The document describes the development of a Schedule of Market Values (SMV) for residential lands using the sales comparison approach. Key steps include:
1) Identifying benchmark properties and establishing a base unit value.
2) Determining adjustment factors for location attributes like views, corners, and slopes.
3) Grouping property sales into value ranges based on their unit values.
4) Collapsing ranges with few occurrences to create the final SMV with 8 subclasses ranging from PHP1,600 to PHP4,500 per square meter. The SMV provides standardized unit values to appraise properties.
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This document provides information about a fieldwork report for a site surveying course. It includes an introduction to levelling, the objective of the fieldwork, apparatus used including an automatic level, levelling rod, tripod and spirit level. Levelling results were presented using the height of collimation and rise/fall methods. Adjusted results were shown after distributing a small error. The levelling was found to be acceptable as the error of closure was within the allowed maximum. The document concluded the fieldwork was successfully completed to obtain data for the report.
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An Introduction to Statistical Methods and Data Analysis.pdfSandra Valenzuela
This document provides a table of standard normal curve areas. The table lists z-scores from -5 to 5 in increments of 0.1 on the left side. For each z-score, the corresponding area under the standard normal curve is provided to four decimal places. The areas decrease as the z-scores decrease from 0 to -5 and increase as the z-scores increase from 0 to 5. Below the table, it notes that the areas were computed using the R function pnorm and that the shaded area represents the probability Pr(Z ≤ z).
The document provides details about the Panglao Tower residential condominium development including its location, master development plan, floor plans, unit specifications and prices. Specifically, it summarizes that Panglao Tower will be an 18-floor development located in Metro Park, Pasay City with 269 residential units of different sizes ranging from studios to 2-bedroom units. It also outlines the payment terms and sample unit price computations.
The project involves designing a hard rock mine for a greenfield gold deposit located in Papua New Guinea. An initial pre-feasibility study has been conducted including cost estimation, pit optimization, and conclusion. Future tasks include developing an open pit and underground mine design using Vulcan software, reserve calculation, production scheduling, and further economic evaluation and risk assessment.
Control Charts in Lab and Trend Analysissigmatest2011
Go through this presentation by Sigma Test and Research Centre and know about control charts in lab and trend analysis. To know more about us visit our website.
Project Management and Development Economics Project (DE)Pang Khai Shuen
The document proposes developing 26' x 80' double-storey shop/office lots, 22' x 75' double-storey terrace houses, and 20' x 60' low-cost houses on a 10-acre land beside Taylor's University. It includes details of the proposed development such as the number and size of units, land size calculations, percentage allocation for each type of development, and a financial appraisal of the development costs and projected profits. The development is estimated to cost RM38.2 million and projected to generate a gross profit of RM16.3 million, representing a 30% return on the RM54.5 million estimated gross development value.
This document provides information about a fieldwork report for a site surveying course. It includes an introduction to levelling, the objective of the fieldwork, apparatus used including an automatic level, levelling rod, tripod and spirit level. Levelling results were presented using the height of collimation and rise/fall methods. Adjusted results were shown after distributing a small error. The levelling was found to be acceptable as the error of closure was within the allowed maximum. The document concluded the fieldwork was successfully completed to obtain data for the report.
This document provides the results of a site surveying fieldwork report on levelling. The objectives were to find elevation differences between points and establish points at given elevations. Apparatus used included an automatic level, levelling rod, tripod, and spirit level. Levelling was conducted between 11 points including a benchmark. Results showed an error of -0.009m. Using the height of collimation and rise/fall methods, reduced levels were calculated and adjusted using error distribution. The maximum allowable error was +/-39.799mm, so the levelling was acceptable. The fieldwork helped obtain necessary data to complete the report.
An Introduction to Statistical Methods and Data Analysis.pdfSandra Valenzuela
This document provides a table of standard normal curve areas. The table lists z-scores from -5 to 5 in increments of 0.1 on the left side. For each z-score, the corresponding area under the standard normal curve is provided to four decimal places. The areas decrease as the z-scores decrease from 0 to -5 and increase as the z-scores increase from 0 to 5. Below the table, it notes that the areas were computed using the R function pnorm and that the shaded area represents the probability Pr(Z ≤ z).
The document provides details about the Panglao Tower residential condominium development including its location, master development plan, floor plans, unit specifications and prices. Specifically, it summarizes that Panglao Tower will be an 18-floor development located in Metro Park, Pasay City with 269 residential units of different sizes ranging from studios to 2-bedroom units. It also outlines the payment terms and sample unit price computations.
The project involves designing a hard rock mine for a greenfield gold deposit located in Papua New Guinea. An initial pre-feasibility study has been conducted including cost estimation, pit optimization, and conclusion. Future tasks include developing an open pit and underground mine design using Vulcan software, reserve calculation, production scheduling, and further economic evaluation and risk assessment.
Control Charts in Lab and Trend Analysissigmatest2011
Go through this presentation by Sigma Test and Research Centre and know about control charts in lab and trend analysis. To know more about us visit our website.
This document outlines a group assignment for a development economics course. It includes details of the proposed development such as land size, number and type of units, and a financial appraisal. The development will include shop/office, terrace, and low-cost housing units totaling 164 units. The financial appraisal estimates construction costs, administrative costs, financing costs, and gross profit. Cash flow projections are provided for a "sell-then-build" approach, with monthly sales and construction progress outlined over a 12 month period.
It is a presentation about GIS in RAPDRP project. DISCOM can use GIS tools and data for their betterment to navigation towards their electrical assets & for calculation of AT&C losses.
The document provides a table with cost and time data for 9 activities in a project. It then asks for the:
1) Normal and crashed durations of each activity.
2) Network diagrams for the normal and crashed scenarios.
3) Calculation of early start, early finish, late start, late finish for the crashed scenario.
4) Calculation of total project cost for normal and crashed scenarios.
5) Identification of the least cost scenario which has a total project cost of Rs. 293,000 and a duration of 19 weeks.
The document analyzes the number of units, financial appraisal, and cash flow for a proposed development project consisting of 198 units across three types: double-storey terrace homes, double-storey shop/offices, and low-cost houses. It provides details on the gross development value, gross development cost, and projected cash inflows and outflows over 24 months from 2013 to 2014. The total development cost is estimated at RM38.6 million and the gross development value is RM55.1 million, indicating a potential profit of RM16.5 million.
The document is a business plan for a WARNET broadband internet cafe. It provides investment and cost projections over a 30 month period. The initial investment is Rp456 million which covers hardware, software, office space rental, training, and operational costs for the first 2 months. Monthly operational costs are estimated at Rp7.4 million. Projected monthly revenue from internet usage fees is Rp112.5 million, resulting in estimated profit balances of Rp583 million after 12 months and Rp2.48 billion after 30 months.
The document discusses using machine learning algorithms like random forests and reinforcement learning for algorithmic trading.
It first reviews market microstructure concepts like limit order books and models for measuring market impact of trades. It then discusses using random forests to forecast short-term price direction from market data features. Finally, it introduces using reinforcement learning to optimize the trading problem by minimizing costs while accounting for the path-dependent nature of market impact.
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Institutional orders generally exceed the absorption capacity in the immediate order book and are frequently split horizontally over time and vertically over price. The task of splitting apart a meta-order is achieved through a sequence of market transactions performed by trading algorithms, causing market impact. Consequently a great deal of research is spent on understanding market impact and its role in algorithm design in order to reduce it.
In this presentation, we discuss an application of Deep Reinforcement Learning to minimise transaction costs across a diverse range of instruments. We first discuss high-frequency market impact and its role in optimal planning for single-position and portfolio trading. We then discuss examples of how machine learning is used in short-term forecasting to augment order placement decisions.
Finally, we discuss how the algorithm considers these effects jointly, how it optimizes a dynamic policy, and how it improves performance against surrogate hand-tuned algorithms.
Francesco Boscolo, member of Tecnalia Offshore Energy Area, presents at FOWT 2018 conference in Marseille a methodology for the design of an umbilical cable for floating offshore platforms, based on static and dynamic analysis in a time domain approach, in order to get a significative time-consuming reduction in the design stage.
AN APPARATUS BASED APPROACH FOR COMPREHENSIVE MEASUREMENT OF BRIGHT BAR PARAM...IRJET Journal
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Stuck with your Forecasting Assignment? Get 24/7 help from tutors with Phd in the subject. Email us at support@helpwithassignment.com
Reach us at http://www.HelpWithAssignment.com
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1. The document discusses the use of game theory to analyze bidding strategies of generators and loads in a deregulated electricity market. It considers different cases where players may overdeclare or underdeclare their capacity to maximize their profits.
2. Generators can gain by overdeclaring capacity during off-peak times and underdeclaring during peaks, while loads can gain from overdeclaring demand during peaks and underdeclaring during off-peaks.
3. The analysis shows generators and loads each have incentives to game the system through strategic bidding. Mechanisms like auditing and penalties are needed to prevent gaming and encourage cooperation for maximum system benefits.
This document provides information about the Lisun Electronics Inc. Moving Mirror Goniospectroradiometer (LSG-2000CCD). It can measure the spatial luminous intensity distribution, color properties, and electrical parameters of luminaires. The LSG-2000CCD meets various international photometry standards and can export data in common lighting software formats. It is suitable for measuring floodlights, street lights, and interior lights.
this system is used to measure spatial luminous intensity distribution of luminaries for floodlight, street lighting and interior lighting, and other photometric parameters such as spatial iso-intensity curve, intensity distribution curve
This document contains statistical data on employee performance (Y1), wages (X1), and work environment (X2) for 99 employees. It includes measures of central tendency (mean, median, mode) and dispersion (standard deviation, variance, range) for each variable. Frequency tables show the distribution of scores for each variable, including the number and percentage of employees in each category.
The document discusses quality control and statistical quality control. It defines quality as properties valued by consumers and quality control as maintaining standards through testing samples. The goal of quality control is to eliminate nonconformities and wasted resources at lowest cost. Statistical quality control uses statistical tools like descriptive statistics, acceptance sampling, and statistical process control to measure and control variation in processes. Examples are provided of x-bar and R charts to determine if a gluing process is in control, as well as P and C charts to monitor defects and complaints.
The document provides 7 examples of statistical analyses and distributions. Example 1 involves drawing a histogram for discrete vehicle arrival data collected over multiple days. Example 2 involves drawing a histogram for continuous component lifetime data. Example 3 involves estimating parameters and variance for discrete vehicle arrival data. Example 4 involves determining if installation time data follows a normal distribution. Example 5 involves estimating parameters for a lognormal model of investment rate data. Example 6 involves using a chi-square test to determine if discrete vehicle arrival data follows a Poisson distribution. Example 7 involves using a chi-square test to determine if mine injury count data follows a Poisson distribution.
This 14-page report details a site surveying fieldwork involving levelling. The report includes an introduction to levelling, objectives, descriptions of apparatus used including an auto-level and tripod, results of the levelling with 10 turning points, adjustments made for a misclosure error of 0.014, a discussion of the methods used, and conclusions. The levelling was conducted to enhance students' knowledge of surveying procedures and applying levelling theories learned in class.
This 14-page report details a site surveying fieldwork involving levelling. The report includes an introduction to levelling, objectives, descriptions of apparatus used including an auto-level, tripod, and staff. Leveling results show reduced levels and line of collimation readings for 10 turning points with adjustments made for a 0.014 misclosure error. The conclusions discuss applying theories taught and producing an acceptable report within the error tolerance.
This 14-page report details a site surveying fieldwork involving levelling. The report includes an introduction to levelling, objectives, descriptions of apparatus used including an auto-level, tripod, and staff. Leveling results show reduced levels and line of collimation readings for 10 turning points with adjustments made for a 0.014 misclosure error. The conclusions discuss applying theories taught and producing an acceptable report within the error tolerance.
This document contains 37 multiple choice questions from a real estate study exam covering topics like property definitions, types of estates, deeds, liens, financing, and other real estate concepts. The questions test understanding of key terms and how specific real estate situations should be classified. Sample questions cover defining a fee simple estate, classifying different types of deeds, identifying parties in a deed of trust, and requirements for notices and procedures related to foreclosure.
A real estate appraiser is someone who estimates the value of real estate professionally. An appraisal estimates the market value of a property as of a specific date. The accuracy of an appraisal depends on factors like the competence and integrity of the appraiser, as well as the availability of pertinent data. Appraisals are used for purposes like obtaining loans, insurance, taxes, and determining just compensation for eminent domain. The three main approaches to valuation in an appraisal are the cost approach, income approach, and market data approach.
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This document outlines a group assignment for a development economics course. It includes details of the proposed development such as land size, number and type of units, and a financial appraisal. The development will include shop/office, terrace, and low-cost housing units totaling 164 units. The financial appraisal estimates construction costs, administrative costs, financing costs, and gross profit. Cash flow projections are provided for a "sell-then-build" approach, with monthly sales and construction progress outlined over a 12 month period.
It is a presentation about GIS in RAPDRP project. DISCOM can use GIS tools and data for their betterment to navigation towards their electrical assets & for calculation of AT&C losses.
The document provides a table with cost and time data for 9 activities in a project. It then asks for the:
1) Normal and crashed durations of each activity.
2) Network diagrams for the normal and crashed scenarios.
3) Calculation of early start, early finish, late start, late finish for the crashed scenario.
4) Calculation of total project cost for normal and crashed scenarios.
5) Identification of the least cost scenario which has a total project cost of Rs. 293,000 and a duration of 19 weeks.
The document analyzes the number of units, financial appraisal, and cash flow for a proposed development project consisting of 198 units across three types: double-storey terrace homes, double-storey shop/offices, and low-cost houses. It provides details on the gross development value, gross development cost, and projected cash inflows and outflows over 24 months from 2013 to 2014. The total development cost is estimated at RM38.6 million and the gross development value is RM55.1 million, indicating a potential profit of RM16.5 million.
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The document discusses using machine learning algorithms like random forests and reinforcement learning for algorithmic trading.
It first reviews market microstructure concepts like limit order books and models for measuring market impact of trades. It then discusses using random forests to forecast short-term price direction from market data features. Finally, it introduces using reinforcement learning to optimize the trading problem by minimizing costs while accounting for the path-dependent nature of market impact.
"Active Learning in Trading Algorithms" by David Fellah, Head of the EMEA Lin...Quantopian
Presented at QuantCon Singapore 2016, Quantopian's quantitative finance and algorithmic trading conference, November 11th.
Institutional orders generally exceed the absorption capacity in the immediate order book and are frequently split horizontally over time and vertically over price. The task of splitting apart a meta-order is achieved through a sequence of market transactions performed by trading algorithms, causing market impact. Consequently a great deal of research is spent on understanding market impact and its role in algorithm design in order to reduce it.
In this presentation, we discuss an application of Deep Reinforcement Learning to minimise transaction costs across a diverse range of instruments. We first discuss high-frequency market impact and its role in optimal planning for single-position and portfolio trading. We then discuss examples of how machine learning is used in short-term forecasting to augment order placement decisions.
Finally, we discuss how the algorithm considers these effects jointly, how it optimizes a dynamic policy, and how it improves performance against surrogate hand-tuned algorithms.
Francesco Boscolo, member of Tecnalia Offshore Energy Area, presents at FOWT 2018 conference in Marseille a methodology for the design of an umbilical cable for floating offshore platforms, based on static and dynamic analysis in a time domain approach, in order to get a significative time-consuming reduction in the design stage.
AN APPARATUS BASED APPROACH FOR COMPREHENSIVE MEASUREMENT OF BRIGHT BAR PARAM...IRJET Journal
The document describes the development of an apparatus for comprehensively measuring various parameters of bright bars, such as overall diameter, circularity error, straightness error, amount of bending, and number of surface cracks. The apparatus uses techniques like optical sensors, dial indicators, and UV lamps to automatically measure the parameters, providing more efficient inspection than manual methods. Test results demonstrated the machine could accurately measure bright bar parameters in less time than traditional individual instrumentation.
Stuck with your Forecasting Assignment? Get 24/7 help from tutors with Phd in the subject. Email us at support@helpwithassignment.com
Reach us at http://www.HelpWithAssignment.com
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1. The document discusses the use of game theory to analyze bidding strategies of generators and loads in a deregulated electricity market. It considers different cases where players may overdeclare or underdeclare their capacity to maximize their profits.
2. Generators can gain by overdeclaring capacity during off-peak times and underdeclaring during peaks, while loads can gain from overdeclaring demand during peaks and underdeclaring during off-peaks.
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2 Development of SMV Using Sales Direct Comparison Approach.pdf
1. Schedule of Market Values (SMV)
• Provides the matrix and other
parameters used in the appraisal and
assessment of real properties
• Lists of locations setting out the base
unit values.
• Shows various influences to value.
• Shows the current market value of
properties.
2. APPRAISAL OF LANDS
The concept of highest and best use. The
PVS defines highest and best use as “The
most probable use of a property which is
Physically possible
Appropriately justified
Legally permissible
Financially feasible, and
which results in the highest value of the
property being valued”
4. APPRAISAL OF LANDS
1. Establish Benchmark Lot Values
• Typical parcel that serves as the model
• Possess characteristics common to the
majority of properties
• Ready reference against which to check
sales or values of other properties
5. APPRAISAL OF LANDS
2. Random Selection of Parcels
1. Simple Random Sampling
• Lottery – needs complete listing of properties.
Easy for small populations but relatively
complicated and time- consuming for large
populations.
• Generation of Random Numbers/digits – better
and more efficient method for selecting a simple
random sample. Computers and even calculators
can be used to generate random digits, however
a complete listing the properties is needed in
this type of random selection.
6. 2. Systematic Sampling – samples are randomly chosen
following certain rules set by the researchers. This
involves choosing the Kth number of the properties, with
k=N/n, but there should be a random start.
Example: Choose a sample size of 10 from a sub-market
area of 500 properties, using a systematic random
sampling., N=500;n=1
Step 1. Determine k (period/interval) ; 500/10= 50, using
systematic random sampling.
Step 2. Put the random start at 15.
Step 3. Include in the samples of the following: 15, 65,
115, 265, 315,365, 415 and 465.
APPRAISAL OF LANDS
7. 3. Stratified Random Sampling.
• Use Strata (Kind, Classification)
4. Cluster Sampling
• Sub-Market Areas
APPRAISAL OF LANDS
8. Cases in the Development of SMV
1. Sales/Direct Comparison Approach
2. Adjustments for Time.
3. Income Capitalization Approach
4. Land Residual Technique
11. Case 1. Development of SMV Using Sales/Direct
Comparison Approach
Identify Base Lot, and uncommon lots:
Sale
Sale
Price
Land
Area
Unit
Value
Description Comment
9 600,000 200 3,300
Flat land, inside lot, no
view or other factor
May establish unit
value
11 550,000 180 3,055
Flat land, inside lot, no
view or other factor
May establish unit
value (Sale 9)
22 500,000 200 2,500
Inside lot, land drops
from road 1.5 meters
17% drop in price
23 620,000 200 3,100
Almost flat land, slightly
slopes down from road
May establish unit
value (Sale 9)
28 600,000 180 3,333
Flat lot, no view, located
on good corner
Corner lot achieved
11% addtl value
12. Case 1. Development of SMV Using Sales/Direct
Comparison Approach
Determine Adjustment Factors:
Using Rounded value of Sales 9, 11 and 23 as
the benchmark lot = P 3,000:
% Adjustment low land
= (UV sale 22-UV sale9)/UV Sale 22 x 100%
= (2,500-3000)/3,000 x 100% = -17%
% Corner Lot
= (UV sale 28-UV sale 9)/UV Sale 28
= (3,333-3000)/3,000 x 100% = +11%
13. Case 1. Development of SMV Using Sales/Direct
Comparison Approach
Sale
Sale
Price
Land
Area
Unit
Value
Description Comment
21 725,000 200 3,625
On higher part of
subdivision, slight slope
from road, and has very
good view.
Higher lot with view
adds 20% value
12 495,000 180 2,750
Flat corner lot but near
to old railway line and
squatters.
Shows reduction in
price 17.5% from
standard corner
price.
30 700,000 200 3,500
Good flat piece of land
on main road
Main road location
indicates 16%
increase over base
price
14. Case 1. Development of SMV Using Sales/Direct
Comparison Approach
Determine Adjustment Factors:
% Adjustment low land
= (3,625-3000)/3,000 x 100% = +20%
% Blighted lot (squatters) with corner influence
= (3,000 x 111%) = 3,333 (with Corner Influence)
= (2,750 – 3,333)/3,333 x 100% = -17.5%
%Effect to Main Road
= (UV sale 30-UVsale 9)/UV Sale 30
= (3,500-3000)/3,000 x 100% = +16%
15. Case 1. Development of SMV Using Sales/Direct
Comparison Approach
Determine Adjustment Factors:
• Base unit value = Php3,000/m2 (Sales
9,11,23.)
• Sloping down = deduct 16% (Sale 22)
• Corner lots = add 11% (Sale 28)
• With a view = add 20% (Sale 21)
• Blighted Status (Squatters) = deduct 17%
(Sale 12)
• Lots along main road – 16% higher (Sale 30)
16. Using all the Sales
Data, formulate the
Schedule of Market
Values
19. Case 1. Development of SMV Using Sales/Direct
Comparison Approach
Group the values into ranges with an interval of ± 5%
from midpoint
a. C1 = 1,500 (set MP)
b. B1 = C1 x (100%-5%)
=1,425
c. D1 = C1 x (100%+5%)-1
= 1,574
d. B2 = D1 + 1
= 1,575
e. C2 = B2 x (100%+5%)
= 1,700 (Rnd)
f. D2 = C2 x (100%+5%)-1
= 1784
and so on…
E = number of UV
occurring in the range
A B C D E
Range Low 5% Mid High 5% Freq
1 1,425 1,500 1,574 1
2 1,575 1,700 1,784 0
3 1,785 1,900 1,994 1
4 1,995 2,100 2,204 1
5 2,205 2,300 2,414 1
6 2,415 2,500 2,624 2
7 2,625 2,800 2,939 6
8 2,940 3,100 3,254 8
9 3,255 3,400 3,569 6
10 3,570 3,700 3,884 3
11 3,885 4,100 4,304 2
12 4,305 4,500 4,724 0
13 4,725 5,000 5,249 1
20. Case 1. Development of SMV Using Sales/Direct
Comparison Approach
Limit the set of ranges by collapsing few occurrences.
Range Mid Freq
1 1,500 1
2 1,700 0
3 1,900 1
4 2,100 1
5 2,300 1
6 2,500 2
7 2,800 6
8 3,100 8
9 3,400 6
10 3,700 3
11 4,100 2
12 4,500 0
13 5,000 1
Due to too many ranges, collapse Ranges
1 & 2, 3 to 5 and 11 to 13
To collapse, compute the average of the
mid values then round-off
Range Low Mid High
1 1,425 1,600 1,784
2 1,785 2,100 2,414
3 2,415 2,500 2,624
4 2,625 2,800 2,939
5 2,940 3,100 3,254
6 3,255 3,400 3,569
7 3,570 3,700 3,884
8 3,885 4,500 5,249
21. Case 1. Development of SMV Using Sales/Direct
Comparison Approach
Sub Class MV
R1 4,500
R2 3,700
R3 3,400
R4 3,100
R5 2,800
R6 2,500
R7 2,100
R8 1,600
Sort the ranges from highest to
lowest value.
Label the corresponding sub-
class.
Warning: Care should be taken in collapsing
ranges, the interval between a midpoint
increases thereby inappropriately
overvalue or undervalue properties.
22. Case 1. Development of SMV Using Sales/Direct
Comparison Approach
Criteria for Sub-Classification:
R1 Along main road
Along interior road with view
Relatively flat
….
R2 Along interior roads
No view
Relatively flat
….
R3 ….
23. Case 1. Development of SMV Using Sales/Direct
Comparison Approach
Adjustment Factors:
Corner Influence = +11%
Sunken Lots less than 1.5m = 0% (No
adjustment)
Sunken lots at 1.5m or more = -16%
Blighted Status (presence of squatters) = -17%
24. Case 1. Development of SMV Using Sales/Direct
Comparison Approach
Participants Exercise:
Sale
Sale
Price
Land
Area
Unit
Value
Description Comment
9 405,000 180
Flat lot with road right of
way, no view
May establish unit
value.
10 450,000 200
Flat lot farthest from the
main road slightly
sloping
May establish unit
value
Given two more sales, determine the unit values,
Adjustment factors, criteria for sub-classification and
Make corresponding adjustments to the SMV.
26. Case 3. Development of SMV Using Income Capitalization
Approach
Ground Rent – Rent for vacant land.
-lower capitalization rate due to durability of
the lot
Caution over:
Short term Ground Rent – Rent for
convenience
Long term Ground Rent – if has no use for
the immediate future.
27. Given two more sales, determine the unit values,
Adjustment factors, criteria for sub-classification and
Make corresponding adjustments to the SMV.
Case 3. Development of SMV Using Income Capitalization
Approach
1 10m x2om 200 5,000 Flat land, inside lot, no view or other factor
2 9mx20m 180 4,600 Flat land, inside lot, no view or other factor
3 10m x 20m 200 4,500
Inside lot, land drops from road by 1.5
meters (i.e. slopes down)
4 10m x 20m 200 5,000
Almost flat land, sight fall from road (slope
down)
5 9m x 20m 180 5,300 Flat lot, no view, located on good corner.
6 10m x 20m 200 7,500
On higher part of subdivision, has slight
slope (fall) from road, and has very good
view.
7 9m x 20m 180 3,800
Flat corner lot but near to old railway line
and squatters.
8 10m x 20m 200 6,000 Good flat piece of land
28. Formula:
V = I / Cr
Case 3. Development of SMV Using Income Capitalization
Approach
Where:
V = Value
I = Net Income
CR = Capitalization Rate
CR = I / V x 100%
29. Case 3. Development of SMV Using Income Capitalization
Approach
Participants Exercise:
Ppty Area M Value
from TD
Net Annual
Rent
Cap
Rate
Utilization
a b c d e=d/c f
A 657 300,000 96,000 Whole Area
B 200 650,000 60,000 Whole Area
C 287 1,700,000 144,000 Only ½ utilized,
rest idle
D 1,150 400,000 45,000 Plant Propagation
Average Capitalization Rate
Determine valid data, estimate the CR:
30. Specific and General Factors as a basis for Criteria and
Adjustment Factors
Do:
• Match pair and determine their difference.
Example: Similar lots, one with view, the other
without
• Determine common differences that may serve as a
criteria or adjustment factor.
• Minor variation are ignored and individual appraisal is
done for uncommon factors.
Note:
• Adjustment factors are peculiar to a property.
• Criteria affects a number of properties (Sub-
Classification)
31. Case 3. Development of SMV Using Income Capitalization
Approach
Estimate the CR from known valid sales and
rentals.
Sale Area Market
Value
Net Annual
Rent
Capitalization
Rate
a b c d e=d/c
A 400 1,100,000 100,000 9.09%
B 200 650,000 68,000 10.46%
C 230 700,000 65,000 9.29%
D 150 400,000 45,000 11.25%
Average Capitalization Rate 10.02% say 10%
32. Case 3. Development of SMV Using Income Capitalization
Approach
Lot
(a)
Land
Area
(b)
Net
Mo.
Rent
(c)
CR
%
(d)
Market
Value
(e)
UV w/
Inf (f)
Influences
(g)
Adj.
to UV
(Inf)
(h)
Unit
Value
without
influence
(i)
Rnded
Unit
Value
(j)
1 200 5,000 10 600,000 3,000 Flat inside lot, no other
factor
0% 3,000 3,000
2 180 4,600 10 552,000 3,067 Flat, inside lot, no other
factor
0% 3,067 3,000
3 200 4,500 10 540,000 2,700 Inside lot, drops to 1.5m -17% 3,159 3,000
4 200 5,000 10 600,000 3,000 Almost flat, slight slope 0% 3,000 3,000
5 180 5,300 10 636,000 3,533 Flat, no view, good corner. +11% 3,145 3,000
6 200 7,500 10 900,000 4,500 High location, slight slope
very good view
+20% 3,600 3,500
7 180 3,800 10 456,000 2,533 Flat, corner lot, near old
railway line and squatters.
-17% 2,964 3,000
8 200 6,000 10 720,000 3,600 Good flat land on main road. 0% 3,600 3,500
e = (c)12/d f = e/b i = f(100%-h)
33. Schedule of Market Values
Sub Classification Unit Value
R1 3,500
R2 3,000
R3 2,500
Case 3. Development of SMV Using Income Capitalization
Approach
34. Case 3. Development of SMV Using Income Capitalization
Approach
Criteria for Sub-Classification:
R1 Along main road
Along interior road with view
Relatively flat
….
R2 Along interior roads
No view
Relatively flat
….
R3 ….
35. Case 3. Development of SMV Using Income Capitalization
Approach
Adjustment Factors:
Corner Influence = +11%
Sunken Lots less than 1.5m = 0% (No
adjustment)
Sunken lots at 1.5m or more = -16%
Blighted Status (presence of squatters) = -17%
36. Case 3. Development of SMV Using Income Capitalization
Approach
Note:
Where there are no rental data specific only to
the land, identify similar lands with
improvements which rental adheres more to
the land rather than its improvement.
Example:
• Car Wash
• Parking lots
• Display areas
37. Case 4. Development of SMV Using Land
Residential Technique
Given:
Parcel 1
Land Area = 200
Total Building Area (2s)= 180m2
Building Age = New
Selling Price = Php 1.85 million
With Block fences = 60 1m
Paving = 83 m2
Conditions:
Lands are similarly situated.
Buildings are similarly constructed.
Paving = Php 800 / m2
Determine the land unit value of Parcel 1.
Parcel 2
Land Area = 180m2 (9m x 20m)
Unit Value = Php 3,000/m2
Building Age = 5 years old
Depreciation Rate = 5.5%
Total Building Area (2s)= 140m2
Selling Price = Php 1.45 million
With Block fences = Php 1,200/1m
38. Case 4. Development of SMV Using Land Residential Technique
Solution:
Determine land value and building value of Parcel 2.
Land Value = 180m2 x Php 3,000/m2 = Php 540,000
Block Fences = Perimeter x Php 1,200/ 1m = 58 1m x Php 1,200/1m
= Php 69,600 say Php 70,000
Depreciated Building Value = 1,450,000 – 540,000-70,000
= Php 840,000
Building Value New = Php 840,000 / (1.00-.055) = Php 888,889
Building Unit Value = Php 888,889/140m2 = Php 6,350/m2
= Php 6,500/m2
39. Case 4. Development of SMV Using Land Residential Technique
Apply the unit value of building to parcel 1:
Value of Building = 180m2 x Php 6,500/m2
= Php 1,170,000
Value of Fence = 60 1m x Php 1,200/1m = 72,000
Value of Pavement = 83 m2 x Php 800/m2 = Php 66,400
Value of Land (Parcel 1) = 1,850,000 – 1,170,000 – 72,000 – 66,400
= Php 541,600
Unit Value of Land = Php 541,600/200m2 = Php 2,708/m2
= say Php 3,000/m2
By using the same residual technique in extracting the value of other
lands, a schedule of market value could be developed. Again the criteria
are determined by the conditions of the land while the adjustment factors
are de determined by the physical characteristics of land.