289 research outputs found
Uniform Estimates for Eulerian-Lagrangian Methods for Singularly Perturbed Time-Dependent Problems
We prove a priori optimal-order error estimates in a weighted energy norm for several Eulerian–Lagrangian methods for singularly perturbed, time-dependent convection-diffusion equations with full regularity. The estimates depend only on certain Sobolev norms of the initial and right-hand side data, but not on ε or any norm of the true solution, and so hold uniformly with respect to ε. We use the interpolation of spaces and stability estimates to derive an ε-uniform estimate for problems with minimal or intermediate regularity, where the convergence rates are proportional to certain Besov norms of the initial and right-hand side data
Significant wave height forecasting based on the hybrid EMD-SVM method
1957-1962Prediction of significant wave height (SWH) is considered an effective method in marine engineering and prevention of marine disasters. Support vector machine (SVM) model has limitations in processing nonlinear and non-stationary SWH time series. Fortunately, empirical mode decomposition (EMD) can effectively deal with the complicated series. So, the SWH prediction method based on EMD and SVM is proposed by combining the advantages of both methods. A statistical analysis was carried out to compare the results of two models i.e., between the hybrid EMD-SVM and SVM. In addition, two models are used for forecasting SWH with 3, 6, 12 and 24 hours lead times, respectively. A high R value of different prediction times for the hybrid model. Results indicate that SWH prediction of the hybrid EMD-SVM model is superior to the SVM model
C-Procgen: Empowering Procgen with Controllable Contexts
We present C-Procgen, an enhanced suite of environments on top of the Procgen
benchmark. C-Procgen provides access to over 200 unique game contexts across 16
games. It allows for detailed configuration of environments, ranging from game
mechanics to agent attributes. This makes the procedural generation process,
previously a black-box in Procgen, more transparent and adaptable for various
research needs.The upgrade enhances dynamic context management and
individualized assignments, while maintaining computational efficiency.
C-Procgen's controllable contexts make it applicable in diverse reinforcement
learning research areas, such as learning dynamics analysis, curriculum
learning, and transfer learning. We believe that C-Procgen will fill a gap in
the current literature and offer a valuable toolkit for future works
Optimal dividend and capital injection under spectrally positive Markov additive models
This paper studies De Finetti's optimal dividend problem with capital
injection under spectrally positive Markov additive models. Based on dynamic
programming principle, we first study an auxiliary singular control problem
with a final payoff at an exponential random time. The double barrier strategy
is shown to be optimal and the optimal barriers are characterized in analytical
form using fluctuation identities of spectrally positive Levy processes. We
then transform the original problem under spectrally positive Markov additive
models into an equivalent series of local optimization problems with the final
payoff at the regime-switching time. The optimality of the regime-modulated
double barrier strategy can be confirmed for the original problem using results
from the auxiliary problem and the fixed point argument for recursive
iterations.Comment: Keywords: Spectrally positive Levy process, regime switching, De
Finetti's optimal dividend, capital injection, double barrier strategy,
singular contro
On De Finetti's control under Poisson observations: optimality of a double barrier strategy in a Markov additive model
In this paper we consider the De Finetti's optimal dividend and capital
injection problem under a Markov additive model. We assume that the surplus
process before dividends and capital injections follows a spectrally positive
Markov additive process. Dividend payments are made only at the jump times of
an independent Poisson process. Capitals are required to be injected whenever
needed to ensure a non-negative surplus process to avoid bankruptcy. Our
purpose is to characterize the optimal periodic dividend and capital injection
strategy that maximizes the expected total discounted dividends subtracted by
the total discounted costs of capital injection. To this end, we first consider
an auxiliary optimal periodic dividend and capital injection problem with final
payoff under a single spectrally positive L\'evy process and conjecture that
the optimal strategy is a double barrier strategy. Using the fluctuation theory
and excursion-theoretical approach of the spectrally positive L\'evy process
and the Hamilton-Jacobi-Bellman inequality approach of the control theory, we
are able to verify the conjecture that some double barrier periodic dividend
and capital injection strategy solves the auxiliary problem. With the results
for the auxiliary control problem and a fixed point argument for recursive
iterations induced by the dynamic programming principle, the optimality of a
regime-modulated double barrier periodic dividend and capital injection
strategy is proved for our target control problem.Comment: arXiv admin note: text overlap with arXiv:2207.0266
Optimal portfolio under ratio-type periodic evaluation in incomplete markets with stochastic factors
This paper studies a type of periodic utility maximization for portfolio
management in an incomplete market model, where the underlying price diffusion
process depends on some external stochastic factors. The portfolio performance
is periodically evaluated on the relative ratio of two adjacent wealth levels
over an infinite horizon. For both power and logarithmic utilities, we
formulate the auxiliary one-period optimization problems with modified utility
functions, for which we develop the martingale duality approach to establish
the existence of the optimal portfolio processes and the dual minimizers can be
identified as the "least favorable" completion of the market. With the help of
the duality results in the auxiliary problems and some fixed point arguments,
we further derive and verify the optimal portfolio processes in a periodic
manner for the original periodic evaluation problems over an infinite horizon.Comment: 28 pages, 33 conferenc
Efficient -Clique Listing: An Edge-Oriented Branching Strategy
-clique listing is a vital graph mining operator with diverse applications
in various networks. The state-of-the-art algorithms all adopt a
branch-and-bound (BB) framework with a vertex-oriented branching strategy
(called VBBkC), which forms a sub-branch by expanding a partial -clique with
a vertex. These algorithms have the time complexity of , where is the number of edges in the graph and
is the degeneracy of the graph. In this paper, we propose a BB framework with a
new edge-oriented branching (called EBBkC), which forms a sub-branch by
expanding a partial -clique with two vertices that connect each other (which
correspond to an edge). We explore various edge orderings for EBBkC such that
it achieves a time complexity of , where
is an integer related to the maximum truss number of the graph and we
have . The time complexity of EBBkC is better than that of VBBkC
algorithms for since both and are
bounded by . Furthermore, we develop specialized
algorithms for sub-branches on dense graphs so that we can early-terminate them
and apply the specialized algorithms. We conduct extensive experiments on 19
real graphs, and the results show that our newly developed EBBkC-based
algorithms with the early termination technique consistently and largely
outperform the state-of-the-art (VBBkC-based) algorithms.Comment: This paper has been accepted by SIGMOD 202
Can the Black Lives Matter Movement Reduce Racial Disparities? Evidence from Medical Crowdfunding
Using high-frequency donation records from a major medical crowdfunding site
and careful difference-in-difference analysis, we demonstrate that the 2020 BLM
surge decreased the fundraising gap between Black and non-Black beneficiaries
by around 50\%. The reduction is largely attributed to non-Black donors. Those
beneficiaries in counties with moderate BLM activities were most impacted. We
construct innovative instrumental variable approaches that utilize weekends and
rainfall to identify the global and local effects of BLM protests. Results
suggest a broad social movement has a greater influence on charitable-giving
behavior than a local event. Social media significantly magnifies the impact of
protests
The Adaptive Market Hypothesis:An empirical study on the UK stock market
This paper uses the FTSE 350 daily data and subsample method to detect the Adaptive Market Hypothesis (AMH) in the UK stock market. We performed a range of linear and nonlinear tests on sixteen two-yearly subsamples to capture the time-varying characteristic of market efficiency from 1987 to 2018. Both linear and nonlinear test results provide evidence that the market efficiency is not an all-or-nothing condition, and stock returns experience predictable and unpredictable periods. In addition, we find there is a downward trend for the January effect in the UK stock market during the sample period. Meanwhile, the analysis result suggests that AMH based on its more realistic assumptions provides a better explanation of the January effect than the Efficient Market Hypothesis
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