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... employs a multinomial Naive Bayesian model to classify sentences within documents. Economic aspects are identified in a pre-processing step, that employssa link analysis using the TextRank algorithm =-=[8,9]-=-. The second phase measures sentiment expressed for the economic aspects, using a count of terms from the GeneralsInquirer dictionary [17]. The third phase employs Latent Dirichlet Allocation (LDA)sto...

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...eneralsInquirer dictionary [17]. The third phase employs Latent Dirichlet Allocation (LDA)sto infer intensifiers/diminishers that may change the meaning of the economic aspectssand economic sentiment =-=[10]-=-,[7]. Specifically, the model categorizes whether thesmagnitude of the economic aspects has ‘intensified’ or ‘diminished’ over times[11,12]. We refer to the resulting topic clusters as directional top...

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...thods is to combine the predictions of several models built with a given learningsalgorithm in order to improve generalizability and robustness over a single model. Wesuse the Random Forest algorithm =-=[30]-=-, that employs a diverse set of classifiers bysintroducing randomness into the classifier construction. Experiments were validateds2sCentral bank communications announced in August 1997 were excluded ...

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...explored avenue of research.s2.2 Background: sentiment analysissTraditionally, fine-grained sentiment analysis has been researched for the classification of online user reviews of products and movies =-=[16]-=-. Readers are often not onlysinterested in the general sentiment towards an aspect but also a detailed opinion analysis for each of these aspects [7]. Evaluation is conducted by comparing model classi...

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...s intended to improve the robustness of the LDA model for statistical inference. We implement standard settings for LDA hyper-parameters, α = 50/K andsβ=.01, where the number of topics K is set to 20 =-=[25]-=-. We manually annotate two ofsthe topic clusters that capture ‘directional’ information [1] and appear to act as intensifiers/diminishers of meaning. We label the clusters directional topic clusters. ...

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...ch identifies 'growth', 'price', 'rate', and 'econom' as the most frequently occurring terms for the US economy. Using the four economic aspects, thessystem employs a multinomial Naive Bayesian model =-=[24]-=- to categorize sentencesswithin each document. The resulting classification labels form the basis upon whichssentiment analysis is applied.s3.2 Polarity detectionsIn the second phase, the model comput...

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... colors reflect differentscommunities identified using the Clauset-Newman-Moore algorithm.sWe define economic aspects by employing a greedy algorithm to detect communities of terms within the network =-=[31]-=-. The economic growth aspect detects the frequency of the terms: ‘demand’, ‘goods’, ‘services’, ‘investment’. The prices aspectsdetects the terms: ‘inflation’, ‘prices’ , ‘money’, ‘markets’, ‘currency...

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...e close of business one day after. This narrow time window helpssto minimize the influence on investors’ interest rate expectations from other financialsmarket factors that may occur at the same time =-=[28]-=-.s4.2 Experiment setupsWe design the evaluation of the prediction model in stages to enhance our understanding of the model components. For a baseline, we evaluate the system’s predictions bysusing on...

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...p, that employssa link analysis using the TextRank algorithm [8,9]. The second phase measures sentiment expressed for the economic aspects, using a count of terms from the GeneralsInquirer dictionary =-=[17]-=-. The third phase employs Latent Dirichlet Allocation (LDA)sto infer intensifiers/diminishers that may change the meaning of the economic aspectssand economic sentiment [10],[7]. Specifically, the mod...

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... employs a multinomial Naive Bayesian model to classify sentences within documents. Economic aspects are identified in a pre-processing step, that employssa link analysis using the TextRank algorithm =-=[8,9]-=-. The second phase measures sentiment expressed for the economic aspects, using a count of terms from the GeneralsInquirer dictionary [17]. The third phase employs Latent Dirichlet Allocation (LDA)sto...

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...oweringsinterest rates1 [6]. This motivates a need for fine-grained sentiment analysis, to automatically detect economic aspects and predict the central bank sentiment expressedstowards these aspects =-=[7]-=-. Such a model would provide investors with an automatedssystem to decipher the complexities and interactions of economic aspects, to interpretsthe consequences of these interactions for the future pa...

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...ange the meaning of the economic aspectssand economic sentiment [10],[7]. Specifically, the model categorizes whether thesmagnitude of the economic aspects has ‘intensified’ or ‘diminished’ over times=-=[11,12]-=-. We refer to the resulting topic clusters as directional topic clusters. Finally,san ensemble tree combines the model components to predict the impact of the communications on financial market intere...

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...d the measurement of thesaspects is only known with significant time delay.sThe traditional approach to text-mining within the field of finance is to count termssusing the General Inquirer dictionary =-=[17,18]-=-. The dictionary classifies words according to multiple categories, including 1,915 positive words and 2,291 negative words.sThe General Inquirer was developed for psychology and sociology research an...

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... an approach issstatistical, because it links all co-occurring terms without considering their meaningsor function in text. Centrality is often used to estimate the importance of a word in asdocument =-=[22]-=-, and is a way of deciding on the importance of a vertex within a graphsthat takes into account global information recursively computed from the entire graph,srather than relying only on local vertex-...

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... Inquirer was developed for psychology and sociology research andswhile it is used for text mining within the field of finance, little research has beensconducted as to its suitability within finance =-=[19]-=-. Aspects that are frequently mentioned in central bank communications, such as the terms ‘employment’, ‘unemployment’ and ‘growth’, are not classified by the General Inquirer dictionary. Adjectivessa...

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...omputed from the entire graph,srather than relying only on local vertex-specific information [23]. The main advantagesof such a representation is that selected terms are independent of their language =-=[21]-=-.s3 Model to predict changes in investors’ expectationssIn this section we describe the four phases of the system. First, the system detectsssalient references to economic aspects and employs a multin...

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...at all.s2.3 Background: keyword detectionsGraph-based algorithms have received much attention [8] as an approach to keyphrasesextraction and are considered to be state-of-the-art unsupervised methods =-=[20]-=-. In asgraph representation of a document, nodes are words or phrases, and edges representsco-occurrence or semantic relations. The underlying assumption is that all words insthe text have some relati...

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... fromsfinancial market patterns. Interest rate futures contracts are financial instruments thatsenable investors to insure against or speculate on uncertainty about the future level ofsinterest rates =-=[27]-=-. Changes in the price of the futures contracts therefore reflectschanges in investors’ views on the future direction in central bank interest rates. Investors’ interest rate expectations for the foll...

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...indicates a more accurate prediction.sSpearman's rho is a non-parametric measure of the degree of linear association between the predicted and realized values, and is bound between the range -1 to +1 =-=[29]-=-.sA positive Spearman's rho indicates the model’s predictive ability; a negative valuesindicates a poor model fit.s4.3 Experiment resultssThe evaluation metrics from the model components are shown in ...

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...iding on the importance of a vertex within a graphsthat takes into account global information recursively computed from the entire graph,srather than relying only on local vertex-specific information =-=[23]-=-. The main advantagesof such a representation is that selected terms are independent of their language [21].s3 Model to predict changes in investors’ expectationssIn this section we describe the four ...

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...lsbank communications as a central bank policy instrument [1,2]. Central banks communicate qualitative information to the financial market through statements, minutes,sspeeches, and published reports =-=[3]-=-. Communication is an important tool that a centralsbank can use to avert a crisis, by providing investors with its assessment of the riskssand the measures it views as necessary to reduce those risks...

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... mining·link analysis·financial marketss1 IntroductionsPost the global financial crisis, there has been a dramatic change in the use of centralsbank communications as a central bank policy instrument =-=[1,2]-=-. Central banks communicate qualitative information to the financial market through statements, minutes,sspeeches, and published reports [3]. Communication is an important tool that a centralsbank can...

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...theirseconomic toolkit [1,2]. Effective communications enhance a central bank’s publicstransparency, accountability and credibility [13], which in turn aids its ability to implement economic policies =-=[14]-=-. To date, there has been little research into text mining of central bank communications. In [14], the impact of different types of communications (press releases, speeches, interviews, and news conf...

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...erage compared to thesthree and six month series. Furthermore, the twelve month forecast horizon is consistent with the time horizon over which that the Bank of England conducts its economic policies =-=[2]-=-. To isolate the effect of the central bank communication on investors’ expectations, we compute the percentage change in the interest rate futures contract, as measured from the close of business on ...

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...nhanced forward guidance’, as an important policy instrument within theirseconomic toolkit [1,2]. Effective communications enhance a central bank’s publicstransparency, accountability and credibility =-=[13]-=-, which in turn aids its ability to implement economic policies [14]. To date, there has been little research into text mining of central bank communications. In [14], the impact of different types of...

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...n the economy [1],s[4]. Previous studies suggest that effective central bank communications can mitigatesand potentially prevent a financial crisis; ineffective communications may exacerbatesone [1], =-=[5]-=-. In [4], the Swedish central bank, the Riksbank, is criticized because itsscommunications were “not clear or strong enough” leading up to the global financialscrisis, such that the bank’s information...

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...as a negativessignal for the direction of future interest rates. During the financial crisis of 20072009, high inflation was considered to be a positive signal by effectively loweringsinterest rates1 =-=[6]-=-. This motivates a need for fine-grained sentiment analysis, to automatically detect economic aspects and predict the central bank sentiment expressedstowards these aspects [7]. Such a model would pro...

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... the language used in the documents. In [3], a term countingsapproach is adopted to analyze the sentiment contained within the meeting minutes ofsthe US central bank (the Federal Reserve). In [3] and =-=[15]-=- Latent Semantic Analysis issemployed to analyze the sentiment contained within the Bank of Canada’s minutes.sThe intention of this study is to design a fine-grained sentiment analysis approach tosana...