• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1557-1567
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• 2014

In this paper, I propose a general hypothesis that after the enactment of the Sarbanes-Oxley Act (SOA) financial statements convey more accurate and reliable corporate information to investors who in turn reflect such improvements in stock prices and test four practical hypotheses that simultaneously feature the degree of information asymmetry, forecast bias, and investor reaction to biased earnings information. The empirical results unanimously suggest that the post-SOA investors take advantage of the improvement in informational efficiency and accuracy and actively adjust for analyst forecast bias in earnings forecasts. The SOA indeed appears to achieve its primary goal of investor protection.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.199-207
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• 2019

This study aims to analyze the profitability of Robo-Advisors portfolio combined with the analysts' forecasts on the Korean stock prices. Sample stocks are 8 blue-chips and sample period is from 2003 to 2019. Robo-Advisor portfolio was suggested using the Black-Litterman model combined with the analysts' forecasts and its profitability was analyzed. Empirical result showed the suggested Robo-Advisor algorithm produced 1% annual excess return more than that of the benchmark. The study documented that the analysts' forecasts had an economic value when applied in the Robo-Advisor portfolio despite the prevalent blames from investors. The profitability on small or medium-sized stocks will need to be analyzed in the Robo-Advisor context because their information is relatively less known to investors and as such is expected to be strongly influenced by the analysts' forecasts.

• Knowledge Management Research
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• v.13 no.5
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• pp.1-13
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• 2012

This study investigates whether firm-specifics affect forecast accuracy using a sample of IPO firms in Korea. The forecasts accuracy can be differentiated depending on firm specifics. This study uses the foreign investor, intangible asset and patents as firm specifics. The analysts are divided into two groups by firm-specifies(foreign investors ratio of low and high, intangible asset ratio of low and high, patents of acquisition) and also examine the degree of analysts's forecast accuracy over the two groups. and examined the degree of the analysts' forecast accuracy over the two groups. The sample is composed of 460 IPO (Initial Public Offering) firms listed on the KOSDAQ (Korean Securities Dealers Automated Quotations) for the period from 2001 to 2009. The analysts' forecast accuracy is much higher in the group of high foreign investor but is lower in the group of high intangible assets and patents. Also, the group of high foreign investors respectively interacts with group of high intangible assets ratio and group of patents of acquisition. In result, The analysts' forecast accuracy is higher because foreign investor is decreased information asymmetry. This study compares suggests that patents may be helpful for predicting forecast accuracy.