scholarly journals Weighted Quantile Regression Forests for Bimodal Distribution Modeling: A Loss Given Default Case

Entropy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 545 ◽  
Author(s):  
Michał Gostkowski ◽  
Krzysztof Gajowniczek
Keyword(s):  
Quantile Regression ◽  
Bimodal Distribution ◽  
Ordinary Least Squares ◽  
Mean Value ◽  
Loss Given Default ◽  
Ensemble Technique ◽  
Internal Rating ◽  
Enabling Institutions ◽  
The Impact ◽  
Weighted Quantile Regression

Due to various regulations (e.g., the Basel III Accord), banks need to keep a specified amount of capital to reduce the impact of their insolvency. This equity can be calculated using, e.g., the Internal Rating Approach, enabling institutions to develop their own statistical models. In this regard, one of the most important parameters is the loss given default, whose correct estimation may lead to a healthier and riskless allocation of the capital. Unfortunately, since the loss given default distribution is a bimodal application of the modeling methods (e.g., ordinary least squares or regression trees), aiming at predicting the mean value is not enough. Bimodality means that a distribution has two modes and has a large proportion of observations with large distances from the middle of the distribution; therefore, to overcome this fact, more advanced methods are required. To this end, to model the entire loss given default distribution, in this article we present the weighted quantile Regression Forest algorithm, which is an ensemble technique. We evaluate our methodology over a dataset collected by one of the biggest Polish banks. Through our research, we show that weighted quantile Regression Forests outperform “single” state-of-the-art models in terms of their accuracy and the stability.

A quantile regression approach to evaluate the relative impact of global and local factors on the MENA stock markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Slah Bahloul ◽  
Nawel Ben Amor
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Stock Returns ◽  
Stock Markets ◽  
Financial Integration ◽  
Ordinary Least Squares ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
The Impact

PurposeThis paper investigates the relative importance of local macroeconomic and global factors in the explanation of twelve MENA (Middle East and North Africa) stock market returns across the different quantiles in order to determine their degree of international financial integration.Design/methodology/approachThe authors use both ordinary least squares and quantile regressions from January 2007 to January 2018. Quantile regression permits to know how the effects of explanatory variables vary across the different states of the market.FindingsThe results of this paper indicate that the impact of local macroeconomic and global factors differs across the quantiles and markets. Generally, there are wide ranges in degree of international integration and most of MENA stock markets appear to be weakly integrated. This reveals that the portfolio diversification within the stock markets in this region is still beneficial.Originality/valueThis paper is original for two reasons. First, it emphasizes, over a fairly long period, the impact of a large number of macroeconomic and global variables on the MENA stock market returns. Second, it examines if the relative effects of these factors on MENA stock returns vary or not across the market states and MENA countries.

scholarly journals Environmental, Social, Governance Risk and Corporate Sustainable Growth Nexus: Quantile Regression Approach

2021 ◽  
Vol 18 (20) ◽  
pp. 10865
Author(s):  
Xiaodong Teng ◽  
Yanzhi Wang ◽  
Aiguo Wang ◽  
Bao-Guang Chang ◽  
Kun-Shan Wu
Keyword(s):  
Quantile Regression ◽  
Negative Relationship ◽  
Ordinary Least Squares ◽  
Sustainable Growth ◽  
Detailed Knowledge ◽  
Course Of Action ◽  
Regression Approach ◽  
Negative Effect ◽  
Sustainable Growth Rate ◽  
The Impact

Despite a huge body of literature revealing that the effect of environmental, social and governance (ESG) scores on a firms' financial performance and value, it lacks the empirical research on the nexus between corporate sustainable growth and ESG risk in the existing research. The paper aims to examine the nexus between ESG risk and corporate sustainable growth. This study utilizes a quantile regression approach to explore how ESG risk affects corporate sustainable growth (proxied by sustainable growth rate, SGR). The ordinary least squares estimation results confirm that ESG significantly negatively affects corporate sustainable growth. The quantile regression results reveal ESG risk has a significant negative effect on corporate sustainable growth in the upper quantiles of SGR, but not in the lower and median quantiles. The results show that the impact of ESG risk on the corporate sustainable growth is asymmetric and affected by the distribution of SGR. Furthermore, the research results identify that the negative relationship between ESG risk and corporate sustainable growth is particularly apparent for firms in environmentally sensitive industries. This study greatly contributes to existing literature, as with this detailed knowledge, managers can make decisions based on these associations and identify the most lucrative course of action.

Quantile regression: an alternative approach to modelling forest area burned by individual fires

2018 ◽  
Vol 27 (8) ◽  
pp. 538 ◽  
Author(s):  
Baburam Rijal
Keyword(s):  
Quantile Regression ◽  
Forest Ecosystems ◽  
Fire Regime ◽  
Model Fitting ◽  
Ordinary Least Squares ◽  
Mean Value ◽  
Mixed Effects ◽  
Least Squares Regression ◽  
Fire Size ◽  
Large Fires

Components of a fire regime have long been estimated using mean-value-based ordinary least-squares regression. But, forest and fire managers require predictions beyond the mean because impacts of small and large fires on forest ecosystems and wildland–urban interfaces are different. Therefore, different action plans are required to manage potential fires of varying sizes that demand size-based modelling tools. The objective of this study was to compare two model-fitting techniques, namely quantile mixed-effects (QME) model and ordinary linear mixed-effects (LME) model for constructing distributions of model-predicted small and large fires. I examined these techniques by modelling the fire size of individual escaped wildfires. Results showed that the LME-predicted fire size approximately coincided to the 0.75 quantile. The LME model produced more biased predictions at the two extremes, both of which manifest great importance in forest ecosystems and fire management. Modelling the distributions for small and large fires using quantile regression can reduce such biases along with giving unbiased mean estimates. This study concludes that quantile modelling is an effective approach to complement ordinary regression that helps predict the size-based risks of individual fires more precisely, and that could allow managers to better plan resources when managing fires.

scholarly journals The Impact of Pandemics Sentiment on the Global Art Market

2021 ◽  
Vol 9 ◽  
Author(s):  
Wei Wang
Keyword(s):  
Quantile Regression ◽  
Least Squares ◽  
Art Market ◽  
Ordinary Least Squares ◽  
Global Level ◽  
Uncertainty Shocks ◽  
The World ◽  
The Impact ◽  
Global Art

This paper investigates the effects of pandemics sentiment (the World Pandemics Discussion Index) on the returns of the global art market from 1998Q1 to 2021Q2 at the global level. The Ordinary Least Squares and the Quantile Regression estimations indicate that global pandemics sentiment positively affects the returns of the global art market. This evidence means that investing in the art market can hedge the uncertainty shocks related to pandemics at the global level.

Board characteristics and real performance in Malaysian state-owned enterprises (SOEs)

2017 ◽  
Vol 66 (8) ◽  
pp. 1064-1086 ◽  
Author(s):  
Fekri Ali Shawtari ◽  
Muslim Har Sani Mohamad ◽  
Hafiz Majdi Abdul Rashid ◽  
Abdullah Moh’d Ayedh
Keyword(s):  
Quantile Regression ◽  
Ordinary Least Squares ◽  
Performance Measure ◽  
Influential Factor ◽  
New Developments ◽  
Content Type ◽  
Board Characteristics ◽  
Real Performance ◽  
The Impact ◽  
The Relationship

Purpose The purpose of this paper is to investigate the relationship between board characteristics and real performance among state-owned enterprises (SOEs) in Malaysia in a longitudinal period following the introduction of transformation policy. Design/methodology/approach The study deviates from prior research in utilising a real performance measure rather than traditional measures of performance. The authors adopt the quantile regression approach to examine the impact of board characteristics on real performance in a comparison using ordinary least squares. Findings The results of quantile regression reveal that the impact of board mechanisms on real performance was not as expected. Specifically, board size and duality had a bearing on real performance. Board independence also is considered as influential factor through the time. However, such effects were not homogenous across different quantiles. The dummy year variable to compare the period pre- and post-transformation policy reveals that the dummy year is not significant, indicating that performance post-transformation is indifferent compared to the pre-transformation policy period. Practical implications It is important for government to reconsider the policies embedded in the transformation policy. This study provides insights on the enhancement of board effectiveness and new developments regarding GLCs. Originality/value This is an early to attempt to measure real performance and its link to board characteristics in SOEs post-transformation policy.

scholarly journals The impact of the 2008 financial crisis on food security and food expenditures in Mexico: a disproportionate effect on the vulnerable

2014 ◽  
Vol 18 (16) ◽  
pp. 2934-2942 ◽  
Author(s):  
Mireya Vilar-Compte ◽  
Sebastian Sandoval-Olascoaga ◽  
Ana Bernal-Stuart ◽  
Sandhya Shimoga ◽  
Arturo Vargas-Bustamante
Keyword(s):  
Food Security ◽  
Financial Crisis ◽  
Quantile Regression ◽  
Least Squares ◽  
Logistic Model ◽  
Ordinary Least Squares ◽  
2008 Financial Crisis ◽  
Food Expenditures ◽  
The 2008 Financial Crisis ◽  
The Impact

AbstractObjectiveThe present paper investigated the impact of the 2008 financial crisis on food security in Mexico and how it disproportionally affected vulnerable households.DesignA generalized ordered logistic regression was estimated to assess the impact of the crisis on households’ food security status. An ordinary least squares and a quantile regression were estimated to evaluate the effect of the financial crisis on a continuous proxy measure of food security defined as the share of a household’s current income devoted to food expenditures.SettingBoth analyses were performed using pooled cross-sectional data from the Mexican National Household Income and Expenditure Survey 2008 and 2010.SubjectsThe analytical sample included 29 468 households in 2008 and 27 654 in 2010.ResultsThe generalized ordered logistic model showed that the financial crisis significantly (P<0·05) decreased the probability of being food secure, mildly or moderately food insecure, compared with being severely food insecure (OR=0·74). A similar but smaller effect was found when comparing severely and moderately food-insecure households with mildly food-insecure and food-secure households (OR=0·81). The ordinary least squares model showed that the crisis significantly (P<0·05) increased the share of total income spent on food (β coefficient of 0·02). The quantile regression confirmed the findings suggested by the generalized ordered logistic model, showing that the effects of the crisis were more profound among poorer households.ConclusionsThe results suggest that households that were more vulnerable before the financial crisis saw a worsened effect in terms of food insecurity with the crisis. Findings were consistent with both measures of food security – one based on self-reported experience and the other based on food spending.

The evolution of herd behavior: Will herding disappear over time?

2019 ◽  
Vol 36 (4) ◽  
pp. 637-661 ◽  
Author(s):  
Kalugala Vidanalage Aruna Shantha
Keyword(s):  
Civil War ◽  
Quantile Regression ◽  
Political Instability ◽  
Political Stability ◽  
Ordinary Least Squares ◽  
Least Square ◽  
Herd Behavior ◽  
Absolute Deviation ◽  
Content Type ◽  
The Impact

Purpose The purpose of this paper is to examine the evolutionary nature of herding phenomenon in the context of a frontier stock market, the Colombo Stock Exchange of Sri Lanka. Design/methodology/approach This study applies the cross-sectional absolute deviation methodology for daily frequencies of data of all the common stocks listed during the period from April 2000 to March 2018. The regression coefficients are estimated by using both the ordinary least square and the quantile regression procedures. Findings The findings reveal significant changes to the pattern of herding over different market periods, each with specific characteristics. Herding is strongly evident in up and down market days in the 2000-2009 period, during which the market was highly uncertain with the impact of the political instability of the country due to the Civil War on the stock trading. Even after this Civil War period, herd tendency is strongly manifested toward the up market direction as a result of the investors’ optimism about the country’s economy and political stability, which caused to a speculative bubble in the market. After that, it is turned into negative herding due to the panic selling occurred in view of the uncertainty of the inflated prices, which led to a market crash. Notably, herding appears to be consistently absent over the period after the crash, despite the presence of herd motives such as high market uncertainties triggered by political instability and economic crisis during that period. Research limitations/implications The findings suggest that herd behavior is an evolving phenomenon in financial markets. Consistent with the adaptive market hypothesis, the absence of herding evident after the market crash could be attributed to the investors’ learning of the irrationality of herding/negative herding for adapting to market conditions. As a result, herding and negative herding tendencies declined and disappeared at the aggregate market level. Originality/value This study contributes to the literature by providing novel evidence on the evolutionary nature of behavioral biases, particularly herding, as predicted by the adaptive market hypothesis. With the application of the quantile regression procedure, in addition to customary used ordinary least squares approach, it also provides robust evidence on this phenomenon.

MODELLING THE EFFECTS OF MATERNAL SOCIO-DEMOGRAPHIC CHARACTERISTICS ON THE PRETERM AND TERM BIRTH WEIGHT DISTRIBUTIONS IN GREECE USING QUANTILE REGRESSION

2012 ◽  
Vol 45 (3) ◽  
pp. 375-390 ◽  
Author(s):  
GEORGIA VERROPOULOU ◽  
CLEON TSIMBOS
Keyword(s):  
Birth Weight ◽  
Quantile Regression ◽  
Preterm Births ◽  
Ordinary Least Squares ◽  
Demographic Characteristics ◽  
Prior History ◽  
Weight Distributions ◽  
Higher Educational Attainment ◽  
Term Births ◽  
The Impact

SummaryThe present study aims at modelling the effects of maternal socio-demographic characteristics on the birth weight distribution in Greece. The analysis is based on nationwide vital registration micro-data; 103,266 single live births recorded in 2006 are considered. Quantile regression models, allowing for the effects of covariates to vary across the conditional distribution of the dependent variable, birth weight, are applied to preterm and term births separately. The statistical analysis shows that the effects of most factors differentiate across the birth weight distributions. Ordinary Least Squares (OLS) coefficients, on the other hand, systematically underestimate effects at the lower tail and overestimate effects among heavier babies. Hence, quantile regression has a strong advantage over the OLS method. The findings also indicate that birth weight distributions of term and preterm infants are distinct and should be analysed separately. For both distributions female sex, primiparity, age of mother over 35 and prior history of stillbirths and child deaths are related to lower birth weight while higher educational attainment has a protective effect. Among term births, illegitimacy, living in big metropolitan areas and immigrant status of the mother are also significant predictors. For preterm births the impact of age of mother, parity and, in particular, prior stillbirths or deceased children is very pronounced.

scholarly journals Determinants of the Price of Housing in the Province of Alicante (Spain): Analysis Using Quantile Regression

2019 ◽  
Vol 11 (2) ◽  
pp. 437 ◽  
Author(s):  
Raul-Tomas Mora-Garcia ◽  
Maria-Francisca Cespedes-Lopez ◽  
V. Raul Perez-Sanchez ◽  
Pablo Marti ◽  
Juan-Carlos Perez-Sanchez
Keyword(s):  
Multivariate Analysis ◽  
Quantile Regression ◽  
Ordinary Least Squares ◽  
Hedonic Pricing ◽  
Average Price ◽  
Pricing Model ◽  
Hedonic Pricing Model ◽  
Adequate Funding ◽  
The Impact ◽  
The Relationship

After almost a decade of crisis, the housing market in Spain shows significant signs of recovery, with increases in both the average price and the number of sales transactions. Housing is the main asset for the majority of households, and it also has the most resources devoted to it, thus, when it comes to buying a residence, people do not only look at the asset’s intrinsic characteristics, but also consider other particularities such as the neighbourhood, accessibility to services, availability of public transport or adequate funding. The study aimed to analyse and quantify the relationship that exists between the asking price of second-hand housing on the market in Alicante and the attributes that characterise them. This was done using a multivariate analysis to estimate a hedonic pricing model by ordinary least squares and a quantile regression to analyse the impact of the characteristics in different price ranges. The results show the segmentation of the prices in the Alicante market, with higher prices in the northern coastal area over the southern and inland comarcas.

Diversity and the Performance of Selected Financial Institutions of Asia

2018 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Shafaque Fatima ◽  
Saqib Sharif
Keyword(s):  
Financial Institutions ◽  
Positive Impact ◽  
Financial Institution ◽  
Gender Diversity ◽  
Business Case ◽  
Ordinary Least Squares ◽  
Cross Sectional ◽  
Age Diversity ◽  
The Impact ◽  
Nationality Diversity

Linking with the business case for diversity, this study examines whether the top management team (TMT) and the board of directors (BODs) diversity has a positive impact on financial institution (FI) performance in select countries of Asia least researched domain. We use data from 119 financial institutions across Asia for the year 2015, initially 1,447 institutions; however, incomplete data was excluded from final analysis. We use three proxies for diversity, that is, nationality diversity, gender diversity, and age diversity of TMT and BODs. To investigate the impact of TMT and BODs diversity, cross-sectional ordinary least-squares estimation is applied, using Return on Average Assets (ROAA%) as a measure of performance.  We find that nationality diversity and age diversity is positively and significantly related to FIs performance. Our evidence indicates that executives and board members with diverse exposure and younger age improve FIs profitability. However, there is no significant relationship between gender and FIs performance.

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