Music sentiment and stock returns around the world
There was a time in history when researchers believed that the human species ultimately acted rationally and rationally (for example, when dealing with economic problems). What was brought about by the emergence of animal spirits (Keynes) and later pioneers of behavioral finance such as Kahneman and Tversky was a recognition that this was different. We often do not do what is in our best interest. Quite the opposite. These sentiments hardly agree with normal logic, but they cause market anomalies.
Researchers love finding the causes and reasons and linking behavioral anomalies to stock market performance.Many anomalies are related to various problems Sentiment measuresderived from alternative data Source and today we introduce an interesting new potential relationship where investor mood and sentiment supersede music sentiment.
This study introduces a new measure of investor sentiment that captures actual sentiment rather than shocks to sentiment. (Edmans et al., 2021)’s main finding is a positive and significant relationship between music sentiment and contemporaneous market returns, controlling for global market returns, seasonality, and macroeconomic variables. That’s it.
Interestingly, they also found a significant price reversal in the following week. Taken together, their findings are consistent with a subsequent reversal of sentiment-induced temporary mispricing. A series of validation tests shows that seasonal factors such as lower mood months, increased cloud cover, and coronavirus-related restrictions are associated with significant declines in music-based sentiment indicators . The relationship between music sentiment and market returns becomes stronger when countries impose trading restrictions such as bans on short selling during the COVID-19 pandemic, which is consistent with greater restrictions on arbitrage.
Figure 1 Shows a graph of all sample averages SWAV [stream-weighted average valence] Beyond the country. Music sentiment also predicts increases in net mutual fund flows and decreases in government bond returns, and absolute sentiment precedes increases in stock market volatility. Overall, our study provides evidence that a proxy for a country’s public’s actual sentiment is significantly correlated with asset prices.
author: Alex Edmunds, Adrian Fernandez-Perez, Alexandre Garrel, Ivan Indriwan
title: Music sentiment and stock returns around the world
Link: https://ssrn.com/abstract=4057537
Abstract:
In this paper, we introduce a real-time, continuous measure of national sentiment that is non-verbal and globally comparable: the positivity of the songs individuals choose to listen to. It is a direct measure of mood and does not pre-specify the specific events that influence mood or assume the extent of its impact on investors. We validate music-based emotion measures by correlating them with mood swings caused by seasonal factors, weather conditions, and coronavirus-related restrictions. We find that music sentiment is positively correlated with same-week stock market returns and negatively correlated with the following week’s returns, consistent with sentiment-induced temporal mispricing. This result also holds true for daily analysis and is even stronger when arbitrage is limited by trading limits. Music sentiment also predicts increases in net mutual fund flows, and absolute sentiment precedes increases in stock market volatility. Consistent with a flight to safety, this is negatively related to government bond returns.
As always, we present some impressive figures and tables.
Notable quotes from academic research papers:
“Our primary analysis examines the relationship between music sentiment and stock market returns. We control for historical returns, global market returns, seasonality, weather conditions, and macroeconomic variables. However, we found a clear and significant association between music sentiment and contemporaneous returns: a one standard deviation increase in music sentiment was associated with weekly returns of 8.1 basis points (bps), annualized This effect reverses the following week: a one standard deviation increase in music sentiment predicts a 7.0 bps or -3.7% annualized decline in next week’s returns. This is consistent with previous theoretical and empirical findings that temporary mispricing caused by al., 1990; Baker and Wurgler, 2006, 2007; Edmans, Garcia, Norli, 2007; Ben-Rephael, Kandel, Wohl, 2012).
Daily analysis yields similar results. Sentiment toward music is associated with a significant increase in stock returns over the same period, which then reverses. Our results apply to both dollar and local currency returns. However, if he excludes one country at a time to make sure it’s not due to a specific country, and the 50 most streamed songs by country to address concerns about Spotify recommending songs. This applies if you exclude. user.
Our music-based sentiment measurement also includes subjectivity, as the valence algorithm was initially trained based on expert opinion. However, the sentiment measure applies to songs from all over the world, increasing comparability. Equivalent words have different meanings in different languages, but music is less ambiguous. As is often emphasized, “music is a universal language.” Mehl et al. (2019) studied 315 cultures and found that they used similar types of music in similar contexts, suggesting that music has universal characteristics that perhaps reflect commonalities in human cognition around the world. This suggests that there are certain characteristics. Therefore, the song value scale may be globally applicable. Additionally, music captures indescribable emotions that cannot be expressed through word-based emotional measurements.
This paper is also related to research investigating high-frequency proxies of emotions using non-textual sources. Obaid and Pukthuanthong (2021) estimate US sentiment through a sample of editorial news photos. Like them, we are researching ways to convey emotions more effectively than words, but vocally rather than visually. Our analysis also differs in that it considers endogenous measures of mood, examines 40 countries, and analyzes equity capital flows and government bond returns in addition to stock returns.
Finally, our study is part of a new literature stream using big data in finance. Musical emotions meet her three characteristics of big data identified by Goldstein, Spatt, and Ye (2021). It is large and aggregates the listening behavior of all Spotify listeners by country on a daily basis. This is high-dimensional because a song has multiple characteristics that affect its valence scale. It is also unstructured and requires an algorithm to evaluate its positivity. All three characteristics mean that music streaming is a highly available and comprehensive measure of consumption, and its positivity can be assessed to form a proxy for national sentiment.
It can be seen that the average value for South American countries is high. SWAVwhile the average for Asian countries is low SWAV. Figure 2 plots the daily SWAV of three countries over time: the United States and Brazil (one of the countries with the highest average values). SWAV), Taiwan (one of the lowest countries).nevertheless SWAV It shows both persistence and change over time, which can be exploited to construct music-based emotion measurements. Daily coefficient of variation (standard deviation divided by mean) SWAV Calculated separately for each country, the average is 5.5%.sustainability of SWAV This is because music-based sentiment measurement SWAV.
To align music sentiment measurements with stock market and macroeconomic data, weekly levels are used to avoid asynchronies between stock market opening and closing times and the time period in which Spotify reports daily statistics. It is compiled by. Such asynchrony leads to daily measurements. SWAV Daily price-to-earnings ratios partially lead in some indexes and lag in others. We define our sentiment measure as the weekly change in sentiment. This is to control for country-level differences in the average level of sentiment, as shown in Figure 1, and also because we expect changes in sentiment to cause changes in stock prices. ”
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