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Determinants of Financial Distress in Large Financial Institutions: Evidence from U.S. Bank Holding Companies

, 2016
type="main" xml:id="coep12105-abs-0001"> We investigate determinants of financial distress in large financial institutions based on the Distance-to-Default and Z-Scores measures. Using data of U.S.
Zhichao Zhang, Li Xie, Xiangyun Lu, Zhuang Zhang   +3 more
semanticscholar   +1 more source

Does the Yield Spread Predict Recessions in the Euro Area?

, 2005
Fabio Moneta
semanticscholar   +1 more source

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Predicting Future Earnings Changes Using Machine Learning and Detailed Financial Data

Journal of Accounting Research, 2022
We use machine learning methods and high-dimensional detailed financial data to predict the direction of one-year-ahead earnings changes. Our models show significant out-of-sample predictive power: the area under the Receiver Operating Characteristics ...
XI CHEN, Yang HA (TONY) CHO, Yiwei Dou, B. Lev   +3 more
semanticscholar   +1 more source

The COVID-19 Shock and Challenges for Time Series Models

Social Science Research Network, 2021
We document the impact of COVID-19 on frequently employed time series models, with a focus on euro area inflation. We show that for both single equation models (Phillips curves) and Vector Autoregressions (VARs) estimated parameters change notably with ...
Elena Bobeica, Benny Hartwig
semanticscholar   +1 more source

What Can Bayesian Inference Do for Accounting Research?

Journal of Financial Reporting, 2023
Bayesian statistics is a framework for combining new data with existing forms of information to yield more precise inferences than are possible using the data alone. Its greatest practical advantages are the flexibility it offers in incorporating prior
H. Schütt
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Liquidity Premium and Liquidity-Adjusted Return and Volatility: illustrated with a Liquidity-Adjusted Mean Variance Framework and its Application on a Portfolio of Crypto Assets

Social Science Research Network, 2023
We establish innovative measures of liquidity premium Beta on both asset and portfolio levels, and corresponding liquidity-adjusted return and volatility, for selected crypto assets. We develop liquidity-adjusted ARMA-GARCH/EGARCH representation to model
Qiandan Deng
semanticscholar   +1 more source

Forecasting Inflation in Argentina: A Probabilistic Approach

Ensayos Económicos, 2023
Probability forecasts are gaining popularity in the macroeconomic discipline as point forecasts lack the ability to capture the level of uncertainty in fundamental variables like inflation, growth, exchange rate, or unemployment.
Tomás Marinozzi
semanticscholar   +1 more source

ПРОГНОЗУВАННЯ ПОКАЗНИКІВ ІННОВАЦІЙНОСТІ ІНДУСТРІЇ ТУРИЗМУ У ПЕРІОДІ ПОСТКОНФЛІКТНОГО ВІДНОВЛЕННЯ

Проблеми і перспективи розвитку підприємництва, 2023
УДК 338.48:332.145; JEL Classification: C53, D74, L83, O18, R58 Цвілий С.М. ПРОГНОЗУВАННЯ ПОКАЗНИКІВ ІННОВАЦІЙНОСТІ ІНДУСТРІЇ ТУРИЗМУ У ПЕРІОДІ ПОСТКОНФЛІКТНОГО ВІДНОВЛЕННЯ Мета.
Сергій Цвілий
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Greek GDP Forecasting Using Bayesian Multivariate Models

Social Science Research Network
Building on a proper selection of macroeconomic variables for constructing a Gross Domestic Product (GDP) forecasting multivariate model (Kazanas, 2017), this paper evaluates whether alternative Bayesian model specifications can provide greater ...
Zacharias G. Bragoudakis, Ioannis Krompas   +1 more
semanticscholar   +1 more source

How to Dominate the Historical Average

The Review of financial studies
We present a novel methodology for the out-of-sample forecast of the equity premium. Our predictive slope coefficient is a conservative constant that has a lower bias than the zero slope employed by the historical average, but has the same variance. We
Kaiqiang Li, Yingying Li, Changlei Lyu, Jialin Yu   +3 more
semanticscholar   +1 more source