The study investigates the stock price movement of quoted Nigerian oil and gas firms using the Markovian model. Specifically, the study estimates the change in likelihoods and steady-state distribution of the share prices of the firms to determine the average time spent by the share price to...

In this paper, we present a stochastic optimal control model to optimize an insurance firm problem in the case where its cash-balance process is assumed to be described by a stochastic differential equation driven by Teugels martingales. Noticing that the insurance firm is able to control its...

The COVID-19 pandemic has led to enormous data movements that strongly affect parameters and forecasts from standard VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine transitory and persistent changes in volatility. The resulting...

We aim to assess the impact of a pandemic data point on the calibration of a stochastic multi-population mortality projection model and its resulting projections for future mortality rates. Throughout the paper, we put focus on the Li and Lee mortality model, which has become a standard for...

This article presents a new approach for building robust portfolios based on stochastic efficiency analysis and periods of market downturn. The empirical analysis is done on assets traded on the Brazil Stock Exchange, B3 (Brasil, Bolsa, Balcão). We start with information on the assets from...

This paper proposes a Skewed Stochastic Volatility (SSV) model to model time varying, asymmetric forecast distributions to estimate Growth at Risk as introduced in Adrian, Boyarchenko, and Giannone's (2019) seminal paper "Vulnerable Growth". In contrary to their semi-parametric approach, the SSV...

Optimal trading strategies for pairs trading have been studied by models that try to find either optimal shares of stocks by assuming no transaction costs or optimal timing of trading fixed numbers of shares of stocks with transaction costs. To find optimal strategies that determine optimally...

We study an optimal liquidation problem with multiplicative price impact in which the trend of the asset's price is an unobservable Bernoulli random variable. The investor aims at selling over an infinite time-horizon a fixed amount of assets in order to maximize a net expected profit...

We present the Generalized Gamma (GG) distribution as a possible risk neutral distribution (RND) for modeling European options prices under Heston's stochastic volatility (SV) model. We demonstrate that under a particular reparametrization, this distribution, which is a member of the...

The behavior of the optimal exercise price of American puts near expiry has been well studied under the Black-Scholes model as a result of a series of publications. However, the behavior of the optimal exercise price under a stochastic volatility model, such as the Heston model, has not been...

The stochastic inequality test is an exact non-parametric test that can be used to infer whether values in one random sample tend to be higher than in another. In addition it can be used to derive a confidence interval around an intuitive measure of effect size that is readily interpretable...

We examine the performance of initial public offerings (IPO) using a stochastic dominance approach that allows us to capture IPO investors’ preferences for higher moments of the returns distribution. We use a comprehensive sample of 6,671 IPOs in the U.S. with IPO dates from 1980 to 2012, and...

The COVID-19 pandemic has led to enormous data movements that strongly affect parameters and forecasts from standard VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine transitory and persistent changes in volatility. The resulting...

The classical Black-Scholes model describes the market behavior assuming that the volatility process is a constant, and the Heston model extends it to the case where the volatility is a stochastic process. Then, the rough Bergomi (rBergomi) model was proposed to improve the description of the...

I study the business cycle properties of wage posting models with random search, for which the distributions of employment and wages play a nontrivial role for the equilibrium path. In fact, the main result of this paper is that the distribution of firms is one of the most important elements to...

Stochastic volatility models are very flexible models able to characterize financial volatility evolution. This article explores computational capabilities based on Graphical Processing Units to simulate many Monte Carlo Markov chains in estimating stochastic volatility model parameters through...

Stochastic volatility models are very flexible models able to characterize financial volatility evolution. This article explores computational capabilities based on Graphical Processing Units to simulate many Monte Carlo Markov chains in estimating stochastic volatility model parameters through...

This paper examines the different types of incentives that countries face when deciding to take part in a federal fiscal system. The optimal degree of participation depends on the structural parameters of the economy and on the properties of the federal fiscal system. Firstly, the paper examines...

A dynamic pre-positioning problem is proposed to efficiently respond to victims’ needs for relief supplies under uncertain and dynamic demand in humanitarian relief. The problem is formulated as a multi-stage stochastic programming model that considers pre-positioning with multi-stage...

We introduce in this article the EWMA Heston model, a markovian stochastic volatility model able to capture a wide range of empirical features related to volatility dynamics while being more tractable for simulations than rough volatility models based on fractional processes. After having...

This paper investigates whether it is possible to entertain simultaneously two attractive views about US GDP. The first is that long term growth in US GDP is attributable to an empirically plausible specification of random technical progress. The second is that deviations of GDP from a fitted...

The cross-section of options holds great promise for identifying return distributions and risk premia, but estimating dynamic option valuation models with latent state variables is challenging when using large option panels. We propose a particle MCMC framework with a novel filtering approach...

In this paper, we show that a time-dependent local stochastic volatility (SLV) model can be reduced to a system of autonomous PDEs that can be solved using the heat kernel, by means of the Wei-Norman factorization method and Lie algebraic techniques. Then, we compare the results of traditional...

This papers documents notes on probability distribution and average of asset returns. In summary, I argue that 1) wave function describes probabilities of asset returns, 2) following Cauchy distribution of returns makes diversification conditionally useless in terms of risk management, 3) median...

Properties of a binary choice probability function p defined on multiattributed outcomes are studied to represent p as a transformation of additive difference evaluations of receiving and foregone outcomes into the unit interval. We use an algebraic assumption to obtain an additive difference...