Prediction of photoperiodic regulators from quantitative gene circuit models

Photoperiod sensors allow physiological adaptation to the changing seasons. The external coincidence hypothesis postulates that a light-responsive regulator is modulated by a circadian rhythm. Sufficient data are available to test this quantitatively in plants, though not yet in animals. In Arabidopsis, the clock-regulated genes CONSTANS (CO) and FLAVIN, KELCH, F-BOX (FKF1) and their lightsensitive proteins are thought to form an external coincidence sensor. We use 40 timeseries of molecular data to model the integration of light and timing information by CO, its target gene FLOWERING LOCUS T (FT), and the circadian clock. Among other predictions, the models show that FKF1 activates FT. We demonstrate experimentally that this effect is independent of the known activation of CO by FKF1, thus we locate a major, novel controller of photoperiodism. External coincidence is part of a complex photoperiod sensor: modelling makes this complexity explicit and may thus contribute to crop improvement

Information diffusion in the U.S. real estate investment trust market

This study examines the information diffusion process in the U.S. Real Estate Investment Trust (REIT) market with a focus on the impacts of changing market environments, information supply, and information demand on the lead-lag effect. The results suggest that a significant lead-lag relationship exists between the lagged returns of big REITs and the current returns of small REITs. This relationship has slightly decreased along with policy and environment changes that occurred in the U.S. REIT market during the study period from 1986 to 2012, while still remaining significant in the most recent REIT market. The process of information diffusion is becoming unstable in recent years and the reverse lead-lag effect from small REITs to big REITs is observed especially when REIT market liquidity and return volatility are high. The lead-lag effect among REITs is driven largely by slow adjustment to negative information, which is magnified by a lack of information supply, especially as demand for such information increases. Finally, information flow from REITs with more media coverage to those with less media coverage becomes even more sluggish than the information flow from big REITs to small REITs

The macroeconomic effects of Government asset purchases: evidence from postwar US housing credit policy

We document the portfolio activity of federal housing agencies and provide evidence on its impact on mortgage markets and the economy. Through a narrative analysis, we identify historical policy changes leading to expansions or contractions in agency mortgage holdings. Based on those regulatory events that we classify as unrelated to short-run cyclical or credit market shocks, we find that an increase in mortgage purchases by the agencies boosts mortgage lending and lowers mortgage rates. Agency purchases influence prices in other asset markets and stimulate residential investment. Using information in GSE stock prices to construct an alternative instrument for agency purchasing activity yields very similar results as our benchmark narrative identification approach

Modeling and Estimation of Synchronization in Multistate Markov-Switching Models

This paper develops a Markov-Switching vector autoregressive model that allows for imperfect synchronization of cyclical regimes in multiple variables, due to phase shifts of a single common cycle. The model has three key features: (i) the amount of phase shift can be different across regimes (as well as across variables), (ii) it allows the cycle to consist of any number of regimes J ≥ 2, and (iii) it allows for regime-dependent volatilities and correlations. In an empirical application to monthly returns on size-based stock portfolios, a three-regime model with asymmetric phase shifts and regime-dependent heteroscedasticity is found to characterize the joint distribution of returns most adequately. While large- and small-cap portfolios switch contemporaneously into boom and crash regimes, the large-cap portfolio leads the small-cap portfolio for switches to a moderate regime by a month