arXiv research

The paper addresses frequentist regret of Linear Thompson Sampling in stochastic linear bandits.

New study reveals a polynomial penalty for adapting to unknown margin parameters in batched nonparametric bandits.

A new method boosts exploration in bandit algorithms, reducing regret.

Improved statistical inference for adaptive Thompson Sampling.

Randomized exploration in linear bandits achieves optimal regret bounds.

The purpose of this paper is to provide further understanding into the structure of the sequential allocation ("stochastic multi-armed bandit", or MAB) problem by establishing probability one finite horizon bounds and convergence rates for the sample (or "pseudo") regret associated with two simple classes of allocation…

New algorithms for linear bandits avoid norm knowledge, reducing regret.

A new metric, Weighted Regret, unifies FDR and power evaluation in online multiple testing.

New method improves mHealth user engagement using Thompson sampling for count data.

Unified analysis of Gaussian Process Thompson Sampling without discretization.

News on inflation and monetary policy impacts US household inflation expectations.

New core inflation measure predicts future headline inflation.

Paper stabilizes bandit learning with regularization, improving inference under adaptive sampling.

A new test improves statistical inference in bandit algorithms without sacrificing adaptiveness.

This paper proposes the use of wavelet methods to estimate U.S. core inflation. It explains wavelet methods and suggests they are ideally suited to this task. Comparisons are made with traditional CPI-based and regression-based measures for their performance in following trend inflation and predicting future inflation.…

Bitcoin reacts negatively to inflation surprises, contrary to belief.

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

Consider the problem of sampling sequentially from a finite number of $N \geq 2$ populations, specified by random variables $X^i_k$, $i = 1,\ldots , N,$ and $k = 1, 2, \ldots$; where $X^i_k$ denotes the outcome from population $i$ the $k^{th}$ time it is sampled. It is assumed that for each fixed $i$, $\{ X^i_k \}_{k …

Consider the problem of a controller sampling sequentially from a finite number of $N \geq 2$ populations, specified by random variables $X^i_k$, $i = 1,\ldots , N,$ and $k = 1, 2, \ldots$; where $X^i_k$ denotes the outcome from population $i$ the $k^{th}$ time it is sampled. It is assumed that for each fixed $i$, $\{…

The paper discusses the role of monetary policy when potential output depends on the inflation rate. If the intention of the central bank is to maximize actual output growth, then it has to be credibly committed to a strict inflation targeting rule, and to take the MOGIR (the Maximizing Output Growth Inflation Rate) as…

ZICO learns DAGs from zero-inflated count data efficiently.

The evolution of inflation, p(t), and unemployment, UE(t), in Japan has been modeled. Both variables were represented as linear functions of the change rate of labor force, dLF/LF. These models provide an accurate description of disinflation in the 1990s and a deflationary period in the 2000s. In Japan, there exists a …

New ZIPLN model accounts for zero-inflation in multivariate count data.

Regularized mixtures improve inflation and interest rate forecasts, especially correcting overconfidence.

Generative models' evaluation scores can be misleading, leading to inflated grades.

Paper proposes copula-based models for analyzing multivariate zero-inflated continuous data.

We test for the long-run relationship between stock prices, inflation and its uncertainty for different U.S. sector stock indexes, over the period 2002M7 to 2015M10. For this purpose we use a cointegration analysis with one structural break to capture the crisis effect, and we assess the inflation uncertainty based on …

The paper evaluates various forecasting methods for inflation, finding ML models superior.

Interest rate market models, like the LIBOR market model, have the advantage that the basic model quantities are directly observable in financial markets. Inflation market models extend this approach to inflation markets, where zero-coupon and year-on-year inflation-indexed swaps are the basic observable products. For …

Starting with an ideal triangulation of the interior of a compact 3-manifold M with boundary, no component of which is a 2-sphere, we provide a construction, called an inflation of the ideal triangulation, to obtain a strongly related triangulations of M itself. Besides a step-by-step algorithm for such a construction,…

Paper uses LSTM to predict inflation, finds it performs well over long periods.

Paper introduces ZIPTF and C-ZIPTF for better tensor factorization of zero-inflated count data.

We model the rate of inflation and unemployment in Austria since the early 1960s within the Phillips/Fisher framework. The change in labour force is the driving force representing economic activity in the Phillips curve. For Austria, this macroeconomic variable was first tested as a predictor of inflation and unemploym…

The paper analyzes global inflation's systemic nature and its impact on equity markets.

We develop a model to price inflation and interest rates derivatives using continuous-time dynamics that have some links with macroeconomic monetary DSGE models equipped with a Taylor rule: in particular, the reaction function of the central bank, the bond market liquidity, inflation and growth expectations play an imp…

Study uses social network data to analyze regional inflation trends.

Optimal text-based indices track VIX and inflation.

This article is an extension of the work of one of us (Coopersmith, 2011) in deriving the relationship between certain interest rates and the inflation rate of a two component economic system. We use the well-known Fisher relation between the difference of the nominal interest rate and its inflation adjusted value to e…

New model improves European inflation and interest rate predictions.

We study the shape of inflated surfaces introduced in \cite{B1} and \cite{P1}. More precisely, we analyze profiles of surfaces obtained by inflating a convex polyhedron, or more generally an almost everywhere flat surface, with a symmetry plane. We show that such profiles are in a one-parameter family of curves which w…

Funds inflate their returns due to price pressure, leading to wealth reallocation and market crashes.

This study explains and mitigates inflated returns and turnover in SPO-based portfolio optimization.

Zero-inflated datasets, which have an excess of zero outputs, are commonly encountered in problems such as climate or rare event modelling. Conventional machine learning approaches tend to overestimate the non-zeros leading to poor performance. We propose a novel model family of zero-inflated Gaussian processes (ZiGP) …

Paper tackles online learning for DR management with incentives.

In the late 90's, after severe financial and economic crisis, accompanied by inflation and exchange rate instability, Eastern Europe emerged into two groups of countries with radically contrasting monetary regimes (Currency Boards and Inflation targeting). The task of our study is to compare econometrically the perform…

This thesis renovates classic models for pricing inflation derivatives.

New bandit algorithms improve sparse reward learning.

The problem of causal inference is to determine if a given probability distribution on observed variables is compatible with some causal structure. The difficult case is when the causal structure includes latent variables. We here introduce the $\textit{inflation technique}$ for tackling this problem. An inflation of a…