• Title/Summary/Keyword: Market anomaly

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Foreign Exchange Risk Premia and Goods Market Frictions

  • Moon, Seongman
    • East Asian Economic Review
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    • v.19 no.1
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    • pp.3-38
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    • 2015
  • Fama's (1984) volatility relations show that the risk premium in foreign exchange markets is more volatile than, and is negatively correlated with the expected rate of depreciation. This paper studies these relations from the perspective of goods markets frictions. Using a sticky-price general equilibrium model, we show that near-random walk behaviors of both exchange rates and consumption, in response to monetary shocks, can be derived endogenously. Based on this approach, the paper provides quantitative results on Fama's volatility relations.

A Study of TOM(Turn-of-the-Month) Effect in KOSDAQ Market (코스닥시장의 월바뀜(TOM)효과에 관한 연구)

  • Hong, Geon-Pyo;Im, In-Seob;Oh, Hyun-Tak
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.1
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    • pp.308-316
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    • 2015
  • The purpose of this study is to verify TOM(turn-of-the-month) effect in the Kosdaq market, and that to compare to TOM effect of KOSPI for supporting degree of identification and to find new features. For this study, as the study basis sample, we used the daily data of the KOSDAQ from January 1996 to December 2013 and verified the TOM effect through yearly, monthly, classification by event as financial crisis, different period of TOM in order to clarify the effect of the KOSPI and KOSDAQ. As a result, We find that the TOM effect in KOSDAQ is always present uniformly in yearly, monthly, event-specific, which unlike TOM period also in KOSPI and generally TOM effect in KOSDAQ market which has larger volatility was appeared more pronouncedly than KOSPI market, and particularly TOM effect of KOSDAQ was larger than that of KOSPI on financial crisis occasion. But TOM effect of KOSDAQ was less stable than KOSPI.

The Relationship between Default Risk and Asset Pricing: Empirical Evidence from Pakistan

  • KHAN, Usama Ehsan;IQBAL, Javed
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.3
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    • pp.717-729
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    • 2021
  • This paper examines the efficacy of the default risk factor in an emerging market context using the Fama-French five-factor model. Our aim is to test whether the Fama-French five-factor model augmented with a default risk factor improves the predictability of returns of portfolios sorted on the firm's characteristics as well as on industry. The default risk factor is constructed by estimating the probability of default using a hybrid version of dynamic panel probit and artificial neural network (ANN) to proxy default risk. This study also provides evidence on the temporal stability of risk premiums obtained using the Fama-MacBeth approach. Using a sample of 3,806 firm-year observations on non-financial listed companies of Pakistan over 2006-2015 we found that the augmented model performed better when tested across size-investment-default sorted portfolios. The investment factor contains some default-related information, but default risk is independently priced and bears a significantly positive risk premium. The risk premiums are also found temporally stable over the full sample and more recent sample period 2010-2015 as evidence by the Fama-MacBeth regressions. The finding suggests that the default risk factor is not a useless factor and due to mispricing, default risk anomaly prevails in the Pakistani equity market.

A study of future scenario forecasting of autonomous vehicle industry (자율주행 자동차 산업의 미래 시나리오 예측 연구)

  • Joo, Baegsu;Kim, Jieun
    • Journal of Technology Innovation
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    • v.30 no.2
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    • pp.1-27
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    • 2022
  • In recent years, the autonomous vehicle industry has changed drastically. So the needs and interests in predicting future technologies and market prospects of the autonomous vehicle field have been very increased. However, considering the characteristics of the automotive industry, which has various factors, complex correlation of them and big influence on each other, the study of systematic future forecasting methodologies are urgent and necessary which are applicable to autonomous vehicle industry. In this research, the two methods such as "Field Anomaly Relaxation" and "Multiple Perspective Concept" were analyzed and chosen, which are suitable to automotive industry. By the combination of two methods this research developed and examined the three future scenarios related to core technologies and industry trends. And these scenarios feasibility was verified by experts and evaluation checklist. This research has a contribution that this future scenario forecasting approach can be applied to the industries which have various volatility like the autonomous vehicle industry.

The Prediction of the Apartment Construction Project Cashflow with Changing Sales Point (분양시기 변동에 따른 공동주택 건설공사 현금흐름 예측)

  • Bae Jun-Ho;Kim Jae-Jun
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • autumn
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    • pp.234-237
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    • 2003
  • The Korean housing supply have been provided by the Pre-construction sales system. The Pre-construction sales system contributed to large housing supply. But it followed by the market anomaly. Along the housing market is changing to tile market for consumers, it requires new policy and regulations. This market changes and needs to modify the policy make a discussion about introducing the Post-construction sales system. it concerns to change the time to sale. This paper analyzes the present feasibility study and makes a tool to predict construction cashflow considering changed sales point. The sales timing leads to decide the amount of financial costs in the construction project and that cost affects to the feasibility. The accurate cashflow prediction is required for a successful apartment construction delivery.

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Cash Flow Anomalies Associated with Business Conditions in Korean Stock Market

  • Yoon, Bo-Hyun;Son, Sam-Ho
    • Journal of Distribution Science
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    • v.12 no.5
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    • pp.61-69
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    • 2014
  • Purpose - Many studies report that returns on hedge portfolios that eliminate particular risk types are abnormal from traditional asset pricing models' perspectives. This study examines the pervasiveness of anomalous returns conditioned on business cycle and group size. Research design, data, and methodology - Using KOSPI and KOSDAQ market data from July 1991 to December 2013, we categorize stocks into appropriately sized groups, and dichotomize our sample periods into expansion and recession periods then, we construct hedge portfolios by sorting stocks by anomaly variables and calculate their returns. Results - Four anomalies, including earnings yield, net stock issue, total asset growth, and liquidity appear pervasive across all groups for the entire sample period. However, only the hedge returns of net stock issues are significant across all group sizes during both expansion and recession. Conclusions - A net stock issue can be an appropriate proxy for expected growth of book equity for all group sizes in recessions. This finding could provide insights to investment industry participants and to researchers interested in the relationship between expected growth of book equity and business cycle risk.

An Empirical Study of the Trading Rules on the basis of Market Anomalies and Technical Analysis (시장이상현상과 기술적 분석을 이용한 거래전략에 관한 연구)

  • Ohk, Ki-Yool;Lee, Min-Kyu
    • Management & Information Systems Review
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    • v.37 no.1
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    • pp.41-53
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    • 2018
  • This study validates the trading rules based market anomalies and technical analysis in the Korean stock market. For the analysis, we built decile portfolios on the basis of corporate characteristics factors that clearly demonstrate specific patterns of stock returns including the firm size, book-to-market equity, and accruals. This portfolio was used to develop a portfolio based on the moving average trading strategy which was used for popular technical analysis tools, and then that was evaluated using the Sharpe ratio. We also created a zero-cost portfolio to identify the profitability and success rate of the moving average trading strategy. We lastly sought to ensure a more robust evaluation by calculating the Sortino ratio of the portfolio based on the moving average trading strategy with various lags. Key findings from this validation are as follows. First, a smaller firm size, a higher book-to-market equity, and lower accruals led to larger average returns. Second, the risk-adjusted performance of the moving average trading strategy was the highest in terms of the firm size, followed by book-to-market equity and accruals. Third, the returns of the zero-cost portfolios all had a positive value, with its overall success rate hovering over 68.8%, demonstrating the successfulness of the moving average trading strategy. Fourth, various evaluations revealed the economic usefulness of our trading strategy that used market anomalies and technical analysis.

Sector Investment Strategy with the Black-Litterman Model (블랙리터만 모형을 이용한 섹터지수 투자 전략)

  • Song, Jung-Min;Lee, Young-Ho;Park, Gi-Gyoung
    • Korean Management Science Review
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    • v.29 no.1
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    • pp.57-71
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    • 2012
  • In this paper, we deal with a sector investment strategy by implementing the black-litterman model that incorporates expert evaluation and sector rotation momentum. Expert evaluation analyzes the relative performance of the industry sector compared with the market, while sector rotation momentum reflects the price impact of significant sector anomaly. In addition, we consider the portfolio impact of sector cardinality and weight constraints within the context of mean-variance portfolio optimization. Finally, we demonstrate the empirical viability of the proposed sector investment strategy with KOSPI 200 data.

Lunar Effect on Stock Returns and Volatility: An Empirical Study of Islamic Countries

  • MOHAMED YOUSOP, Nur Liyana;WAN ZAKARIA, Wan Mohd Farid;AHMAD, Zuraidah;RAMDHAN, Nur'Asyiqin;MOHD HASAN ABDULLAH, Norhasniza;RUSGIANTO, Sulistya
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.5
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    • pp.533-542
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    • 2021
  • The main objective of this article is to investigate the existence of the lunar effect during the full moon period (FM period) and the new moon period (NM period) on the selected Islamic stock market returns and volatilities. For this purpose, the Ordinary Least Squares model, Autoregressive Conditional Heteroscedasticity model, Generalised Autoregressive Conditional Heteroscedasticity model and Generalised Autoregressive Conditional Heteroscedasticity-in-Mean model are employed using the mean daily returns data between January 2010 and December 2019. Next, the log-likelihood, Akaike Information Criterion and Schwarz Information Criterion value are analyzed to determine the best models for explaining the returns and volatility of returns. The empirical results have deduced that, during the NM period, excluding Malaysia, the total mean daily returns for all of the selected countries have increased mean daily returns in contrast to the mean daily returns during the FM period. The volatility shocks are intense and conditional volatility is persistent in all countries. Subsequently, the volatility behavior tends to have lower volatility during the FM period and NM period in the Islamic stock market, except Malaysia. This article also concluded that the ARCH (1) model is the preferred model for stock returns whereas GARCH-M (1, 1) is preferred for the volatility of returns.

Anomaly Detection System of Smart Farm ICT Device (스마트팜 ICT기기의 이상탐지 시스템)

  • Choi, Hwi-Min;Kim, Joo-Man
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.2
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    • pp.169-174
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    • 2019
  • This paper propose a system to notify the user that detects failure of malfunction of smart farm ICT devices. As the fourth industrial revolution approaches, agriculture is also fused with ICT technology to improve competitiveness. Smart farming market is rapidly growing every year, but there is still a lack of standardization and certification systems. Especially, smart farm devices that are widely used in Korea are different in product specifications, software and hardware are developed separately, and quality and compatibility are poor. Therefore, a system that can recognize the abnormality of the equipment due to the frequent damage of farmers using low cost smart farm equipment is needed. In this paper, we review smart farm domestic and overseas policy trends and domestic smart agriculture trends, analyze smart farm failure or malfunctions and proactively prevent them, and propose a system to inform users when problems occur.