arXiv research

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

ZICO learns DAGs from zero-inflated count data efficiently.

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

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

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

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

Contrastive learning benefits from generated data but can be harmed by it too.

Study uses social network data to analyze regional inflation trends.

New model improves European inflation and interest rate predictions.

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 …

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

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

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

New core inflation measure predicts future headline inflation.

Proposes a stable classifier using inflated argmax for multiclass classification.

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) …

Intraductal papillary mucinous neoplasm (IPMN) is a precursor to pancreatic ductal adenocarcinoma. While over half of patients are diagnosed with pancreatic cancer at a distant stage, patients who are diagnosed early enjoy a much higher 5-year survival rate of $34\%$ compared to $3\%$ in the former; hence, early diagno…

The evolution of the rate of price inflation and unemployment in Japan has been modeled within the Phillips curve framework. As an extension to the Phillips curve, we represent both variables as linear functions of the change rate of labor force. All models were first estimated in 2005 for the period between 1980 and 2…

Deep model tackles zero-inflated multi-species abundance estimation.

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.

Improved statistical inference for adaptive Thompson Sampling.

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

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…

The paper analyzes the non-Gaussian behavior of inflation and unemployment over 70 years using multifractal methods.

Proposes a new model to predict travel demand with zero-inflated and long-tail characteristics.

The paper models US inflation and hyperinflation using monetary and GDP data.

New inflation model captures correlations and skew in interest rates.

Markov Chain Monte Carlo (MCMC) sampling from a posterior distribution corresponding to a massive data set can be computationally prohibitive since producing one sample requires a number of operations that is linear in the data size. In this paper, we introduce a new communication-free parallel method, the Likelihood I…

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 …

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

A new method inflates and deflates data manifolds to estimate densities without losing universality.

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 …

We construct models for the pricing and risk management of inflation-linked derivatives. The models are rational in the sense that linear payoffs written on the consumer price index have prices that are rational functions of the state variables. The nominal pricing kernel is constructed in a multiplicative manner that …

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,…

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…

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 proposes a neural network approach for high inflation investment portfolios with leverage constraints.

In a previous analysis the problem of "zero-inflated" time data (caused by high frequency trading in the electronic order book) was handled by left-truncating the inter-arrival times. We demonstrated, using rigorous statistical methods, that the Weibull distribution describes the corresponding stochastic dynamics for a…

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 methods provide stable ranking without assumptions on data distributions.

The paper models and predicts co-occurrence counts using Gamma regression.

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.

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…

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