scholarly journals The Adaptive Market Hypothesis and the Day‑of‑the‑Week Effect in African Stock Markets: the Markov Switching Model

2019 ◽  
Vol 22 (3) ◽  
pp. 145-162 ◽  
Author(s):  
Adefemi A. Obalade ◽  
Paul Francois Muzindutsi
Keyword(s):  
Stock Markets ◽  
Stock Exchange ◽  
Markov Switching ◽  
Markov Switching Model ◽  
Market Conditions ◽  
Analytical Technique ◽  
Switching Model ◽  
Bear Market ◽  
Johannesburg Stock Exchange ◽  
Day Of The Week

In line with the Adaptive Market Hypothesis (AMH), the objective of this study is to investigate how the day‑of‑the‑week (DOW) effect behaves under different bull and bear market conditions in African stock markets, and to examine the likelihood of being in a bull or bear regime for each market. A Markov Switching Model (MSM) was employed as the analytical technique. The results show that the DOW effect appears in one regime and disappears in another, in all markets, as rooted in the AMH. Lastly, all markets, except the Johannesburg Stock Exchange have a higher tendency to be in a bearish state than a bullish one. Our findings show that active investment management may yield profits for investors investing in most African markets during bearish conditions.

scholarly journals Modeling South African Banks closing stock prices: a Markov-Switching Approach

2016 ◽  
Vol 8 (1(J)) ◽  
pp. 36-40
Author(s):  
Diteboho Xaba ◽  
Ntebogang Dinah Moroke ◽  
Johnson Arkaah ◽  
Charlemagne Pooe
Keyword(s):  
Stock Prices ◽  
Autoregressive Model ◽  
Stock Price ◽  
Stock Exchange ◽  
Markov Switching ◽  
Markov Switching Model ◽  
Switching Model ◽  
Johannesburg Stock Exchange ◽  
Augmented Dickey Fuller ◽  
National Bank

In this paper, we provide evidence that the five variables used in the study were nonlinear in nature, while finding a better Markov-switching model. The study used dailydata obtained from the Johannesburg Stock Exchange over the period from January 2010 to December 2012. An extension of Markov Switching with autoregressive model was used for empirical analysis. Prior to using this model, the series were tested for nonlinear unit root with modified Kapetanois-Shin-Snell nonlinear Augmented Dickey-Fuller (KSS-NADF) test which successfully provided positive results.Other preliminary tests selected the first lag as optimal and confirmed that stock prices may switch between two regimes. Further empirical findings proved that stock prices can be successfully modelled with Markov Switching Autoregressive model of order one. First National bank was found to have 99.64% longer stock price stability if adjustments regards tofinancialpolicies are made. Capitec Bank was the least favoured among the banks.

scholarly journals ALGORITMA GENERALIZED REDUCED GRADIENT BERBASIS MARKOV-SWITCHING MODEL UNTUK OPTIMISASI PORTOFOLIO SAHAM PERBANKAN DI INDONESIA

2019 ◽  
Vol 13 (10) ◽  
pp. 2095
Author(s):  
Denny Nurdiansyah ◽  
Alif Yuanita Kartini
Keyword(s):  
Markov Switching ◽  
Markov Switching Model ◽  
Switching Model ◽  
Bear Market ◽  
Bull Market ◽  
Reduced Gradient ◽  
Generalized Reduced Gradient

Optimisasi  portofolio pada dasarnya menggunakan model Markowitz dalam menghasilkan portofolio yang efisien, namun portofolio yang terbentuk tidak baik ketika return saham memiliki perubahan regime, seperti pada periode ‘bear’ and ‘bull’ market. Tujuan dari penelitian ini adalah mengembangkan optimisasi portofolio dengan mempertimbangkan kasus perubahan regime, serta menerapkannya pada data runtun waktu yang memiliki perubahan regime dalam rangka pembentukan portofolio yang lebih efisien. Metode yang digunakan adalah algoritma generalized reduced gradient (GRG) berbasis Markov-switching model (MSwM). Pada penulisan ini akan dihasilkan algoritma pemrograman dalam software R untuk membuat paket program GRG berbasis MSwM yang akan digunakan untuk optimisasi portofolio pada kasus perubahan regime. Kinerja portofolio yang terbentuk dievaluasi dengan pengukuran risiko yaitu standar deviasi. Jenis data yang digunakan adalah data sekunder yang berisi saham-saham perbankan dari enam saham terpilih yang aktif di IDX Bursa Efek Indonesia pada tahun 2013-2018, yaitu: saham BRI, BNI, BTN, Bank Mandiri, BCA, dan Bank Danamon. Hasil diperoleh algoritma pemrograman untuk program GRG berbasis MSwM untuk optimisasi portofolio pada kasus perubahan regime, serta diperoleh portofolio saham perbankan yang optimal untuk tiga kriteria investor. Pada penelitian ini, portofolio terbaik jatuh pada kriteria investor yaitu meminimalkan risiko pada ekspektasi return tertentu. Penelitian ini memberikan kesimpulan bahwa algoritma GRG berbasis MSwM menghasilkan bobot portofolio berdasarkan fenomena “bull” and “bear” market, sehingga bobot portofolio yang terbentuk lebih realistis didalam pasar modal.

scholarly journals Can Adaptive Market Hypothesis Explain the Existence of Seasonal Anomalies? Evidence from Dhaka Stock Exchange, Bangladesh

2021 ◽  
Vol 15 (2) ◽  
pp. 198-223
Author(s):  
Tahmina Akhter ◽  
Othman Yong
Keyword(s):  
Stock Exchange ◽  
Circuit Breaker ◽  
Time Varying ◽  
Markov Switching Model ◽  
Market Conditions ◽  
Switching Model ◽  
Emerging Stock Markets ◽  
General Index ◽  
Rolling Window ◽  
Stock Market Bubbles

This paper examines the behavior of seasonal anomalies in Dhaka Stock Exchange (DSE) of Bangladesh and whether the time varying nature of the anomalies is in line with Adaptive Market Hypothesis (AMH). With this aim the research investigated whether the changes in market conditions, for example: up and down market states, stock market bubbles and crashes, initiation of automated trading system and circuit breaker system can affect the behavior of calendar anomalies and therefore, can provide justification for the seasonal patterns in DSE. To achieve the stated objectives, this study utilizes daily general index values of DSE from 1993 to 2018, with GARCH (1,1) model, Markov switching model, subsample analysis and rolling window analysis. The findings support the existence of AMH at DSE in the form of time-varying nature of seasonal anomalies. However, not all seasonal anomalies examined in the study were found to grow weaker over time. The most important finding of this study is that the investors in emerging stock markets, for example DSE, may not learn from the past investment experiences and show the adapting ability towards changed market conditions in the same manner like the investors in a developed market.

Regimes in CDS Spreads: A Markov Switching Model of iTraxx Europe Indices

2006 ◽  
Author(s):  
Carol Alexander ◽  
Andreas Kaeck
Keyword(s):  
Markov Switching ◽  
Markov Switching Model ◽  
Switching Model

A Markov-Switching model for building occupant activity estimation

2019 ◽  
Vol 183 ◽  
pp. 672-683 ◽  
Author(s):  
Sebastian Wolf ◽  
Jan Kloppenborg Møller ◽  
Magnus Alexander Bitsch ◽  
John Krogstie ◽  
Henrik Madsen
Keyword(s):  
Markov Switching ◽  
Markov Switching Model ◽  
Switching Model ◽  
Activity Estimation
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