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Cost of Illiquidity: Marketability and Liquidity Discounts in a Margrabe Exchange Option Framework
Journal of Forensic Accounting Research, 2023Market declines of 2008–2009 and 2022–2023 brought renewed attention to the issue of illiquidity and the attendant costs faced by the stockholders. Margrabe exchange option-based models have been employed widely for estimating the cost of illiquidity ...
Ashok Bhardwaj Abbott
semanticscholar +1 more source
What is Missing in Asset-Pricing Factor Models?
Social Science Research Network, 2022Our objective is to develop a methodology to price the cross section of asset returns. Despite the hundreds of systematic risk factors considered in the literature (“factor zoo”), there is still a sizable pricing error.
Massimo Dello Preite +3 more
semanticscholar +1 more source
Option Pricing with Time-Varying Volatility Risk Aversion
The Review of financial studies, 2022We introduce a pricing kernel with time-varying volatility risk aversion to explain the observed time variations in the shape of the pricing kernel. When combined with the Heston-Nandi GARCH model, this framework yields a tractable option pricing model
P. Hansen, Chen Tong
semanticscholar +1 more source
Foreign Trade Review, 2022
The imposition of restrictive trade policies and consequent fabrication of foreign trade statistics acts as hindrance for effective policy formulations in the developing countries.
Samir Das, A. Biswas
semanticscholar +1 more source
The imposition of restrictive trade policies and consequent fabrication of foreign trade statistics acts as hindrance for effective policy formulations in the developing countries.
Samir Das, A. Biswas
semanticscholar +1 more source
South Asian Journal of Macroeconomics and Public Finance, 2021
Determinism and non-linear behaviour in log-return and conditional volatility time series of the stock market index is examined for twenty-six countries.
Zouhaier Dhifaoui
semanticscholar +1 more source
Determinism and non-linear behaviour in log-return and conditional volatility time series of the stock market index is examined for twenty-six countries.
Zouhaier Dhifaoui
semanticscholar +1 more source
Alpha Go Everywhere: Machine Learning and International Stock Returns
Social Science Research Network, 2020We apply machine learning techniques to predict international stock returns using firm characteristics. Market-specific training is important, as neural network models (NNs) achieve stronger results when they are trained in each market separately than ...
Darwin Choi, Wenxi Jiang, Chao Zhang
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Uncertainty and the Economy: The Evolving Distributions of Aggregate Supply and Demand Shocks
Social Science Research Network, 2021We estimate the time-varying distribution of aggregate supply (AS) and aggregate demand (AD) shocks. We distinguish between traditional Gaussian uncertainty and “bad” uncertainty, associated with negative skewness.
G. Bekaert +2 more
semanticscholar +1 more source
Greek GDP Forecasting Using Bayesian Multivariate Models
Social Science Research NetworkBuilding 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 +1 more
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Does Deep Learning with Multilayer Perceptron Perform Well in Predicting Credit Risk?
Journal of Applied Finance & BankingThis paper investigates the effectiveness of using Deep Learning with Multilayer Perceptron (MLP) to assess credit risk in banks. To this end, its performance is compared with that of Support Vector Machine (SVM), Gradient Boosting, Decision Tree (Random
Ulysses Araújo Bispo, M. Tessmann
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American Economic Review: Insights, 2018
A statistician takes an action on behalf of an agent, based on the agent’s self-reported personal data and a sample involving other people. The action that he takes is an estimated function of the agent’s report.
K. Eliaz, R. Spiegler
semanticscholar +1 more source
A statistician takes an action on behalf of an agent, based on the agent’s self-reported personal data and a sample involving other people. The action that he takes is an estimated function of the agent’s report.
K. Eliaz, R. Spiegler
semanticscholar +1 more source