Does Social Media Sentiment Matter in the Pricing of U.S. Stocks?

Although the models cannot entirely capture the reality, they are essential in the analysis and problem solving, and the same could be said about asset pricing models. These models had a long journey from the CAPM model to the most recent Fama French five-factor model. However, the asset pricing models still rely on fundamentals, and as we see in the practice every day, the financial markets or investors are not always rational, and prices tend to deviate from their fundamental values. Past research has already suggested that the assets are driven by both the fundamentals and sentimen. The novel research of Koeppel (2021) continues in the exploration of the hypothesis mentioned above and connects the sentiment with the factors in Fama´s and French´s methodology. The most interesting result of the research is the construction of the sentiment risk factor based on the direct search-based sentiment indicators. The data are sourced by the MarketPsych that analyze information flowing on social media. For comparison, public news is not a source of such exploitable sentiment indicator.

The sentiment score extracted from social media can be exploited to augment the Fama French five factors model. Based on the results, this addition seems to be justified. Adding the sentiment to the pure fundamental model explains more variation and reduce the alphas (intercepts). Moreover, the factor is unrelated to the well-known and established risk factors utilized in the previous asset pricing models, including the momentum. Finally, the sentiment factor seems to be outperforming several other factors, even those established as the smart beta factors.

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A Robust Approach to Multi-Factor Regression Analysis

Practitioners widely use asset pricing models such as CAPM or Fama French models to identify relationships between their portfolios and common factors. Moreover, each asset class has some widely-recognized asset pricing model, from equities through commodities to even cryptocurrencies. 

However, which model can we use if our portfolio is complex and consists of many asset classes? Which factors should we include and which should we omit? (Especially if we have a database that consists of several hundreds of potential factors). Additionally, we know that equities influence bonds, commodities influence equities and vice versa. Hence the question, what about the cross-asset relationships? 

These are the problems and questions we faced when looking for a methodology for our Multi-Factor Analysis report in the Quantpedia Pro platform. This blog post aims to introduce the model, its logic and the method we have decided to use. 

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Large Cap Analysis

Every week, through these posts, we point to interesting academic research papers. This week´s blog is slightly different, yet no less engaging. This blog includes numerous interesting charts from more than hundred charts in the CUSTOM REPORT: U.S. LARGE INDEX by the PHILOSOPHICAL ECONOMICS using OSAM Research Database. The report consists of the visually presented analysis of the U.S. Large index. The analysis includes the composition, returns, individual stocks, sector and factor allocations, and six fundamentals. The report contains comprehensive information about the large caps in the U.S. market from 1963 to 2020 and is worthy of a look.

We wish you all Merry Christmas …

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The Active vs Passive: Smart Factors, Market Portfolio or Both?

While there may be debates about passive and active investing, and even blogs about the numbers of active funds that were outperformed by the market, the history taught us that the outperformance of active or passive investing is cyclical. As a proxy for the active investing, the new Quantpedia’s research paper examines factor strategies and their smart allocation using fast or slow time-series momentum signals, the relative weights based on the strength of the signals and even blending the signals. While the performance can be significantly improved, using those smart approaches, the factors still got beaten by the market in both US and EAFE sample. However, the passive approach did not show to be superior. The factor strategies and market are significantly negatively correlated and impressively complement each other. The combined Smart Factors and market portfolio vastly outperforms both factors and market throughout the sample in both markets. With the combined approach, the ever-present market falls can be at least mitigated or profitable thanks to the factors.

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Stock Price Overreaction to ESG Controversies

Nobody can doubt that in the recent period, ESG investing has significantly grown and is a staple part of the financial markets. The academic literature has also grown with the popularity of ESG investing. The negative, mixed and positive results for ESG scores in portfolios have evolved, and generally, there is a consent that ESG scoring can be a vital part of the portfolio management process. It can be observed that in the past, the ESG scores were not priced in the equity market and still, the ESG is not priced in the corporate bond market (apart from Europe). Nowadays, the investors react to the ESG scores, but the research paper of Cui and Docherty (2020) has novel insights that investors may react too much to the ESG. Their research shows that investors overreact to the negative ESG events and stocks connected with negative ESG events sharply fall, but the prices have mean-reverting properties. As a result, there is a reversal after bad ESG events. Stocks firstly sharply fall, but then their prices are reverted to the previous values. Therefore, this paper is interesting from the market pricing or efficiency point, but it also can be utilized by a reversal investor.

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Can Analysts Predict Performance of the US and International Stocks?

Analysts recommendations are quite puzzling topic among both practitioners and academics as well. The most important question related to the analysts is straightforward: what is the value of their recommendations? The research paper of Azvedo and Müller (2020) brings light on this topic, but also explores the relation of analysts recommendations and market anomalies. In line with other literature, it seems that the recommendations are significantly more valuable in international markets compared to the US market. While the prediction ability of analysts is not present in the US market, less developed markets and markets with higher limits-to-arbitrage are connected with valuable recommendations. Secondly, using around 200 cross-sectional anomalies, authors show that analysts are more lined up with anomaly-based composite mispricing measures in international markets. Therefore, there is not a bias from analysts to recommend overvalued stocks in global markets compared to the well-developed US market. We highlight several results and tables, but the paper is full of impressive results, ideas and tables. Therefore, we invite you to read this blog post as well as the source research paper.

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Resurrecting the Value Premium

Nowadays, the value factor is a hot topic among practitioners and researchers as well. It is commonly known that equity factors have a cyclical performance, but many argue that value underperforms for too long. Therefore, many say that the classical HML value factor of Fama and French is dead. On the other hand, there is an emerging amount of research papers that study the value investing with an aim to make some alterations that would result in a profitable factor as the classic B/M ratio looks like it’s not a sensible value factor anymore. This branch of literature was recently enriched by novel research of Blitz and Hanauer (2020). By including more value metrics, altering the investment universe and applying basic risk management techniques, value strategy can become profitable in the long term. Although the modification is sensible, it stills suffer in a recent period. Only time will tell whether the novel resurrected value factors would emerge again as many times in the past…

Authors: David Blitz and Matthias X. Hanauer

Title: Resurrecting the Value Premium

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First-Half Month Cash-Flow News and Momentum in Stocks

Stock prices react to the new information that investors continually receive from many sources. There are some major events, which are commonly connected with a new piece of information and subsequent reactions of investors. For example, quarterly earnings-announcements are the cause of the post-earnings announcement drift or PEAD. According to the PEAD, prices tend to continue to drift up (down) after positive (negative) news. But news related to quarterly announcements is not the only important information. A novel research paper written by the Hong and Yu explores implications of the month-end reporting, analyst revisions and management guidance that are coming to market usually in the first half of each month and are also connected with drifts that offer practitioners profitable opportunities.

Authors: Claire Yurong Hong and Jialin Yu

Title: Month-End Reporting, Cash-Flow News, and Asset Pricing

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Settling the Size Matter

Equity factors are not as straightforward as they may seem to be. There is an ongoing debate about their usability or expected return since they have a cyclical nature. Moreover, the modern trend of smart beta only fuels this debate. Novel research by Blitz and Hanauer examines the size factor and sheds some light on this elusive anomaly. The size seems to be weak as a stand-alone factor, but it’s far from useless. The academic paper suggests that the size factor can be an important addition to the other equity factors as it helps to unlock the full potential of the quality, value or momentum factors.

Authors: Blitz, David and Hanauer, Matthias Xaver

Title: Settling the Size Matter

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