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Last UpdateWed, 26 Apr 2017 3am

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California

US REAL ESTATE TEAM, April 26, 2017


We are currently BULLISH on the real estate market in California. Our research of the real estate market is driven by a quantitative model designed to predict future housing prices within a cycle framework. The algorithm investigates the relationship between housing market trends and key macro drivers such as prime and subprime mortgage rates, affordability, lending conditions, housing starts, homebuilder confidence, home sales and inventories, purchase and refinance mortgage volumes, mortgage delinquency rates, foreclosure rates, bankruptcy rates, rent growth, consumer credit demand, remodeling activities, home vacancy rates, rental vacancy rates, debt service ratios, mortgage spreads, inflation rates, payroll, unemployment rates, jobless claims, wages, household saving rates, personal income, and consumer confidence. The time series of the components are analyzed to determine the outlook for housing prices in California. Heavy weightings are given to drivers that reflect supply and demand in the real estate market.



Based on a scale from 0 to 100, with 100 being the most bullish and 0 being the most bearish, our latest model reading for housing prices in California is 88.45. The average return of the bullish periods projected by the model is 26.59% and the annualized return of the bullish periods is 10.58%. Measuring the risk-adjusted performance, the model has produced a Sharpe Ratio of 4.22, which is driven by the model's standard deviation of 2.51%. For comparison purpose, the Sharpe Ratio of the buy and hold strategy for the real estate market in California is 1.20. The Sortino Ratio, which measures the relative returns of the model over its downside deviation of 0.25%, is at 31.88. The Calmar Ratio, which is the ratio of the average return over the maximum price drop in real estate market downturns, is at 11.45. The calculation of the model for housing prices in California took 1.83 hours per CPU core to complete at our central computation workstations, which are a group of powerful computers that perform statistical computation continuously 24 hours day and 7 days a week to produce real-time investment ratings for the real estate market in California.



Our model result indicates that housing prices in California will perform well both in absolute returns and on a risk-adjusted basis. Accordingly, our view of the real estate market in California is bullish. The table below shows selected drivers that have significant recent updates. They are among the large macro database on which we perform statistical analysis to develop views on the real estate market. We do not rely only on any single factor to model our investments. Instead, the cross relationships of all the factors and time series are researched back over many real estate cycles in both secular bullish and bearish periods. The goal of our algorithm is to project future housing price trends and optimize the risk/return profile of real estate investments in California.



Our Housing Price Indicator for California is the most timely housing price gauge that we know of. Our propriety methodology removes the delays (typically by a quarter) associated with other housing series. This allows our indicators to lead the housing indices from other sources by more than three months and the government indices by five months, giving our users a significant advantage in obtaining timely price information to enter and exit the real estate market in California ahead of other home buyers and real-estate investors.