Periods of high mortgage interest rates that characterized the early 1980s have escalated the use of assumption financing in home buying. In these periods, there is an increased demand for alternative sources of financing and a movement away from conventional sources. The purpose of this study is to provide a theoretical and empirical analysis of the effect of the increased use of assumption financing on selling prices of single-family residential housing. Aside from physical characteristics, the financing arranged by the homebuyer is considered a major influence in determining house prices. This is especially true in real estate appraisal practice where differences in types of financing are one of the major categories of adjustment (see [1], [4], and [10]).

Frank K. Reilly, Ralph E. Smith, Glenn L. Johnson, A Correction and Update Regarding Individual Common Stocks as Inflation Hedges, The Journal of Financial and Quantitative Analysis, Vol. 10, No. 5 (Dec., 1975), pp. 871-880

The results of this study indicate that the individual common stocks in the Dow-Jones. Industrial Average were not consistent inflation hedges. Assuming an 8.2 percent normal required rate of return, none of the common stocks was a complete inflation hedge during all three recent inflationary periods tested. Even assuming a zero normal required rate of return á la traditional investment theory, only six (20 percent) of the thirty common stocks sampled were inflation hedges during all three inflationary periods.

Beginning in the 1990s, firms often continue to trade on the major national exchanges after Chapter 11 bankruptcy filings. For bankruptcies filed from 1993–2003, we find that the more negative the filing period price reaction, the more favorable the immediate post-filing returns, on average. This reversal is not attributable to bid-ask bounce, it holds after controlling for other factors associated with post-filing returns, and it appears more attributable to the activities of large traders than to small traders. Supplementary tests reveal that the pattern of post-filing returns differs significantly for bankruptcies filed in bull versus bear markets. Bankruptcies filed during the 1993 to 1999 bull market enjoy substantial but short-lived reversals averaging one-third of the filing period price plunge. These reversals are inconsistent with efficient assimilation of the bankruptcy information. In contrast, we find no evidence of post-filing reversals for bankruptcies filed from 2000 to 2003.

We examine whether political corruption impedes innovation. Using a comprehensive sample of U.S. firms, we find that corruption has a substantial, negative relation with the quantity and quality of innovation. These results are robust to using various fixed effects, proxies for corruption and innovation, and subsamples. To establish causality, we employ 2 instruments for corruption: local ethnic diversity and the corruption of the state a firm’s founder grew up in. Corruption appears to reduce innovation output both on average and for the most innovative firms. Overall, this evidence is consistent with the notion that corruption reduces social welfare by impeding innovation.

Using comprehensive account-level data, we separate Chinese retail investors into 5 groups and document strong heterogeneity in trading dynamics and performances. Retail investors with smaller account sizes cannot predict future returns correctly, display daily momentum patterns, fail to process public news, and show overconfidence and gambling preferences, while retail investors with larger account balances predict future returns correctly, display contrarian patterns, and incorporate public news in trading. Using performance measures established in previous literature, we find that smaller retail investors suffer from poor stock selection abilities and trading costs, while large retail investors’ stock selection abilities are offset by trading costs.

This article presents a unique test of the effectiveness of technical analysis in different sentiment environments by focusing on its usage by perhaps the most sophisticated and astute investors, namely, hedge fund managers. We document that during high-sentiment periods, hedge funds using technical analysis exhibit higher performance, lower risk, and superior market-timing ability than nonusers. The advantages of using technical analysis disappear or even reverse in low-sentiment periods. Our findings are consistent with the view that technical analysis is relatively more useful in high-sentiment periods with larger mispricing, which cannot be fully exploited by arbitrage activities because of short-sale impediments.

The growing popularity of home-sharing platforms such as Airbnb, partly fueled by hosts’ ability to evade local taxes and regulations, has been shown to elevate housing costs by reallocating long-term housing units to the short-term rental market. This study assesses whether enhanced tax enforcement can mitigate this trend. We analyze staggered tax collection agreements between Airbnb and Florida counties, wherein Airbnb collects taxes from the hosts directly. Using a difference-in-differences methodology, we find these agreements significantly slow the growth of housing costs, highlighting the importance of tax policy in addressing the sharing economy’s influence on housing affordability.