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Atul Rai

Bio: Atul Rai is an academic researcher from Wichita State University. The author has contributed to research in topics: Earnings & Earnings management. The author has an hindex of 11, co-authored 32 publications receiving 400 citations. Previous affiliations of Atul Rai include University of Szeged & University of Alabama in Huntsville.

Papers
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Journal ArticleDOI
TL;DR: In this article, the authors show that a high proportion of firms with small cumulative profits or losses at the beginning of the fourth quarter report small annual profits rather than small annual losses, which suggests that upward earnings management causes the kink and indicates which firms are likely to manage earnings upward.

123 citations

Proceedings ArticleDOI
02 Sep 2018
TL;DR: A Convolutional Neural Network Architecture based on the popular Very Deep VGG CNNs, with key modifications to accommodate variable length spectrogram inputs, reduce the model disk space requirements and reduce the number of parameters, resulting in significant reduction in training times is proposed.
Abstract: The success of any Text Independent Speaker Identification and/or Verification system relies upon the system’s capability to learn discriminative features. In this paper we propose a Convolutional Neural Network (CNN) Architecture based on the popular Very Deep VGG [1] CNNs, with key modifications to accommodate variable length spectrogram inputs, reduce the model disk space requirements and reduce the number of parameters, resulting in significant reduction in training times. We also propose a unified deep learning system for both Text-Independent Speaker Recognition and Speaker Verification, by training the proposed network architecture under the joint supervision of Softmax loss and Center loss [2] to obtain highly discriminative deep features that are suited for both Speaker Identification and Verification Tasks. We use the recently released VoxCeleb dataset [3], which contains hundreds of thousands of real world utterances of over 1200 celebrities belonging to various ethnicities, for benchmarking our approach. Our best CNN model achieved a Top1 accuracy of 84.6%, a 4% absolute improvement over VoxCeleb’s approach, whereas training in conjunction with Center Loss improved the Top-1 accuracy to 89.5%, a 9% absolute improvement over Voxceleb’s approach.

63 citations

Proceedings ArticleDOI
04 May 2020
TL;DR: The proposed CNN front-end fitted with the proposed convolutional attention modules outperform the no-attention and spatial-CBAM baselines by a significant margin on the VoxCeleb benchmark, concluding that simultaneously modelling temporal and frequency attention translates to better real-world performance.
Abstract: Majority of the recent approaches for text-independent speaker recognition apply attention or similar techniques for aggregation of frame-level feature descriptors generated by a deep neural network (DNN) front-end. In this paper, we propose methods of convolutional attention for independently modelling temporal and frequency information in a convolutional neural network (CNN) based front-end. Our system utilizes convolutional block attention modules (CBAMs) [1] appropriately modified to accommodate spectrogram inputs. The proposed CNN front-end fitted with the proposed convolutional attention modules outperform the no-attention and spatial-CBAM baselines by a significant margin on the VoxCeleb [2], [3] speaker verification benchmark. Our best model achieves an equal error rate of 2.031% on the VoxCeleb1 test set, which is a considerable improvement over comparable state of the art results. For a more thorough assessment of the effects of frequency and temporal attention in real-world conditions, we conduct ablation experiments by randomly dropping frequency bins and temporal frames from the input spectrograms, concluding that instead of modelling either of the entities, simultaneously modelling temporal and frequency attention translates to better real-world performance.

45 citations

Journal ArticleDOI
TL;DR: The Free Cash Flow/Small-Cap Anomaly as discussed by the authors is an anomaly in small-cap as discussed by the authors, which occurs when the free cash flow/small-cap anomaly is large.
Abstract: (1994). The Free Cash Flow/Small-Cap Anomaly. Financial Analysts Journal: Vol. 50, No. 5, pp. 33-42.

23 citations

Posted Content
TL;DR: In this paper, an investment strategy based on free cash flow is presented. But the strategy selects securities into a "long" portfolio that outperforms the market index, returns of similar size securities, and returns of comparable risk (beta and book-to-market) securities.
Abstract: This paper examines an investment strategy based on free cash flows. The strategy selects securities into a "long" portfolio that outperforms the market index, returns of similar size securities, and returns of similar risk (beta and book-to-market) securities. The portfolio includes firms that are consistent free cash flow generators, that have low financial leverage, and that sell at low free cash flow multiples.

23 citations


Cited by
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Journal ArticleDOI
TL;DR: This paper pointed out that the "quality" of earnings is a function of the firm's fundamental performance and suggested that the contribution of a firms fundamental performance to its earnings quality is suggested as one area for future work.
Abstract: Researchers have used various measures as indications of "earnings quality" including persistence, accruals, smoothness, timeliness, loss avoidance, investor responsiveness, and external indicators such as restatements and SEC enforcement releases. For each measure, we discuss causes of variation in the measure as well as consequences. We reach no single conclusion on what earnings quality is because "quality" is contingent on the decision context. We also point out that the "quality" of earnings is a function of the firm's fundamental performance. The contribution of a firm's fundamental performance to its earnings quality is suggested as one area for future work.

2,633 citations

Journal ArticleDOI
TL;DR: In this paper, the authors point out that the quality of earnings is a function of the firm's fundamental performance and suggest that the contribution of a firms fundamental performance to its earnings quality is suggested as one area for future work.

2,140 citations

Journal ArticleDOI
TL;DR: In this paper, the effect of audit effort on earnings management using a unique database of hours worked by auditors on 9,738 audits in Greece between 1994 and 2002 was investigated.

559 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated investors' reactions to revenue and expense surprises around preliminary earnings announcements and found that investors value more highly a dollar of revenue surprise than a dollars of expense surprise.
Abstract: This study investigates investors' reactions to revenue and expense surprises around preliminary earnings announcements. Results show that investors value more highly a dollar of revenue surprise than a dollar of expense surprise. Results further show that these differential market reactions to revenue and expense surprises vary systematically for growth versus value firms and depend on (a) the proportion of variable to total costs, (b) the relative persistence of sales and expenses, and (c) the proportion of operating to total expenses. Results highlight the importance of interpreting the earnings surprise in the context of its sources—e.g. surprise in revenues or in total expenses.

331 citations

Journal ArticleDOI
TL;DR: The authors examined how adjustments to earnings during year-end audits affect measures of earnings quality and found that audit adjustments cause earnings to become smoother and more persistent, which results in higher accrual quality.

136 citations