For this month’s JQES, we decide to conduct a comprehensive review of all academic papers published in either working paper repositories or peer-reviewed journals in 2018 and 2019 year-to-date. After going through thousands of articles, we pick over 150 papers for this issue.
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On December 29th and 30th, 2018, we held our 2nd annual global quantitative and macro investing conference in New York City. Over 400 buy-side investment professionals, academics, and researchers from Europe, US, Canada, China, Japan, and Australia attended the event.
Given the strength of the US economy, surprisingly, the yield curve has been flattening this year and is almost inverted in the last few months. Finally, last week, the 10-year US treasury yield spiked to over 3.2%, hitting the highest level since May 2011, which widened the yield spread. Whether this is a temporary movement or marks the turning point of the bond market, remains to be seen. Regardless, the slope of the yield curve will be watched closely by investors, as it has an outstanding record of predicting recessions. In this month’s JQES, we provide a list of relevant academic papers on how the yield curve (yield spread) is applied in statistical models to forecast economic activities and asset pricing.
The trade conflicts sparked by President Trump’s protectionist policies against its major trading partners have unnerved the global equity market. The escalating trade war between US and China is especially concerning to investors, which could have significant implications for the global economy. In this JQES issue, we provide a list of relevant academic papers on trade policy, focusing on free trade and protectionism.
Similarly to how we prioritize our own research, we choose speakers for our QES conferences primarily on the quality of their papers. We went through thousands of academic papers published in the last 12 months and applied a hybrid machine learning plus domain expert approach to identify six academic researchers – all have new, innovative, and cutting edge research. We also presented our latest research on Systematic Alpha from Risk Arbitrage (SARA) and introduced our Port@ Analytics platform.
The year 2018 will be dominated by policy interventions. The administration’s infrastructure package is in the works after the successful passage of tax reform last year. After a decade of expansionary monetary policy, the Fed has signaled it is tightening with multiple rate hikes and balance sheet normalization on the horizon – all under a new Chairman. Investors are also watching closely the actions by the ECB and Bank of Japan. In this month’s JQES, we provide a list of some of the most influential and relevant academic papers which focus on the impact that monetary and fiscal policy have on economic conditions and asset prices.
Luo’s QES Team held an inspiring seminar on the dynamic China A share market on February 9 at Wolfe’s New York City office. Over 50 buy-side investment professionals, researchers and data scientists attended the event.
Wolfe Research’s QES team held its inaugural global quantitative and macro investing conference on November 14th and 15th in New York City. Nearly 500 buy-side investment professionals, academics, investment researchers, traditional as well as alternative data vendors, data scientist, and technologists attended the event.
This month, we highlight a paper studying how credit card payment data can be used in stock selection (see Agarwal, et al [2017). Furthermore, (see Rohal, et al ), Chew, et al  provides a relatively complete framework for textual analysis. Both credit card payment and NLP are active areas of research that we are currently pursuing. However, the relatively short history of data coverage for most alternative data sources pose a serious challenge for statistical analysis. Ledoit, et al  introduce the DCC-NL covariance matrix estimator and show how it can be used in cross-sectional market anomaly detection, especially limited data history.
This month, we highlight one recent academic paper by Löffler, et al , using linguistic tone analysis on Moody’s rating reports. Löffler, et al  research coincides with one of our recent papers (see Rohal, et al ), in which we apply NLP (Natural Language Processing) and machine learning techniques on corporate filing data from the EDGAR database. We are in the process to expand our research to other textual datasets.
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