Anchoring and Asymmetric Information in the Real Estate Market: A Machine Learning Approach

Conventional wisdom suggests that non-local buyers usually pay a premium for home purchases. While the standard contract theory predicts that non-local buyers may pay such a price premium because of the higher cost of gathering information, behavioral economists argue that the premium is due to buyer anchoring biases in relation to the information. Both theories support such a price premium proposition, but the empirical evidence is mixed. In this study, we revisit this conundrum and put forward a critical test of these two alternative hypotheses using a large-scale housing transaction dataset from Hong Kong. A novel machine-learning algorithm with the latest technique in natural language processing where applicable to multi-languages is developed for identifying non-local Mainland Chinese buyers and sellers. Using the repeat-sales method that avoids omitted variable biases, non-local buyers (sellers) are found to buy (sell) at a higher (lower) price than their local counterparts. Taking advantage of a policy change in transaction tax specific to non-local buyers as a quasi-experiment and utilizing the local buyers as counterfactuals, we found that the non-local price premium switches to a discount after the policy intervention. The result implies that the hypothesis of anchoring biases is dominant.

A Qualitative Exploration of Heuristics and Cognitive Biases in Auditor Judgements

Professional judgement is inherent in financial statement audits because various methods, techniques, or approaches prescribed in auditing standards do not provide auditors with detailed guidance or specific audit criteria. While auditors are expected to exercise their judgements based on careful reasoning, there is a possibility that they do not always follow such an approach and instead make their judgements using heuristics. This study aims to penetrate and reveal whether there are cognitive biases in the judgements of auditors and what heuristics lead to these biases. This study employs a qualitative research design and uses ethnomethodology as a research approach. Data were collected using in-depth semi-structured interviews with 15 auditors who were either partners, managers, seniors, or juniors at a public accounting firm. Using the heuristic-bias framework as a theoretical lens and based on an analysis involving data condensation, data display, and conclusion drawing and verification, this study identifies five types of biases that auditors can experience: jumping to conclusions, groupthink, representativeness, availability, and anchoring biases. The results of this study present practical implications for auditors, accounting professional associations, public accounting firms, and academic institutions. That is, the findings provide insights for formulating strategies aimed at raising auditors’ awareness about possible systematic errors, or biases, in professional judgements when auditors rely on heuristics as a simplifying judgement-making strategy.

Price Adjustments on Ex-Right Dates in Cases of Right Offerings

Using a sample of 618 right offerings made between 2004 and 2016, this study analyzes price adjustments on ex-right dates. The major results are as follows. First, as the ratio of reference price divided by the ex-right opening price is calculated as 0.9613, price adjustments are significantly less than the value of preemptive rights. We also document additional price decreases after ex-right dates. The smaller price drops on ex-right dates and delayed adjustments are evidence of market inefficiency. Second, the listing of preemptive rights certificates makes price adjustments on ex-right dates more efficient. Third, the abnormal return on ex-right dates is 4.24%, which is significantly positive. Fourth, the trading strategies of purchasing at cum-right prices, selling at ex-right prices, and purchasing new shares generate a 2.59% return, and foreign investors are most likely to follow such trading strategies. In addition, for the fourth quartile, which has the largest preemptive rights value, the abnormal return on ex-right dates is 9.31%, and the trading strategy generates a 5.77% return. In summary, although the Korea Exchange discloses a reference price for efficient adjustment, price adjustment on ex-right dates is not efficient, thus generating profitable investment opportunities. Significant abnormal returns owing to inefficient price adjustments on ex-right dates are partly consistent with anchoring biases.

The Significance Of Anchoring Bias In Estimating Financial And Economic Indicators: An Experimental Study In Indonesia Setting

Anchoring, in Behavioral Finance terminology, refers to people's tendency to rely too much on the initial piece of information offered (the "anchor"). Anchoring is widely found in decion making processes, where people make estimates about the likelihood of uncertain events or to predict or recall certain values or outcomes by considering the anchor value and adjusting it upwards or downwards to reach a final estimate. Such adjustments are often insufficient, leaving a cognitive bias in the direction of the initial anchor value (Tversky & Kahneman, 1974). This experimental study was performed in order to detect the presence of anchoring bias in Indonesian setting. Following Kudryavtsev and Cohen (2010)’s procedure, we randomly devided participants into two groups, namely: “control group” (where participants did not receive any anchor value) and “anchoring group” (where participants received some anchoring values). Participants in both groups were instructed to provide their best estimations or answers to questions regarding financial and economic issues. Anchors and the questions were presented with the same order and were expressed in the same scale. Using students of Master of Management Program Universitas Gadjah Mada as respondents, this research was aimed to see whether the answers provided by participants in the anchoring group were affected by the anchor values. Further, we would like to test whether the degree of anchoring biases among female respondents were higher than the biases among male respondents; whether questions related to older topics created higher anchoring biases than the newer ones; and finally, whether anchoring bias among non-finance major students were higher than those among finance students. The results show that anchoring biases were identified among all participants. However, we could not identify higher degree of anchoring bias among female participants than those among male participants. Similarly, we did not identify higher biases in answering questions with older topics than the newer ones. Finally, higher degree of anchoring biases were found among non-finance major students than in finance major students, suggesting the type of knowledge might affect the degree of anchoring bias.