Exploring the determinants of liquidity with big data – market heterogeneity in German markets

2018 ◽  
Vol 36 (1) ◽  
pp. 3-18 ◽  
Author(s):  
Marcelo Cajias ◽  
Philipp Freudenreich
Keyword(s):  
Big Data ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
City Centre ◽  
Content Type ◽  
Rental Market ◽  
Hazards Model ◽  
German Cities

Purpose The purpose of this paper is to examine the market liquidity (time-on-market (TOM)) and its determinants, for rental dwellings in the largest seven German cities, with big data. Design/methodology/approach The determinants of TOM are estimated with the Cox proportional hazards model. Hedonic characteristics, as well as socioeconomic and spatial variables, are combined with different fixed effects and controls for non-linearity, so as to maximise the explanatory power of the model. Findings Higher asking rent and larger living space decrease the liquidity in all seven markets, while the age of a dwelling, the number of rooms and proximity to the city centre accelerate the letting process. For the other hedonic characteristics heterogeneous implications emerge. Practical implications The findings are of interest for institutional and private landlords, as well as governmental organisations in charge of housing and urban development. Originality/value This is the first paper to deal with the liquidity of rental dwellings in the seven most populated cities of Europe’s second largest rental market, by applying the Cox proportional hazards model with spatial gravity variables. Furthermore, the German rental market is of particular interest, as approximately 60 per cent of all rental dwellings are owned by private landlords and the German market is organised polycentrically.

Money transfer between banks

2019 ◽  
Vol 38 (2) ◽  
pp. 283-295
Author(s):  
Andrea Lippi ◽  
Laura Barbieri ◽  
Federica Poli
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Financial Advisors ◽  
Data Set ◽  
Financial Intermediary ◽  
Content Type ◽  
Financial Advisor ◽  
Hazards Model

Purpose The purpose of this paper is to examine which individual traits of financial advisors influence portfolio transfer speed when a financial advisor recommends investors to migrate to a new financial intermediary. Design/methodology/approach With reference to the years 2014–2016, one of the three leading Italian tied-agent banks provided the authors with an exclusive and unique data set containing information regarding the financial advisors who had become tied agents, transferring their existing portfolios from their previous banks (traditional or tied-agent banks). The authors observed the ability of the migrant financial advisor in successfully transferring the entire portfolio declared within 12 months of observation. To investigate empirically which personal traits of financial advisors determine their success in the rapid transfer of clients’ portfolios to a new financial intermediary, the authors applied a Cox proportional hazards model. Findings The authors find that factors such as age, type of bank of origin and size of the managed financial portfolio positively affect the speed transfer. Practical implications The obtained results may be interesting for guiding recruiting policies of financial intermediaries. Social implications Regulators should closely examine the phenomenon analyzed in this paper to avoid conflict of interests. Originality/value The literature on this topic is scarce, mainly due to the lack of available data. This paper represents an original contribution to open a new field of research.

scholarly journals Risk factors associated with major adverse cardiac and cerebrovascular events following percutaneous coronary intervention: a 10-year follow-up comparing random survival forest and Cox proportional-hazards model

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Maryam Farhadian ◽  
Sahar Dehdar Karsidani ◽  
Azadeh Mozayanimonfared ◽  
Hossein Mahjub
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Coronary Intervention ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Hazards Model ◽  
Cerebrovascular Events ◽  
Long Term Follow Up ◽  
Stent Length

Abstract Background Due to the limited number of studies with long term follow-up of patients undergoing Percutaneous Coronary Intervention (PCI), we investigated the occurrence of Major Adverse Cardiac and Cerebrovascular Events (MACCE) during 10 years of follow-up after coronary angioplasty using Random Survival Forest (RSF) and Cox proportional hazards models. Methods The current retrospective cohort study was performed on 220 patients (69 women and 151 men) undergoing coronary angioplasty from March 2009 to March 2012 in Farchshian Medical Center in Hamadan city, Iran. Survival time (month) as the response variable was considered from the date of angioplasty to the main endpoint or the end of the follow-up period (September 2019). To identify the factors influencing the occurrence of MACCE, the performance of Cox and RSF models were investigated in terms of C index, Integrated Brier Score (IBS) and prediction error criteria. Results Ninety-six patients (43.7%) experienced MACCE by the end of the follow-up period, and the median survival time was estimated to be 98 months. Survival decreased from 99% during the first year to 39% at 10 years' follow-up. By applying the Cox model, the predictors were identified as follows: age (HR = 1.03, 95% CI 1.01–1.05), diabetes (HR = 2.17, 95% CI 1.29–3.66), smoking (HR = 2.41, 95% CI 1.46–3.98), and stent length (HR = 1.74, 95% CI 1.11–2.75). The predictive performance was slightly better by the RSF model (IBS of 0.124 vs. 0.135, C index of 0.648 vs. 0.626 and out-of-bag error rate of 0.352 vs. 0.374 for RSF). In addition to age, diabetes, smoking, and stent length, RSF also included coronary artery disease (acute or chronic) and hyperlipidemia as the most important variables. Conclusion Machine-learning prediction models such as RSF showed better performance than the Cox proportional hazards model for the prediction of MACCE during long-term follow-up after PCI.

scholarly journals Elevated plasma growth and differentiation factor 15 predicts incident anemia in older adults aged 60 years and older

2020 ◽  
Author(s):  
Yuko Yamaguchi ◽  
Marta Zampino ◽  
Toshiko Tanaka ◽  
Stefania Bandinelli ◽  
Yusuke Osawa ◽  
...  
Keyword(s):  
Older Adults ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Differentiation Factor ◽  
Hazards Model ◽  
Increased Risk ◽  
The Relationship

Abstract Background Anemia is common in older adults and associated with greater morbidity and mortality. The causes of anemia in older adults have not been completely characterized. Although elevated circulating growth and differentiation factor 15 (GDF-15) has been associated with anemia in older adults, it is not known whether elevated GDF-15 predicts the development of anemia. Methods We examined the relationship between plasma GDF-15 concentrations at baseline in 708 non-anemic adults, aged 60 years and older, with incident anemia during 15 years of follow-up among participants in the Invecchiare in Chianti (InCHIANTI) Study. Results During follow-up, 179 (25.3%) participants developed anemia. The proportion of participants who developed anemia from the lowest to highest quartile of plasma GDF-15 was 12.9%, 20.1%, 21.2%, and 45.8%, respectively. Adults in the highest quartile of plasma GDF-15 had an increased risk of developing anemia (Hazards Ratio 1.15, 95% Confidence Interval 1.09, 1.21, P<.0001) compared to those in the lower three quartiles in a multivariable Cox proportional hazards model adjusting for age, sex, serum iron, soluble transferrin receptor, ferritin, vitamin B12, congestive heart failure, diabetes mellitus, and cancer. Conclusions Circulating GDF-15 is an independent predictor for the development of anemia in older adults.

scholarly journals Dementia Adjudication Triggers Associated With Increased Mortality for Older Australians: Evidence From ASPREE

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 161-161
Author(s):  
Jane Banaszak-Holl ◽  
Xiaoping Lin ◽  
Jing Xie ◽  
Stephanie Ward ◽  
Henry Brodaty ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
The Elderly ◽  
Cox Proportional Hazards ◽  
Service Planning ◽  
Cox Proportional Hazards Model ◽  
Cognitive Test ◽  
Risk Of Death ◽  
Hazards Model ◽  
Using Data

Abstract Research Aims: This study seeks to understand whether those with dementia experience higher risk of death, using data from the ASPREE (ASPirin in Reducing Events in the Elderly) clinical trial study. Methods: ASPREE was a primary intervention trial of low-dose aspirin among healthy older people. The Australian cohort included 16,703 dementia-free participants aged 70 years and over at enrolment. Participants were triggered for dementia adjudication if cognitive test results were poorer than expected, self-reporting dementia diagnosis or memory problems, or dementia medications were detected. Incidental dementia was adjudicated by an international adjudication committee using the Diagnostic and Statistical Manual for Mental Disorders (DSM-IV) criteria and results of a neuropsychological battery and functional measures with medical record substantiation. Statistical analyses used a cox proportional hazards model. Results: As previously reported, 1052 participants (5.5%) died during a median of 4.7 years of follow-up and 964 participants had a dementia trigger, of whom, 575 (60%) were adjucated as having dementia. Preliminary analyses has shown that the mortality rate was higher among participants with a dementia trigger, regardless of dementia adjudication outcome, than those without (15% vs 5%, Χ2 = 205, p <.001). Conclusion: This study will provide important analyses of differences in the hazard ratio for mortality and causes of death among people with and without cognitive impairment and has important implications on service planning.

scholarly journals Evaluation of Changes on World Stock Exchanges in Connection with the SARS-CoV-2 Pandemic. Survival Analysis Methods

Risks ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 121
Author(s):  
Beata Bieszk-Stolorz ◽  
Krzysztof Dmytrów
Keyword(s):  
Survival Analysis ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Stock Exchange ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Stock Exchanges ◽  
Analysis Methods ◽  
Hazards Model ◽  
Kaplan Meier

The aim of our research was to compare the intensity of decline and then increase in the value of basic stock indices during the SARS-CoV-2 coronavirus pandemic in 2020. The survival analysis methods used to assess the risk of decline and chance of rise of the indices were: Kaplan–Meier estimator, logit model, and the Cox proportional hazards model. We observed the highest intensity of decline in the European stock exchanges, followed by the American and Asian plus Australian ones (after the fourth and eighth week since the peak). The highest risk of decline was in America, then in Europe, followed by Asia and Australia. The lowest risk was in Africa. The intensity of increase was the highest in the fourth and eleventh week since the minimal value had been reached. The highest odds of increase were in the American stock exchanges, followed by the European and Asian (including Australia and Oceania), and the lowest in the African ones. The odds and intensity of increase in the stock exchange indices varied from continent to continent. The increase was faster than the initial decline.

scholarly journals Association between milk and yogurt intake and mortality: a community-based cohort study (Yamagata study)

BMC Nutrition ◽  
2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Akiko Nakanishi ◽  
Erika Homma ◽  
Tsukasa Osaki ◽  
Ri Sho ◽  
Masayoshi Souri ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Hazard Analysis ◽  
Total Mortality ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Milk Intake ◽  
Community Based ◽  
Hazards Model ◽  
Kaplan Meier

Abstract Background Dairy products are known as health-promoting foods. This study prospectively examined the association between milk and yogurt intake and mortality in a community-based population. Methods The study population comprised of 14,264 subjects aged 40–74 years who participated in an annual health checkup. The frequency of yogurt and milk intake was categorized as none (< 1/month), low (< 1/week), moderate (1–6/week), and high (> 1/day) intake. The association between yogurt and milk intake and total, cardiovascular, and cancer-related mortalities was determined using the Cox proportional hazards model. Results During the follow-up period, there were 265 total deaths, 40 cardiovascular deaths and 90 cancer-related deaths. Kaplan–Meier analysis showed that the total mortality in high/moderate/low yogurt intake and moderate/low milk intake groups was lower than that in none group (log-rank, P < 0.01). In the multivariate Cox proportional hazard analysis adjusted for possible confounders, the hazard ratio (HR) for total mortality significantly decreased in high/moderate yogurt intake group (HR: 0.62, 95% confidence interval [CI]: 0.42–0.91 for high intake, HR: 0.70, 95%CI: 0.49–0.99 for moderate intake) and moderate milk intake group (HR: 0.67, 95% CI: 0.46–0.97) compared with the none yogurt and milk intake groups. A similar association was observed for cancer-related mortality, but not for cardiovascular mortality. Conclusions Our study showed that yogurt and milk intake was independently associated with a decrease in total and cancer-related mortalities in the Japanese population.

scholarly journals Clinical impact of regression from sustained to paroxysmal atrial fibrillation: the Fushimi AF registry

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
A Fujino ◽  
H Ogawa ◽  
S Ikeda ◽  
K Doi ◽  
Y Hamatani ◽  
...  
Keyword(s):  
Cardiac Death ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Clinical Impact ◽  
Cox Proportional Hazards Model ◽  
Cardiac Events ◽  
Hazards Model ◽  
Adverse Cardiac Events

Abstract Background Atrial fibrillation (AF) commonly progresses from paroxysmal type to sustained type in the natural course of the disease, and we previously demonstrated that the progression of AF was associated with increased risk of clinical adverse events. There are some patients, though less frequently, who regress from sustained to paroxysmal AF, but the clinical impact of the regression of AF remains unknown. Purpose We sought to investigate whether regression from sustained to paroxysmal AF is associated with better clinical outcomes. Methods Using the dataset of the Fushimi AF Registry, patients who were diagnosed as sustained (persistent or permanent) AF at baseline were studied. Conversion of sustained AF to paroxysmal AF during follow-up was defined as regression of AF. Major adverse cardiac events (MACE) were defined as the composite of cardiac death, stroke, and hospitalization for heart failure (HF). Event rates were compared between the patients with and without regression of AF. In patients with sustained AF at baseline, predictors of MACE were identified using Cox proportional hazards model. Results Among 2,253 patients who were diagnosed as sustained AF at baseline, regression of AF was observed in 9.0% (202/2,253, 2.0 per 100 patient-years) during a median follow-up of 4.0 years. Of these, 24.3% (49/202, 4.6 per 100 patient-years) of the patients finally recurred to sustained AF during follow-up. The proportion of asymptomatic patients was lower in patients with regression of AF than those without (with vs without regression; 49.0% vs 69.5%, p&lt;0.01). The percentage of beta-blocker use at baseline was similar between the two groups (37.2% vs 33.8%, p=0.34). The prevalence of patients who underwent catheter ablation or electrical cardioversion during follow-up was higher in patients with regression of AF (catheter ablation: 15.8% vs 5.5%; p&lt;0.01, cardioversion: 4.0% vs 1.4%; p&lt;0.01, respectively). The rate of MACE was significantly lower in patients with regression of AF as compared with patients who maintained sustained AF (3.7 vs 6.2 per 100 patient-years, log-rank p&lt;0.01). Figure shows the Kaplan-Meier curves for MACE, cardiac death, hospitalization for heart failure, and stroke. In patients with sustained AF at baseline, multivariable Cox proportional hazards model demonstrated that regression of AF was an independent predictor of lower MACE (adjusted hazard ratio [HR]: 0.50, 95% confidence interval [CI]: 0.28 to 0.88, p=0.02), stroke (HR: 0.51, 95% CI: 0.30 to 0.88, p=0.02), and hospitalization for HF (HR: 0.50, 95% CI: 0.29 to 0.85, p=0.01). Conclusion Regression from sustained to paroxysmal AF was associated with a lower incidence of adverse cardiac events. Funding Acknowledgement Type of funding source: None

Inter-pregnancy interval and later pediatric cardiovascular health of the offspring – a population-based cohort study

2020 ◽  
pp. 1-5
Author(s):  
Majdi Imterat ◽  
Tamar Wainstock ◽  
Eyal Sheiner ◽  
Gali Pariente
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Population Based ◽  
Cox Proportional Hazards ◽  
Cardiovascular Morbidity ◽  
Cox Proportional Hazards Model ◽  
Hazards Model ◽  
Kaplan Meier ◽  
Inter Pregnancy Interval

Abstract Recent evidence suggests that a long inter-pregnancy interval (IPI: time interval between live birth and estimated time of conception of subsequent pregnancy) poses a risk for adverse short-term perinatal outcome. We aimed to study the effect of short (<6 months) and long (>60 months) IPI on long-term cardiovascular morbidity of the offspring. A population-based cohort study was performed in which all singleton live births in parturients with at least one previous birth were included. Hospitalizations of the offspring up to the age of 18 years involving cardiovascular diseases and according to IPI length were evaluated. Intermediate interval, between 6 and 60 months, was considered the reference. Kaplan–Meier survival curves were used to compare the cumulative morbidity incidence between the groups. Cox proportional hazards model was used to control for confounders. During the study period, 161,793 deliveries met the inclusion criteria. Of them, 14.1% (n = 22,851) occurred in parturient following a short IPI, 78.6% (n = 127,146) following an intermediate IPI, and 7.3% (n = 11,796) following a long IPI. Total hospitalizations of the offspring, involving cardiovascular morbidity, were comparable between the groups. The Kaplan–Meier survival curves demonstrated similar cumulative incidences of cardiovascular morbidity in all groups. In a Cox proportional hazards model, short and long IPI did not appear as independent risk factors for later pediatric cardiovascular morbidity of the offspring (adjusted HR 0.97, 95% CI 0.80–1.18; adjusted HR 1.01, 95% CI 0.83–1.37, for short and long IPI, respectively). In our population, extreme IPIs do not appear to impact long-term cardiovascular hospitalizations of offspring.

A promising predictor of mortality— A cohort study (Preprint)

2021 ◽  
Author(s):  
Ji Ha Ling
Keyword(s):  
Intensive Care ◽  
Poor Prognosis ◽  
Medical Information ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Hazards Model ◽  
Clinical Biomarker ◽  
Secondary Result

UNSTRUCTURED Severe inflammation leads to poor prognosis for intensive care unit hospitalized patients. The is a biomarker used to monitor inflammation and immune response, which can predict poor prognosis of various diseases. However, it is unclear whether NLR is associated with all-cause mortality in ICU patients. This study investigated the correlation between MLR and ICU results. Extract clinical data from Medical Information Mart for Intensive Care III (MIMIC-III) database, which contains health data of more than 50,000 patients. The main result was 30-day mortality, and the secondary result was 90-day mortality. Use the Cox proportional hazards model to reveal the association between MLR and results. Multivariable analyses were used to control for confounders. NLR is a promising clinical biomarker, which can be used as a available predictor of ICU mortality.

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