Quantitative Methods for Real Estate Investment

Quantitative Methods for Real Estate Investment (REMF30); Module Assessment; Option A (Residential Real Estate); Introduction; In last few years, most developed economies in the world have experienced one of the worst housing market disruptions in the recorded history. UK housing market is no exception. A sharp decline in house price is being followed by a ratherhesitant recovery. Over the last several months, the decline has slowed and the market is even showing sporadic signs of turn-around. Most experts feel that, though worst is over, the recovery appears severely subdued due to multitude of factors i.e. a combination of cautious optimism by the investors, still feeble balance sheet condition of the builders, overly cautious credit market, weak job market, and on top of all this, ongoing public sector spending cuts. In summary, current economic and financial conditions remain quite fluid. The purpose of the assignment is to get you to look at the current position of the UK housing markets and make an informed and analytically rigorous view of the prospects for UK house prices.; ; Output; You are required to produce a technical report on the outlook for UK house prices. The report should be technically rigorous and consistent with pricing principles/theory (you should include academic references in an Appendix). The guide length of the assignment is 2,500 words (or equivalent). All word counts are for guidance only. Unless the specific requirement of an individual assignment states that the word limit is strict, then there is some discretion with the guide length. Aspects that you should take into consideration include the following:; Option B (Commercial Real Estate); Introduction; Econometric models are routinely applied to generate rental forecasts for commercial real estate markets. While most of these models incorporate sophisticated estimations of price responses to changes in future demand, modelling the supply side of the market seems to be less developed and in some cases less successful. Most econometric models include one or more of the following factors: current or future rental income, capitalisation rates, vacancy rates, replacement costs, cost of capital and competing local schemes as explanatory variables. On the other hand, predictability of future supply is aided by the inertia of the market. Almost by definition, tomorrow’s new supply is already under construction today. There are a number of intervening factors, however, that render accurate modelling of future supply a more difficult task than the inherent time lags in planning, construction and delivery would suggest.; The purpose of this project is to analyse the current situation of the London City Office market and provide an informed and analytically rigorous view of the market dynamics with a view to forecasting rental growth for the next few years.The current situation of the London office market makes for an interesting backdrop for this project. Speculative development deliveries are on a steep downward path which has underpinned the recent surge in prime rental growth.; ; Output; The main task is to produce a technical report on the outlook for London City Office rent. You should try to model rental growth looking at the possible determinants or drivers of the market. Furthermore, you should provide an assessment/forecast of the outlook for rental growth for the next three years, that is, supply as at the end of 2014, 2015, and 2016.; The report should be technically rigorous and consistent withtheory (you should include academic references). The guide length of the assignment is 2,500 words (or equivalent). All word counts are for guidance only. Aspects that you should take into consideration include the following:; DATASETS; For Options A and B, you will be provided with the datasets (emailed to you in the week of December2, 2013) containing a number of variables that you might find useful for modelling house prices and office rent.; ; DATA DETAILS FOR ASSESSMENT – OPTION (A) AND OPTION (B); NOTE: PLEASE DO NOT USE THESE DATASETS FOR ANY OTHER PURPOSES THAN THIS ASSIGNMENT.; Option (A): Housing Data; Excel file – ‘REMF30_project_Option_A.xls’ with 5 tabs for data on UK, South-East region, Yorkshire-Humber region, South-West region, North-West region.; Variable descriptions are provided.; Option (B): London Office Market; Excel file – ‘REMF30_project_Option_B.xls’ with one tab ‘City_Data’; Variable descriptions are provided in comment boxes.; The forecast values of some variables are also given.; Structure of the assignment; A good assignment will:; While I strongly encourage you to produce good theoretical model, the emphasis should also be on due diligence in terms of the empirical aspects and application of the tools and techniques. You should aim to understand how to do an empirical study and try to apply your learning from this module with real data. However, a good empirical study should reflect sound theoretical underpinning. One should know what causal relationship he/she is estimating and why there is a justification for the estimation.; ; Suggested outline;

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