| Nome |
# |
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A random forest algorithm to improve the Lee–Carter mortality forecasting: impact on q-forward, file e3835325-824b-15e8-e053-a505fe0a3de9
|
362
|
|
Longevity risk management through Machine Learning: state of the art, file e3835328-85e9-15e8-e053-a505fe0a3de9
|
297
|
|
Application of Machine Learning to Mortality Modeling and Forecasting, file e3835320-7366-15e8-e053-a505fe0a3de9
|
296
|
|
A deep learning integrated Lee-Carter model, file e3835320-744e-15e8-e053-a505fe0a3de9
|
228
|
|
Maximum Market Price of Longevity Risk under Solvency Regimes: The Case of Solvency II., file e3835317-1713-15e8-e053-a505fe0a3de9
|
125
|
|
COVID-19 crisis and resilience: challenges for the insurance sector, file e383532b-cd91-15e8-e053-a505fe0a3de9
|
104
|
|
The Importance of Economic Variables on London Real Estate Market: A Random Forest Approach, file e3835328-1bd0-15e8-e053-a505fe0a3de9
|
85
|
|
Machine Learning and Financial Literacy: An Exploration of Factors Influencing Financial Knowledge in Italy, file e383532b-25ef-15e8-e053-a505fe0a3de9
|
74
|
|
Automatic Balance Mechanisms for Notional Defined Contribution pension systems guaranteeing social adequacy and financial sustainability: an application to the Italian pension system, file e3835328-21eb-15e8-e053-a505fe0a3de9
|
69
|
|
Preface: recent developments in financial modelling and risk management, file e383532b-ff0a-15e8-e053-a505fe0a3de9
|
63
|
|
Neural Networks for quantile claim amount estimation: a quantile regression approach, file c56ac012-6288-4082-88cc-8fbd17533ed5
|
29
|
|
LI-CoD Model. From Lifespan Inequality to Causes of Death, file e3835328-10e3-15e8-e053-a505fe0a3de9
|
23
|
|
Managing longevity and disability risks in life annuities with long term care, file e3835312-2749-15e8-e053-a505fe0a3de9
|
11
|
|
Quantile Regression Neural Network for Quantile Claim Amount Estimation, file e383532d-f827-15e8-e053-a505fe0a3de9
|
9
|
|
Pricing Critical Illness Insurance from Prevalence Rates: Gompertz versus Weibull, file e383531b-2df7-15e8-e053-a505fe0a3de9
|
6
|
|
A complex networks approach to pension funds, file e3835325-53db-15e8-e053-a505fe0a3de9
|
6
|
|
Allungamento della vita media e rischio assicurativo, file e3835316-2a85-15e8-e053-a505fe0a3de9
|
5
|
|
Natural hedging in long-Term care insurance, file e3835319-e62e-15e8-e053-a505fe0a3de9
|
5
|
|
Longevity bond pricing models: an application to the Italian annuity market and pension schemes, file e3835311-8856-15e8-e053-a505fe0a3de9
|
4
|
|
null, file e383532c-e349-15e8-e053-a505fe0a3de9
|
4
|
|
Longevity Bonds: an Application to the Italian Annuity Market, file e3835312-3a1b-15e8-e053-a505fe0a3de9
|
3
|
|
Modelli attuariali per la stima di basi tecniche relative ad assicurazioni di persone, file e3835316-c637-15e8-e053-a505fe0a3de9
|
3
|
|
An option pricing approach for measuring Solvency Capital Requirements in Insurance Industry, file e383531c-c5d9-15e8-e053-a505fe0a3de9
|
3
|
|
Fuzzy clustering of the healthy life expectancy decomposition: A multi-population analysis, file 58f1658f-4293-4d4b-9fb8-82a61e9d9570
|
2
|
|
null, file 64e6cf55-6f68-4132-9db4-0b5bcf587513
|
2
|
|
A tensor-based approach to cause-of-death mortality modeling, file c62e4e23-b53f-4b7f-9792-a15a95848063
|
2
|
|
A longevity basis risk analysis in a joint FDM framework, file e3835316-4dbf-15e8-e053-a505fe0a3de9
|
2
|
|
Stima di basi tecniche per assicurazioni LTC, malattie gravi e invalidità, file e3835316-f046-15e8-e053-a505fe0a3de9
|
2
|
|
Measuring and Hedging the basis risk by Functional Demographic Models, file e3835316-f535-15e8-e053-a505fe0a3de9
|
2
|
|
Data Science and machine learning in insurance, file e3835324-30d2-15e8-e053-a505fe0a3de9
|
2
|
|
De-risking long-term care insurance, file e3835325-4da3-15e8-e053-a505fe0a3de9
|
2
|
|
Life expectancy and lifespan disparity forecasting: a long short-term memory approach, file e3835328-2bb9-15e8-e053-a505fe0a3de9
|
2
|
|
Clustering-based simultaneous forecasting of life expectancy time series through Long-Short Term Memory Neural Networks, file e383532d-bef4-15e8-e053-a505fe0a3de9
|
2
|
|
Improving longevity risk management through machine learning, file e383532e-5d31-15e8-e053-a505fe0a3de9
|
2
|
|
An Application of the Tensor-Based Approach to Mortality Modeling, file 89c2e01e-ad79-4d6f-b79b-0efacdf7670c
|
1
|
|
A cohort study on the gender gap in mortality through the Tucker3 model, file 98e68328-16c2-4cd3-a515-8b790d681950
|
1
|
|
Modelling and managing longevity and disability risks in Long Term Care insurance, file e3835312-2005-15e8-e053-a505fe0a3de9
|
1
|
|
A health insurance pricing model based on prevalence rates: Application to critical illness insurance, file e3835312-61b5-15e8-e053-a505fe0a3de9
|
1
|
|
Measuring and Hedging the basis risk by Functional Demographic Models, file e3835316-f048-15e8-e053-a505fe0a3de9
|
1
|
|
Network analysis of pension funds investments, file e383532c-cf98-15e8-e053-a505fe0a3de9
|
1
|
|
Insurance Role for Handling the COVID-19 impact on Business and Society, file e383532c-e7e6-15e8-e053-a505fe0a3de9
|
1
|
|
Mutual peer-to-peer insurance: The allocation of risk, file e383532d-bef5-15e8-e053-a505fe0a3de9
|
1
|
|
Causes-of-Death Specific Estimates from Synthetic Health Measure: A Methodological Framework, file e383532d-c860-15e8-e053-a505fe0a3de9
|
1
|
|
Fundamental ratios as predictors of ESG scores: a machine learning approach, file e383532d-cf25-15e8-e053-a505fe0a3de9
|
1
|
|
Modelling Health Transitions in Italy: A Generalized Linear Model with Disability Duration, file e383532d-fa79-15e8-e053-a505fe0a3de9
|
1
|
|
The Neural Network Lee–Carter Model with Parameter Uncertainty: The Case of Italy, file e383532e-2b3f-15e8-e053-a505fe0a3de9
|
1
|
|
Deep learning in predicting cryptocurrency volatility, file e383532e-6a5b-15e8-e053-a505fe0a3de9
|
1
|
|
An application of contrast trees for mortality models diagnostic and boosting, file e383532e-6ec9-15e8-e053-a505fe0a3de9
|
1
|
|
Predicting the second wave of COVID-19 pandemic through the Dynamic Evolving Neuro Fuzzy Inference System, file e383532f-233c-15e8-e053-a505fe0a3de9
|
1
|
| Totale |
1.851 |