Testing an Algorithm with Asymmetric Markov-Switching GARCH Models in US Stock Trading

In the present paper, we extend the current literature in algorithmic trading with Markov-switching models with generalized autoregressive conditional heteroskedastic (MS-GARCH) models. We performed this by using asymmetric log-likelihood functions (LLF) and variance models. From 2 January 2004 to 19 March 2021, we simulated 36 institutional investor’s portfolios. These used homogenous (either symmetric or asymmetric) Gaussian, Student’s t-distribution, or generalized error distribution (GED) and (symmetric or asymmetric) GARCH variance models. By including the impact of stock trading fees and taxes, we found that an institutional investor could outperform the S&P 500 stock index (SP500) if they used the suggested trading algorithm with symmetric homogeneous GED LLF and an asymmetric E-GARCH variance model. The trading algorithm had a simple rule, that is, to invest in the SP500 if the forecast probability of being in a calm or normal regime at t + 1 is higher than 50%. With this configuration in the MS-GARCH model, the simulated portfolios achieved a 324.43% accumulated return, of which the algorithm generated 168.48%. Our results contribute to the discussion on using MS-GARCH models in algorithmic trading with a combination of either symmetric or asymmetric pdfs and variance models.

Instability in regime switching models

In this paper, we look at the instability of a self-exciting regime-switching autoregressive model, specifically regime-switching models that are locally stable in each of their regimes. It turns out that the local stability of each regime is insufficient to ensure the overall stability of the model. The instability’s mechanism is described, and a sufficient condition for the instability is provided.

Existence and Uniqueness of Nontrivial Periodic Solutions to a Discrete Switching Model

To control the spread of mosquito-borne diseases, one goal of the World Mosquito Program’s Wolbachia release method is to replace wild vector mosquitoes with Wolbachia-infected ones, whose capability of transmitting diseases has been greatly reduced owing to the Wolbachia infection. In this paper, we propose a discrete switching model which characterizes a release strategy including an impulsive and periodic release, where Wolbachia-infected males are released with the release ratio α1 during the first N generations, and the release ratio is α2 from the (N+1)-th generation to the T-th generation. Sufficient conditions on the release ratios α1 and α2 are obtained to guarantee the existence and uniqueness of nontrivial periodic solutions to the discrete switching model. We aim to provide new methods to count the exact numbers of periodic solutions to discrete switching models.

Application of Markov Regime Switching Autoregressive Model to Gold Prices in Pakistan

The goal of this study is to investigate the performance of the Markov regime switching autoregressive (MRS-AR) model to estimate and forecast the gold prices in Pakistan. Initial analysis of the data covering from January 1995 to January 2019 reveals the existence of nonstationarity, heteroscedasticity, and structural changes. The dynamics of the data are studied in two distinct regimes. The empirical analysis provides evidence that the regime shifts are mattered and MRS-AR model is found to be suitable even in the case of nonstationarity. Moreover, it is worthwhile to note that the Markov regime switching successfully captures the nonlinearities and heteroscedasticity underlying the selected data and provides efficient forecasts. Based on empirical evidence it is recommended that the applications of regime switching models should be promoted in other fields of life.

Modeling and forecasting of rainfall reoccurrence changes using Markov Switching in Iran

This paper represents the recurrence (reoccurrence) changes in the rainfall series using Markov Switching models (MSM). The switching employs a dynamic pattern that allows a linear model to be combined with nonlinearity models a discrete structure. The result is the Markov Switching models (MSM) reoccurrence predicting technique. Markov Switching models (MSM) were employed to analyze rainfall reoccurrence with spatiotemporal regime probabilities. In this study, Markov Switching models (MSM) were used based on the simple exogenous probability frame by identifying a first-order Markov process for the regime probabilities. The Markov transition matrix and regime probabilities were used to analyze the rainfall reoccurrence in 167 synoptic and climatology stations. The analysis results show a low distribution from 0.0 to 0.2 (0–20%) per day spatially from selecting stations, probability mean of daily rainfall recurrence is 0.84, and a different distribution based on the second regime was found to be more remarkable to the rainfall variability. The rainfall reoccurrence in daily rainfall was estimated with relatively low variability and strong reoccurrence daily with ranged from 0.851 to 0.995 (85.1–99.5%) per day based on the spatial distribution. The variability analysis of rainfall in the intermediate and long variability and irregular variability patterns would be helpful for the rainfall variability for environmental planning.

Using regime-switching models in Sharia-compliant stocks: performance assessment of investors with discriminated risk-appetite

Purpose The paper aims to assess the performance of investors that are discriminated based on their risk-appetite who intend to invest in listed Sharia-compliant (SC) stocks to maximize their portfolios’ wealth through two different models (i.e. regime-switching [RS] and non-RS). Design/methodology/approach Study period (i.e. November 18, 2015–May 31, 2019), well described in two distinct volatility-related bull-regime and bear-regime, is divided into in-sample and out-sample where Rs. 1.00 is invested on the out-sample start date. Each investor’s cumulated wealth forecasted through different models is checked daily throughout the out-sample period, and then, analyzed based on investors’ cumulated ending wealth, and Sharpe ratio (SR) is obtained through different models. Findings The ending wealth of risk-averse and risk-neutral investors obtained through RS-models increased 5.27 times while that of risk-taker investors increased 5.13 times. However, ending wealth obtained through non-RS models remained far low. The SR remained unchanged among investors. However, the SR of RS models (i.e. 1.0867) is higher than that of non-RS models (i.e. 0.8681). Overall, RS model-based investments outperformed in all categories of investors. Practical implications The study helps the investor during the process of portfolio diversification in their asset(s) selection and limited capital apportionment decisions. It also helps market regulators in formulating regulations and the policymakers in articulating/implementing policies that may protect the stakeholders form consequent disasters, particularly when market switches regimes. Originality/value The uniqueness stems from its focus on risk-appetite discriminated investors’ portfolio wealth maximization issue examined through technical analysis using two completely distinct models in the emerging market’s listed SC stocks.

Biomechanical evaluation of stress distributions at the implant-abutment complex and peri-implant bone around mandibular dental implants with different neck geometries and inclinations

This study aimed to investigate the effects of the different dental implant neck designs, diameters, and inclinations, on the stress distributions at the mandibular crestal bone and implant-abutment complex, using three-dimensional (3D) finite element stress analysis (FEA) method. Finite element models of three-unit fixed partial dentures supported with two same length implants (10 mm), placed on the second premolar and second molar regions, were designed. Eight different models were designed according to the implants’ neck designs (platform switching/traditional), diameters (4.1 mm/4.8 mm) and the tilting angles of the posterior implants (0°/15°). The anterior implants’ widths were 4.1 mm and the neck design of the anterior implants matched the posterior implants. Two types of 100-N loads in vertical and 30° oblique directions were applied separately onto each central fossae and functional cusps of the fixed partial dentures crowns. Algor Fempro Software was used for the simulation and evaluation of the stress levels at the implant-abutment complex and the crestal bone. Stress levels measured at the crestal bone were found to be lower for the platform switching models. However, the platform switching design generated higher stress magnitudes within the implant-abutment complex. Inclined placement of posterior implants increased the amount of stress at the crestal bone around both implants. Biomechanically, selection of the largest diameter possible when using tilted platform switched implants may be recommended at the posterior mandible.