
November 2023 Update
November 3, 2023 — October 2023 was a weak month for financial markets, with bonds, stocks, and commodities all down. Though interest rates continued to
November 3, 2023 — October 2023 was a weak month for financial markets, with bonds, stocks, and commodities all down. Though interest rates continued to
October 3, 2023 — In an apt metaphor for the month, JFK Airport in New York saw 8 inches of rain last Friday, a record
September 4, 2023 — As the summer winds down and kids get ready to go back to school (and as the U.S. men and women
August 3, 2023 — We’ve had many conversations with people asking us about tax strategies. In response, we’ve done a deep-dive into the topic on
July 31, 2023 — This is our white paper on tax-loss harvesting: download paper. (Photo by L.D.I.A on Unsplash)
July 6, 2023 — June was a strong month for QuantStreet, continuing our outperformance relative to a number of asset allocation benchmarks since launch.[1] In
June 3, 2023 — May was a good month for QuantStreet, continuing our outperformance relative to a number of asset allocation benchmarks since launch.1 We
May 4, 2023 — This month, we are changing how we share our research with readers and clients. We will try to keep the present
April 6, 2023 — March 2023 represented a drastic change in the narrative that had prevailed in markets for most of 2022 and early-2023. The
An increase in “unusual” news with negative sentiment predicts an increase in stock market volatility. Unusual positive news forecasts lower volatility. Our analysis is based on over 360,000 articles on 50 large financial companies, published during the period of 1996–2014…
We develop a classification methodology for the context and content of news articles to predict risk and return in stock markets in 51 developed and emerging economies. A parsimonious summary of news, including topic-specific sentiment, frequency, and unusualness (entropy) of word flow…
We analyze methods for selecting topics in news articles to explain stock returns. We find, through empirical and theoretical results, that supervised Latent Dirichlet Allocation (sLDA) implemented through Gibbs sampling in a stochastic EM algorithm will often overfit returns to the detriment…
In the movie “True Lies,” Arnold Schwarzenegger plays the role of a skilled spy. In one scene, he is injected with truth serum in preparation for interrogation. Under the influence of the truth serum, he reveals how he plans to kill his captors and escape and then applies his skills and weapons…
We develop a model of information and portfolio choice in which ex ante identical investors choose to specialize because of fixed attention costs required in learning about securities. Without this friction, investors would invest in all securities and would be indifferent across a wide range of information choices…
We develop a model of investor information choices and asset prices where the availability of information about fundamentals is time-varying. A competitive research sector produces more information when more investors are willing to pay for that research…
Technical analysis, also known as charting,’ has been part of financial practice for many decades, but this discipline has not received the same level of academic scrutiny and acceptance as more traditional approaches such as fundamental analysis. One of the main obstacles is the highly subjective nature of technical analysis…
The well-documented underreaction of stock prices to news exhibits substantial time variation. We show that higher risk-bearing capacity of financial intermediaries, lower passive ownership of stocks, and greater informativeness of news increase price responses to contemporaneous news…
We study the performance of many traditional and novel, text-based variables for in-sample and out-of-sample forecasting of oil spot, futures, and energy company stock returns, and changes in oil volatility, production, and inventories. After controlling for small-sample biases, we find evidence of in-sample predictability…
The initial phase of the COVID-19 pandemic was characterized by voluminous, highly negative news coverage. Markets overreacted to uninformative news, and reacted more to news during high volatility periods. News coverage responded to lagged market activity, and causally impacted contemporaneous returns…