We present a probabilistic bilingual capitalization model for capitalizing machine translation outputs using conditional random fields. Experiments carried out on three language pairs and a variety of experiment conditions show that our model significantly outperforms a strong monolingual capitalization model baseline, especially when working with small datasets and/or European language pairs.

In this study we explore market power in 13 EU banking sectors for the years 2007 to 2019 by estimating a structural model with demand and supply equations, where mark-up of price over marginal cost is parameterized as measure banks’ conduct that depends on selected factors. Our evidence indicates banks enjoy significant degree power, which shows decreasing trend time some difference across cou...

We owe thanks to Frans Tempelaar and Luigi Zingales for useful comments. We retain all responsibility for content. Abstract We argue that in an unreliable enforcement regime, transactions tend to become intermediated through institutions or concentrated among agents bound by some form of private enforcement. Provision of funding shifts from risk capital to debt, and from markets to institutions...

The rapid proliferation of microblogs such as Twitter has resulted in a vast quantity of written text becoming available that contains interesting information for NLP tasks. However, the noise level in tweets is so high that standard NLP tools perform poorly. In this paper, we present a statistical truecaser for tweets using a 3-gram language model built with truecased newswire texts and tweets...

The Sukuk market has become the fastest growing segment of the Islamic financial services industry. Governments and other corporate entities have started tapping the local and international Sukuk markets in order to raise the required funds. The investor base is also expanding and Sukuk has now become a popular and obvious choice for retail investors in a number of jurisdictions. However, becau...

This study attempts to find the usefulness of Joint Learning to the tasks of Named Entity Recognition (NER) and Capitalization Generation, and tries to shed more light on Joint Learning models for Natural Language Processing in general. The study goes further to look for feature sets that help or do not help the Joint task. This is achieved by using Dynamic Conditional Random Fields (DCRFs) as ...

The motivation behind this study is to experimentally look at the connection between capital market improvement and monetary development in Nigeria. examination investigated Central Bank of Nigeria quarterly information from 1981Q1 2017Q4 with E-sees programming bundle (variant 9.0). Vector Auto Regression (VAR) procedure was utilized investigate information, while theory testing depended on Bl...

Since the 1960s, rapid development of institutional investors is a prominent feature of global financial market. In china, full circulation of stock will realize after the completion of Split Share Structure Reform. Under the circumstance of institutional investors holding a large scale of stock, will they change their invest style? Whether they place more emphasis on value investment and conce...

In Sorani Kurdish, one of the most useful orthographic features in named-entity recognition – capitalization – is absent, as the language’s Perso-Arabic script does not make a distinction between uppercase and lowercase letters. We describe a system for deriving an inferred capitalization value from closely related languages by phonological similarity, and illustrate the system using several re...