【正文】 to the population’s anisms and tests for fitness. Fitness is defined as how well the anism solves a particular problem. Each change of the population’s anism(s) results in a new generation. There is a body of literature related to predicting future returns. One such example is using fundamental financial analysis to predict higher than average returns . An other example is what has e to be known as the Piotroski score . This method identified 9 specific ratios that could be used to predict above average returns in firms with high book to market values. This work was extended to employ financial statement analysis to pre dict returns in high book to market firms. Next, an information technology approach was developed by applying and a geic algorithm which applied and modified weights to each of the 9 financial ratios and applied to the Brazilian stock market. While decision trees have been employed in accounting, finance, an operations management applying geic algorithms to in crease the accuracy of decision trees was conducted by. Research has also applied an information technology approach to financial distress prediction . 232. METHODOLOGY The null and research hypotheses to be tested in this re search are: 1) H0 = Based on the efficient market hypothesis the attributes required for valuation will differ from year to year by at least half the total number of attributes. 2) H1 = Based on the adaptive market hypothesis the attributes will naturally evolve and will differ from year to year by less than half the total number of attributes. The dataset was selected from CompuServe’s global database. The data was then filtered to include data from the years 2022 through 2022. Only panies from GBR were selected in the dataset to avoid anomalies arising from local variations such as currency exchange rates. Only panies that remained active were selected. From this 66 CompuServe attributes were retrieved which could be extracted from financial statements and puted for each stock with each stock identified by a unique identifier. The attribute which most accurately reflects the performance of a business firm for the pur poses of this study is called “price39。s” which is puted as the price + dividends. The reason this attribute was chosen as the target is price + dividends have a large effect on the market cap of a business firm. The datasets contained a minimum of 676 records and a maximum of 1129 records with an average of 877 records. The reason for the differences was an increase in publically traded panies during the range of years (20222022). 243. CONCLUSIONS AND FUTURE DIRECTIONS Determining which attributes from financial statement analysis for predicting the direction of market capitalization is a daunting task. The efficient market hypothesis would lead us to believe that there is a large variation between years on which attributes are important in predicting market capitalization. We have demonstrated that the variation between years is smaller than half the total number of financial statement attributes available for determining future market capitalization. In fact, there was a variation of less than 9%. This study is limited by the amount of attributes applied to this task. Future re search will address this limitation. Additionally, the dataset employed in this study was limited to a single country in an established market. Future research will employ both additional countries as well as emerging markets in order to draw conclusions between established versus emerging markets as well as between countries in the same category. Finally, this study was limited by the number of years incorporated into the datasets which will be addressed in extensions to this work. The implications of this research apply to a broad audience who are interested in fundamental financial statement analysis and market capitalization valuation. 25文獻(xiàn)翻譯應(yīng)用信息技術(shù)，以財(cái)務(wù)報(bào)表分析的市值預(yù)測摘要確定哪些屬性可以用于預(yù)測一個(gè)商業(yè)公司的市值是可以從會(huì)計(jì)及財(cái)務(wù)與信息技術(shù)的交叉研究中受益的原則一項(xiàng)艱巨的任務(wù)。在我們的方法中的決策樹和遺傳算法的軟件信息技術(shù)應(yīng)用到基本的財(cái)務(wù)報(bào)表數(shù)據(jù)，以支持用于預(yù)測一個(gè)公司，定義為市場資本值的價(jià)值方向的決策過程。決策過程不同于每年。然而，變化量是至關(guān)重要的一個(gè)成功的決策過程。所提出的研究問題是“多少變化之間的年發(fā)生？ ”我們假設(shè)的變化量，可能在決策過程中采用的財(cái)務(wù)報(bào)表的屬性比小一半的數(shù)量。我們開發(fā)了一個(gè)系統(tǒng)，該系統(tǒng)測試的變化量之間長達(dá)數(shù)年之達(dá)到健身的目標(biāo)水平需要幾代人的量。該假說是使用從普數(shù)據(jù)庫的全局?jǐn)?shù)據(jù)庫中篩選的數(shù)據(jù)進(jìn)行測試。該結(jié)果支持研究假設(shè)，推進(jìn)我們走向回答所研究的問題。這項(xiàng)研究的意義是用人財(cái)務(wù)報(bào)表分析時(shí)，適用于市值和商業(yè)企業(yè)的財(cái)務(wù)評(píng)估，提高決策過程的可能性。關(guān)鍵詞：基本面分析；市值；會(huì)計(jì)信息系統(tǒng)261 引言本研究的目的是探討不同年份之間，其中財(cái)務(wù)報(bào)表屬性是用于確定一個(gè)商業(yè)公司的市值增加或減少最關(guān)鍵的變化量。我們推測的變化量為可在決策過程可以采用的財(cái)務(wù)報(bào)表的屬性比一半小的數(shù)目。這是通過應(yīng)用信息技術(shù)為基礎(chǔ)的方法來確定哪些屬性是最關(guān)鍵的決策過程以評(píng)價(jià)未來的市值進(jìn)行測試。確定從基本的財(cái)務(wù)報(bào)表分析的屬性是在預(yù)測股票的表現(xiàn)難能可貴的是在任何投資策略的關(guān)鍵一步。長期以來，人們一直接受的金融市場是信息上的效率。這被稱為有效市場假說。換句話說，它是無法預(yù)測的市場表現(xiàn)或決定哪些金融國換貨屬性是最關(guān)鍵的一個(gè)商業(yè)公司的估值。與此相反的有效市場假說，適應(yīng)性市場假說指出，市場發(fā)展的基礎(chǔ)上競爭，自然選擇和適應(yīng)。有文學(xué)的本體與預(yù)測未來的回報(bào)。其中一個(gè)例子是使用基本的財(cái)務(wù)分析來預(yù)測高于平均水平的回報(bào)更高。安另一個(gè)例子是已經(jīng)到了被稱為 Piotroski 得分。這種方法確定了可以用來預(yù)測上述企業(yè)中具有較高的書的市場價(jià)值平均回報(bào)特定比例。這項(xiàng)工作擴(kuò)展至雇用財(cái)務(wù)報(bào)表分析來預(yù)測回報(bào)高的書推向市場的企業(yè)。其次，信息技術(shù)的方法是通過應(yīng)用和其應(yīng)用和修改的權(quán)重各財(cái)務(wù)比率，并應(yīng)用到巴西股市遺傳算法開發(fā)的。而決策樹已受聘于會(huì)計(jì)，財(cái)務(wù)，運(yùn)營管理應(yīng)用遺傳算法在折痕的決策樹的精度是由進(jìn)行。研究還應(yīng)用了信息技術(shù)的方法來財(cái)務(wù)困境預(yù)測。272 研究方法null 和研究假設(shè)在此重新搜索測試是：1 ） H0 =根據(jù)有效市場假說需要估值的屬性將從去年有所不同，以逐年屬性至少有一半的總數(shù)。2 ） H1 =基于自適應(yīng)市場假說的屬性會(huì)自然發(fā)展，并將于今年有所不同，以一年按屬性少于總?cè)藬?shù)的一半。該數(shù)據(jù)集是從普數(shù)據(jù)庫的全局?jǐn)?shù)據(jù)庫選中。然后將數(shù)據(jù)進(jìn)行過濾，包括只有從 GBR 公司在數(shù)據(jù)集中被選中，以避免從當(dāng)?shù)氐淖兓?，如貨幣匯率產(chǎn)生的異常從 2022 年到 2022 年的數(shù)據(jù)。只有保持活躍企業(yè)入選。從這 66 普數(shù)據(jù)庫進(jìn)行了檢索的屬性可從財(cái)務(wù)報(bào)表中摘錄，并計(jì)算出每只股票每確定一個(gè)唯一的標(biāo)識(shí)符股票。其中最準(zhǔn)確地反映了公司的業(yè)務(wù)為 pur姿勢這項(xiàng)研究的性能屬性被稱為“價(jià)格的” ，這是計(jì)算為價(jià)格+股息。這個(gè)屬性被選為目標(biāo)的原因是價(jià)格+分紅對(duì)一個(gè)商業(yè)公司的市值有很大影響。該數(shù)據(jù)集包含至少 676 條記錄，最大為1129 的記錄，平均為 877 的記錄。究其原因，區(qū)別是增加了公開上市交易的公司的年范圍內(nèi)（ 20222022 年）期間。283 結(jié)論和未來發(fā)展方向確定哪些屬性從財(cái)務(wù)報(bào)表分析，預(yù)測市值的方向是一項(xiàng)艱巨的任務(wù)。有效市場假說會(huì)導(dǎo)致我們相信，有多年間變化大上的屬性是在預(yù)測市值重要。我們已經(jīng)證明，不同年份之間的差異小于財(cái)務(wù)報(bào)表總數(shù)的一半屬性可用于確定未來的市值。事實(shí)上，有少于 9 ％的變化。本研究由施加到該任務(wù)的屬性的數(shù)量的限制。未來重新搜索將解決此限制。此外，在本研究中所采用的數(shù)據(jù)集被限制在一個(gè)單一國家在一個(gè)既定的市場。未來的研究將同時(shí)采用更多的國家以及新興市場，以吸引確立與新興市場以及在同一類國家之間的結(jié)論。最后，這項(xiàng)研究是由年并入將在擴(kuò)展這項(xiàng)工作需要解決的數(shù)據(jù)集數(shù)的限制。本研究的意義適用于廣大的觀眾誰感興趣的基本財(cái)務(wù)報(bào)表分析及市值估值。