<p>Management Discussion and Analysis (MD&amp;A) sections provide significant insights into a firm's performance and outlook, making them critical for investors and analysts. Existing dictionaries used for text analysis in finance are often general. They lack the specificity needed for accurate sentiment analysis of Annual Report of a company, especially within the MD&amp;A section. The current research addresses this gap by developing a domain-specific lexicon dictionary designed to quantify tone and risk sentiment for the MD&amp;A sections of corporate annual reports. The dictionary was constructed using both inductive and deductive approaches, incorporating word lists specific to the finance domain. The study also undertook rigorous reliability and validity tests, including test–retest reliability, parallel forms reliability, and interrater agreement, ensuring the robustness of the developed lexicon. The dictionary's predictive power was tested by correlating its sentiment scores with future firm performance indicators like return on equity (ROE), return on assets, and Tobin’s Q. The results showed that the tone and risk sentiment derived from the developed dictionary significantly predict future firm performance, with a positive tone correlating with higher future ROE. The study, thus, contributes to the field of financial communication by developing domain-specific dictionaries for tone and risk measures for a section of annual report. This will allow various stakeholders to analyse corporate disclosures more meaningfully. It will lead to more informed decisions with respect to future performance and investments by investors. Further, the findings from this study can be leveraged to reduce information asymmetry and make markets more efficient.</p>