Stock market and investment : the signaling role of the market

The author examines the role of the stock market as a signal to managers in undertaking capital expenditures. He concludes that while both managerial and market perceptions are integral, managerial perception is of greater importance. The evidence suggeststhat, as a statistic, the Q ratio is not sufficient to explain firms'capital expenditure decisions. Thus, the standard Q model of investment should be modified to provide a more meaningful description of a firm's capital spending decisions. Overall, the results suggest that stock market activity has only limited implications for the economy's resource allocation process. Evidence for the Q theory of investment confirms previous findings in the literature that the model's poor empirical perfomance was partly the result of using aggregate data for the whole economy. Also, since market perception plays only a limited role in determining capital expenditures, shareholder myopia is unlikely to result in managerial myopia. The implications for developing countries are: while the stock market may not be central to a firm's capital spending decisions, it is not a sideshow either. The market plays an important signaling role for managers. This is a powerful rationale for financial reform and capital development in developing countries. The results also suggest that complaints that stock market activity leads to misallocation of resources may be exaggerated.Economic Theory&Research,International Terrorism&Counterterrorism,Markets and Market Access,Payment Systems&Infrastructure,Fiscal&Monetary Policy,Markets and Market Access,Environmental Economics&Policies,International Terrorism&Counterterrorism,Economic Theory&Research,Access to Markets

The stockmarket as a source of finance : a comparison of U.S. and Indian firms

In seeking funding, a firm's main choice is between external and internal financing. And, says the author, the evidence suggests that the stock market plays only a limited role providing finance for both U.S. and Indian firms. The author finds that internal finance plays less of a role for Indian firms than for U.S. firms - and external debt a bigger role. This is consistent with theoretical predictions, given that information and agency problems are less severe for Indian firms than for U.S. firms. (India's financial system is predominantly bank-oriented, more like German and Japanese financial systems than American and British systems.) The author's estimate of the role of the stock market as a source of finance is lower than other estimates, partly because of methodological approach: he studied sources and uses of funds, rather than the financing of net asset growth and capital expenditures. To the extent that these findings for India are generalizable to the other developing countries - analysis was restricted to the stock market's role in providing finance - the author concludes that the development of stock markets is unlikely to spur corporate growth in developing countries. And there is a caveat: foreign investors have played only a limited role in the slow-paced privatization of India's state-owned enterprises - although in recent years, despite delayed reform of the securities market, foreign institutional investors have begun to invest more. In emerging markets in Eastern Europe and LatinAmerica, foreign investors have played a much more active role in privatization, chiefly by investing in those stock markets.International Terrorism&Counterterrorism,Payment Systems&Infrastructure,Banks&Banking Reform,Financial Intermediation,Decentralization,Economic Theory&Research,Housing Finance,International Terrorism&Counterterrorism,Financial Intermediation,Banks&Banking Reform

Second-order Temporal Pooling for Action Recognition

Deep learning models for video-based action recognition usually generate features for short clips (consisting of a few frames); such clip-level features are aggregated to video-level representations by computing statistics on these features. Typically zero-th (max) or the first-order (average) statistics are used. In this paper, we explore the benefits of using second-order statistics. Specifically, we propose a novel end-to-end learnable feature aggregation scheme, dubbed temporal correlation pooling that generates an action descriptor for a video sequence by capturing the similarities between the temporal evolution of clip-level CNN features computed across the video. Such a descriptor, while being computationally cheap, also naturally encodes the co-activations of multiple CNN features, thereby providing a richer characterization of actions than their first-order counterparts. We also propose higher-order extensions of this scheme by computing correlations after embedding the CNN features in a reproducing kernel Hilbert space. We provide experiments on benchmark datasets such as HMDB-51 and UCF-101, fine-grained datasets such as MPII Cooking activities and JHMDB, as well as the recent Kinetics-600. Our results demonstrate the advantages of higher-order pooling schemes that when combined with hand-crafted features (as is standard practice) achieves state-of-the-art accuracy.Comment: Accepted in the International Journal of Computer Vision (IJCV

Elastic Properties of Carbon nanotubes : An atomistic approach

Energetically the single sheet of graphite (graphene) is more stable than the nanotube. The energy difference between the two systems can be directly related to the strain energy involved in rolling up the graphene sheet to form the nanotube. We have carried out first principle electronic structure calculations and evaluated the strain energy as a function of the nanotube radius. The dependence of the strain energy on the diameter of the nanotube has been found by several groups to be welldescribed by a continuum elasticity model. We attempt to examine why this is the case and show where atomistics enter the description.Comment: 10 pages, 4 figure

Bulk and nano GaN: Role of Ga d states

We have studied the role of Ga 3d states in determining the properties of bulk as well as nanoparticles of GaN using PAW potentials. A significant contribution of the Ga d states in the valence band is found to arise from the interaction of Ga 4d states with the dominantly N p states making up the valence band. The errors arising from not treating the Ga 3d states as a part of the valence are found to be similar, ~ 1%, for bulk as well as for nanoclusters of GaN.Comment: 17 pages, 7 figure