This paper analyses the use of modal auxiliaries in an investment fund prospectus and how they are translated into Swedish. The semantics of modal auxiliaries is a rather fuzzy area. One modal verb such as may or will can have several different meanings, depending on the textual and situational context. Correctly interpreting the modal verbs is an important prerequisite for an accurate translation. A theoretical background founded on linguistic studies and grammatical presentations by Palmer (2001), Huddleston and Pullum (2002), Coates (1983), Teleman et al. (1999) and Wärnsby (2006) and others, provides a framework for analysing the meanings of the modal verbs in the source text and determining the most equivalent expressions in the Swedish modal system. Different types of modality, such as epistemic, deontic and dynamic, are discussed, along with the different textual and situational factors associated with each type. The analysis includes the most frequent modal auxiliaries found in the source text, namely (in the order of frequency from high to low) may, will, should, can, shall and must. Each modal verb is analysed in terms of its meanings and possible Swedish translations are discussed. One interesting aspect highlighted in the study is the close relationship between modality and futurity, which is particularly true for will. Due to the nature of the source text as a legal contract between the investment fund and the investors, the use of modal verbs specific to legal register is also considered in the analysis. The analysis shows that an awareness of the various factors associated with different types of modality and the linguistic features typical for the particular text type can help the translator correctly interpret and translate the modal verbs as accurately and consistently as possible.

財務報表中的主觀性詞彙往往影響市場中的參與者對於報導公司價值和獲利能力衡量的決策判斷。因此，公司的管理階層往往有高度的動機小心謹慎的選擇用詞以隱藏負面的消息而宣揚正面的消息。然而使用人工方式從文字量極大的財務報表挖掘有用的資訊往往不可行，因此本研究採用人工智慧方法驗證美國財務報表中的主觀性多字詞 (subjective MWEs) 和公司的財務狀況是否具有關聯性。多字詞模型往往比傳統的單字詞模型更能掌握句子中的語意情境，因此本研究應用條件隨機域模型 (conditional random field) 辨識多字詞形式的意見樣式。另外，本研究的實證結果發現一些跡象可以印證一般人對於財務報表的文字揭露往往與真實的財務數字存在有落差的印象；更發現在負向的盈餘變化情況下，公司管理階層通常輕描淡寫當下的短拙卻堅定地承諾璀璨的未來。 / Subjective assertions in financial statements influence the judgments of market participants when they assess the value and profitability of the reporting corporations. Hence, the managements of corporations may attempt to conceal the negative and to accentuate the positive with "prudent" wording. To excavate this accounting phenomenon hidden behind financial statements, we designed an artificial intelligence based strategy to investigate the linkage between financial status measured by annual earnings and subjective multi-word expressions (MWEs). We applied the conditional random field (CRF) models to identify opinion patterns in the form of MWEs, and our approach outperformed previous work employing unigram models. Moreover, our novel algorithms take the lead to discover the evidences that support the common belief that there are inconsistencies between the implications of the written statements and the reality indicated by the figures in the financial statements. Unexpected negative earnings are often accompanied by ambiguous and mild statements and sometimes by promises of glorious future.