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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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4.2%8.3%12.5%16.7% · Sep 199519922001200920172026
48 results for Past Spending Maximum

Study optimal consumption for loss-averse agents considering past spending peaks.

problem Optimal consumption for loss-averse agents with reference to past spending maximum.
method Adopted S-shaped utility, concave envelope, HJB variational inequality, dual transform, and smooth-fit conditions.
result Obtained piecewise closed-form solutions for optimal consumption and investment control.

The paper analyzes optimal consumption with past spending maximum as a reference.

problem Optimal consumption with past spending maximum as a reference.
method Path-dependent exponential utility, Hamilton-Jacobi-Bellman (HJB) equation, dual transform, smooth-fit principle.
result Closed-form solutions for optimal investment and consumption strategies in each region.

New framework guides resource usage to achieve sublinear regret in adversarial settings.

problem Achieving sublinear regret in online decision making with changing reward and cost distributions.
method General primal-dual methods guided by spending plans that ensure balanced resource usage.
result Achieves sublinear regret with respect to spending plans that balance resource usage.

This paper improves credit line impact analysis by considering spending as a distribution.

problem Previous studies on credit lines' impact on spending have overlooked the distributional nature of spending.
method Developed a distribution-valued estimator framework to extend existing real-valued estimators.
result Credit lines positively influence spending across all quantiles, but more towards luxuries as they increase.

Investors adjust spending based on a social norm, spending less during losses and more during gains.

problem Managing spending and portfolio decisions while adhering to a social norm.
method Formulated a preference ordering with two CRRA preference orderings, solved analytically and numerically.
result Annual spending should be lower than expected financial return and procyclical, with spending cuts following losses.

The effects of saving and spending patterns on holding time distribution of money are investigated based on the ideal gas-like models. We show the steady-state distribution obeys an exponential law when the saving factor is set uniformly, and a power law when the saving factor is set diversely. The power distribution c…

2005-07-20abs ↗pdf ↗

Automating the customer analytics process is crucial for companies that manage distinct customer bases. In such data-rich and dynamic environments, visualization plays a key role in understanding events of interest. These ideas have led to the popularity of analytics dashboards, yet academic research has paid scant att…

2015-11-17abs ↗pdf ↗

Optimizes retirement spending and asset allocation to maximize withdrawals and shortfall.

problem Risk of depleting retirement savings with constant withdrawal rules.
method Dynamic asset allocation to maximize weighted EW and ES.
result Dynamic strategy outperforms constant withdrawal and asset allocation rules.

This paper solves the problem of optimal dynamic consumption, investment, and healthcare spending with isoelastic utility, when natural mortality grows exponentially to reflect Gompertz' law and investment opportunities are constant. Healthcare slows the natural growth of mortality, indirectly increasing utility from c…

2019-01-02abs ↗pdf ↗

Study optimal healthcare spending under Epstein-Zin preferences for longevity.

problem Optimizing healthcare spending to extend longevity under Epstein-Zin preferences.
method Formulated Epstein-Zin utilities over a controllable random horizon using backward stochastic differential equations and HJB equations.
result Calibrated model accurately reflects actual mortality data and compares healthcare efficacy between countries.

During the Great Recession, Democrats in the United States argued that government spending could be utilized to "grease the wheels" of the economy in order to create wealth and to increase employment; Republicans, on the other hand, contended that government spending is wasteful and discouraged investment, thereby incr…

2014-10-22abs ↗pdf ↗

The paper introduces neural INGARCH models for time series of counts.

problem Analyzing time series of counts using traditional INGARCH models.
method Combining artificial neural networks with INGARCH models.
result Neural INGARCH models outperform traditional models in information loss.

Certain biological neurons demonstrate a remarkable capability to optimally compress the history of sensory inputs while being maximally informative about the future. In this work, we investigate if the same can be said of artificial neurons in recurrent neural networks (RNNs) trained with maximum likelihood. Empirical…

2019-10-21abs ↗pdf ↗

Estimates causal effect of managed care plans on NYC Medicaid spending.

problem Generalizing causal estimates to a target population not well-represented by randomized studies.
method Conditional cross-design synthesis estimators combining randomized and observational data.
result Estimates causal effect of managed care plans on health care spending.

In this paper, we work in the framework of the Merton problem but we impose a drawdown constraint on the consumption process. This means that consumption can never fall below a fixed proportion of the running maximum of past consumption. In terms of economic motivation, this constraint represents a type of habit format…

2012-10-18abs ↗pdf ↗

This work investigates training infinite mixtures with maximum likelihood for improved uncertainty quantification.

problem Improving uncertainty quantification in neural networks.
method Investigates training infinite mixtures with maximum likelihood instead of variational inference.
result The proposed method leads to stochastic networks with increased predictive variance, improved robustness, and higher entropy on out-of-distribution data.

Develops new Markov processes with switching rates and past dependence.

problem Modeling processes with dynamic switching rates and path dependence.
method Introduces a new class of Markov jump processes with regime switching and path dependence. Derives distributional properties and maximum likelihood estimates.
result Maximum likelihood estimates of the process parameters are derived in closed form and have asymptotic normality.

Understanding consumption dynamics and its impact on the whole economy and welfare within the present economic crisis is not an easy task. Indeed the level of consumer demand for different goods varies with the prices, consumer incomes and demographic factors. Furthermore crisis may trigger different behaviors which re…

2017-04-23abs ↗pdf ↗

The distribution of health care payments to insurance plans has substantial consequences for social policy. Risk adjustment formulas predict spending in health insurance markets in order to provide fair benefits and health care coverage for all enrollees, regardless of their health status. Unfortunately, current risk a…

2019-01-28abs ↗pdf ↗

While all kinds of mixed data -from personal data, over panel and scientific data, to public and commercial data- are collected and stored, building probabilistic graphical models for these hybrid domains becomes more difficult. Users spend significant amounts of time in identifying the parametric form of the random va…

2017-10-09abs ↗pdf ↗

Study improves retail demand forecasting by integrating macroeconomic data.

problem Lack of accurate demand forecasting due to incomplete data.
method Enriched time series data with macroeconomic variables; compared regression and machine learning models.
result Improved accuracy in predicting retail demand through comprehensive data integration.

This work analyzes the maximum-margin bias in quasi-homogeneous neural networks.

problem Analyzing the maximum-margin bias in quasi-homogeneous neural networks.
method Geometric analysis of gradient dynamics for quasi-homogeneous models.
result Gradient flow implicitly favors a subset of parameters, leading to asymmetric norm minimization.

Estimates missing distributions using nearest neighbors with kernel methods.

problem Missing data and unobserved confounding in multivariate distributions.
method Distributional matrix completion framework with kernel nearest neighbors.
result Consistent recovery of underlying distributions with missing data.

We show that if Teichmüller geodesics spend enough time in the thick part of moduli space, they display CAT(-1)-type properties. In particular, they exponentially contract along strongly stable leaves. As an application we prove two closing lemmas.

2018-08-29abs ↗pdf ↗

We compute the asymptotic growth rate of the number N(C, R) of closed geodesics of length less than R in a connected component C of a stratum of quadratic differentials. We prove that for any 0 < θ< 1, the number of closed geodesics of length at most R that spend at least θ-fraction of time outside of a compact subset …

2012-06-25abs ↗pdf ↗

A major challenge in Bayesian Optimization is the boundary issue (Swersky, 2017) where an algorithm spends too many evaluations near the boundary of its search space. In this paper, we propose BOCK, Bayesian Optimization with Cylindrical Kernels, whose basic idea is to transform the ball geometry of the search space us…

2018-06-05abs ↗pdf ↗

For the first time ever, we analyze a unique public procurement database, which includes information about a number of bidders for a contract, a final price, an identification of a winner and an identification of a contracting authority for each of more than 40,000 public procurements in the Czech Republic between 2006…

2013-09-01abs ↗pdf ↗

Bitcoin mining costs remain stable despite increased activity.

problem Stability of Bitcoin mining costs despite rising energy consumption.
method Estimation of global energy cost over a decade, considering changing oil costs and technological improvements.
result The cost of Bitcoin mining has remained relatively stable since 2010, relative to the volume of transactions.

We study the motion of an nn-dimensional closed spacelike hypersurface in a Lorentzian manifold in the direction of its past directed normal vector, where the speed equals a positive power pp of the mean curvature. We prove that for any p(0,1]p\in (0,1], the flow exists for all time when the Ricci tensor of the ambient s…

2006-02-13abs ↗pdf ↗

We study investment strategy in different models of financial markets, where the investors cannot reach a perfect knowledge about available assets. The investor spends a certain effort to get information; this allows him to better choose the investment strategy, and puts a selective pressure upon assets. The best strat…

1999-12-17abs ↗pdf ↗

DE is a new exploration method that limits resource usage based on expected improvement and surprise.

problem Limited exploration in large action spaces when resources are scarce.
method Delight-gated exploration (DE) that limits exploration actions based on a gate price set by the product of expected improvement and surprise.
result DE outperforms ε\varepsilon-greedy and Thompson Sampling in terms of regret across various bandit and MDP settings.

The paper optimizes retirement spending considering habit formation and pension income.

problem Optimizing lifetime consumption under habit formation and pension income.
method Time inhomogeneous stochastic control problem with numerical solution using finite difference scheme.
result Consumption patterns change over time based on habit and optimal strategy.

Combines model-based and model-free RL for better financial market performance.

problem Challenges of Reinforcement Learning in volatile financial markets.
method Adapts model-based RL with model-free RL, incorporating contextual signals and walk-forward analysis.
result Outperforms traditional financial models in various metrics.

Paper studies optimal investing for retirees with risk constraints.

problem Retirees' longevity and living standard risks in a fluctuating market.
method Formulated as a portfolio choice problem under time-varying risk capacity constraint. Derived optimal investment strategy using differential equations. Demonstrated endogenous spending measure and active investment strategy.
result Time-varying risk capacity constraint impacts asset allocation in retirement.

Generative Adversarial Networks (GANs) have been promising in the field of image generation, however, they have been hard to train for language generation. GANs were originally designed to output differentiable values, so discrete language generation is challenging for them which causes high levels of instability in tr…

2018-04-08abs ↗pdf ↗

We solve a lifecycle model in which the consumer's chronological age does not move in lockstep with calendar time. Instead, biological age increases at a stochastic non-linear rate in time like a broken clock that might occasionally move backwards. In other words, biological age could actually decline. Our paper is ins…

2018-11-25abs ↗pdf ↗