New formulas estimate life insurance benefits with less computation.
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Study validates Libor model for insurance benefits calculation.
Within the context of traditional life insurance, a model-independent relationship about how the market value of assets is attributed to the best estimate, the value of in-force business and tax is established. This relationship holds true for any portfolio under run-off assumptions and can be used for the validation o…
We investigate the relationship between market efficiency of rice futures transaction in Osaka and the Japanese government intervention in rice distributions by directly buying and selling rice during the interwar period, from the middle 1910s to 1939, considering the context of "discretion versus rules." We use a time…
Study shows human advisors use context to improve student outcomes in algorithm-assisted advising.
We present a methodology for obtaining explicit solutions to infinite time horizon optimal stopping problems involving general, one-dimensional, Itô diffusions, payoff functions that need not be smooth and state-dependent discounting. This is done within a framework based on dynamic programming techniques employing var…
We analyze an optimal stopping problem with random maturity under a nonlinear expectation with respect to a weakly compact set of mutually singular probabilities . The maturity is specified as the hitting time to level of some continuous index process at which the payoff process is even allowed to have…
Evidence acquisition costs influence disclosure behavior and preference.
FinRobot AI agent for equity research provides comprehensive insights.
We analyze expenditure patterns of discretionary funds by Brazilian congress members. This analysis is based on a large dataset containing over million expenses made publicly available by the Brazilian government. This dataset has, up to now, remained widely untouched by machine learning methods. Our main contribut…
Robinhood users react strongly to overnight price changes and big losers, trading quickly after extreme losses.
The paper examines how macroeconomic control tools lost effectiveness, leading to a 'dark ages' period.
The study identifies extremal dependence in financial markets using a bootstrap-based testing procedure.
As part of Basel II's incremental risk charge (IRC) methodology, this paper summarizes our extensive investigations of constructing transition probability matrices (TPMs) for unsecuritized credit products in the trading book. The objective is to create monthly or quarterly TPMs with predefined sectors and ratings that …
Equivalences are known between problems of singular stochastic control (SSC) with convex performance criteria and related questions of optimal stopping, see for example Karatzas and Shreve [SIAM J. Control Optim. 22 (1984)]. The aim of this paper is to investigate how far connections of this type generalise to a non co…
Predicts stock volatility using Twitter data and random forests.
Develops a new framework for integrating satellite allocations in small portfolios.
Cost-benefit analysis often assumes accurate estimates, but this study finds significant inaccuracies.
This paper uses PCA and FA for feature selection in credit rating.
Facing a heavy task, any single person can only make a limited contribution and team cooperation is needed. As one enjoys the benefit of the public goods, the potential benefits of the project are not always maximized and may be partly wasted. By incorporating individual ability and project benefit into the original pu…
Study examines the impact of employment benefit costs on firm profitability.
Paper explores how to design federated learning protocols that benefit all participants while maintaining privacy.
Distributed, controllable energy storage devices offer several benefits to electric power system operation. Three such benefits include reducing peak load, providing standby power, and enhancing power quality. These benefits, however, are only realized during peak load or during an outage, events that are infrequent. T…
Develops a test to assess if human experts add value to predictions.
Oil is perceived as a good diversification tool for stock markets. To fully understand this potential, we propose a new empirical methodology that combines generalized autoregressive score copula functions with high frequency data and allows us to capture and forecast the conditional time-varying joint distribution of …
The paper introduces a new algorithm for fair decision-making in outcome control tasks.
We present new minimax results that concisely capture the relative benefits of source and target labeled data, under covariate-shift. Namely, we show that the benefits of target labels are controlled by a transfer-exponent that encodes how singular Q is locally w.r.t. P, and interestingly allows situations where tr…
One of the findings of the recent literature is that the 2008 financial crisis caused reduction in international diversification benefits. To fully understand the possible potential from diversification, we build an empirical model which combines generalised autoregressive score copula functions with high frequency dat…
The article first describes characteristics of major infrastructure projects. Second, it documents a much neglected topic in economics: that ex ante estimates of costs and benefits are often very different from actual ex post costs and benefits. For large infrastructure projects the consequence is cost overruns, benefi…
In this paper we present a numerical valuation of variable annuities with combined Guaranteed Minimum Withdrawal Benefit (GMWB) and Guaranteed Minimum Death Benefit (GMDB) under optimal policyholder behaviour solved as an optimal stochastic control problem. This product simultaneously deals with financial risk, mortali…
Finance has benefited from the Wolfram's NKS approach but it can and will benefit even more in the future, and the gains from the influence may actually be concentrated among practitioners who unintentionally employ those principles as a group.
The quality of an induced model by a learning algorithm is dependent on the quality of the training data and the hyper-parameters supplied to the learning algorithm. Prior work has shown that improving the quality of the training data (i.e., by removing low quality instances) or tuning the learning algorithm hyper-para…
We identify action representations from video data, proving their statistical benefits.
Study adaptive clinical trial methods for identifying patient subpopulations with treatment benefit.
The paper introduces a method to measure the benefits of incidental supervision signals.
Hierarchical reinforcement learning has demonstrated significant success at solving difficult reinforcement learning (RL) tasks. Previous works have motivated the use of hierarchy by appealing to a number of intuitive benefits, including learning over temporally extended transitions, exploring over temporally extended …
The paper studies the benefits of curriculum learning in linear regression tasks.
We introduce Graph Neural Processes (GNP), inspired by the recent work in conditional and latent neural processes. A Graph Neural Process is defined as a Conditional Neural Process that operates on arbitrary graph data. It takes features of sparsely observed context points as input, and outputs a distribution over targ…
A new method sorts projects using Quicksort and Bradley-Terry model for uncertain long-term benefits.
Kernel methods benefit from enforcing invariance, reducing generalization error.
The paper prices a new life insurance policy for couples, considering various contingent benefits.
Actuaries tackle loss of earning capacity in Denmark, balancing public benefits and private insurance.
The paper analyzes the benefit-cost ratio for feature selection in machine learning.
We discuss the binary nature of funding impact in derivative valuation. Under some conditions, funding is either a cost or a benefit, i.e., one of the lending/borrowing rates does not play a role in pricing derivatives. When derivatives are priced, considering different lending/borrowing rates leads to semi-linear BSDE…
There are clear benefits associated with a particular consumer choice for many current markets. For example, as we consider here, some products might carry environmental or `green' benefits. Some consumers might value these benefits while others do not. However, as evidenced by myriad failed attempts of environmental p…
Study evaluates when splitting classifiers can improve performance despite disparate treatment.
Success in the quest for artificial intelligence has the potential to bring unprecedented benefits to humanity, and it is therefore worthwhile to investigate how to maximize these benefits while avoiding potential pitfalls. This article gives numerous examples (which should by no means be construed as an exhaustive lis…
Curriculum learning shows marginal benefits over random ordering on standard datasets.