Jennifer Huang

Component-Based Face Recognition with 3D Morphable Models

We present a system for pose and illumination invariant face recognition that combines two recent advances in the computer vision field: 3D morphable models and component-based recognition. A 3D morphable model is used to compute 3D face models from three input images of each subject in the training database. The 3D models are rendered under varying pose and illumination conditions to build a large set of synthetic images. These images are then used for training a component-based face recognition system. The face recognition module is preceded by a fast hierarchical face detector resulting in a system that can detect and identify faces in video images at about 4 Hz. The system achieved a recognition rate of 88% on a database of 2000 real images of ten people, which is significantly better than a comparable global face recognition system. The results clearly show the potential of the combination of morphable models and component-based recognition towards pose and illumination invariant face recognition.

Face Recognition Using Component-Based SVM Classification and Morphable Models

We present a novel approach to pose and illumination invariant face recognition that combines two recent advances in the computer vision field: component-based recognition and 3D morphable models. In a first step a 3D morphable model is used to generate 3D face models from only two input images from each person in the training database. By rendering the 3D models under varying pose and illumination conditions we then create a vast number of synthetic face images which are used to train a component-based face recognition system. In preliminary experiments we show the potential of our approach regarding pose and illumination invariance.

Component-based face recognition with 3D morphable models

We present a system for pose and illumination invariant face recognition that combines two recent advances in the computer vision field: 3D morphable models and component-based recognition. A 3D morphable model is used to compute 3D face models from three input images of each subject in the training database. The 3D models are rendered under varying pose and illumination conditions to build a large set of synthetic images. These images are then used for training a component-based face recognition system. The face recognition module is preceded by a fast hierarchical face detector resulting in a system that can detect and identify faces in video images at about 4 Hz. The system achieved a recognition rate of 88% on a database of 2000 real images of ten people, which is significantly better than a comparable global face recognition system. The results clearly show the potential of the combination of morphable models and component-based recognition towards pose and illumination invariant face recognition.

Market liquidity, asset prices, and welfare

This paper represents an equilibrium model for the demand and supply of liquidity and its impact on asset prices and welfare. We show that, when constant market presence is costly, purely idiosyncratic shocks lead to endogenous demand of liquidity and large price deviations from fundamentals. Moreover, market forces fail to lead to efficient supply of liquidity, which calls for potential policy interventions. However, we demonstrate that different policy tools can yield different efficiency consequences. For example, lowering the cost of supplying liquidity on the spot (e.g., through direct injection of liquidity or relaxation of ex post margin constraints) can decrease welfare while forcing more liquidity supply (e.g., through coordination of market participants) can improve welfare.

Taxable and Tax-Deferred Investing: A Tax-Arbitrage Approach

We analyze an intertemporal portfolio problem with both taxable and tax-deferred retirement accounts. Using a tax-arbitrage argument, we identify conditions under which the optimal location decision (where to place an asset) is separable from the allocation decision (how much to allocate to each asset). Investors place highly taxed assets in the tax-deferred account to maximize the tax benefit and adjust their taxable portfolios to achieve the optimal risk exposure. We show that the two-account problem can be reduced to a taxable-account-only problem. The results are robust to capital gains tax deferrals, consumption and contribution decisions, and stochastic tax rates. The Author 2008. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.We analyze an intertemporal portfolio problem with both taxable and taxdeferred (retirement) accounts when investors are allowed to borrow and short-sell in taxable accounts. Using a tax-arbitrage argument, we show that the optimal location decision (of where to place an asset) is separable from the allocation decision (of portfolio composition among assets). Investors choose asset location to maximize the effective tax subsidy received for investing in tax-deferred accounts, and they derive the optimal allocation by replacing tax-deferred assets with taxable replicating portfolios and reducing the two-account problem to a taxable-account-only problem. ∗The author thanks John Cox, Stephen Ross, and especially Jiang Wang for advice and constant encouragement. The author also appreciates comments from Kenneth French, Lorenzo Garlappi, Jim Poterba, Laura Starks, Sheridan Titman, and seminar participants at Asset Location Conference at Stanford, Boston College, Cornell, Duke, MIT, New York University, Ohio State University, Penn State University, Stanford, University of British Columbia, University of Chicago, University of North Carolina, University of South California, University of Texas at Austin, Yale, and all Ph.D students at MIT finance lunch. Address correspondence to Jennifer Huang, Department of Finance, B6600, McCombs School of Business, University of Texas at Austin, Austin, TX 78712. Email: jennifer.huang@bus.utexas.edu, Phone: (512)232-9375, Fax: (512)471-5073, and Web: //www.bus.utexas.edu/Faculty/Jennifer.Huang.

Are ETFs Replacing Index Mutual Funds

We develop an equilibrium model to investigate whether an Exchange-Traded Fund (ETF) is a more efficient indexing vehicle than an Open-Ended Mutual Fund (OEF). We find that while flow-induced trading is costly to OEF investors, it is also beneficial to those investors who cause the flow -- it is simply a zero-sum game. Indeed, the OEF structure can be viewed as providing insurance for investors with liquidity shocks, and hence is beneficial for risk averse investors. However, this liquidity insurance is not without cost -- it can cause moral hazard %that induce excessive trading and reduce the OEF performance. Moreover, we find that investors with higher individual liquidity needs prefer to invest via the OEF since they benefit more from the liquidity insurance. Surprisingly, the OEF structure is still viable despite the concentration of higher-liquidity-need investors in the OEF. The reason is that flow-induced trading costs depend only on the aggregate liquidity need, not on individual liquidity needs, which cancel out at the fund level. As a result, OEFs and ETFs coexist in equilibrium with different liquidity clienteles. Finally, we derive empirical predictions that ETFs are better suited for narrower and less liquid underlying indexes, and for investors with longer investment horizons.

Market Liquidity, Asset Prices, and Welfare

This paper presents an equilibrium model for the demand and supply of liquidity and its impact on asset prices and welfare. We show that when constant market presence is costly, purely idiosyncratic shocks lead to endogenous demand of liquidity and large price deviations from fundamentals. Moreover, market forces fail to lead to efficient supply of liquidity, which calls for potential policy interventions. However, we demonstrate that different policy tools can yield different efficiency consequences. For example, lowering the cost of supplying liquidity on the spot (e.g., through direct injection of liquidity or relaxation of ex post margin constraints) can decrease welfare while forcing more liquidity supply (e.g., through coordination of market participants) can improve welfare.

Metformin and Rapamycin Reduce Pancreatic Cancer Growth in Obese Prediabetic Mice by Distinct MicroRNA-Regulated Mechanisms

Metformin treatment is associated with a decreased risk and better prognosis of pancreatic cancer (PC) in patients with type 2 diabetes, but the mechanism of metformin’s PC growth inhibition in the context of a prediabetic state is unknown. We used a Panc02 pancreatic tumor cell transplant model in diet-induced obese (DIO) C57BL/6 mice to compare the effects of metformin and the direct mammalian target of rapamycin (mTOR) inhibitor rapamycin on PC growth, glucose regulation, mTOR pathway signaling, and candidate microRNA (miR) expression. In DIO/prediabetic mice, metformin and rapamycin significantly reduced pancreatic tumor growth and mTOR-related signaling. The rapamycin effects centered on decreased mTOR-regulated growth and survival signaling, including increased expression of let-7b and cell cycle–regulating miRs. Metformin (but not rapamycin) reduced glucose and insulin levels and expression of miR-34a and its direct targets Notch, Slug, and Snail. Metformin also reduced the number and size of Panc02 tumor spheres in vitro and inhibited the expression of Notch in spheroids. Our results suggest that metformin and rapamycin can both inhibit pancreatic tumor growth in obese, prediabetic mice through shared and distinct mechanisms. Metformin and direct mTOR inhibitors, alone or possibly in combination, represent promising intervention strategies for breaking the diabetes-PC link.

MARKET STRUCTURE, SECURITY PRICES, AND INFORMATIONAL EFFICIENCY

We consider an economy with an incomplete securities market and heterogeneously informed investors. Each investor trades in the market to hedge the risk to his endowment and to speculate on future security payoffs using his private information. We examine the efficiency of the securities market in allocating risk and transmitting information under different market structures, as defined by the set of securities traded in the market. We show that the introduction of derivative securities can decrease the markets efficiency in revealing information on security payoffs, and increase the equity premium and price volatility in the market.

Government Debt and Corporate Leverage: International Evidence

We investigate the impact of government debt on corporate financing decisions. We document a negative relation between government debt and corporate leverage using data on 40 countries between 1990 and 2014. This negative relation holds only for government debt that is financed domestically and is stronger for larger and more profitable firms and in countries with more developed equity markets. In order to address potential endogeneity concerns, we use an instrumental variable approach based on military spending and a quasi-natural experiment based on the introduction of the Euro currency. Our findings suggest that government debt crowds out corporate debt.