Housing Collateral, Consumption Insurance, and Risk Premia: An Empirical Perspective

In a model with housing collateral, the ratio of housing wealth to human wealth shifts the conditional distribution of asset prices and consumption growth. A decrease in house prices reduces the collateral value of housing, increases household exposure to idiosyncratic risk, and increases the conditional market price of risk. Using aggregate data for the United States, we find that a decrease in the ratio of housing wealth to human wealth predicts higher returns on stocks. Conditional on this ratio, the covariance of returns with aggregate risk factors explains 80% of the cross‐sectional variation in annual size and book‐to‐market portfolio returns.     

Coastal development moratoria and housing prices

This article draws upon event study methodology typically employed in the field of empirical finance to explore the impact of a development moratorium on housing prices in Los Angeles County. Time-series analysis is employed to examine hedonic price-series, return-series, and cumulative returns for prototypical housing units by geographic location and housing type based on ex ante hypotheses about the relative impact of a coastal development moratorium on the market segments that these price and return data represent. In particular, housing prices, returns, and cumulative returns inside and outside the impacted area are examined as are the same measures for housing segmented by age and density. Housing prices in the impacted area experience a significant sustained increase of 6.8 percent and a 10.9 percent spike as of the event date relative to housing prices outside the area. Perhaps more convincing is a cumulative increase in relative returns of over 26 percent in the impacted area versus the inland area during the 22 months prior to the event date. The difference in returns is not significant after the event date. Consistent results are found for properties segmented by age and density. Application of this approach depends on the availability of large volumes of transactions to permit the construction of price-series and return-series in the market segments suggested by the research design.     

Stabilizing non-fundamental asset price movements under discretion and limited information

Inflation, output and interest rate stabilization are all potential central bank objectives. We explore whether monetary policy should respond to asset price fluctuations when they are driven by irrational expectational shocks to the future returns to capital. In our model, an optimistic shock to future returns generates both an increase in equity prices and physical investment. The increased investment is inefficient and, thus, a central bank optimally responds to this expectations shocks. This induces a trade-off between stabilizing nominal prices and non-fundamental asset price movements. We compare the optimal policy under different assumptions: full versus limited information and commitment versus discretion. If the central bank has limited information about whether an asset price movement has a fundamental or non-fundamental origin, then the central bank responds less aggressively to the non-fundamental exuberance shocks than under full information. Without commitment, a central bank responds more aggressively to non-fundamental exuberance shocks.     

Implicit pricing across residential rental submarkets

This paper examines implicit price differences of rental housing characteristics across various property types to measure whether determinants of rents are valued in the aggregate or separately. The results show that hedonic price functions are not identical across property types, which suggests that ordinary least squares is not the appropriate estimation technique when modeling the implicit prices for an aggregate rental market. Generalized least squares estimation of a random coefficient model removes the restriction of fixed parameters imposed by OLS and allows estimation of implicit prices for rental markets containing multiple property types.     

房价预期与城镇居民家庭股市参与——理论探讨与微观经验证据

本文基于中国家庭金融调查数据,通过构建理论模型和实证检验分析了房价预期与家庭股市参与的关系,考察了行为金融偏差在房价预期影响股市参与过程中的作用,并根据背景风险、社会网络和户主特征进行异质性分析。结果表明:(1)房价上涨预期通过降低居民家庭的股票收益率预期和增加住房资产,进而降低居民家庭的股市参与概率和参与程度;(2)“心理账户”以及“有限关注”的存在显著弱化了房价上涨预期对家庭股市参与的负向作用;(3)房价上涨预期对股市参与概率和参与程度的负向作用在收入风险更高、健康状况更差、社会网络水平较低以及受教育程度偏低的家庭中更大。因此,稳定房价预期能够通过提升家庭股市参与,进而从需求角度促进股票市场的健康发展。     

A note on cointegration of international stock market indices

Cointegration is frequently used to assess the degree of interdependence of financial markets. We show that if a stock's price follows a stock specific random walk, market indices cannot be cointegrated. Indices are a mere combination of n different random walks which itself is non-stationary by construction. We substantiate the theoretical propositions using a sample of 28 stock indices as well as a simulation study. In the latter we simulate stock prices, construct indices and test whether these indices are cointegrated. We show that while heteroscedasticity misleads cointegration tests, it is not sufficient to explain the high correlation between stock market index returns. A common random walk component and correlated price innovations are necessary to reproduce this feature.     

Stock market prices do not follow random walks: evidence from a simple specification test

In this article we test the random walk hypothesis for weeklystock market returns by comparing variance estimators derivedfrom data sampled at different frequencies. The random walkmodel is strongly rejected for the entire sample period (1962-1985)and for all subperiods for a variety of aggregate returns indexesand size-sorted portfolios. Although the rejections are duelargely to the behavior of small stocks, they cannot be attributedcompletely to the effects of infrequent trading or time-varyingvolatilities. Moreover, the rejection of the random walk forweekly returns does not support a mean-reverting model of assetprices.     

The Construction of Residential Housing Price Indices: A Comparison of Repeat-Sales,Hedonic-Regression,and Hybrid Approaches

This article examines a number of hypotheses that underpin the repeat-sales and hedonic approaches to the construction of housing price indices, as well as the practical problems associated with the implementation of either approach. We also examine a hybrid procedure that combines elements of both the repeat-sales and hedonic-regression techniques. For our sample of individual home sales in Oakland and Fremont California over an 18-year period, repeat-sales methods are subject to sample selection bias; the maintained assumption of time constancy of implicit prices of housing attributes is violated; the repeat-sales estimator is extremely sensitive to influential observations; and the usual method used to correct for heteroskedasticity in repeat-sale housing returns is inappropriate in our sample. Hedonic techniques are better suited to contend with index number problems per se, as they can accommodate changing attribute prices over time. They also appear to give rise to more reliable estimates of price indices, as unusual observations have less effect on estimated price indices. Drawbacks of the hedonic approach include the usual concern with omitted attributes, and their effect on the estimated price index.     

房价波动、金融稳定与最优宏观审慎政策

本文通过构建包含家庭住房抵押借款摩擦和银行贷款摩擦的动态随机一般均衡模型,重点考察了异质性冲击下房价波动对金融稳定的影响。研究发现,房价上涨会导致银行风险溢价及杠杆率显著上升,进而加剧金融体系的内在不稳定。为降低房价波动及维护金融稳定,选取两类宏观审慎政策工具进行逆周期调控实验,结果表明,在住房需求冲击下,金融管理部门应选取贷款价值比政策,且应对房贷积极调控,而对房价进行中性调控。在最终产品部门生产率冲击、房地产部门生产率冲击及跨期偏好冲击下,应选取资本充足率政策,但对房贷和房价调控力度的把握则存在差异。本研究为厘清房价波动对金融稳定的动态传导机制,以及金融管理部门如何选取宏观审慎政策工具以稳定房价并降低系统性金融风险提供了启示。     

Hedging Housing Risk*

An unusually rich source of data on housing prices in Stockholm is used to analyze the investment implications of housing choices. This empirical analysis derives market-wide price and return series for housing investment during a 13-year period, and it also provides estimates of the individual-specific, idiosyncratic, variation in housing returns. Because the idiosyncratic component follows an autocorrelated process, the analysis of portfolio choice is dependent upon the holding period. We analyze the composition of household investment portfolios containing housing, common stocks, stocks in real estate holding companies, bonds, and t-bills. For short holding periods, the efficient portfolio contains essentially no housing. For longer periods, low-risk portfolios contain 15 to 50 percent housing. These results suggest that there are large potential gains from policies or institutions that would permit households to hedge their lumpy investments in housing. We estimate the potential value of hedges in reducing risk to households, yet yielding the same investment returns. The value is surprisingly large, especially to poorer homeowners.     

Time to wealth goals in capital accumulation

This paper considers the problem of investment of capital in risky assets in a dynamic capital market in continuous time. The model controls risk, and in particular the risk associated with errors in the estimation of asset returns. The framework for investment risk is a geometric Brownian motion model for asset prices, with random rates of return. The information filtration process and the capital allocation decisions are considered separately. The filtration is based on a Bayesian model for asset prices, and an (empirical) Bayes estimator for current price dynamics is developed from the price history. Given the conditional price dynamics, investors allocate wealth to achieve their financial goals efficiently over time. The price updating and wealth reallocations occur when control limits on the wealth process are attained. A Bayesian fractional Kelly strategy is optimal at each rebalancing, assuming that the risky assets are jointly lognormal distributed. The strategy minimizes the expected time to the upper wealth limit while maintaining a high probability of reaching that goal before falling to a lower wealth limit. The fractional Kelly strategy is a blend of the log-optimal portfolio and cash and is equivalently represented by a negative power utility function, under the multivariate lognormal distribution assumption. By rebalancing when control limits are reached, the wealth goals approach provides greater control over downside risk and upside growth. The wealth goals approach with random rebalancing times is compared to the expected utility approach with fixed rebalancing times in an asset allocation problem involving stocks, bonds, and cash.     

On Indexing Commercial Real Estate Properties and Portfolios

Commercial real estate indices play an important role in performance evaluation and overall investment strategy. However, the issue of how representative they are of the returns on portfolios of commercial properties is an open issue. Our study addresses this topic by analyzing a sample of 12,427 repeat sales transactions between Q4 2000 and Q2 2011. We find that the aggregate real estate indices (Moody’s REAL CPPI) do a good job of tracking real returns when portfolios of more than 20 properties are considered. At this level, tracking is somewhat less effective than our benchmark of the S&P500 and its component stocks. Compared to the average root mean squared deviation (RMSD) from one asset, randomly selected portfolios with 20 assets reduce the RMSD by 75 % for the S&P500 compared to 66 % for the aggregate index. These results suggest that the aggregate indices can be effective in hedging and evaluating the performance of direct real estate investment. We further find that tracking at the property type level provides little benefit over using an aggregate index. However, indexing using a property type and location matched index provides lower tracking error for any level of diversification.     

An examination of IPO secondary market returns

IPO stock prices increased approximately 2.3% on the first day of secondary market trading over the period 1993 through 2003. While these aftermarket returns are accentuated during 1999 and 2000, they persist after the bubble burst and even increase as a percentage of total underpricing. We explore several non-mutually exclusive hypotheses to explain our findings including price support, laddering, retail sentiment, and information asymmetry. Our results are most consistent with the view that higher secondary market returns accrue to IPOs with more information asymmetries possibly due to price and aggregate demand uncertainty.     

Consumption-based equity valuation

Using a CCAPM-based risk-adjustment model, we perform yearly valuations of a large sample of stocks listed on NYSE, AMEX, and NASDAQ over a 30-year period. The model differs from standard valuation models in the sense that it adjusts forecasted residual income for risk in the numerator rather than through a risk-adjusted cost of equity in the denominator. The risk adjustments are derived based on assumptions about the time-series properties of residual income returns and aggregate consumption rather than on historical stock returns. We compare the performance of the model with several implementations of standard valuation models, both in terms of median absolute valuation errors (MAVE) and in terms of excess returns on simple investment strategies based on the differences between model and market prices. The CCAPM-based valuation model yields a significantly lower MAVE than the best performing standard valuation model. Both types of models can identify investment strategies with subsequent excess returns. The CCAPM-based valuation model yields time-series of realized hedge returns with more and higher positive returns and fewer and less negative returns compared with the time-series of realized hedge returns based on the best performing standard valuation model for holding periods from 1 to 5 years. In a statistical test of 1-year-ahead excess return predictability based on the models’ implied pricing errors, the CCAPM-based valuation model is selected as the better model. Using the standard series of aggregate consumption and the nominal price index, a reasonable level of relative risk aversion, and calibrated growth rates in the continuing value at each valuation date, the CCAPM-based valuation model produces small risk adjustments to forecasted residual income and low continuing values. Compared with standard valuation models, it relies less on estimated parameters and speculative elements when aggregating residual earnings forecasts into a valuation.     

To buy or not to buy? The value of contradictory analyst signals

We study the predictive ability of individual analyst target price changes for post-event abnormal stock returns within each recommendation category. Although prior studies generally demonstrate the investment value of target prices, we find that target price changes do not cause abnormal returns within each recommendation level. Instead, contradictory analyst signals (e.g., strong buy reiterations with large target price decreases) neutralize each other, whereas confirmatory signals reinforce each other. Further, our analysis reveals that large target price downgrades can be explained by preceding stock price decreases. However, upgrades are not preceded by stock price increases, thereby demonstrating asymmetric analyst behavior when adjusting target prices to stock prices. Our results suggest that investors should treat recommendations with caution when they are issued with large contradictory target price changes. Thus, instead of blindly following a recommendation, investors might put more weight on the change in the corresponding target price and consider transaction costs.     

Information, Search, and House Prices: Revisited

Buyers pay different prices for nearly identical homes. One explanation for this is that housing markets are thin, resulting in price bargaining between sellers and buyers. If the relative bargaining power of buyers varies, so will sales prices. One hypothesis is that the relative bargaining strength of buyers coming from outside the local market relative to that of local residents is weak, because distant buyers have high search costs and may know less about the nuances of the local market. Our results, based upon a large number of single-family home transactions from the state of Florida, lend support to this hypothesis. Another related hypothesis is that buyers?? price expectations are anchored to prices they were accustomed to at their previous residence. Hence, if they come from high price markets they will tend to pay more for their new home. This hypothesis is also supported by our results.     

On the efficacy of stop-loss rules in the presence of overnight gaps

A stop-loss rule is a risk management tool whereby the investor predefines some condition that, upon being triggered by market dynamics, implies the liquidation of her outstanding position. Such a tool is widely used by practitioners in financial markets with the hope of improving their investment performance by cutting losses and consolidating gains. We analyze in this work the performance of four popular implementations of stop-loss rules applied to asset prices whose returns are modeled with consideration of overnight gaps, that is, jumps from the closing price of one day to the opening price of the next trading day. In addition, our models include acute momentary price drops (flash crashes), which are often believed to erode the performance gains that might be derived from stop-loss rules. For this analysis we consider different models of asset returns: random walk, autoregressive and regime-switching models. In addition, we test the performance of the considered stop-loss rules in a non-parametric, data-driven framework based on the stationary bootstrap. As a general conclusion we find that, even when including overnight gaps and flash crashes in our price models, in rising markets stop-loss rules improve the expected risk-adjusted return according to most metrics, while improving absolute expected return in falling markets. Furthermore, we find that in general the simple fixed percentage stop-loss rule may be, in risk-adjusted terms, the most powerful among the popular rules that this work considers.     

Stock returns,aggregate earnings surprises,and behavioral finance

We study the stock market's reaction to aggregate earnings news. Prior research shows that, for individual firms, stock prices react positively to earnings news but require several quarters to fully reflect the information in earnings. We find a substantially different pattern in aggregate data. First, returns are unrelated to past earnings, suggesting that prices neither underreact nor overreact to aggregate earnings news. Second, aggregate returns correlate negatively with concurrent earnings; over the last 30 years, for example, stock prices increased 5.7% in quarters with negative earnings growth and only 2.1% otherwise. This finding suggests that earnings and discount rates move together over time and provides new evidence that discount-rate shocks explain a significant fraction of aggregate stock returns.     

The Choice of Methodology for Computing Housing Price Indexes: Comparisons of Temporal Aggregation and Sample Definition

Housing transactions are executed and recorded daily, but are routinely pooled into longer time periods for the measurement and analysis of housing price trends. We utilize an unusually rich data set, covering essentially all arm's length housing sales in Sweden for a dozen years, in an attempt to understand the effect of temporal aggregation upon estimates of housing prices and their volatilities. This rich data set also provides a unique opportunity to compare the results using the conventional weighted repeat sales model (WRS) to those based on a research strategy which incorporates all available information on house sales. The results indicate the clear importance of temporal disaggregation in the estimation of housing prices and volatilities—regardless of the model employed.The appropriately disaggregated model is then used as a benchmark to compare estimates of the course of housing prices produced by the two models during the twelve year period 1981–1993. These results indicate that much of the difference between estimates of price movements can be attributed to the data limitations which are inherent in the repeat sales approach. The results, thus, suggest caution in the interpretation of government-produced price indices or those produced by private firms based on the repeated sales model.     

Are Stock Returns Predictable? A Test Using Markov Chains

This paper uses a Markov chain model to test the random walk hypothesis of stock prices. Given a time series of returns, a Markov chain is defined by letting one state represent high returns and the other represent low returns. The random walk hypothesis restricts the transition probabilities of the Markov chain to be equal irrespective of the prior years. Annual real returns are shown to exhibit significant nonrandom walk behavior in the sense that low (high) returns tend to follow runs of high (low) returns in the postwar period.