A5017363326- Financial Risk and Volatility Modeling
- Stochastic processes and financial applications
- Market Dynamics and Volatility
- Complex Systems and Time Series Analysis
- Stock Market Forecasting Methods
- Point processes and geometric inequalities
- Monetary Policy and Economic Impact
- Insurance, Mortality, Demography, Risk Management
- Probability and Risk Models
- Advanced Thermodynamics and Statistical Mechanics
- Insurance and Financial Risk Management
- Capital Investment and Risk Analysis
- Diffusion and Search Dynamics
- Economic theories and models
- SARS-CoV-2 detection and testing
- Banking stability, regulation, efficiency
- Forecasting Techniques and Applications
- Advanced Banach Space Theory
- Approximation Theory and Sequence Spaces
- COVID-19 diagnosis using AI
- Economic Theory and Policy
- Neural Networks and Applications
- Mathematical and Theoretical Analysis
- SARS-CoV-2 and COVID-19 Research
- Risk and Portfolio Optimization
Jomo Kenyatta University of Agriculture and Technology
2016-2024
Technical University of Kenya
2020
We characterize a Hawkes point process with kernel proportional to the probability density function of Mittag-Leffler random variables. This decays as power law exponent $\beta +1 \in (1,2]$. Several analytical results can be proved, in particular for expected intensity and number events counting process. These are used validate algorithms that numerically invert Laplace transform well Monte Carlo simulations Finally, derive full distribution events. The this paper available at {\tt...
Precise recognition of a time series path is important to policy makers, statisticians, economists, traders, hedgers and speculators alike. The correct also key ingredient in pricing models. This study uses daily futures prices crude oil other distillate fuels. paper considers the statistical properties energy spot investigates trends that underlie price dynamics order gain further insights into possible nuances discovery market dynamics. family ARMA-GARCH models was explored. depict varying...
Non-linear partial differential equations have been increasingly used to model the price of options in realistic market setting when transaction costs arising hedging portfolios are taken into account. This paper focuses on finding numerical solution non-linear equation corresponding a Bermudan call option with variable for an asset under information-based framework. The finite difference method is implemented approximate and its Greeks. Numerical examples presented prices compared...
Kenya has registered over 300,000 cases of COVID-19 and is a high-burden tuberculosis country. Tuberculosis diagnosis was significantly disrupted by the pandemic. Access to timely diagnosis, which key effective management COVID-19, can be expanded made more efficient through integrated screening. Decentralized testing at community level further increases access, especially for underserved populations, requires robust systems data process management. This study delivered commercial motorbike...
This paper proposes an innovative semiparametric nonlinear fuzzy-EGARCH-ANN model to solve the problem of accurate modeling for forecasting stock market volatility. has been developed by a combination FIS, ANN, and EGARCH models. Because proposed is highly gradient-based parameter estimation methods might not give global optimal parameters models, study decided use evolutionary algorithms instead. In particular, differential evolution (DE) algorithm suggested model. After this,...
In this paper, the cosine Fréchet loss distribution is proposed as a modified version of using F-Loss generator. The statistical properties and actuarial measures are studied. maximum likelihood estimators studied simulations carried out to ascertain behavior estimators. It observed that consistent. plots density show decreasing right-skewed shapes. hazard rate function reversed-J, increasing-constant-decreasing, bathtub, upside-down bathtub From skewness kurtosis plots, always positive...
The Bermudan option pricing problem with variable transaction costs is considered for a risky asset whose price process derived under the information-based model. formulated as value function of an optimal stopping problem, which stochastic control given by non-linear second order partial differential equation. theory viscosity solutions applied to solve such that also solution corresponding Bellman Under some regularity assumptions, existence and uniqueness equation are application Perron...
The objective of this study is, to show the importance incorporating jumps in both returns and volatility dynamics for Bitcoin. For that purpose, we introduce Double Exponential Jump-Diffusion model with Stochastic Volatility (DEJDSVJ) contains asymmetric jumps. use Markov Chain Monte Carlo methods estimation has proved meaningful presence Bitcoin price volatility. Moreover, based on options market, a comparison between underlying model, Jump Diffusion (DEJD) (no Jumps) (SV) shows goodness...
Volatility prediction plays a vital role in financial data. The time series movements of stock prices are commonly characterized as highly nonlinear and volatile. This study is aimed at enhancing the accuracy return volatility forecasts for by investigating their price through integration diverse models. Thus, integrated four powerful methods: seasonal autoregressive (AR) moving average (MA), generalized AR conditional heteroskedasticity (ARCH) family models, convolutional neural network...
The impacts of extremely high temperatures on plants, human beings and animals’ health have been studied in several parts the world. However, extreme events are uncommon only attracted attention recently. In this study, temperature behavior was modelled through application value theory using maximum monthly over a 36 years period. Data from Mandera, Wajir Lodwar stations generalized (GEV) Pareto distributions (GPD) models. results revealed that GEV model better modelling because it had least...
This paper aims at examining volatility spillover effects among the returns of three out four securities exchanges in East Africa. Vector autoregressive model was used to return series evolution; and, Johansen co-integration test, further applied examine any possibilities co-integration. Dynamic conditional correlation then employed explore dynamics variances. Daily closing all share indices data spanning period 29 February 2008 28 2018 used. The results study revealed that, there is...
The co-evolution and co-movement of financial time series are utmost importance in contemporary finance, especially when considering the joint behaviour asset price realizations. ability to model interdependencies volatility spill-over effects introduces interesting dimensions finance. This paper explores co-integrating relationships between crude oil distillate fuel prices. Existence multivariate relations bidirectional Granger-Causality is established among series. It also that even after...
In this study, we evaluate energy forward dynamics modeled as time-change Hilbert-space of linear functional. The is represented an element function. Representing and futures contracts a time-changing stochastic process in functions shows clearly, that arbitrage-free price can be derived from the buy-and hold strategy market thereby enabling investors willing to salvage uncertainties well Arrow-Debreu situations execute spot or depending on time place becomes favorable. With clock measuring...
In this paper, a robust analysis of volatility forecasting the GBP-ETB exchange rate was provided using weekly data spanning period June 30, 2003-January 24, 2020. To our knowledge, first study that focuses on high-frequency and Fuzzy-EGARCH-ANN econometric model. The research finds best performing model in terms one-step ahead forecasts based realized computed from underlying daily series is Fuzzy-EGARCH-ANN(1, 2, 1) with students t-distribution.
The usefulness of heavy-tailed distributions for modeling insurance loss data is arguably an important subject actuaries.Appropriate use trigonometric functions allows a good understanding the mathematical properties, limits over parameterization, and gives better applicability in different datasets.Thus, proposed method ensures that no additional parameter(s) is/are introduced bit to make distribution from F-Loss family flexible.The purpose this paper improve flexibility without introducing...
Gerber-Shiu function is the joint distribution of time to ruin, surplus before ruin and deficit at ruin. In this paper, we propose a non-parametric estimator expected discounted penalty function; for compound Poisson risk model perturbed by diffusion also called Wiener-Poisson model. The based on Fourier cosine series expansion method. It shows that our has fast convergence rate. We derived some simulation examples show effectiveness under finite sample.
Discrepancies between theoretical option pricing models and actual market prices create arbitrage opportunities in financial markets. Despite being widely used pricing, the famous Black-Scholes model estimates values based on strict assumption of no arbitrage. In addition, its assumptions constant volatility log-normal asset price distribution may not fully capture real-world dynamics, resulting mispricing potential opportunities. The Information-based is adopted as an alternative to address...
In this paper, we consider the Schwartz’s one-factor model for a storable commodity and futures contract on that commodity. We introduce analysis of asymptotic arbitrage in models by proving prices process allows exponential with geometric decaying failure probability. Next, find comparison that, under some similar conditions, our result is corresponding assets (stronger) version Föllmer Schachermayer’s stated modeling setting Ornstein-Uhlenbeck financial security assets.
The Black- Scholes model is a well-known for hedging and pricing derivative securities. However, it exhibits some systematic biases or unrealistic assumptions like the log-normality of asset returns constant volatility. A number studies have attempted to reduce these in different ways. objective this study value European call option using non-parametric parametric model. Amongst approaches used improve accuracy Wavelet-based This found as promising alternative far options concerned, due its...
In this study, the evaluation of pricing framework for predicting West Texas Intermediate crude oil stock was implemented where detailed analysis with varying changepoint shows that an arbitrage-free forward price can be derived from buy-and hold strategy in energy market thereby enabling investors willing to salvage uncertainties as well Arrow-Debreu situations execute a spot or contracts depending on time and place becomes favorable.