## 3 Results
### Valence/Sentiment Analysis  
Share price movements are assumed to be a reasonable proxy for sentiment following the new information provided within the investor day presentations [7]. For example, we should expect a positive share price movement following positive news. Figure 5, top left, shows the relationship between polarity scores in IDTs and share price movements for each company and time period. A correlation analysis indicates the presence of a small yet statistically significant correlation (Pearson's \(\rho=0.16,p<0.001<\alpha=0.05\)). In other words, the existence of more positive terms being used during the Q&A section of an insurer's investor day presentation was subsequently reflected in a positive share price movement. Figure 4: Semantic frame for “climat” in 2018 (**left**) and in 2020 (**right**) insurance reports. Note: node size reflects degree centrality, i.e., the semantic frame size of each word in the overall cognitive network. Words are clustered in Louvain communities only for the sake of visualisation (see also [5]). Figure 5: **Top left**: Share price movements vs. polarity scores (2014–2021). **Top right**: Scatter plot between share price movements and sentiment scores. **Bottom left**: Comparing share-price movement and subjectivity scores (2014–2021). **Bottom right**: US insurance industry sentiment analysis over the years. Polarity is a mix of positive and negative sentiment patterns. Hence, the next step is to assess how each of these parts determines the above result. This is shown in Figure 5, top right, which separates firms in four different quadrants according to their positive and negative sentiment scores. Firms for which both negative and positive sentiment scores were correlated with share prices would be those with price movements showing relatively higher positive correlations against positive sentiment (X axis) and higher negative correlation with negative sentiment (Y axis), i.e., firms with correlated prices should fall in the bottom right quadrant. Unfortunately, only a round 33% of firms are clustered in this quadrant. Notice that these results might further improve with the advent of insurance-specific lexicons. The one we are using here, the Loughran and McDonald lexicon [28], is a generic one for financial services, which might be missing sentiment scores specific to the context of the insurance sector. Another element that could distort this analysis is that market analysts typically update their opinion on a sector based on the first reporting firm [8]. For example, if _Admiral_ holds its investor day presentation setting out positive loss experience, analysts may assume all UK motor insurers will have had a good 6-months. Consequently, the share price for the other insurers (such as Direct Line) would also move. Any subsequent movements on the day of _Direct Line_'s actual presentation would represent the relative movement to the sector's expectation regardless of whether it is overall positive from the firm's perspective. Such a relationship is naturally more complex but should be considered as part of future refinements. Figure 5, bottom right, shows the polarity scores over time for US insurers, which enables a consistent time series for each quarter (noting that most European insurers only provide updates every 6 months). Interestingly, in insurers' IDTs, the sentiment of analysts in Q&A sections is consistently lower than the sentiment scores of company sections. This pattern persists across 7 years and cannot be caused by a systematic data analysis bias, since both the Q&A and company sections are analysed through the same pipeline and with the same sentiment lexicon (see Methods). We rather interpret this finding in view of analyst perspectives potentially challenging management, whilst the company section arguably reflects a marketing opportunity focusing on future positive opportunities for the insurer. Secondly, the lowest sentiment trends in the US insurance sectors are found to be at the start of the COVID-19 pandemic, in early 2020.