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{{Other uses|Forecast (disambiguation)}}
'''Forecasting''' is the process of making statements about events whose actual outcomes (typically) have not yet been observed. A commonplace example might be [[Approximation|estimation]] of some variable of interest at some specified future date.  [[Prediction]] is a similar, but more general term. Both might refer to formal statistical methods employing [[time series]], [[cross-sectional data|cross-sectional]] or [[longitudinal study|longitudinal]] data, or alternatively to less formal judgemental methods.  Usage can differ between areas of application: for example, in [[hydrology]], the terms "forecast" and "forecasting" are sometimes reserved for estimates of values at certain specific [[future]] times, while the term "prediction" is used for more general estimates, such as the number of times floods will occur over a long period.  
 
[[Risk]] and [[uncertainty]] are central to forecasting and prediction; it is generally considered good practice to indicate the degree of uncertainty attaching to forecasts. In any case, the data must be up to date in order for the forecast to be as accurate as possible.<ref>{{cite web|url=http://www.forecastingprinciples.com/index.php/faq| title=Answers to Frequently Asked Questions| author=Scott Armstrong, Fred Collopy, Andreas Graefe and Kesten C. Green| accessdate=May 15, 2013}}</ref> <!-- old FAQ version here: http://qbox.wharton.upenn.edu/documents/mktg/research/FAQ.pdf -->
 
==Categories of forecasting methods==
===Qualitative vs. quantitative methods===
 
Qualitative forecasting techniques are subjective, based on the opinion and judgment of consumers, experts; they are appropriate when past data are not available.
They are usually applied to intermediate- or long-range decisions. Examples of qualitative forecasting methods are {{cn|date=May 2012}} informed opinion and judgment, the [[Delphi method]], [[market research]], and historical life-cycle analogy.
 
Quantitative forecasting [[mathematical model|models]] are used to forecast future data as a function of past data; they are appropriate when past data are available.
These methods are usually applied to short- or intermediate-range decisions. Examples of quantitative forecasting methods are{{cn|date=May 2012}} last period demand, simple and weighted N-Period [[moving average]]s, simple [[exponential smoothing]], and multiplicative seasonal indexes.
 
===Naïve approach===
 
Naïve forecasts are the most cost-effective objective forecasting model, and provide a benchmark against which more sophisticated models can be compared.  For stationary time series data, this approach says that the forecast for any period equals the historical average. For time series data that are stationary in terms of [[Unit root|first difference]]s, the naïve forecast equals the previous period's actual value.
 
===Time series methods===
 
[[Time series]] methods use historical data as the basis of estimating future outcomes.
 
*[[Moving average]]
*[[Weighted moving average]]
*[[Kalman filtering]]
*[[Exponential smoothing]]
*[[Autoregressive moving average model|Autoregressive moving average (ARMA)]]
*[[Autoregressive integrated moving average|Autoregressive integrated moving average (ARIMA)]]
:e.g. [[Box-Jenkins]]
*[[Extrapolation]]
*[[Linear prediction]]
*[[Trend estimation]]
*[[Growth curve]]
 
===Causal / econometric forecasting methods===
 
Some forecasting methods try to identify the underlying factors that might influence the variable that is being forecast. For example, including information about climate patterns might improve the ability of a model to predict umbrella sales. Forecasting models often take account of regular seasonal variations. In addition to climate, such variations can also be due to holidays and customs: for example, one might predict that sales of college football apparel will be higher during the football season than during the off season.<ref>{{cite book|last=Nahmias|first=Steven|title=Production and Operations Analysis|year=2009}}</ref>
 
Several informal methods used in causal forecasting do not employ strict algorithms {{clarifyme|date=December 2013}}, but instead use the judgment of the forecaster. Some forecasts take account of past relationships between variables: if one variable has, for example, been approximately linearly related to another for a long period of time, it may be appropriate to extrapolate such a relationship into the future, without necessarily understanding the reasons for the relationship.
 
Causal methods include:
 
*[[Regression analysis]] includes a large group of methods for predicting future values of a variable using information about other variables. These methods include both [[parametric statistics|parametric]] (linear or non-linear) and [[Nonparametric regression|non-parametric]] techniques.
 
*[[ARMAX|Autoregressive moving average with exogenous inputs (ARMAX)]]<ref>{{cite book|last=Ellis|first=Kimberly|title=Production Planning and Inventory Control Virginia Tech|year=2008|publisher=McGraw Hill|isbn=978-0-390-87106-0}}</ref>
 
Quantitative forecasting models are often judged against each other by comparing their in-sample or out-of-sample [[mean square error]], although some researchers have advised against this.<ref>{{cite journal|url=http://marketing.wharton.upenn.edu/ideas/pdf/armstrong2/armstrong-errormeasures-empirical.pdf | title = Error Measures For Generalizing About Forecasting Methods: Empirical Comparisons | author = J. Scott Armstrong and Fred Collopy | journal = International Journal of Forecasting | volume = 8 | pages = 69–80 | year = 1992}}</ref>
 
===Judgmental methods===
 
Judgmental forecasting methods incorporate intuitive judgements, opinions and subjective [[probability]] estimates.
 
*[[Composite forecasts]]
*[[Delphi method]]
*[[Forecast by analogy]]
*[[Scenario building]]
*[[Statistical survey]]s
*[[Technology forecasting]]
 
===Artificial intelligence methods===
*[[Artificial neural networks]]
*[[Group method of data handling]]
*[[Support vector machine]]s
 
Often these are done today by specialized programs loosely labeled
*[[Data mining]]
*[[Machine Learning]]
*[[Pattern Recognition]]
 
===Other methods===
 
*[[Simulation]]
*[[Prediction market]]
*[[Probabilistic forecasting]] and [[Ensemble forecasting]]
 
==Forecasting accuracy==
 
The forecast error is the difference between the actual value and the forecast value for the corresponding period.
 
<math>\ E_t = Y_t - F_t </math>
 
where E is the forecast error at period t, Y is the actual value at period t, and F is the forecast for period t.
 
Measures of aggregate error:
 
{| class=wikitable
|-
|[[Mean absolute error]] (MAE)
|<math>\ MAE = \frac{\sum_{t=1}^{N} |E_t|}{N} </math>
|-
|[[Mean Absolute Percentage Error]] (MAPE)
|<math>\ MAPE = \frac{\sum_{t=1}^N |\frac{E_t}{Y_t}|}{N} </math>
|-
|Mean Absolute Deviation (MAD)
|<math>\ MAD = \frac{\sum_{t=1}^{N} |E_t|}{N} </math>
|-
|Percent Mean Absolute Deviation (PMAD)
|<math>\ PMAD = \frac{\sum_{t=1}^{N} |E_t|}{\sum_{t=1}^{N} |Y_t|} </math>
|-
|[[Mean squared error]] (MSE) or [[Mean squared prediction error]] (MSPE)
|<math>\ MSE = \frac{\sum_{t=1}^N {E_t^2}}{N} </math>
|-
|Root Mean squared error (RMSE)
|<math>\ RMSE = \sqrt{\frac{\sum_{t=1}^N {E_t^2}}{N}} </math>
|-
|[[Forecast skill]] (SS)
|<math>\ SS = 1- \frac{MSE_{forecast}}{MSE_{ref}} </math>
|-
|Average of Errors (E)
|<math>\ \bar{E}=  \frac{\sum_{i=1}^N {E_i}}{N} </math>
|}
 
Business forecasters and practitioners sometimes use different terminology in the industry. They refer to the PMAD as the MAPE, although they compute this as a volume weighted MAPE.{{cn|date=May 2012}} For more information see [[Calculating demand forecast accuracy]].
 
'''See also'''
 
*[[Calculating demand forecast accuracy]]
*[[Consensus forecasts]]
*[[Forecast error]]
*[[Predictability]]
*[[Prediction interval]]s, similar to [[confidence interval]]s
*[[Reference class forecasting]]
 
==Applications of forecasting==
 
Climate change and increasing energy prices have led to the use of [[Egain Forecasting]] for buildings. This attempts to reduce the energy needed to heat the building, thus reducing the emission of greenhouse gases. Forecasting is used in [[Customer Demand Planning]] in everyday business for manufacturing and distribution companies.
 
Forecasting has also been used to predict the development of conflict situations. Forecasters perform research that uses empirical results to gauge the effectiveness of certain forecasting models.<ref>{{cite web|url=http://qbox.wharton.upenn.edu/documents/mktg/research/FAQ.pdf | title = Answers to Frequently Asked Questions | author = J. Scott Armstrong, Kesten C. Green and Andreas Graefe | year = 2010}}</ref> However research has shown that there is little difference between the accuracy of the forecasts of experts knowledgeable in the conflict situation and those by individuals who knew much less.<ref>{{cite journal|url=http://marketing.wharton.upenn.edu/documents/research/Value%20of%20expertise.pdf | title = The Ombudsman: Value of Expertise for Forecasting Decisions in Conflicts | author = Kesten C. Greene and J. Scott Armstrong | journal = Interfaces | volume = 0 | pages = 1–12 | year = 2007 | publisher = INFORMS}}</ref>  
 
Similarly, experts in some studies argue that role thinking{{clarifyme|date=December 2013}} does not contribute to the accuracy of the forecast.<ref>{{cite journal|url= http://www.forecastingprinciples.com/paperpdf/Escalation%20Bias.pdf | title = Role thinking: Standing in other people’s shoes to forecast decisions in conflicts | author = Kesten C. Green and J. Scott Armstrong| journal = Role thinking: Standing in other people’s shoes to forecast decisions in conflicts | volume = 39 | pages = 111–116 | year = 1975}}</ref> The discipline of demand planning, also sometimes referred to as supply chain forecasting, embraces both statistical forecasting and a consensus process. An important, albeit often ignored aspect of forecasting, is the relationship it holds with [[planning]]. Forecasting can be described as predicting what the future ''will'' look like, whereas planning predicts what the future ''should'' look like.<ref>{{cite web|url=http://www.forecastingprinciples.com/index.php?option=com_content&task=view&id=3&Itemid=3 |title=FAQ |publisher=Forecastingprinciples.com |date=1998-02-14 |accessdate=2012-08-28}}</ref><ref>
{{cite web|url=http://www.qbox.wharton.upenn.edu/documents/mktg/research/INTFOR3581%20-%20Publication%
2015.pdf |format=PDF | title = Structured analogies for forecasting | author = Kesten C. Greene and J. Scott Armstrong |publisher = qbox.wharton.upenn.edu}}</ref> There is no single right forecasting method to use. Selection of a method should be based on your objectives and your conditions (data etc.).<ref>{{cite web|url=http://www.forecastingprinciples.com/index.php?option=com_content&task=view&id=3&Itemid=3#D._Choosing_the_best_method |title=FAQ |publisher=Forecastingprinciples.com |date=1998-02-14 |accessdate=2012-08-28}}</ref> A good place to find a method, is by visiting a selection tree. An example of a selection tree can be found here.<ref>{{cite web|url=http://www.forecastingprinciples.com/index.php?option=com_content&task=view&id=17&Itemid=17 |title=Selection Tree |publisher=Forecastingprinciples.com |date=1998-02-14 |accessdate=2012-08-28}}</ref>
Forecasting has application in many situations:
 
*[[Supply chain management]] - Forecasting can be used in supply chain management to ensure that the right product is at the right place at the right time. Accurate forecasting will help retailers reduce excess inventory and thus increase profit margin. Studies have shown that extrapolations are the least accurate, while company earnings forecasts are the most reliable.{{clarifyme|date=December 2013}}<ref>{{cite journal|url=http://www.forecastingprinciples.com/paperpdf/Monetary%20Incentives.pdf | title = Relative Accuracy of Judgmental and Extrapolative Methods in Forecasting Annual Earnings | author = J. Scott Armstrong| journal = Journal of Forecasting | volume = 2 | pages = 437–447 | year = 1983}}</ref> Accurate forecasting will also help them meet consumer demand.
*[[Economic forecasting]]
*[[Earthquake prediction]]
*[[Egain forecasting]]
*[[Land use forecasting]]
*[[PECOTA|Player and team performance in sports]]
*[[Political forecasting]]
*[[Product forecasting]]
*[[Sales forecasting]]
*[[Technology forecasting]]
*[[Telecommunications forecasting]]
*[[Transport planning]] and [[Transportation forecasting]]
*[[Weather forecasting]], [[Flood forecasting]] and [[Meteorology]]
 
==Limitations==
 
Limitations pose barriers beyond which forecasting methods cannot reliably predict.
 
=== Performance limits of fluid dynamics equations ===
As proposed by [[Edward Lorenz]] in 1963, long range weather forecasts, those made at a range of two weeks or more, are impossible to definitively predict the state of the atmosphere, owing to the [[chaos theory|chaotic nature]] of the [[fluid dynamics]] equations involved. Extremely small errors in the initial input, such as temperatures and winds, within numerical models double every five days.<ref>{{cite book|title=Storm Watchers|pages=222–224|year=2002|author=Cox, John D.|publisher=John Wiley & Sons, Inc.|isbn=0-471-38108-X}}</ref>
 
=== Complexity introduced by the technological singularity ===
{{Main|Technological singularity}}
 
The [[technological singularity]] is the theoretical emergence of [[superintelligence]] through technological means.<ref>Superintelligence. Answer to the 2009 EDGE QUESTION: "WHAT WILL CHANGE EVERYTHING?": http://www.nickbostrom.com/views/superintelligence.pdf</ref> Since the capabilities of such intelligence would be difficult for an unaided human mind to comprehend, the technological singularity is seen as an occurrence beyond which events cannot be predicted.
 
[[Ray Kurzweil]] predicts the singularity will occur around 2045 while [[Vernor Vinge]] predicts it will happen some time before 2030.
 
==See also==
<div style="-moz-column-count:2; column-count:2;">
* [[Collaborative planning, forecasting, and replenishment|CPFR]]
* [[Forecasting bias]]
* [[Foresight (future studies)]]
* [[Futures studies]]
* [[Futurology]]
* [[Optimism bias]]
* [[Planning]]
* [[Strategic foresight]]
* [[Technology forecasting]]
* [[Wind power forecasting]]
* [[Earthquake prediction]]
* [[Weather forecasting]]
* [[Time Series]]
</div>
 
==References==
{{Reflist}}
*{{cite book
|author = [[Armstrong, J. Scott]] (ed.)
|title= ''Principles of forecasting: a handbook for researchers and practitioners
|year= 2001
|publisher= Kluwer Academic Publishers
|location= Norwell, Massachusetts
|language= [[English language|English]]
|isbn= 0-7923-7930-6
}}
*{{cite book
| author=Ellis, Kimberly
| title = Production Planning and Inventory Control
| year = 2010
| publisher = McGraw-Hill
| language = [[English language|English]]
| isbn = 0-412-03471-9
}}
*{{cite book
| author=Geisser, Seymour
| authorlink =Seymour Geisser
| title = Predictive Inference: An Introduction
| date = 1 June 1993
| publisher = Chapman & Hall, CRC Press
| language = [[English language|English]]
| isbn = 0-390-87106-0
}}
*{{cite book
| author=Gilchrist, Warren
| title = Statistical Forecasting
| year = 1976
| publisher = John Wiley & Sons
| location = London
| language = [[English language|English]]
| isbn = 0-471-99403-0
}}
*Hyndman, R.J., Koehler, A.B (2005) [http://www.robjhyndman.com/papers/mase.pdf "Another look at measures of forecast accuracy"], Monash University note.
*{{cite book
| author=Makridakis, Spyros
| coauthors=Wheelwright, Steven; [[Hyndman, Rob J.]]
| title= Forecasting: methods and applications
| url= http://www.robjhyndman.com/forecasting/
| year=1998
| publisher = John Wiley & Sons
| location = New York
| language = [[English language|English]]
| isbn= 0-471-53233-9
}}
*{{cite book
|author = Kress, George J.  
|coauthors= Snyder, John
|title= ''Forecasting and market analysis techniques: a practical approach
|date= 30 May 1994
|publisher= Quorum Books
|location= Westport, Connecticut, London
|language= [[English language|English]]
|isbn= 0-89930-835-X
}}
*{{cite book
| author=Rescher, Nicholas
| authorlink =Nicholas Rescher
| title = Predicting the future: An introduction to the theory of forecasting
| year = 1998
| publisher = State University of New York Press
| language = [[English language|English]]
| isbn = 0-7914-3553-9
}}
*Sasic Kaligasidis, A et al. (2006) Upgraded weather forecast control of building heating systems. p.&nbsp;951 ff in Research in Building Physics and Building Engineering Paul Fazio (Editorial Staff), ISBN 0-415-41675-2
*Taesler, R. (1990/91) Climate and Building Energy Management. Energy and Buildings, Vol. 15-16, pp 599 – 608.
*[[Peter Turchin|Turchin, P.]] (2007) "Scientific Prediction in Historical Sociology: Ibn Khaldun meets Al Saud". In:[http://edurss.ru/cgi-bin/db.pl?cp=&page=Book&id=53185&lang=en&blang=en&list=Found ''History & Mathematics: Historical Dynamics and Development of Complex Societies.''] Moscow: KomKniga. ISBN 978-5-484-01002-8
*United States Patent 6098893 Comfort control system incorporating weather forecast data and a method for operating such a system (Inventor Stefan Berglund)
 
==External links==
{{wiktionary|predict}}
{{wiktionary|forecast}}
*[http://www.forecastingprinciples.com Forecasting Principles: ''"Evidence-based forecasting"'']
*[http://www.forecasters.org International Institute of Forecasters]
*[http://www.itl.nist.gov/div898/handbook/pmc/section4/pmc4.htm Introduction to Time series Analysis (Engineering Statistics Handbook)] - A practical guide to Time series analysis and forecasting
*[http://www.statsoft.com/textbook/sttimser.html Time Series Analysis]
*[http://www.ifs.du.edu Global Forecasting with IFs]
*[http://www.quakefinder.com Earthquake Electromagnetic Precursor Research]
 
[[Category:Data analysis]]
[[Category:Statistical forecasting]]
[[Category:Time series analysis]]
[[Category:Supply chain management terms]]
[[Category:Supply chain analytics]]
 
[[ar:تنبؤ]]
[[bg:Предвиждане на бъдещи събития]]
[[cs:Prognóza]]
[[de:Prognose#Betriebswirtschaft]]
[[eu:Aurresan]]
[[fr:Prévision]]
[[hi:भविष्यवाणी]]
[[ru:Предсказание]]
[[simple:Forecasting]]

Revision as of 00:03, 31 December 2013

I'm Fernando (21) from Seltjarnarnes, Iceland.
I'm learning Norwegian literature at a local college and I'm just about to graduate.
I have a part time job in a the office.

my site; wellness [continue reading this..] Forecasting is the process of making statements about events whose actual outcomes (typically) have not yet been observed. A commonplace example might be estimation of some variable of interest at some specified future date. Prediction is a similar, but more general term. Both might refer to formal statistical methods employing time series, cross-sectional or longitudinal data, or alternatively to less formal judgemental methods. Usage can differ between areas of application: for example, in hydrology, the terms "forecast" and "forecasting" are sometimes reserved for estimates of values at certain specific future times, while the term "prediction" is used for more general estimates, such as the number of times floods will occur over a long period.

Risk and uncertainty are central to forecasting and prediction; it is generally considered good practice to indicate the degree of uncertainty attaching to forecasts. In any case, the data must be up to date in order for the forecast to be as accurate as possible.[1]

Categories of forecasting methods

Qualitative vs. quantitative methods

Qualitative forecasting techniques are subjective, based on the opinion and judgment of consumers, experts; they are appropriate when past data are not available. They are usually applied to intermediate- or long-range decisions. Examples of qualitative forecasting methods are Template:Cn informed opinion and judgment, the Delphi method, market research, and historical life-cycle analogy.

Quantitative forecasting models are used to forecast future data as a function of past data; they are appropriate when past data are available. These methods are usually applied to short- or intermediate-range decisions. Examples of quantitative forecasting methods areTemplate:Cn last period demand, simple and weighted N-Period moving averages, simple exponential smoothing, and multiplicative seasonal indexes.

Naïve approach

Naïve forecasts are the most cost-effective objective forecasting model, and provide a benchmark against which more sophisticated models can be compared. For stationary time series data, this approach says that the forecast for any period equals the historical average. For time series data that are stationary in terms of first differences, the naïve forecast equals the previous period's actual value.

Time series methods

Time series methods use historical data as the basis of estimating future outcomes.

e.g. Box-Jenkins

Causal / econometric forecasting methods

Some forecasting methods try to identify the underlying factors that might influence the variable that is being forecast. For example, including information about climate patterns might improve the ability of a model to predict umbrella sales. Forecasting models often take account of regular seasonal variations. In addition to climate, such variations can also be due to holidays and customs: for example, one might predict that sales of college football apparel will be higher during the football season than during the off season.[2]

Several informal methods used in causal forecasting do not employ strict algorithms Template:Clarifyme, but instead use the judgment of the forecaster. Some forecasts take account of past relationships between variables: if one variable has, for example, been approximately linearly related to another for a long period of time, it may be appropriate to extrapolate such a relationship into the future, without necessarily understanding the reasons for the relationship.

Causal methods include:

  • Regression analysis includes a large group of methods for predicting future values of a variable using information about other variables. These methods include both parametric (linear or non-linear) and non-parametric techniques.

Quantitative forecasting models are often judged against each other by comparing their in-sample or out-of-sample mean square error, although some researchers have advised against this.[4]

Judgmental methods

Judgmental forecasting methods incorporate intuitive judgements, opinions and subjective probability estimates.

Artificial intelligence methods

Often these are done today by specialized programs loosely labeled

Other methods

Forecasting accuracy

The forecast error is the difference between the actual value and the forecast value for the corresponding period.

Et=Yt−Ft

where E is the forecast error at period t, Y is the actual value at period t, and F is the forecast for period t.

Measures of aggregate error:

Mean absolute error (MAE) MAE=∑t=1N|Et|N
Mean Absolute Percentage Error (MAPE) MAPE=∑t=1N|EtYt|N
Mean Absolute Deviation (MAD) MAD=∑t=1N|Et|N
Percent Mean Absolute Deviation (PMAD) PMAD=∑t=1N|Et|∑t=1N|Yt|
Mean squared error (MSE) or Mean squared prediction error (MSPE) MSE=∑t=1NEt2N
Root Mean squared error (RMSE) RMSE=∑t=1NEt2N
Forecast skill (SS) SS=1−MSEforecastMSEref
Average of Errors (E) E¯=∑i=1NEiN

Business forecasters and practitioners sometimes use different terminology in the industry. They refer to the PMAD as the MAPE, although they compute this as a volume weighted MAPE.Template:Cn For more information see Calculating demand forecast accuracy.

See also

Applications of forecasting

Climate change and increasing energy prices have led to the use of Egain Forecasting for buildings. This attempts to reduce the energy needed to heat the building, thus reducing the emission of greenhouse gases. Forecasting is used in Customer Demand Planning in everyday business for manufacturing and distribution companies.

Forecasting has also been used to predict the development of conflict situations. Forecasters perform research that uses empirical results to gauge the effectiveness of certain forecasting models.[5] However research has shown that there is little difference between the accuracy of the forecasts of experts knowledgeable in the conflict situation and those by individuals who knew much less.[6]

Similarly, experts in some studies argue that role thinkingTemplate:Clarifyme does not contribute to the accuracy of the forecast.[7] The discipline of demand planning, also sometimes referred to as supply chain forecasting, embraces both statistical forecasting and a consensus process. An important, albeit often ignored aspect of forecasting, is the relationship it holds with planning. Forecasting can be described as predicting what the future will look like, whereas planning predicts what the future should look like.[8][9] There is no single right forecasting method to use. Selection of a method should be based on your objectives and your conditions (data etc.).[10] A good place to find a method, is by visiting a selection tree. An example of a selection tree can be found here.[11] Forecasting has application in many situations:

Limitations

Limitations pose barriers beyond which forecasting methods cannot reliably predict.

Performance limits of fluid dynamics equations

As proposed by Edward Lorenz in 1963, long range weather forecasts, those made at a range of two weeks or more, are impossible to definitively predict the state of the atmosphere, owing to the chaotic nature of the fluid dynamics equations involved. Extremely small errors in the initial input, such as temperatures and winds, within numerical models double every five days.[13]

Complexity introduced by the technological singularity

Mining Engineer (Excluding Oil ) Truman from Alma, loves to spend time knotting, largest property developers in singapore developers in singapore and stamp collecting. Recently had a family visit to Urnes Stave Church.

The technological singularity is the theoretical emergence of superintelligence through technological means.[14] Since the capabilities of such intelligence would be difficult for an unaided human mind to comprehend, the technological singularity is seen as an occurrence beyond which events cannot be predicted.

Ray Kurzweil predicts the singularity will occur around 2045 while Vernor Vinge predicts it will happen some time before 2030.

See also

References

43 year old Petroleum Engineer Harry from Deep River, usually spends time with hobbies and interests like renting movies, property developers in singapore new condominium and vehicle racing. Constantly enjoys going to destinations like Camino Real de Tierra Adentro.

  • 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

    My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
  • 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

    My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
  • 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

    My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
  • 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

    My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
  • Hyndman, R.J., Koehler, A.B (2005) "Another look at measures of forecast accuracy", Monash University note.
  • 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

    My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
  • 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

    My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
  • 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

    My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
  • Sasic Kaligasidis, A et al. (2006) Upgraded weather forecast control of building heating systems. p. 951 ff in Research in Building Physics and Building Engineering Paul Fazio (Editorial Staff), ISBN 0-415-41675-2
  • Taesler, R. (1990/91) Climate and Building Energy Management. Energy and Buildings, Vol. 15-16, pp 599 – 608.
  • Turchin, P. (2007) "Scientific Prediction in Historical Sociology: Ibn Khaldun meets Al Saud". In:History & Mathematics: Historical Dynamics and Development of Complex Societies. Moscow: KomKniga. ISBN 978-5-484-01002-8
  • United States Patent 6098893 Comfort control system incorporating weather forecast data and a method for operating such a system (Inventor Stefan Berglund)

External links

Property Brokers and Team Managers – Looking for good Actual Estate Agency to join or contemplating which is the Finest Property Agency to join in Singapore? Join Leon Low in OrangeTee Singapore! In OrangeTee, we've much more attractive commission structure than before, enrichment courses, 10 most vital components to hitch OrangeTee and 1 motive to join Leon Low and his Workforce. 1. Conducive working environment

Via PropNex International, we continually construct on our fame in the international property enviornment. Click here for more of our abroad initiatives. Instances have modified. We don't see those unlawful hawkers anymore. Instead, nicely dressed property brokers were seen reaching out to people visiting the market in the morning. Real estate can be a lonely enterprise and it is straightforward to really feel demoralised, especially when there are no enquiries despite your greatest effort in advertising your shopper's property. That is the place having the fitting assist from fellow associates is essential. Our firm offers administration services for condominiums and apartments. With a crew of qualified folks, we assist to make your estate a nicer place to stay in. HDB Flat for Hire 2 Rooms

Achievers are all the time the first to check new technologies & providers that can help them enhance their sales. When property guru first began, many brokers didn't consider in it until they began listening to other colleagues getting unbelievable outcomes. Most brokers needs to see proof first, before they dare to take the first step in attempting. These are often the late comers or late adopters. There is a purpose why top achievers are heading the wave or heading the best way. Just because they try new properties in singapore issues ahead of others. The rest just observe after!

Firstly, a Fraudulent Misrepresentation is one that is made knowingly by the Representor that it was false or if it was made without belief in its fact or made recklessly without concerning whether or not it is true or false. For instance estate agent A told the potential consumers that the tenure of a landed property they are considering is freehold when it is really one with a ninety nine-yr leasehold! A is responsible of constructing a fraudulent misrepresentation if he is aware of that the tenure is the truth is a ninety nine-yr leasehold instead of it being freehold or he didn't consider that the tenure of the house was freehold or he had made the assertion with out caring whether or not the tenure of the topic property is in fact freehold.

I such as you to be, am a brand new projects specialist. You've got the conception that new tasks personnel should be showflat certain. Should you're eager, let me train you the right way to master the entire show flats island vast as a substitute of getting to stay just at 1 place. Is that attainable you may ask, well, I've achieved it in 6 months, you can too. Which company is well-recognized and is actually dedicated for developing rookie within the industry in venture sales market with success? Can a rookie join the company's core group from day one? I wish to propose a third class, which I have been grooming my agents in the direction of, and that is as a Huttons agent, you will be able to market and have knowledge of ALL Huttons projects, and if essential, projects exterior of Huttons as properly.

GPS has assembled a high workforce of personnel who are additionally well-known figures in the native actual property scene to pioneer this up-and-coming organization. At GPS Alliance, WE LEAD THE WAY! Many people have asked me how I managed to earn S$114,000 from my sales job (my third job) at age 24. The reply is easy. After graduation from NUS with a Historical past diploma, my first job was in actual estate. Within the ultimate part of this series, I interview one of the top agents in ERA Horizon Group and share with you the secrets to his success! Learn it RIGHT HERE

Notice that the application must be submitted by the appointed Key Government Officer (KEO) such as the CEO, COO, or MD. Once the KEO has submitted the mandatory paperwork and assuming all documents are in order, an email notification shall be sent stating that the applying is permitted. No hardcopy of the license might be issued. A delicate-copy could be downloaded and printed by logging into the CEA website. It takes roughly four-6 weeks to course of an utility. Property Brokers and Team Managers – Looking for good Actual Estate Agency to join or contemplating which is the Finest Property Agency to join in Singapore? Join Leon Low in OrangeTee Singapore! In OrangeTee, we've much more attractive commission structure than before, enrichment courses, 10 most vital components to hitch OrangeTee and 1 motive to join Leon Low and his Workforce. 1. Conducive working environment

Via PropNex International, we continually construct on our fame in the international property enviornment. Click here for more of our abroad initiatives. Instances have modified. We don't see those unlawful hawkers anymore. Instead, nicely dressed property brokers were seen reaching out to people visiting the market in the morning. Real estate can be a lonely enterprise and it is straightforward to really feel demoralised, especially when there are no enquiries despite your greatest effort in advertising your shopper's property. That is the place having the fitting assist from fellow associates is essential. Our firm offers administration services for condominiums and apartments. With a crew of qualified folks, we assist to make your estate a nicer place to stay in. HDB Flat for Hire 2 Rooms

Achievers are all the time the first to check new technologies & providers that can help them enhance their sales. When property guru first began, many brokers didn't consider in it until they began listening to other colleagues getting unbelievable outcomes. Most brokers needs to see proof first, before they dare to take the first step in attempting. These are often the late comers or late adopters. There is a purpose why top achievers are heading the wave or heading the best way. Just because they try new properties in singapore issues ahead of others. The rest just observe after!

Firstly, a Fraudulent Misrepresentation is one that is made knowingly by the Representor that it was false or if it was made without belief in its fact or made recklessly without concerning whether or not it is true or false. For instance estate agent A told the potential consumers that the tenure of a landed property they are considering is freehold when it is really one with a ninety nine-yr leasehold! A is responsible of constructing a fraudulent misrepresentation if he is aware of that the tenure is the truth is a ninety nine-yr leasehold instead of it being freehold or he didn't consider that the tenure of the house was freehold or he had made the assertion with out caring whether or not the tenure of the topic property is in fact freehold.

I such as you to be, am a brand new projects specialist. You've got the conception that new tasks personnel should be showflat certain. Should you're eager, let me train you the right way to master the entire show flats island vast as a substitute of getting to stay just at 1 place. Is that attainable you may ask, well, I've achieved it in 6 months, you can too. Which company is well-recognized and is actually dedicated for developing rookie within the industry in venture sales market with success? Can a rookie join the company's core group from day one? I wish to propose a third class, which I have been grooming my agents in the direction of, and that is as a Huttons agent, you will be able to market and have knowledge of ALL Huttons projects, and if essential, projects exterior of Huttons as properly.

GPS has assembled a high workforce of personnel who are additionally well-known figures in the native actual property scene to pioneer this up-and-coming organization. At GPS Alliance, WE LEAD THE WAY! Many people have asked me how I managed to earn S$114,000 from my sales job (my third job) at age 24. The reply is easy. After graduation from NUS with a Historical past diploma, my first job was in actual estate. Within the ultimate part of this series, I interview one of the top agents in ERA Horizon Group and share with you the secrets to his success! Learn it RIGHT HERE

Notice that the application must be submitted by the appointed Key Government Officer (KEO) such as the CEO, COO, or MD. Once the KEO has submitted the mandatory paperwork and assuming all documents are in order, an email notification shall be sent stating that the applying is permitted. No hardcopy of the license might be issued. A delicate-copy could be downloaded and printed by logging into the CEA website. It takes roughly four-6 weeks to course of an utility.

ar:تنبؤ bg:Предвиждане на бъдещи събития cs:Prognóza de:Prognose#Betriebswirtschaft eu:Aurresan fr:Prévision hi:भविष्यवाणी ru:Предсказание simple:Forecasting

  1. ↑ Template:Cite web
  2. ↑ 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

    My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
  3. ↑ 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

    My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
  4. ↑ One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

    In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

    Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

    Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

    A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

    The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

    There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
  5. ↑ Template:Cite web
  6. ↑ One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

    In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

    Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

    Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

    A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

    The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

    There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
  7. ↑ One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

    In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

    Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

    Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

    A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

    The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

    There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
  8. ↑ Template:Cite web
  9. ↑ Template:Cite web
  10. ↑ Template:Cite web
  11. ↑ Template:Cite web
  12. ↑ One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

    In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

    Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

    Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

    A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

    The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

    There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
  13. ↑ 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

    My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
  14. ↑ Superintelligence. Answer to the 2009 EDGE QUESTION: "WHAT WILL CHANGE EVERYTHING?": http://www.nickbostrom.com/views/superintelligence.pdf
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