Nearest Neighbor and Kernel Survival Analysis: Nonasymptotic Error Bounds and Strong Consistency Rates

We establish the first nonasymptotic error bounds for Kaplan-Meier-based nearest neighbor and kernel survival probability estimators where feature vectors reside in metric spaces. Our bounds imply rates of strong consistency for these nonparametric estimators and, up to a log factor, match an existing lower bound for conditional CDF estimation. Our proof strategy also yields nonasymptotic guarantees for nearest neighbor and kernel variants of the Nelson-Aalen cumulative hazards estimator. We experimentally compare these methods on four datasets. We find that for the kernel survival estimator, a good choice of kernel is one learned using random survival forests.Comment: International Conference on Machine Learning (ICML 2019

A Latent Source Model for Nonparametric Time Series Classification

For classifying time series, a nearest-neighbor approach is widely used in practice with performance often competitive with or better than more elaborate methods such as neural networks, decision trees, and support vector machines. We develop theoretical justification for the effectiveness of nearest-neighbor-like classification of time series. Our guiding hypothesis is that in many applications, such as forecasting which topics will become trends on Twitter, there aren't actually that many prototypical time series to begin with, relative to the number of time series we have access to, e.g., topics become trends on Twitter only in a few distinct manners whereas we can collect massive amounts of Twitter data. To operationalize this hypothesis, we propose a latent source model for time series, which naturally leads to a "weighted majority voting" classification rule that can be approximated by a nearest-neighbor classifier. We establish nonasymptotic performance guarantees of both weighted majority voting and nearest-neighbor classification under our model accounting for how much of the time series we observe and the model complexity. Experimental results on synthetic data show weighted majority voting achieving the same misclassification rate as nearest-neighbor classification while observing less of the time series. We then use weighted majority to forecast which news topics on Twitter become trends, where we are able to detect such "trending topics" in advance of Twitter 79% of the time, with a mean early advantage of 1 hour and 26 minutes, a true positive rate of 95%, and a false positive rate of 4%.Comment: Advances in Neural Information Processing Systems (NIPS 2013

The financing behavior of Dutch firms

This paper investigates the financing behaviour of Dutch firms by testing whether a firm’s financing decisions are determined by certain factors identified in various theories. Since a firm’s financing decision is reflected in the changes of its leverage, our research focuses on the relationship between a firm’s debt ratio change and the changes in certain factors. The approach used in the paper is the structural equation modeling (SEM) technique. The model identifies various important factors that are related to Dutch firms’ financing decisions. The empirical results provide moderate support for the static trade-off theory, the pecking-order hypothesis, as well as the dynamic capital structure model. However, our data set is insuffi- cient to confirm the static trade-off theory, and our results provide little evidence to back the asymmetric information argument behind the pecking-order hypothesis.

The determinants of Dutch capital structure choice

This paper uses the structural equation modeling (SEM) technique to empirically test the determinants of capital structure choice for Dutch firms. We include major factors identified by capital structure theories and construct proxies for these factors with consideration of specific institutional settings in the Netherlands. We also carefully rescale the observed variables in order to conform with the linear structure of the model and the multivariate normality assumption. Our empirical results shed many important insights on Dutch firms’ financing behavior. In particular, we identified important factors that have so far been ignored in the literature for the Dutch capital structure choice. Furthermore our results provide evidence supporting the “static trade-off" hypothesis. While the “pecking-order" behavior is observed for Dutch firms, our results cast doubt on the rationale of asymmetric information behind the “pecking-order" hypothesis. We also point out that the static cross-section evidence is not sufficient to conclude whether or not the management of Dutch firms is entrenched. Models based on the dynamic behavior of firms’ capital structure choice are called for such tests.

Average Crop Revenue Election (ACRE) Program or Traditional Government Payment Programs: What Factors Matter?

Rankings of different risk management portfolios including Average Crop Revenue Election (ACRE), traditional government payment programs, crop insurance and hedging in futures; and optimal choices of insurance coverage levels and hedge ratios are evaluated for a representative central Indiana corn farm, using Monte Carlo simulation and optimization of expected utilities. The changes of preference between ACRE and traditional government programs under comprehensive scenarios of price and yield risks are studied. Also, Interactions between ACRE and other risk management instruments are examined, and government costs and risk management efficiencies between ACRE and traditional government programs are compared. The results show a strong preference of ACRE for the representative central Indiana corn farm in 2009, due to high ACRE guarantee price and expected drop in corn price from 2008 level. Even if the farm faces weak dependence between farm and aggregate yield, the risk could not offset the addition value ACRE could provide for this year. Also, it is found that there are synergistic effects between ACRE and two individual crop insurance plans but antagonistic effects between ACRE and group insurance plans. ACRE is more efficient than traditional government programs in terms of expected program costs.ACRE, Farm Bill, crop insurance, willingness to pay, government expenditure, government programs, Agricultural and Food Policy, Agricultural Finance, Risk and Uncertainty,

The intermediate and spin-liquid phase of the half-filled honeycomb Hubbard model

We obtain the phase-diagram of the half-filled honeycomb Hubbard model with density matrix embedding theory, to address recent controversy at intermediate couplings. We use clusters from 2-12 sites and lattices at the thermodynamic limit. We identify a paramagnetic insulating state, with possible hexagonal cluster order, competitive with the antiferromagnetic phase at intermediate coupling. However, its stability is strongly cluster and lattice size dependent, explaining controver- sies in earlier work. Our results support the paramagnetic insulator as being a metastable, rather than a true, intermediate phase, in the thermodynamic limit