The Research and Examination of Bull Market and Bear Market

2019 ◽  
Vol 08 (04) ◽  
pp. 631-645
Author(s):  
昱 刘
Keyword(s):  
Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Haifei Liu ◽  
Tingqiang Chen ◽  
Zuhan Hu

This empirical research applies cointegration in the traditional measurement method first to build directed weighted networks in the context of stock market. Then, this method is used to design the indicators and the value simulation for measuring network fluctuation and studying the dynamic evolution mechanism of stock market transaction networks as affected by price fluctuations. Finally, the topological structure and robustness of the network are evaluated. The results show that network structure stability is strong in the bull market stage and weak in the bear market stage. And the convergence rate of the dynamic evolution of network fluctuation is higher in the bull market stage than in the bear market stage.


2016 ◽  
Vol 8 (5) ◽  
pp. 260 ◽  
Author(s):  
Fang Fang ◽  
Weijia Dong ◽  
Xin Lv

This paper investigates how China’s stock market reacts to short-term interest rates, as represented by the Shanghai Interbank Offered Rate (Shibor). We adopt the Markov Regime Switching model to divide China’s stock market into Medium, Bull and Bear market; and then examine how Shibor influences market returns and risk in different market regimes. We find that short-term interest rates have a significant negative effect on stock returns in Medium and Bull market, but could not affect stock returns in Bear market. In addition, different maturities of Shibor have different effects on stock returns. Furthermore, we find that the short-term interest rates have a negative effect on market risk in Bull market, but a positive effect in Bear market. Our findings show that China’s market is quite peculiar and distinctive from the U.S. market or other developed countries’ markets in many ways.


2018 ◽  
Vol 8 (6) ◽  
pp. 745-761
Author(s):  
Yunpeng Sun ◽  
Xueying Wang

This study uses Markov switching vector autoregression (MS-VAR) model to explore the asymmetric effects of China’s monetary policy on the stock market in the bull market and the bear market. With China’s economy in a rapid development, China’s stock market as the main representative of the virtual economy has attracted large assets. Since 1990 to the present, China’s stock market has experienced several times states’ change between the bull market and bear market. The results indicate that China’s quantity-based direct instrument and price-based indirect instrument have asymmetric effects on the stock market in the bull market and the bear market. Moreover, the relationship between China’s economy and stock market exist a degree of dichotomy. Furthermore, China’s monetary policy has stronger effects on the bull market than the bear market.


1997 ◽  
Vol 24 (1) ◽  
pp. 26-29 ◽  
Author(s):  
Robert D. Arnott ◽  
Peter L. Bernstein
Keyword(s):  

2019 ◽  
Vol 15 (2) ◽  
pp. 232-242
Author(s):  
Aniek Hindrayani ◽  
Fadikia K Putri ◽  
Inda F Puspitasari

Abstract: This study analyzes the spillover effects of the US monetary policy on the ASEAN stock market with Markov switching model and investigates differences in empirical results of each country from ASEAN member. The results of this study have important implications for asset price allocation, specifically in the case of a transition between US and other small countries. The results showed that the ASEAN stock market is more affected by the US interest rates during bull-market than bear-markets. This can be seen from the increasing of stock market volatility during expansion comparing with recession period. Therefore, the stock markets of ASEAN countries will not be easily affected by the dollar rate during financial crisis or the recession period. Keywords: stock market, monetary policy, spillover effect, Markov-switching modelEfek Spillover pada Perubahan Kebijakan Moneter Amerika Terhadap Stock Market di ASEANAbstrak: Penelitian ini menganalisis efek spillover akibat adanya perubahan kebijakan moneter Amerika terhadap stock market di ASEAN dengan model Markov switching dan menginvestigasi terkait ada atau tidaknya perbedaan pada hasil empiris di setiap negara anggota ASEAN. Hasil penelitian ini memberikan implikasi penting bagi mekanisme transisi harga aset, khususnya dari Amerika terhadap negara dengan skala perekonomian kecil. Hasil penelitian menunjukkan bahwa stock market ASEAN lebih mudah terpengaruh oleh tingkat suku bunga Amerika pada saat kondisi bull-market dibandingkan saat bear-market. Hal ini dapat dilihat dari tingginya volatilitas stock market pada saat ekspansi dibandingkan saat periode resesi, sehingga stock market negara-negara ASEAN tidak akan mudah terpengaruh oleh dollar pada saat perekonomian mengalami krisis atau saat periode resesi. Kata kunci: stock market, kebijakan moneter, spillover effect, model Markov-switching


2010 ◽  
Vol 7 (4) ◽  
pp. 453-461
Author(s):  
Lauren Jansma ◽  
Jakobus Daniël van Heerden

This study involves an investigation into the act of risk profiling, and whether or not it will differ during different market trends. The literature review involves an in-depth discussion about risk tolerance and what factors determine it, as well as behavioural finance, bull and bear market phases, strategic asset allocation, and the duty of a diligent financial advisor to his or her clients. In order to conduct the investigation, 210 respondents under the age of 33 years filled out actual risk profile questionnaires, each having one of three market conditions simulated: bear market conditions, bull market conditions, or no market conditions (current market conditions assumed). These three different simulated market conditions form the three groups which were to be compared to each other. Each respondent was categorised based on the type of investor he or she was deemed to be: conservative, moderately conservative, moderate, moderately aggressive, or aggressive. The three groups were then tested using a paired samples T test for statistically significant differences between their means. At a 5% level of significance, the evidence showed that there was not a statistically significant difference between risk profiling during a bull market and risk profiling during a bear market, which resulted in failure to reject the null hypothesis.


2019 ◽  
Vol 13 (10) ◽  
pp. 2095
Author(s):  
Denny Nurdiansyah ◽  
Alif Yuanita Kartini

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.


PsycCRITIQUES ◽  
2016 ◽  
Vol 61 (15) ◽  
Author(s):  
Richard W. Bloom
Keyword(s):  

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