Is Bankruptcy Risk a Systematic Risk? Evidence from Pakistan Stock Exchange

This study empirically investigates the relationship between default risk and cross-section of stock returns in the Pakistan Stock Exchange (PSX). Stock price data from all listed and delisted companies use to calculate monthly returns from 2001-2016. Ohlson's O-score is employed to measure exposure of firm to systematic deviation within bankruptcy risk. Besides, asset-pricing models like the Capital Asset Pricing Model (CAPM) and Fama French (FF) models are employed. Portfolios are sorted in deciles by default probability. This result finds that stocks of firms significantly exposed to not diversified Default Risk yield higher returns. Besides that, the FF models explain cross-sectional stock returns since factors incorporate information on financial distress and default. After that, the book-to-market equity factor is not significant in elucidating returns of distressed firms because of market inefficiency. Results have practical implications for portfolio managers and investors of an emerging economy in developing diversified portfolios during periods of uncertainty and market volatility.JEL Classifications: G12, G15, G33How to Cite:Chhapra, I. U., Zehra, I., Kashif, M., & Rehan, R. (2020). Is Bankruptcy Risk a Systematic Risk? Evidence from Pakistan Stock Exchange. Etikonomi: Jurnal Ekonomi, 19(1), 51 – 62. https://doi.org/10.15408/etk.v19i1.11248

Are Stock Prices a Random Walk? An Empirical Evidence of Asian Stock Markets

Investigating if the market is efficient is an old issue as market efficiency is imperative for channeling investments to best-valued projects and its importance endures. There is contradictory evidence in the literature provided by empirical researches. The primary purpose of this research has been to find out whether share prices are a random walk process by applying multiple unit root tests, Runs Test and newly developed State Space Model. The empirical findings of the study provide sufficient evidence that the stock prices of KSE 100 Index, S &amp; P BSE 500 Index, and CSE All Share Index is not a random walk process and are thus weak form inefficient hypothesis. In this study, the concept of the random walk is examined considering only the stock markets while bypassing the other asset markets. This research supply exciting facts about independent samples from Pakistan, India, and Bangladesh and complement the existing literature on emerging markets.DOI: 10.15408/etk.v17i2.7102</p

Handcrafted features with convolutional neural networks for detection of tumor cells in histology images

Detection of tumor nuclei in cancer histology images requires sophisticated techniques due to the irregular shape, size and chromatin texture of the tumor nuclei. Some very recently proposed methods employ deep convolutional neural networks (CNNs) to detect cells in H&E stained images. However, all such methods use some form of raw pixel intensities as input and rely on the CNN to learn the deep features. In this work, we extend a recently proposed spatially constrained CNN (SC-CNN) by proposing features that capture texture characteristics and show that although CNN produces good results on automatically learned features, it can perform better if the input consists of a combination of handcrafted features and the raw data. The handcrafted features are computed through the scattering transform which gives non-linear invariant texture features. The combination of handcrafted features with raw data produces sharp proximity maps and better detection results than the results of raw intensities with a similar kind of CNN architecture. 2016 IEEE.Scopu