What moves housing markets: A variance decomposition of the rent–price ratio

We apply the dynamic Gordon growth model to the housing market in 23 US metropolitan areas, the four Census regions, and the nation from 1975 to 2007. The model allows the rent–price ratio at each date to be split into the expected present discounted values of rent growth, real interest rates, and a housing premium over real rates. We show that housing premia are variable and forecastable and account for a significant fraction of rent–price ratio volatility at the national and local levels, and that covariances among the three components damp fluctuations in rent–price ratios. Thus, explanations of house-price dynamics that focus only on interest rate movements and ignore these covariances can be misleading. These results are similar to those found for stocks and bonds.     

Price convergence in US cities: a cointegration approach with two structural breaks

This article investigates how the price indices of major cities of the US respond to the shock from a city and from monetary policy. We find that the crisis of Bretton Woods system in 1968 and the oil crisis in 1974 should be incorporated as structural breaks in monetary policy variables and price indices. Using cointegration technique with structural break in our aggregated data, we find that the average half-life is 1.75 years, which is closer to what some of others found in disaggregated data, and that the interest rate is an effective tool for controlling cities’ price in short run.     

ON THE PROFITABILITY OF RESALE PRICE MAINTENANCE WHEN DEMAND IS UNCERTAIN

A previous study finds that in a market where a manufacturer faces uncertain demand and sells to consumers through competitive retailers, the manufacture wishes to support adequate retail inventories by imposing resale price maintenance (RPM). I show that if retail inventories are allocated to consumers through first‐come‐first‐served rule rather than efficient rationing rule in the game with unconstrained retail competition, imposing RPM may not be profitable. It may not encourage more retail inventories either. RPM may also lower consumer surpluses and social welfare. This study casts some doubt on the demand uncertainty theory that supports RPM.     

房地产信贷、价格及市场供求关系研究

本文通过对2000年以来上海房地产信贷与房地产市场关系的实证分析,发现房地产信贷对房地产市场的影响主要表现在需求方而不是供应方,房地产信贷增长对房地产价格和房地产销售量增长有明显的促进作用,但对房地产开发投资没有明显的影响。房地产信贷增长主要由银行流动性状况决定,而不取决于房地产市场状况,但房地产市场供需状况会影响到房地产信贷结构变化,在价格上升时个人购房贷款增长明显,在价格下降时开发贷款增长明显。在短期内,银行信贷可作为平稳房地产市场波动的手段之一,但对于长期而言,只有构建完善的住房供应体系才能保持房地产市场的长期稳定。     

Data vs. information: Using clustering techniques to enhance stock returns forecasting

This paper explores the use of clustering models of stocks to improve both (a) the prediction of stock prices and (b) the returns of trading algorithms.We cluster stocks using k-means and several alternative distance metrics, using as features quarterly financial ratios, prices and daily returns. Then, for each cluster, we train ARIMA and LSTM forecasting models to predict the daily price of each stock in the cluster. Finally, we employ the clustering-empowered forecasting models to analyze the returns of different trading algorithms.We obtain three key results: (i) LSTM models outperform ARIMA and benchmark models, obtaining positive investment returns in several scenarios; (ii) forecasting is improved by using the additional information provided by the clustering methods, therefore selecting relevant data is an important preprocessing task in the forecasting process; (iii) using information from the whole sample of stocks deteriorates the forecasting ability of LSTM models.These results have been validated using data of 240 companies of the Russell 3000 index spanning 2017 to 2022, training and testing with different subperiods.     

Stock price synchronicity to oil shocks across quantiles: Evidence from Chinese oil firms

This paper investigates behaviour of stock price synchronicity to oil shocks across quantiles for Chinese oil firms. The spillover effects of the oil market on a firm are segregated into firm-specific and market-wide information. First, our results report a higher level of synchronicity by dynamic conditional correlations than by R-square since the former better captures dynamic linear dependence. Second, we find strong evidence of size effect. In particular, stock price synchronicity is generally higher in large-cap firms than in small-cap ones. Oil shocks affect synchronicity in the upper quantiles differently based on firm size. Third, we also find that synchronicity responds to oil shocks significantly in extreme low quantiles, implying that shocks in the oil market are transmitted to Chinese oil firms via firm-specific information. Finally, we determine that oil shocks have little or no immediate impact on stock price synchronicity; instead, cumulative lagged effect is evident. This evidence highlights the lagging effect of spillover of oil shocks on Chinese oil firms.     

The Impact of Monetary Policy and Housing-Purchase Restrictions on Housing Prices in China

This paper examines the level and volatility effect of monetary policy on housing prices in China utilizing a novel set of housing price indices constructed by (Fang, H., QuanlinGu, W. X., & Zhou, L.-A. (2015). Demystifying the Chinese housing boom. NBER Macroeconomics Annual 2015, Volume 30. University of Chicago Press.). We find that in the long-run, average housing prices react positively to inflation, money supply and bank lending growth, and negatively to the reserve requirement ratio and benchmark lending rate. Housing prices in Tier 1 cities respond more sensitively to monetary shocks relative to Tier 2 and 3 cities, possibly due to surging demand and limited supply under housing-purchase restrictions (HPR). We further study the volatility effect of monetary shocks using the GARCH model and find that the benchmark lending rate, reserve requirement ratio and money supply growth have strong negative impact on the volatility of housing price growth. Our benchmark results remain robust after incorporating the HPR policy variable in the estimation, with a significant negative effect of HPR on housing price growth in Tier 1 and Tier 2 cities. Lastly, we conclude with recommendations on future monetary policy design and implementation, with a specific focus on the heterogeneous characteristics of China’s housing market.     

油价冲击、货币政策调整与产出波动——基于中国的经验证据

本文基于我国2001-2010年宏观经济月度数据,采用SVAR模型分析了国际油价波动时,央行货币政策在排除回应油价干扰与未排除干扰下的反应差异及油价波动对产出的影响。研究发现,在排除货币政策回应油价波动干扰后,通过脉冲响应函数反映的油价波动对产出的短期负面影响消失。方差分解结果显示,长期内产出波动由油价冲击和货币政策解释的比例分别为5716%和32480%,比排除干扰前分别下降了2569%和4560%。这说明我国油价冲击带来的经济衰退主要是因为货币政策及其回应油价冲击紧缩所致。此外,面对油价的短期冲击,CPI指数并未随着生产者购进价格指数上升而上升,产出也未发生明显的衰减;但在较长时间内,油价上升会因为相对价格的改变,而影响CPI水平和货币政策,从而对产出产生显著的负面影响。     

伦敦黄金市场的运行与监管模式

伦敦黄金市场不仅是地理意义上的概念,其主要指以电话或路透等电子交易系统联接起来的、向全球提供黄金和白银基准价格以及清算服务的全球交易网络。该文从伦敦黄金市场发展历程、交易与清算机制、会员管理、交易产品、英格兰银行在伦敦黄金市场中的作用,以及黄金市场的监管模式等方面,对其运行和监管情况进行了系统性介绍。     

Pricing mortgage insurance contracts under housing price cycles with jump risk: evidence from the U.K. housing market

Previous studies have investigated the determinants of housing price cycles in the housing market; however, we observed the phenomenon of housing price jumps in the 2007 subprime crisis. This paper presents a discussion on the housing price cycle and abnormal price jumps to describe the behavior of housing prices in the United Kingdom. The empirical results show that the impact factors of housing cycles are market risk and the switching factor. Furthermore, the impact factors of jump risks include the bursting of the housing bubble and financial crises. Therefore, in this paper, we employ the Markov switching model with jump risks to value the MI contracts and analyze the influences of housing price cycles, jump risks, risks of market interest rate, and the prepayment risks on MI premiums. The results of sensitivity analysis show that more volatile housing price index returns, as well as longer periods of higher volatility in housing prices, raise MI premiums. Moreover, the MI premium is positively related to the absolute value of the average jump amplitude and the shock frequency of abnormal events. There is the tradeoff between the market interest rate and the prepayment risk. The influences of market interest rate are different on MI premium with/without prepayment risks.