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1 |
Accounting-based downside risk and stock price crash risk: Evidence from China
ریسک نزولی مبتنی بر حسابداری و خطر سقوط قیمت سهام: شواهدی از چین-2021 In the past 15 years, an emerging literature has extensively studied individual stock price crash risk, which refers to the likelihood
of an abrupt and large-scale drop in stock prices (e.g., Chen et al., 2001; Hutton et al., 2009; Jin and Myers 2006; Kim et al., 2011a, Li
and Zhang 2011b; Kim and Zhang 2016). An important strand of this literature focuses on the Chinese emerging markets where,
arguably, the extent of “bad news hoarding” is severer compared to developed markets due to China’s less effective corporate
governance environment (Wang et al., 2020). In this paper, we examine the relationship between accounting-based downside risk and
stock price crash risk using a large sample of Chinese listed firms.
The contribution of this study lies in a recently developed indicator of earnings fundamentals that is, arguably, more consistent with
“bad news hoarding”: accounting-based downside risk, hereafter denoted as ABDR. Studies have shown that investors care more about
downside losses than upside gain potentials and are therefore more sensitive to losses than to gains (e.g., Gul 1991; Kahneman and
Tversky 1979). Accordingly, Koonce et al. (2005) show that economic agents judge negative and positive expectations differently in
risk management, placing more emphasis on potential loss outcomes. However, earnings volatility and other existing accounting-based
downside risk measures consist of both downside and upside variabilities with equal weights and little research has examined the
downside risk of accounting-based measures. Konchitchki et al. (2016) are the first to construct measures of accounting-based
downside risk and examine its pricing implications in U.S. markets. In particular, this study uses the relative root lower partial
moment as a mathematical foundation to capture exposure to downside risk rather than the overall volatility. Accounting-based
downside risk measures focus on the below-expectation variability in firm performance measures, particularly return-on-assets (ROA).
We extend Konchitchki et al. (2016) by performing an investigation in the Chinese markets. Furthermore, we examine the variation keywords: Accounting-based downside risk | Stock price crash risk | Bad-news hoarding, China | ریسک نزولی مبتنی بر حسابداری | ریسک سقوط قیمت سهام | احتکار اخبار بد، چین |
مقاله انگلیسی |
2 |
Accounting for seasonal effects on cyclist-vehicle crashes
حسابداری برای اثرات فصلی بر روی تصادفات دوچرخه سواری-2021 Crash data is usually aggregated over time where temporal correlation contributes to the unobserved hetero-
geneity. Since crashes that occur in temporal proximity share some unobserved characteristics, ignoring these
temporal correlations in safety modeling may lead to biased estimates and a loss of model power. Seasonality has
several effects on cyclists’ travel behavior (e.g., the distribution of holidays, school schedules, weather varia-
tions) and consequently cyclist-vehicle crash risk. This study aims to account for the effect of seasonality on
cyclist-vehicle crashes by employing two groups of models. The first group, seasonal cyclist-vehicle crash fre-
quency, employs four vectors of the dependent variables for each season. The second group, rainfall involved
cyclist-vehicle crash frequency, employs two vectors of the dependent variables for crashes that occurred on
rainy days and non-rainy days. The two model groups were investigated using three modeling techniques: Full
Bayes crash prediction model with spatial effects (base model), varying intercept and slope model, and First-
Order Random Walk model with a spatial–temporal interaction term. Crash and volume data for 134 traffic
analysis zones (TAZ’s) in the City of Vancouver were used. The results showed that the First-Order Random Walk
model with spatial–temporal interaction outperformed the other developed models. Some covariates have
different associations with crashes depending on the season and rainfall conditions. For example, the seasonal
estimates for the bus stop density are significantly higher for the summer and spring seasons than for the winter
and autumn seasons. Also, the intersection density estimate for a rainy day is significantly higher than a non-
rainy day. This indicates that on a rainy day each intersection to the network adds more risk to cyclists
compared to a non-rainy day. keywords: ایمنی دوچرخه سواری | خطر سقوط فصلی | اثر آب و هوا بر روی خطر سقوط دوچرخه سواران | فضایی | بیل کامل | Cyclist safety | Seasonal crash risk | Weather effect on cyclists’ crash risk | Spatiotemporal | Full Bayes |
مقاله انگلیسی |
3 |
تاثیر کویید-19 بر ریسک سقوط بازار سهام در چین
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 10 - تعداد صفحات فایل doc فارسی: 24 این مقاله به بررسی تاثیر بیماری مسری کویید-19 بر ریسک سقوط بازار سهام در چین می پردازد. بدین منظور ابتدا کجی شرطی توزیع سود را با مدل کجی جی.ای.آر.سی.اچ به عنوان شاخص ریسک سقوط بازار سهام شانگهای برآورد کردیم.سپس شاخص ترس از کویید-19را با داده های شاخص بایدو ساختاربندی کردیم. طبق یافته ها، کجی شرطی واکنش منفی به رشد روزانه در نمونه های تایید شده دارد، که نشان می داد شیوع این بیماری ریسک سقوط بازار سهام را افزایش می دهد. به علاوه احساس ترس این ریسک تاثیر کویید-19 را بدتر می کند. به عبارت دیگر هنگامی که احساس ترس زیاد باشد، ریسک سقوط بازار سهام به شدت تحت تاثیر بیماری همه گیر است. شواهد ما در چند نوع مرگ روزانه و نمونه های جهانی پابرجا است.
واژگان کلیدی: کویید 19 | احساس ترس | احساس سرمایه گذار | ریسک سقوط بازار سهام | کجی. |
مقاله ترجمه شده |
4 |
Highway crash detection and risk estimation using deep learning
تشخیص تصادف بزرگراه و تخمین ریسک با استفاده از یادگیری عمیق-2020 Crash Detection is essential in providing timely information to traffic management centers and the public to
reduce its adverse effects. Prediction of crash risk is vital for avoiding secondary crashes and safeguarding
highway traffic. For many years, researchers have explored several techniques for early and precise detection of
crashes to aid in traffic incident management. With recent advancements in data collection techniques, abundant
real-time traffic data is available for use. Big data infrastructure and machine learning algorithms can utilize this
data to provide suitable solutions for the highway traffic safety system. This paper explores the feasibility of
using deep learning models to detect crash occurrence and predict crash risk. Volume, Speed and Sensor
Occupancy data collected from roadside radar sensors along Interstate 235 in Des Moines, IA is used for this
study. This real-world traffic data is used to design feature set for the deep learning models for crash detection
and crash risk prediction. The results show that a deep model has better crash detection performance and similar
crash prediction performance than state of the art shallow models. Additionally, a sensitivity analysis was
conducted for crash risk prediction using data 1-minute, 5-minutes and 10-minutes prior to crash occurrence. It
was observed that is hard to predict the crash risk of a traffic condition, 10 min prior to a crash. Keywords: Crash detection | Crash prediction | Deep learning |
مقاله انگلیسی |
5 |
عوامل خطر تصادف مرتبط با شدت آسیب رانندگان نوجوان
سال انتشار: 2019 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 25 این مقاله بر شناسایی عوامل خطر تصادف مرتبط با شدت آسیب رانندگان نوجوان تمرکز دارد. دادههای تصادف بهدستآمده از سیستم اطلاعات و ایمنی بزرگراه (HSIS) برای کل ایالت کارولینای شمالی، در سالهای 2011 تا 2013، برای تحلیل و مدلسازی استفاده شد. در میان تمام تصادفات در طول دوره مطالعه، در مجموع 62990 تصادف مربوط به رانندگان نوجوان (15 تا 19 سال) مورد تجزیه و تحلیل قرار گرفتند. مدل بخت های متناسب جزئی برای شناسایی عوامل مؤثر در شدت آسیب رانندگان نوجوان ایجاد شد. نتایج بهدستآمده نشان میدهد که رانندگان نوجوانی که با وسایل نقلیه ورزشی و وانت بارها رانندگی میکنند در مقایسه با رانندگان نوجوانی که با ماشینهای سواری رانندگی میکنند، بیشتر در معرض آسیب شدید هستند. رانندگان نوجوان در روزهای هفته، به ویژه در ساعات اوج ترافیک، بیشتر آسیب می بینند. احتمال درگیر شدن رانندگان نوجوان در تصادفات شدید در روزهای سهشنبه و جمعه در مقایسه با یکشنبهها بیشتر بود. سن، جنسیت، پیکربندی جاده، زمین، شرایط نامطلوب آب و هوا و کنترل دسترسی تاثیر قابل توجهی بر شدت آسیب راننده نوجوان دارند.
کلمات کلیدی: رانندگان نوجوان | تصادف | شدت آسیب | عامل کمک کننده | مدل بخت های متناسب جزئی |
مقاله ترجمه شده |
6 |
National elections and tail risk: International evidence
انتخابات ملّی و خطر دنباله ای: شواهد بین المللی-2018 We investigate stock tail risk around national elections worldwide over the period of 1982–2012. We find that firm stock is less likely to crash during the election years, and is more likely to crash during the post-election period. This inter-temporal pattern is consistent with the suppression of negative information when there is heightened political uncertainty around elections and with the subsequent release of adverse news when the uncertainty is reduced. Further analysis shows that the impact of political uncertainty on tail risk is stronger in countries with poorer investor protection, fewer electoral checks and balances, more uncertain election outcomes and pro-business incumbent governments, in industries which are more politically sensitive, and in firms with larger information asymmetry.
keywords: Political uncertainty |Tail risk |National elections |Political |Risk |Return skewness |Crash risk |
مقاله انگلیسی |
7 |
ایجاد شاخص تعویض باند با استفاده از داده های مسیر خودرو
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 25 اقدامات ایمنی جایگزین (SSM ها) بطور گسترده برای ارزیابی احتمال تصادف که پایه و اساس اقدامات متقابل ایمنی کارآمد است مورد استفاده قرار گرفته اند. برخلاف SSM های موجود، که عمدتاً بر ارزیابی مانورهای طولی خودرو منجر به تصادف جلو به عقب تمرکز دارند، این مقاله یک روش جدید برای ارزیابی ریسک تصادفات، زمانیکه خودروی مورد نظر اقدام به تعوبض باند می کند، ارائه می دهد، این را شاخص ریسک تعویض باند (LCRI) می نامند. یک ویژگی نوین روش پیشنهادی، ترکیب نمودن مقدار زمان مواجهه در تصادفات و میزان مورد انتظار شدت تصادف با اعمال تحلیل درختی خطا (FTA) برای چارچوب ارزیابی است. تعاملات خودرویی بین خودروی مورد نظر و خودروهای مجاور در باند شروع و باند هدف به لحاظ احتمال تصادف حین تعویض باند ارزیابی می شوند. داده های مسیر خودرو که از جریان ترافیکی به دست می آیند، با استفاده از هواپیمای بدون سرنشین که بر روی آزادراه پرواز می کند عکس برداری شده اند و برای بررسی کارایی روش پیشنهادی مورد استفاده قرار می گیرند. این مقاله دربردارنده ی مشخصه های تعویض باند اختیاری و اجباری مشاهده شده در یک منطقه ی کاری و یک منطقه ی عمومی در یک بزرگراه با استفاده از LCRI است. انتظار می رود نتیجه ی این پژوهش در ارزیابی اثربخشی عملکردهای ترافیکی مختلف و راهبردهای کنترلی به لحاظ ایمنی تعویض باند، کارآمد باشد.
کلیدواژه ها: تعویض باند | برآورد ریسک | شاخص فاصله ی توقف | تحلیل درختی خطا | داده های مسیر خودرو |
مقاله ترجمه شده |
8 |
A Hybrid Latent Class Analysis Modeling Approach to Analyze Urban Expressway Crash Risk
یک روش مدل سازي تحلیلی طبقه بندي کم عمق برای تحلیل تصادفات بزرگراه شهری-2017 Crash risk analysis is rising as a hot research topic as it could reveal the relationships between traffic flow
characteristics and crash occurrence risk, which is beneficial to understand crash mechanisms which
would further refine the design of Active Traffic Management System (ATMS). However, the majority of
the current crash risk analysis studies have ignored the impact of geometric characteristics on crash risk
estimation while recent studies proved that crash occurrence risk was affected by the various alignment
features. In this study, a hybrid Latent Class Analysis (LCA) modeling approach was proposed to account for
the heterogeneous effects of geometric characteristics. Crashes were first segmented into homogenous
subgroups, where the optimal number of latent classes was identified based on bootstrap likelihood
ratio tests. Then, separate crash risk analysis models were developed using Bayesian random parameter
logistic regression technique; data from Shanghai urban expressway system were employed to conduct
the empirical study. Different crash risk contributing factors were unveiled by the hybrid LCA approach
and better model goodness-of-fit was obtained while comparing to an overall total crash model. Finally,
benefits of the proposed hybrid LCA approach were discussed.
Keywords: Crash risk analysis | Latent class analysis | Bayesian random parameter model | Unobserved heterogeneity |
مقاله انگلیسی |
9 |
Safety analytics for integrating crash frequency and real-time risk modeling for expressways
تجزیه و تحلیل ایمنی برای یکپارچه سازی فرکانس تصادف و مدلسازی ریسک در زمان واقعی برای بزرگراه ها-2017 To find crash contributing factors, there have been numerous crash frequency and real-time safety studies, but
such studies have been conducted independently. Until this point, no researcher has simultaneously analyzed
crash frequency and real-time crash risk to test whether integrating them could better explain crash occurrence.
Therefore, this study aims at integrating crash frequency and real-time safety analyses using expressway data. A
Bayesian integrated model and a non-integrated model were built: the integrated model linked the crash
frequency and the real-time models by adding the logarithm of the estimated expected crash frequency in the
real-time model; the non-integrated model independently estimated the crash frequency and the real-time crash
risk. The results showed that the integrated model outperformed the non-integrated model, as it provided much
better model results for both the crash frequency and the real-time models. This result indicated that the added
component, the logarithm of the expected crash frequency, successfully linked and provided useful information
to the two models. This study uncovered few variables that are not typically included in the crash frequency
analysis. For example, the average daily standard deviation of speed, which was aggregated based on speed at 1-
min intervals, had a positive effect on crash frequency. In conclusion, this study suggested a methodology to
improve the crash frequency and real-time models by integrating them, and it might inspire future researchers to
understand crash mechanisms better.
Keywords: Crash frequency analysis | Real-time safety analysis | Integrated model | Expected crash frequency | Average daily standard deviation of speed |
مقاله انگلیسی |
10 |
Is vehicle automation enough to prevent crashes? Role of traffic operations in automated driving environments for traffic safety
برای جلوگیری از تصادفات، اتوماسیون وسایل نقلیه کافی است ؟ نقش عملیات ترافیکی در محیط رانندگی اتوماتیک برای ایمنی ترافیک-2017 Automated driving systems (ADSs) are expected to prevent traffic accidents caused by driver carelessness on
freeways. There is no doubt regarding this safety benefit if all vehicles in the transportation system were
equipped with ADSs; however, it is implausible to expect that ADSs will reach 100% market penetration rate
(MPR) in the near future. Therefore, the following question arises: ‘Can ADSs, which consider only situations in
the vicinity of an equipped vehicle, really contribute to a significant reduction in traffic accidents?’ To address
this issue, the interactions between equipped and unequipped vehicles must be investigated, which is the
purpose of this study. This study evaluated traffic safety at different MPRs based on a proposed index to
represent the overall rear-end crash risk of the traffic stream. Two approaches were evaluated for adjusting
longitudinal vehicle maneuvers: vehicle safety-based maneuvering (VSM), which considers the crash risk of an
equipped vehicle and its neighboring vehicles, and traffic safety-based maneuvering (TSM), which considers the
overall crash risk in the traffic stream. TSM assumes that traffic operational agencies are able to monitor all the
vehicles and to intervene in vehicle maneuvering. An optimization process, which attempts to obtain vehicle
maneuvering control parameters to minimize the overall crash risk, is integrated into the proposed evaluation
framework. The main purpose of employing the optimization process for vehicle maneuvering in this study is to
identify opportunities to improve traffic safety through effective traffic management rather than developing a
vehicle control algorithm that can be implemented in practice. The microscopic traffic simulator VISSIM was
used to simulate the freeway traffic stream and to conduct systematic evaluations based on the proposed
methodology. Both TSM and VSM achieved significant reductions in the potential for rear-end crashes. However,
TSM obtained much greater reductions when the MPR was greater than 50%. This study should inspire
transportation researchers and engineers to develop effective traffic operations strategies for automated driving
environments.
Keywords: Traffic safety | Automated driving systems | Traffic operations strategy | Rear-end crash risks | Market penetration rate |
مقاله انگلیسی |