arXiv research

CAMEL enhances manifold embedding and learning with curvature metrics.

CAMEL embeds data into a manifold using curvature-augmented forces.

We propose a calibrated multivariate regression method named CMR for fitting high dimensional multivariate regression models. Compared with existing methods, CMR calibrates regularization for each regression task with respect to its noise level so that it simultaneously attains improved finite-sample performance and tu…

This study analyzes the alignment between charter value and supervision in banks.

Model patching closes subgroup performance gaps in skin cancer classification.

Accurate streamflow prediction largely relies on historical meteorological records and streamflow measurements. For many regions, however, such data are only scarcely available. Facing this problem, many studies simply trained their machine learning models on the region's available data, leaving possible repercussions …

We develop a strong diagnostic for bubbles and crashes in bitcoin, by analyzing the coincidence (and its absence) of fundamental and technical indicators. Using a generalized Metcalfe's law based on network properties, a fundamental value is quantified and shown to be heavily exceeded, on at least four occasions, by bu…

Regional rainfall-runoff modeling is an old but still mostly out-standing problem in Hydrological Sciences. The problem currently is that traditional hydrological models degrade significantly in performance when calibrated for multiple basins together instead of for a single basin alone. In this paper, we propose a nov…

Deep learning framework predicts streamflow and flood probabilities in Australian catchments.

The paper models SOFR and EFFR dynamics, reconciling diffusive and piecewise paths.

There are more than eight hundred interest rates published in China bond market every day. Which are the benchmark interest rates that have broad influences on most interest rates is a major concern for economists. In this paper, multi-variable Granger causality test is developed and applied to construct a directed net…

The study proposes algorithms to minimize rating discordance in missing data.

Overrides of credit ratings are important correctives of ratings that are determined by statistical rating models. Financial institutions and banking regulators agree on this because on the one hand errors with ratings of corporates or banks can have fatal consequences for the lending institutions and on the other hand…

Model credit ratings using economic states with Markov chains.

The paper analyzes how learning rate affects SGD and provides insights into optimal rates.

This paper models short rates with jumps using PDEs.

We first show that there are in fact triangular arbitrage opportunities in the spot foreign exchange markets, analyzing the time dependence of the yen-dollar rate, the dollar-euro rate and the yen-euro rate. Next, we propose a model of foreign exchange rates with an interaction. The model includes effects of triangular…

In this survey paper we discuss recent advances on short interest rate models which can be formulated in terms of a stochastic differential equation for the instantaneous interest rate (also called short rate) or a system of such equations in case the short rate is assumed to depend also on other stochastic factors. Ou…

A novel approach models rating transitions using Lie groups and Deep Learning.

Most of the existing recommender systems use the ratings provided by users on individual items. An additional source of preference information is to use the ratings that users provide on sets of items. The advantages of using preferences on sets are two-fold. First, a rating provided on a set conveys some preference in…

Following widely used in visual recognition concept of relative attributes, the article establishes definition of the relative PCA attributes for a class of objects defined by vectors of their parameters. A new rating model (RELARM) is built using relative PCA attribute ranking functions for rating object description a…

Paper examines pricing and hedging for cross-currency swaps referencing backward-looking rates.

Method calibrates local volatility and stochastic short rate models for equity-rate dynamics.

This paper analyzes the robust growth rate of leveraged ETFs under uncertain parameters.

Examines SOFR derivatives pricing and hedging post-LIBOR discontinuation.

Approximates bond option volatilities using affine short-rate models.

In this paper, we give a new sharp generalization bound of lp-MKL which is a generalized framework of multiple kernel learning (MKL) and imposes lp-mixed-norm regularization instead of l1-mixed-norm regularization. We utilize localization techniques to obtain the sharp learning rate. The bound is characterized by the d…

The currency carry trade is the investment strategy that involves selling low interest rate currencies in order to purchase higher interest rate currencies, thus profiting from the interest rate differentials. This is a well known financial puzzle to explain, since assuming foreign exchange risk is uninhibited and the …

We construct a no-arbitrage model of bond prices where the long bond is used as a numeraire. We develop bond prices and their dynamics without developing any model for the spot rate or forward rates. The model is arbitrage free and all nominal interest rates remain positive in the model. We give examples where our mode…

This paper shows how forward rate interpolations are equivalent to discount factor interpolations in yield curve construction.

The paper introduces a new short rate model with memory components.

Rate-In dynamically adjusts dropout rates during inference to improve uncertainty estimation in neural networks.

We introduce an autoregressive-type model with self-modulation effects for a foreign exchange rate by separating the foreign exchange rate into a moving average rate and an uncorrelated noise. From this model we indicate that traders are mainly using strategies with weighted feedbacks of the past rates in the exchange …

Clarifies interest rate cap rules for loans with unconventional cash flows.

Cyclical learning rate improves neural machine translation performance.

Proves lower discount rates are needed for future losses.

Developed unbiased estimators for Heston model with stochastic interest rates.

We introduce here for the first time the long-term swap rate, characterised as the fair rate of an overnight indexed swap with infinitely many exchanges. Furthermore we analyse the relationship between the long-term swap rate, the long-term yield, see Biagini et al. [2018], Biagini and Härtel [2014], and El Karoui et a…

Rate GENERIC extends thermodynamics principles to non-equilibrium systems.

Two-dimensional transition rates improve life insurance reserve calculations.

Stochastic gradient descent with a large initial learning rate is widely used for training modern neural net architectures. Although a small initial learning rate allows for faster training and better test performance initially, the large learning rate achieves better generalization soon after the learning rate is anne…

This work models overnight rates with jumps and discontinuities, extending classical short-rate models.

GALA adapts learning rates online by aligning gradients, improving deep learning model performance.

The paper tackles fast rates in structured prediction problems.

Paper studies Gaussian approximation in linear regression with rates derived.

Defines a new short rate model and convexity adjustment formulae.

Study finds relevance of exchange and inflation rates to economic factors.

New proof shows not all Salem numbers are growth rates of Coxeter groups.