names date. agenda (do we need this?) decide on this after we finish the presentation

NamesDate

Agenda (Do we need this?)Decide on this after we finish the

presentation

Introduction / HookHousing market crash headlinesRecent news about banks having inadequate

housing modelsVikas’ executive summary introPossibly chart showing rapid decline in US

housing pricesPossibly a timeline of significant events in time

=> Motivation / Idea: Need better housing models!

SolutionThe need for better/good housing modelsTim’s video about what people think=> lack of information => inefficient =>

opportunities for refinement and profit

Project objectives/purpose/usesMortgage-Backed Securities (MBS) valuationHousing market sizeMBS market size => Pie chart??UsesDevelop efficient and robust forecasting

models to understand the housing price process

Predict the evolution of housing prices over medium to long term horizon,

Devise profitable trading strategies

Data Sources and Breakdown(?)Model state-level housing pricesOFHEO HPI

1975-2008 quarterlySingle family units…Other useful/interesting descriptors

Simple returns

MethodologyBuild housing price modelBuild inputs for our forecast

Modeling Approach 2-phase approach in modeling the housing price returns data Time frequency: Monthly

Drift Model Explain the relationship between housing price and

macroeconomic variables Supply and demand equilibrium model

Volatility Model Model the residuals from the drift model to account for extra

sources of volatility (refines the drift model?) Time series techniques

=> Combine the 2-stage models to forecast state-level housing prices for xx-months

Drift Model (format 1)Demand Variables (How to present variables and

metric used – maybe table format??)Unemployment ratePopulation sizeMedian incomeCost of credit / interest rateAvailability of credit => Mortgage originations

Supply VariablesHousing stock => Building permits issuanceForeclosures

Drift Model (Bullet format)Demand Variables

Unemployment ratePopulation sizeMedian incomeCost of credit / interest rateAvailability of credit => Mortgage originations

Supply VariablesHousing stock => Building permits issuanceForeclosures

Volatility ModelGoals/purpose: to explain away period of

high & low volatility (volatility clustering). To account for serial autocorrelations

Univariate time series analysisAutoRegressive-Moving Average

ARMA/GARCH

Overview of Economic VariablesChartsSpecial circumstances?

=> Alternative: Do this after we present our states cause it’s like “Now, let’s look at the inputs to our model?”

=> See slides after the states

Building forecasts (or should we put this after show individual states’ analysis)

Forecast each predictor variable of the drift model

Curve fitting

Or we put the general slide here and go into detail after the individual states’ analysis (i.e. assumptions, charts, etc)

Distribution of statesHeat map (hotpads map or then animation

online)[Trouble/High…] StatesMedium statesStates that are opposite the national trend

=> put these 3 categories of states in a table format?

Geographic segmentation??

FloridaHistorical (non-simple returns) graphBackground information / Current climateOur forecastChallenges / Difficulties to overcome

(curvature hump)Reasons for unusual behavior/trends

CaliforniaHistorical (non-simple returns) graphBackground information / Current climateOur forecastChallenges / Difficulties to overcome


New YorkHistorical (non-simple returns) graphBackground information / Current climateOur forecastChallenges / Difficulties to overcome


Middle stateHistorical (non-simple returns) graphBackground information / Current climateOur forecastChallenges / Difficulties to overcome


Low stateHistorical (non-simple returns) graphBackground information / Current climateOur forecastChallenges / Difficulties to overcome


Opposite stateHistorical (non-simple returns) graphBackground information / Current climateOur forecastChallenges / Difficulties to overcome


Inputs to our model – Macroeconomic VariablesOverview

Possibly explain supply and demand economics???

ChartsSpecial events/circumstances

=> This placement is an alternative to discussing this before the states

ForecastingBuilding on forecast relies on assumptions

Demand Variables ForecastsBuilding on forecast relies on assumptionsAssumptions and Reasoning for:

Unemployment ratePopulation sizeMedian income30-year commitment rateMortgage originations

=> Alternative: Each variable has own slide with “Assumptions and Reasoning” along with an actual curve fit/ forecast for a state graph

Supply Variables ForecastsAssumptions and Reasoning for:

Building permits issuanceForeclosures

=> Alternative: Each variable has own slide with “Assumptions and Reasoning” along with an actual curve fit/ forecast for a state graph

Volatility ForecastsShould we talk about this?What to talk about?-----

Important Take-awaysConclusionsResults

(Special) Thanks / AcknowledgementsSponsor

Dr. Paul ThurstonAgamas Capital Management (?)Tower Research Capital (?)

AdvisorsDr. David MattesonDr. David Ruppert

Faculty & Staff (???)Dr. Kathryn CaggianoSelene Cammer (=> look up last name)Victoria ____Judy Francis ???

QuestionsShould we put this before or after the special

thanks slide??

AppendixMaybe include here data treatment

Interpolation to monthly Influential points treatment

Any formulas, etc

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