inactive).  The transition from Inactive to Active occurs upon the basis that the ‘Budget’ of the Consumer meets the desired price of the marketplace, this is specified through the variable ‘Budget’ defining the probability that this transition will occur – this is adjustable by the user indicating a highly resistive or by accepting the market. ‘Budget’s probability in a real life scenario would be based upon numerous factors however conceptually utilizing the slider can present many of these various situations.

Upon transitioning into an active state an ‘Active consumer’ will attempt to find the closest ‘For sale household’, this is represented and carried out through the ‘Enter’ action.  Upon finding a household the consumer and house will both return to their respected inactive state thus repeating the process.

Demand – ‘Count of active customers – demand’ is then calculated by a count of Consumers transitioned and currently in the Active state. A high demand would be indicative through a high ‘Budget’ responsiveness whilst a low demand would be indicative of a low ‘Budget’ responsiveness. The increase in Price and hence supply of household thus reduces demand and vise versa.  

House (Supply)

The Agent population, ‘Houses’ specifies the total amount of households that can potentially become for sale within the market. This is limited to 112 for conceptual purposes. The Agent ‘House’ exists in two states, either being ‘For Sale’ (Active) or ‘Not for Sale’ (Inactive).  The transition from Inactive to Active occurs upon the basis that the ‘Motivation to Sell’ of the House is satisfied, this satisfaction is specified by a set probability that this transition will occur – this is adjustable by the user indicating a highly responsive or restricted house market. ‘Motivation to sell’ probability in a real life scenario would be based upon numerous factors however conceptually utilizing the slider can present many of these various situations.

Upon transitioning into an active state a ‘For Sale’ house will wait for an ‘Active Customer’ ‘this is represented and carried out through the ‘Search’ action. Upon completion of the action both states become inactive and the process continues.

Supply – ‘Count of houses for sale –supply’ is then calculated by a count of Houses ‘For Sale’ that are currently in the active state. Ultimately a high Motivation to sell would sharply increase supply, whilst a low motivation would have the adverse effects.  

Movement Speed

Movement speed – describes the base movement rate of Consumers. This variable describes the transition into the ‘Inactive’ state of a consumer, ultimately when a household is found and purchased. Movement speed affects both demand and supply in the sense that the transitioning of stages is quickened and more responsive. (Indicated by a more rigid demand and supply curve).

Market Price

In economics Price is a linear function (straight line) of the proportion of houses for sale (positive slope), and also a linear function of the proportion of buyers (negative slope).Therefore , the variable ‘Market Price’ is calculated by 10 * the portion of ‘House’ in the active state (which is the supply) over the portion of ‘Consumers’ in the active state (which is the demand) Ultimately this presents the economic principles  that as Supply is directly related to Price and demand is inversely related to Price.

Note

Each simulation (with the same settings) will present a different and unique simulation. I have set a Random Boolean to the active component that randomizes the amount of Customers or houses that begin in their active state. The probability is only 0.008 but is useful in describing the effects on the market from various position’s and seeing unique models.  

References

https://www.youtube.com/watch?v=ynuoZQbqeUg - Your First ABM/Part II

https://insightmaker.com/insight/35714/Foraging-Model

Real Estate Agent Based Model MGMT220 Business Analytics Ryan Salvaggio 43668070

  • 2 days 18 hours ago