Short Interests in Real Estate Investment Trusts

We examine short interests in equity real estate investment trusts (REITs) between 1994 and 2001. Our results show that only high levels (the 90th percentile) of short interest are associated with significant negative REIT returns as the bearish content of short interest may have been mitigated by the favorable risk characteristics of real estate securities. In addition, the significant negative relationship between short interest and REIT returns applies only to REITs with poor performance. The result implies that the bearish sentiment of short interest could also be mitigated by good REIT managers in a real estate market that is informationally inefficient. The results of a logistic regression model further show that the short selling of REIT shares can be explained by firm-specific factors such as operating efficiency, fundamental value, and liquidity. Given that short interest is not indiscriminately associated with negative REIT returns and that the short positions are firm-specific, the results are consistent with implications that short interests in REITs represent attempts to make short-term profits rather than general bearishness regarding real estate investments.short interest, real estate investment trusts (REITs)

Institutional Investors and ADRs: Three Essays

The three essays which constitute this research study the effects of institutional investors in the ADRs\u27 market. Essay one studies the herding and feedback trading by institutional investors in the ADRs market. The empirical results find that there is a strong positive relation between changes in the ADRs institutional ownership and returns measured over the same period—the herding year (t = month 0 to 11). The ADR portfolios experiencing the largest increase in institutional ownership outperform those experiencing the largest decrease by 15.33 percent per year over the herding year. In addition, return continuation exists for the two years following the herding year (t = month 12 to 23 and t = month 24 to 35). Further research on the post-herding year return of ADRs (t = month 12 to 23) finds that both the past year performance (t = month 0 to 11) and the change in institutional ownership (t = month 0 to 11) play a role in predicting returns of ADRs (t = month 12 to 23). It is also found that ADR institutional investors\u27 herding is positively related to lagged returns, which indicates positive feedback trading by institutional investors of ADRs. The results also confirm that institutional investors participate in momentum strategies, but they do not always herd to past winners and herd away from past losers. The results imply that information is a very important factor in determining institutional herding in the ADRs market. Essay two tests the hypothesis that private information of institutional investors contributes to serial correlations in ADRs daily returns. The results demonstrate that ADR individual security and portfolio daily return autocorrelations are positively related to ADRs\u27 institutional ownership. The results show that ADR portfolios with high institutional ownerships exhibit greater daily return autocorrelations, and the returns on these portfolios lead the returns on ADR portfolios with low institutional ownerships. Thus institutional trading of ADR increases the speed with which information is reflected in prices. The empirical results show that other explanations, such as nonsynchronous trading, bid-ask spread and volatility of ADRs, cannot explain the positive relation between daily return autocorrelations and institutional ownership of ADRs. Essay three examines the effects of noise in the ADR market. The empirical results show that ADR return is affected by investor sentiment. ADR return increases (decreases) when investors are irrationally optimistic (pessimistic). We also find that in the low-noise period, ADRs with high institutional ownership exhibit autocorrelation similar to ADRs with low institutional ownership. However, in the high-noise period. ADRs with high institutional ownership exhibit significant higher autocorrelation than ADRs with low institutional ownership. The result implies institutional investors may have engaged in stealth trading to exploit a noisy market. Through a Granger causality regression, we find that returns on ADR portfolios with high institutional ownership lead the returns of those with low institutional ownership in the low-noise period, confirming that institutional trades reflect market information that is ultimately incorporated into other securities. Finally, we find that institutional investors help reduce volatilities of European ADRs returns. However, for ADRs from Asia and South America, the magnitude of the stabilizing arbitrage positions taken by rational investors is insignificant

New techniques of multiple integral field spectroscopy

The work of this thesis is to investigate new techniques for Integral Field Spectroscopy (IPS) to make the most efficient use of modem large telescopes. Most of the work described is aimed at the FMOS for the SUBARU 8m telescope. Although this is primarily a system for Multiple Object Spectroscopy (MOS) employing single fibres, there is an option to include a multiple-IFS (MIPS) system. Much of this thesis is therefore aimed at the design and prototyping of critical systems for both the IPS and MOS modes of this instrument. The basic theory of IFU design is discussed first. Some particular problems are described and their soludons presented. The design of the MIPS system is described together with the construction and testing of a prototype deployable IFU. The assembly of the pickoff/fore-optics, microlens array and fibre bundle and their testing are described in detail. The estimated performance of the complete module is presented together with suggestions for improving the system efficiency which is currently limited by the performance of the microlens array. The prototyping of the MIPS system is supported by an extensive programme of testing of candidate microlens arrays. Another critical aspect of the instrument is the ability to disconnect the (IPS and MOS) fibre input which is installed on a removable prime focus top-end ring from the spectrographs which are mounted elsewhere on the telescope. This requires high-performance multiple fibre connectors. The designs of connectors for the MOS and IPS modes are described. Results from the testing of a prototype for the MOS mode are presented. This work is supported by a mathematical model of the coupling efficiency which takes into account optical aberrations and alignment errors. The final critical aspect of FMOS which has been investigated is the design of the spectrographs. The baseline system operates in the near-infrared (NIR) but an additional visible channel is an option. Efficient designs for both the visible and NIR systems are presented. The design of the NIR spectrograph presents challenges in the choice of materials for the doublet and triplet lenses employed. The choice of material and the combinations in which they can be used are described. This thesis shows that all these critical aspects of FMOS have good solutions that will result in good performance of the whole instrument. For the multiple IFU system, the prototype demonstrates acceptable performance which can be made excellent by the use of a better microlens array. The multiple fibre connector prototype already indicates excellent performance. Finally, the spectrograph designs presented should result in high efficiency and good image quality

Cascaded Scene Flow Prediction using Semantic Segmentation

Given two consecutive frames from a pair of stereo cameras, 3D scene flow methods simultaneously estimate the 3D geometry and motion of the observed scene. Many existing approaches use superpixels for regularization, but may predict inconsistent shapes and motions inside rigidly moving objects. We instead assume that scenes consist of foreground objects rigidly moving in front of a static background, and use semantic cues to produce pixel-accurate scene flow estimates. Our cascaded classification framework accurately models 3D scenes by iteratively refining semantic segmentation masks, stereo correspondences, 3D rigid motion estimates, and optical flow fields. We evaluate our method on the challenging KITTI autonomous driving benchmark, and show that accounting for the motion of segmented vehicles leads to state-of-the-art performance.Comment: International Conference on 3D Vision (3DV), 2017 (oral presentation

Bounds for deterministic and stochastic dynamical systems using sum-of-squares optimization

We describe methods for proving upper and lower bounds on infinite-time averages in deterministic dynamical systems and on stationary expectations in stochastic systems. The dynamics and the quantities to be bounded are assumed to be polynomial functions of the state variables. The methods are computer-assisted, using sum-of-squares polynomials to formulate sufficient conditions that can be checked by semidefinite programming. In the deterministic case, we seek tight bounds that apply to particular local attractors. An obstacle to proving such bounds is that they do not hold globally; they are generally violated by trajectories starting outside the local basin of attraction. We describe two closely related ways past this obstacle: one that requires knowing a subset of the basin of attraction, and another that considers the zero-noise limit of the corresponding stochastic system. The bounding methods are illustrated using the van der Pol oscillator. We bound deterministic averages on the attracting limit cycle above and below to within 1%, which requires a lower bound that does not hold for the unstable fixed point at the origin. We obtain similarly tight upper and lower bounds on stochastic expectations for a range of noise amplitudes. Limitations of our methods for certain types of deterministic systems are discussed, along with prospects for improvement.Comment: 25 pages; Added new Section 7.2; Added references; Corrected typos; Submitted to SIAD