Analysis of Calendar Effects: Day-of-the-Week Effect on the Stock Exchange of Thailand (SET)

Sutheebanjard, Phaisarn; Premchaiswadi, Wichian

doi:10.7763/ijtef.2010.v1.11

Cited by 19 publications

(7 citation statements)

References 10 publications

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“…The third data limitation is the necessary data to create the precise causal structure of BI mapping (Cheng et al, 2002;. In general, an accurate causal structure of BI mapping can be obtained by detailed interviews with decision makers (O'Keeffe et al, 2016) or learned from a dataset (Sutheebanjard and Premchaiswadi, 2010).…”

Section: Model Limitationsmentioning

confidence: 99%

Using a coupled agent-based modeling approach to analyze the role of risk perception in water management decisions

Hyun

Huang

Yang

et al. 2019

Hydrol. Earth Syst. Sci.

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Abstract. Managing water resources in a complex adaptive natural–human system is a challenge due to the difficulty of modeling human behavior under uncertain risk perception. The interaction between human-engineered systems and natural processes needs to be modeled explicitly with an approach that can quantify the influence of incomplete/ambiguous information on decision-making processes. In this study, we two-way coupled an agent-based model (ABM) with a river-routing and reservoir management model (RiverWare) to address this challenge. The human decision-making processes is described in the ABM using Bayesian inference (BI) mapping joined with a cost–loss (CL) model (BC-ABM). Incorporating BI mapping into an ABM allows an agent's psychological thinking process to be specified by a cognitive map between decisions and relevant preceding factors that could affect decision-making. A risk perception parameter is used in the BI mapping to represent an agent's belief on the preceding factors. Integration of the CL model addresses an agent's behavior caused by changing socioeconomic conditions. We use the San Juan River basin in New Mexico, USA, to demonstrate the utility of this method. The calibrated BC-ABM–RiverWare model is shown to capture the dynamics of historical irrigated area and streamflow changes. The results suggest that the proposed BC-ABM framework provides an improved representation of human decision-making processes compared to conventional rule-based ABMs that do not take risk perception into account. Future studies will focus on modifying the BI mapping to consider direct agents' interactions, up-front cost of agent's decision, and upscaling the watershed ABM to the regional scale.

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Section: Model Limitationsmentioning

confidence: 99%

Using a coupled agent-based modeling approach to analyze the role of risk perception in water management decisions

Hyun

Huang

Yang

et al. 2019

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…We aim to demonstrate that the proposed BC-ABM framework can effectively capture agent's risk perception. In general, an accurate causal structure of BI mapping can be obtained by a detailed interview with decision makers (O'Keeffe et al, 2016) or learned from a dataset (Sutheebanjard and Premchaiswadi, 2010).…”

Section: Limitation and Future Studymentioning

confidence: 99%

Develop a coupled agent-based modeling approach for uncertain water management decisions

Hyun

Huang

Yang

et al. 2019

Preprint

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Abstract. Managing water resources in a complex adaptive natural-human system is subject to a challenging task due to the difficulty of modeling human behavior and decision uncertainty. The interaction between human-engineered systems and natural processes needs to be modeled explicitly, and a formal approach is required to characterize human decision-making processes and quantify the associated uncertainty caused by incomplete/ambiguous information. In this study, we two-way coupled an agent-based model (ABM) with a river-routing and reservoir management model (RiverWare) while ABM uses a bottom-up approach that allows individual decision makers to be defined as agents – each able to make their own decisions based on their objectives and confidence in the acquired information. The human decision-making processes is described in the ABM using Bayesian Inference (BI) mapping joined with a Cost-Loss (CL) model (BC-ABM). Incorporating BI mapping into an ABM allows an agent's internal (psychological) thinking process to be specified by a cognitive map between decisions and relevant preceding factors that could affect decision-making. The associated decision uncertainty is characterized by a risk perception parameter in the BI mapping representing an agent's belief on the preceding factors. Integration of the CL model addresses an agent's behavior caused by changing socioeconomic conditions. We use the San Juan River Basin in New Mexico, USA to demonstrate the utility of this method. The calibrated BC-ABM-RiverWare model is shown to capture the dynamics of historical irrigated area and streamflow changes. The results suggest that the proposed BC-ABM framework provides an improved representation of human decision-making processes compared to conventional rule-based ABMs that does not take uncertainties into account. Future studies will focus on modifying the BI mapping to consider direct agents' interactions, up-front cost, joint human and natural uncertainty evaluation, and upscaling the watershed ABM to the regional scale.

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“…The presence of calendar anomalies has been presented extensively for the last three decades in financial markets. The most common ones are the day-of-the-week effect, monthly effect, weekend effect, holiday effects, within-the-month effect, turn-of-the month effect (Agrawal, Tandon, 1994;Boudreaux, 1995;Smirlock & Starks, 1986;Aggarval & Rivoli, 1989; Barone, 1990;Kato et al, 1990;Gu, 2003;Schwert, 2002;Sutheebanjard & Premchaiswadi, 2010).…”

Section: Introductionmentioning

confidence: 99%

Should Investors on Equity Markets Be Superstitious? (Example of 7 World Stock Indexes Components)

Borowski¹

2018

IJEF

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The problem of efficiency of financial markets, especially the weekend effect has always fascinated scholars and practitioners due to its relationship with the financial market efficiency. The issue is significant from the point of view of assessing the portfolio management effectiveness and behavioral finance. This paper tests the hypothesis of the unfortunate dates effect upon 7 equity indexes components (CAC40, DAX, DJIA, FTSE30, FTSEBIT, NIKKEI225 and SENSE), i.e. 419 companies. For all these equities the following rates of return were analyzed: Close-close, Overnight, Open-open, Open-close. As unfortunate days, the sessions falling on the following dates were selected: 13th and 4th day of the month, Friday the 13th and Tuesday the 13th. The research proved the presence of all kinds of the “unfortunate dates” effects on analyzed markets. The effects were registered for all analyzed rates of return. The most dominating “unfortunate dates effects” resulted to be Tuesday the 13th, proceeding the 4th day of the month effect. This is the first analysis of the presence of the “unfortunate dates effect”, in which other than Close-close returns were examined and fulfils the research gap. 

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Analysis of Calendar Effects: Day-of-the-Week Effect on the Stock Exchange of Thailand (SET)

Cited by 19 publications

References 10 publications

Using a coupled agent-based modeling approach to analyze the role of risk perception in water management decisions

Using a coupled agent-based modeling approach to analyze the role of risk perception in water management decisions

Develop a coupled agent-based modeling approach for uncertain water management decisions

Should Investors on Equity Markets Be Superstitious? (Example of 7 World Stock Indexes Components)

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