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Howard Zhang

Howard Zhang
Vice President, MSCI Research

About the Contributor

Howard Zhang is a member of MSCI’s Equity Core Research team. His areas of expertise include equity factor models, data science and machine learning. Howard holds a master’s degree in mathematics of finance from Columbia University. He is a CFA® charterholder and certified FRM.

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Contributions by Howard Zhang

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  1. BLOG

    Is There a Hedge-Fund-Crowding Factor? 

    Mar 10, 2021 Howard Zhang , George Bonne

    Factor Investing

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    Hedge funds held heavy, relatively illiquid short positions in crowded stocks before the January 2021 short squeeze. We created a risk factor that added explanatory power and may provide insights into potential short squeezes and other risks.

  2. BLOG

    Are (Stock) Bubbles Rising? 

    Feb 12, 2021 George Bonne , Howard Zhang , Jay Yao

    Factor Investing

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    How does one identify or quantify a bubble? We propose a framework for assessing the “bubbliness” of stocks and portfolios, rooted in the idea that bubbles are driven by the same forces, and share characteristics with crowded trades.

  3. BLOG

    Measuring Firms’ Remote-Workforce Abilities 

    Jul 14, 2020 Howard Zhang , Daniel R. Barrera , Manuel Rueda

    Factor Investing , Factors

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    It’s clear that some companies were better positioned to take advantage of a remote work environment than others. We built a hypothetical “remote-operation capacity” factor to seek to measure the effect on different firms.

  4. COVID-19 disrupted the operating models of many businesses and forced a shift to remote working, digitization and low-contact transactions and services, which we term “Remote Operation Capability” (ROC). Some corporations were better positioned to take advantage of a remote, automated and digitized operating environment. We utilized machine-learning and natural language-processing techniques to build a potential ROC factor that looks at the extent to which a company was more likely to thrive in such an environment. The techniques we present potentially could be leveraged to capture other emerging or long-term themes.

  5. Peer selection and understanding relationships between companies play a pivotal role in many areas of finance. Previously, we described a methodology for quantifying the similarity between every pair of companies from the text of their business descriptions in 10-K filings, fundamentals, news mentions and return correlations. We showed how the resulting similarity score matrix could be used to identify pairs or groups of similar companies (peers), which have numerous potential applications. Here we analyze ways to use this data for modeling simple hedging portfolios, minimum-volatility (min vol) portfolios and optimized hedging portfolios.

  6. Peer selection plays a central role in many aspects of finance — including valuation, financial and competitive analysis, risk and portfolio modeling and ESG scoring and alpha generation. One common method of peers identification is industry classification, such as the Global Industry Classification Standard (GICS®). Here we ask if it’s possible to identify and measure relationships between companies from a systematic analysis of various types of data, including fundamentals, news and the text in company filings, and whether this data can help us better understand company relationships and the risks they may bring.

  7. We examine the trading activity and pricing structure in the equity options market to infer the sentiment of options traders on the underlying equity. We find that metrics constructed from the level of options trading activity relative to the underlying stock and from comparing the pricing of puts relative to calls at various moneyness levels have implications for the cross section of stock returns. Importantly, we also find that the information in options sentiment is additive and orthogonal to what is explained by other common style factors such as value and momentum, or by other measures of sentiment such as those derived from short interest or analyst revisions.

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