Appraisal Quality and Residential Mortgage Default: Evidence from Alaska

We empirically examine the effect of appraisal quality on subsequent mortgage loan performance using data from the high volatility housing market of Alaska in the 1980s. We develop measures of appraisal quality by computing the residual between a hedonic estimate of house value using available information from other appraisals compared to actual ex ante appraised value. We then estimate proportional hazard models of mortgage default and find that several measures of appraisal quality, particularly appraised value in excess of hedonic estimates, are significantly related to default risk. Using valuations subsequent to loan default, we are also able to evaluate how well house price indices perform in terms of estimating current loan-to-value and offer some additional evidence on the controversy over the role of net equity versus trigger events as determinants of mortgage default. We also show that defaults are related to ex ante measures of housing market conditions, with additional implications for underwriting policies and the current industry trend away from traditional appraisal and toward automated valuation.     

An empirical analysis of property appraisal and mortgage redlining

The recent literature advances a hypothesis that addresses the possibility of mortgage redlining caused by a dynamic information externality in property appraisals and mortgage lending. In particular, Lang and Nakamura (1993) hypothesize that because property appraisals depend on past transactions, appraisals in neighborhoods where transactions were infrequent tend to be less precise. The greater uncertainty about house valuation in such neighborhoods can lead mortgage lenders to impose stringent requirements on borrowers. Lang and Nakamura's article, like most economic analysis of property appraisals, is theoretical. Using a sample of mortgages purchased by Fannie Mae, we present preliminary research results that cast doubt on appraisal behavioral rules such as weighted averages or backward-looking expectations on which Lang and Nakamura and other theoretical studies are based. Instead, our results refocus attention on the moral hazard issues of appraisal. We find that in more than 80 percent of the cases, the appraisal is between 0 and 5 percent above the transaction purchase price, in only 5 percent of the cases is the appraisal lower, and in 30 percent of the cases, the appraisal and transaction prices are identical. It would take a strong statistical model to generate such occurrences. Our resutls also indicate that appraisal outcomes are used as a risk factor with different weights for loans with different characteristics (loan-to-value ratios and house prices). The results suggest that more empirical investigation of appraisal practices be conducted to verify the validity of conventional wisdom embedded in theoretical studies, and we offer an econometric framework toward this end.     

Intraday trading halts in the Nikkei futures market

The Osaka Securities Exchange (OSE) halts Nikkei 225 index-futures trading when the next transaction is to take place at a price more than ¥30 (prior to February 1994) or ¥60 (from February 1994) away from the previous trading price. This paper examines the efficacy of the intraday price limit rule in terms of price discovery, liquidity and volatility. We also include transaction data from the Singapore International Monetary Exchange (SIMEX) where Nikkei futures are traded simultaneously. The intraday price limit rule generally appears to be ineffective in reducing volatility and avoiding price jumps, at least partly because OSE traders have access to the alternative market at SIMEX.     

Contemporaneous intraday volume, option, and futures volatility transmissions across parallel markets

The primary objective of this article is to investigate volatility transmission across three parallel markets operating on the Sydney Futures Exchange (SFE), both within and out of sample. Half-hourly observations are sampled from transaction data for the share price index (SPI) futures, SPI futures options, and 90-day bank accepted bill (BAB) futures markets, and the analysis is carried out using the simultaneous volatility (SVL) system of equations as well as competing volatility models. The results confirm the poor ability of GARCH models to fit intraday data. This study also applies an artificial nesting procedure to evaluate the out-of-sample volatility forecasts. Implied volatility has very limited (if any) predictive power when evaluated in isolation, whereas the SVL model with implied volatility embedded provides incremental information relative to competing model forecasts.     

A New Spin on the Jumbo/Conforming Loan Rate Differential

This article uses house-price transaction data to estimate volatility in house prices. The volatility parameter is an input into a mortgage-pricing model that is used to simulate the contract interest rate that balances the mortgage contract. By segmenting the house-price transaction into high- and low-valued homes, we are able to estimate a theoretical jumbo/conforming loan rate differential. Simulation results demonstrate that the differences in volatility between high- and low-priced homes can produce a contract loan rate differential, holding all else constant. The article also presents a discussion of the problems inherent to estimating volatilities form assets with infrequent trades and long holding periods.     

(How) has the market become more efficient?

Using a portfolio of Dow Jones Industrial Average index constituents and the index ETF, we document significant intraday deviations from the law of one price. These are especially pronounced at very short time intervals. The extent of deviations is related to volatility, liquidity, and transaction costs of both the index constituents and the ETF. Further, the influence of news arrival, and liquidity (volatility) shocks on the deviations persists for several hours. Finally, we document significant decline (by at least 80%) in the deviations between 1998 and 2010. We find that this decline is largely due to decimalization, the repeal of the uptick rule, and the introduction of automated updating of the NYSE order book. Overall, our findings indicate an increase in operational market efficiency.     

Are Minorities or Minority Neighborhoods More Likely to Get Low Appraisals?

We empirically examine the role of appraisal in the residential mortgage lending process—in particular, the incidence, consequences, and determinants of appraisal below contract purchase price. Using the Boston Federal Reserve Study data set, we find that, as expected, low appraised value significantly increases the probability of mortgage loan application rejection. We find no evidence that low appraised value is related to census tract racial composition, an important finding given the history of the appraisal industry; however, low appraised value is related to proxies for neighborhood quality. Moreover, properties securing adjustable rate mortgages, condominiums, and properties purchased by African American buyers show an increased probability of low appraisal, though the race effect result is highly sensitive to model specification.     

Analysis of Spatial Autocorrelation in House Prices

This article examines spatial autocorrelation in transaction prices of single-family properties in Dallas, Texas. The empirical analysis is conducted using a semilog hedonic house price equation and a spherical autocorrelation function with data for over 5000 transactions of homes sold between 1991:4 and 1993:1. Properties are geocoded and assigned to separate housing submarkets within metropolitan Dallas. Hedonic and spherical autocorrelation parameters are estimated separately for each submarket using estimated generalized least squares (EGLS). We find strong evidence of spatial autocorrelation in transaction prices within submarkets. Results for spatially autocorrelated residuals are mixed. In four of eight submarkets, there is evidence of spatial autocorrelation in the hedonic residuals for single-family properties located within a 1200 meter radius. In two submarkets, the hedonic residuals are spatially autocorrelated throughout the submarket, while the hedonic residuals are spatially uncorrelated in the remaining two submarkets. Finally, we compare OLS and kriged EGLS predicted values for properties sold during 1993:1. Kriged EGLS predictions are more accurate than OLS in six of eight submarkets, while OLS has smaller prediction errors in submarkets where the residuals are spatially uncorrelated and the estimated semivariogram has a large variance.     

Fundamentalists,chartists and asset pricing anomalies

This paper investigates whether excess volatility of asset prices and serial correlations of stock monthly returns may be explained by the interactions between fundamentalists and chartists. Fundamentalists forecast future prices cum dividends through an adaptive learning rule. In contrast, chartists forecast future prices based on the observation of past price movements. Numerical simulations reveal that the interplay of fundamentalists and chartists robustly generates excess volatility of asset prices, volatility clustering, trends in prices (i.e. positive serial correlations of returns) over short horizons and oscillations in prices (i.e. negative serial correlations of returns) over long horizons, often observed in financial data. Moreover, we find that the memory of the learning rule plays a key role in explaining the above-mentioned stylized facts. In particular, we establish that excess volatility of asset prices; volatility clustering and autocorrelation of returns at different horizons emerge when fundamentalists have short memory. However, volatility clustering as well as short-run and long-run dependencies, observed in financial time series, are more pronounced when fundamentalists have longer memory.     

Frequency of Transaction and House Price Modeling

This article examines the characteristics and price behavior of repeatedly transacted properties. Using data from four U.S. counties, we estimate hedonic price models of properties grouped by transaction frequency, and compare estimated standard deviations and estimated appreciation rates by group.For each of four counties studied, we find that estimated house price appreciation is systematically higher among properties that transact more frequently. One possible explanation for this result is that purchasers make property improvements that are not adequately reflected in the available data.We also find that estimated standard deviations of the disturbance term show a marked decrease as the frequency of transaction increases. Since frequently transacting properties are not found to be systematically more homogeneous than seldomly transacting properties, we do not attribute this to any increase in homogeneity for frequently transacting properties, but rather to the length of time elapsed between transactions of properties.The findings of this article suggest that repeat-sales price models may need to be adjusted to account for cross-sectional variation in transaction probabilities---that is, the selectivity of the subsample of properties that transacted (or transacted repeatedly) during any finite study period.     

Return Volatility,Trading Imbalance and the Information Content of Volume

In this paper, we examine the relationship between volume and return volatility using the transaction data. We introduce transaction and volume imbalance measures to capture the information content of trades. These two information measures are shown to have a strong explanatory power for return volatility and contain incremental information about the asset values over and above that conveyed by the size and frequency of trades. Also, return volatility is significantly correlated with the percentage of trading volume taking place at NYSE. This result suggests that NYSE trades are more informative and contribute more to price discovery. There is evidence that price discovery concentrates in more heavily traded stocks, particularly the Dow Jones Stocks. Finally, return volatility is found to be persistent at the intraday level. The persistence level is higher for less frequently traded stocks. Return volatility also exhibits temporal variations. In particular, return volatility is significantly higher in the opening half-hour for less frequently traded stocks. Thus, stocks with different frequencies of trades may follow different volatility processes.     

List price signaling and buyer behavior in the housing market

To determine whether list price contains useful information for anticipating trends in eventual transactions prices, we develop a model of buyer behavior from a search-theoretic perspective. Using data from the Baton Rouge, Louisiana, housing market between 1985 and 1992, we estimate separate price indexes with list price and selling price as the respective dependent variables in the hedonic regressions. Consistent with our theory, we find that the list price may lead the market when functioning as a signal of seller intent, but list price will probably lag a market driven by buyer willingness to purchase. Granger causality tests conducted on quarterly data for the eight-year study support listing price as a leading indicator of selling price. However, an examination of the indexes around the period of market reversal suggest otherwise. Indeed, listing prices appear to contain the least useful information at the times when information would be most valuable: at the peaks and troughs of the market cycle.     

Why do security prices change? A transaction-level analysis of NYSE stocks

This article develops and tests a structural model of intradayprice formation that embodies public information shocks andmicrostructure effects. We use the model to analyze intradaypatterns in bid-ask spreads, price volatility, transaction costs,and return and quote auto-correlations, and to construct metricsfor price discovery and effective trading costs. Informationasymmetry and uncertainty over fundamentals decrease over theday, although transaction costs increase. The results help explainthe U-shaped pattern in intraday bid-ask spreads and volatility,and are also consistent with the intra-day decline in the varianceof ask price changes.     

Value indices of commercial real estate: A comparison of index construction methods

The purpose of this paper is to shed light on the history of commercial property values over the past decade, and to compare different methods of constructing commercial property value indices and returns series. We examine three types of indices: (i) Indices that attempt to reconstructproperty market values by unsmoothing the appraisal-based Russell-NCREIF Index; (ii) Indices that trace average ex posttransaction prices of commercial property over time; and (iii) an index based onunlevering REIT share prices. By comparing the different historical pictures that result from the various index construction methodologies, one gains insight into the nature of commercial property price and valuation behavior. The REIT-based values lead the other indices in time but display greater short-run volatility. The transactions-based indices lag behind the other series in time, and are consistent with the idea that institutional investors attempt to hold onto properties until they can sell them for a price at least equal to the current appraised value, in effect trading off liquidity for reduced volatility.     

Price formation and the appraisal function in real estate markets

A real estate market model characterized by incomplete information, costly search, and varying expectations is presented. The model describes a self-selection process for market participants and a distribution of transaction prices. These transaction prices, which arise from a Nash equilibrium, can be expressed as a noisy signal, reflecting incomplete information as well as the conditions of sale. The appraiser's role is formalized as the task of signal extraction. The model emphasizes the differences in information available to individual buyers and sellers, who make transactions only infrequently, and the appraiser, whose expertise comes from observing many transactions. Based on the model, it is shown that contrary to popular perceptions, appraisal smoothing is consistent with an optimal updating strategy.     

基本养老保险基金投资、股票收益率与股价波动性

以2017—2022年各季度基本养老保险基金投资数据为样本,考察基本养老保险基金投资对股票收益率与股价波动性的影响。结果显示：基本养老保险基金持股比例变化对股票未来收益率有一定预测效应,持股比例增加会加剧股价波动。异质性检验表明,被持股公司规模越大,持股比例变化对股票收益率的影响越不明显,对股价波动性影响的时滞性越强。对于短期持股而言,持股比例增加会加剧股价波动,而对于长期持股而言,持股比例增加有利于稳定股价。鉴于此,应继续推动基本养老保险基金全国统筹,进一步扩大其市场化投资规模、延长投资考核期限,提升基金可持续发展能力。     

Level changes in volatility models

Level shifts confound the estimation of persistence. This paper shows analytically, in simulations, and using high-frequency stock price data that models for financial volatility that feature a separate source of randomness in the volatility equation are less susceptible to this effect. Such models include recently proposed time series models for realized volatility, as opposed to GARCH models for daily observations, which are highly sensitive to unknown shifts, as has been shown before.     

基于B2C的中国互联网用户团购行为的实证研究

基于互联网的团购成为了中国电子商务新的增长点。传统的团购研究多关注成交机制的差异,而新的互联网团购限定了成交价格、谈判区间和边际效应,形成了具有广告效益、利润收益和客户信任为一体的中介平台。通过搜集20家中国主要的团购网站在一年中的销售数据,研究发现品牌因素、折扣大小、累积效应都对参与团购人数产生显著影响。     

Index arbitrage and the pricing relationship between Australian stock index futures and their underlying shares

This paper examines the mispricing of Australian stock index futures. Exogenous and endogenous price volatility is confirmed to have a positive impact on the mispricing spread, after filtering out predictable time series components. More accurate pricing associated with surprise trading volume in the underlying stocks is consistent with arbitrageurs acting to narrow price disparities relative to the futures market. Ex‐ante interest rate volatility is the primary source of risk faced by arbitrageurs and fluctuations in the transaction cost of opening index arbitrage positions influence the extent to which they drive prices towards theoretical fair values.     

证券交易税对证券市场和财政收入的影响分析

各国和地区设置证券交易税的政策目标在于降低股票价格的不稳定性和增加政府的财政收入。为检验上述政策目标能否实现,本文对美国、瑞典、英国、日本、韩国、中国香港、中国台湾几个重要的证券市场进行了分析,得出结论:各国和地区设置证券交易税的政策目标很难实现。