Modeling Financial Time Series with Artificial Neural Networks

Financial time series convey the decisions and actions of a population of human actors over time. Econometric and regressive models have been developed in the past decades for analyzing these time series. More recently, biologically inspired artificial neural network models have been shown to overcome some of the main challenges of traditional techniques by better exploiting the non-linear, non-stationary, and oscillatory nature of noisy, chaotic human interactions. This review paper explores the options, benefits, and weaknesses of the various forms of artificial neural networks as compared with regression techniques in the field of financial time series analysis.CELEST, a National Science Foundation Science of Learning Center (SBE-0354378); SyNAPSE program of the Defense Advanced Research Project Agency (HR001109-03-0001

The Construction and Related Industries in a Changing Socio-Economic Environment: The Case of Hong Kong

Hong Kong is well known for its “housing market bubble”. Both theoretical and empirical studies point to the supply side being the “root of all evil”. This paper takes a preliminary step in understanding the supply side of the Hong Kong market by investigating the construction and related industries. After taking into consideration of the unusual public expenditure, the construction industry seems to be “normal” in international standard. Its relationship with the aggregate economy is also examined. Directions for future research are also suggested.housing, construction, government policy, employment, investment

A New Hybrid Framework to Efficiently Model Lines of Sight to Gravitational Lenses

In strong gravitational lens systems, the light bending is usually dominated by one main galaxy, but may be affected by other mass along the line of sight (LOS). Shear and convergence can be used to approximate the contributions from less significant perturbers (e.g. those that are projected far from the lens or have a small mass), but higher order effects need to be included for objects that are closer or more massive. We develop a framework for multiplane lensing that can handle an arbitrary combination of tidal planes treated with shear and convergence and planes treated exactly (i.e., including higher order terms). This framework addresses all of the traditional lensing observables including image positions, fluxes, and time delays to facilitate lens modelling that includes the non-linear effects due to mass along the LOS. It balances accuracy (accounting for higher-order terms when necessary) with efficiency (compressing all other LOS effects into a set of matrices that can be calculated up front and cached for lens modelling). We identify a generalized multiplane mass sheet degeneracy, in which the effective shear and convergence are sums over the lensing planes with specific, redshift-dependent weighting factors.Comment: 13 pages, 2 figure

Are the markets for factories and offices integrated? Evidence from Hong Kong?

Due to the relocation of manufacturing facilities from Hong Kong to Mainland China, it is widely believed that some vacant private factories have been used as offices in Hong Kong. Yet there is no direct and systematic evidence to support this speculation. In fact, according to MacGregor and Schwann (2003), industrial and commercial real estate shares some common features. Our research attempts to investigate empirically the price and volume relationship between industrial and commercial real estate, using both aggregate and disaggregate data from the industrial and commercial property markets in Hong Kong. The study was built on the observation that economic restructuring and geographical distance will affect the substitutability (and thus the correlation) of different types of property, and utilizes commonly used time series techniques for analysis. Policy implications are discussed.aggregation bias, geographical distance, industrial real estate, substitutability

Optimal Mass Configurations for Lensing High-Redshift Galaxies

We investigate the gravitational lensing properties of lines of sight containing multiple cluster-scale halos, motivated by their ability to lens very high-redshift (z ~ 10) sources into detectability. We control for the total mass along the line of sight, isolating the effects of distributing the mass among multiple halos and of varying the physical properties of the halos. Our results show that multiple-halo lines of sight can increase the magnified source-plane region compared to the single cluster lenses typically targeted for lensing studies, and thus are generally better fields for detecting very high-redshift sources. The configurations that result in optimal lensing cross sections benefit from interactions between the lens potentials of the halos when they overlap somewhat on the sky, creating regions of high magnification in the source plane not present when the halos are considered individually. The effect of these interactions on the lensing cross section can even be comparable to changing the total mass of the lens from 10^15 M_sun to 3x10^15 M_sun. The gain in lensing cross section increases as the mass is split into more halos, provided that the lens potentials are projected close enough to interact with each other. A nonzero projected halo angular separation, equal halo mass ratio, and high projected halo concentration are the best mass configurations, whereas projected halo ellipticity, halo triaxiality, and the relative orientations of the halos are less important. Such high mass, multiple-halo lines of sight exist in the SDSS.Comment: Accepted for publication in ApJ; emulateapj format; 24 pages, 13 figures, 1 table; plots updated to reflect erratu

In vivo imaging of protease activity by Probody therapeutic activation.

Probody™ therapeutics are recombinant, proteolytically-activated antibody prodrugs, engineered to remain inert until activated locally by tumor-associated proteases. Probody therapeutics exploit the fundamental dysregulation of extracellular protease activity that exists in tumors relative to healthy tissue. Leveraging the ability of a Probody therapeutic to bind its target at the site of disease after proteolytic cleavage, we developed a novel method for profiling protease activity in living animals. Using NIR optical imaging, we demonstrated that a non-labeled anti-EGFR Probody therapeutic can become activated and compete for binding to tumor cells in vivo with a labeled anti-EGFR monoclonal antibody. Furthermore, by inhibiting matriptase activity in vivo with a blocking-matriptase antibody, we show that the ability of the Probody therapeutic to bind EGFR in vivo was dependent on protease activity. These results demonstrate that in vivo imaging of Probody therapeutic activation can be used for screening and characterization of protease activity in living animals, and provide a method that avoids some of the limitations of prior methods. This approach can improve our understanding of the activity of proteases in disease models and help to develop efficient strategies for cancer diagnosis and treatment

Accent in digital humanities and language studies: the case in Hong Kong

This paper argues for the importance of the awareness of “DH accent” and demonstrates with examples in English studies how a localised variation of the curriculum facilitates students’ learning in the classroom and at the curriculum level. This study identifies the problem that studies in digital humanities have focused on the Anglo-American world. We demonstrate with an example in the Hong Kong context that even a curriculum of English language studies requires adaptation for the local needs, such as focus on second language learning and knowledge of contrastive grammar with the local language. To achieve these goals, instructors integrate materials that are tailored for students of language studies, who are typically proficient in humanistic argumentation and concepts but less fluent in digital skills. Use cases in teaching and examples of student projects are shown to illustrate the outcome of learning. The study presents important educational implication and direction for future research and education of the digital humanities

Housing Price Dispersion: An Empirical Investigation

price dispersion, search models, macroeconomic factor, time aggregation