机构投资者与个人投资者过度自信行为比较研究

本文首先基于我国A股市场机构股票持有数据,构建了不同的投资组合来区分机构投资者与个人投资者的投资行为。然后运用Granger因果检验与SUR估计,探讨了我国证券市场机构投资者与个人投资者是否具有过度自信行为,结果表明无论是机构投资者还是个人投资者在不同市场状态下都存在交易过多的过度自信认知偏差。并且我国证券市场上个人投资者与机构投资者的过度自信程度在不同的市场状态下并无明显差异。最后提出了相关政策建议。     

Investors’ aspirations and portfolio performance

Based on a large database of individual investors, I analyze the impact of personal financial goals on portfolio performance. I stress the role played by latent investor aspirations as defined in the Behavioral Portfolio Theory framework. I identify two opposite profiles of investors. High-aspirations investors trade more and hold riskier portfolios than the average investor. By contrast, low-aspirations investors are more diversified than the average investor. I find that when controlling for diversification, turnover and usual risk factors, high-aspiration investors underperform their peers, whereas low-aspirations investors outperform them.     

Fool's mate: What does CHESS tell us about individual investor trading performance?

We investigate the short‐term relation between individual investor trading and stock returns on the Australian Securities Exchange. Stocks heavily bought by individual investors underperform stocks heavily sold over the subsequent three days, with respective returns on to a long–short portfolio of ?93, ?67 and ?12 basis points on days one, two and three. Individuals underperform in small and mid‐size stocks when they trade passively using limit orders waiting for the market price to move in their favour. Individuals underperform in large stocks when they trade aggressively using marketable orders. Foreign institutions gain from taking the opposite side of individual trades. We present an information asymmetry‐based explanation for the findings.     

透明度变化对股票市场投资者委托单提交行为和交易成本影响研究

基于2003年12月8日沪深交易所交易前市场透明度改革背景,本文利用一家营业部的投资者报价和交易数据,研究同一个机构投资者和散户投资者在透明度改革前后委托单提交激进程度的变化,以及这种变化对其完成交易的成本的影响。我们发现,透明度改革前后,机构投资者的委托单提交激进程度都显著大于散户投资者的委托单提交激进程度。透明度增加以后,机构投资者的委托单激进程度显著减少,而散户投资者的委托单提交激进程度增加。同时发现,透明度增加以后,机构投资者通过分拆委托单,增加交易次数,导致完成交易的时间增加,但价格影响力基本没有变化,散户投资者的成交时间和价格影响力有显著改善。     

Who moves the stock market in an emerging country – Institutional or retail investors?

By analyzing the dynamic behavior of institutional and retail investors in the Indonesia Stock Exchange using their completed transactions (comprising over 250 million observations), this study highlights that their trading strategies and behavior, in which institutions play a more important role than individuals in the market, are indeed different. Specifically, past trading activities by individual (institutional) investors have significantly affected the current trading behaviors and strategies of individual investors (both investor types). Furthermore, retail (institutional) investors are most likely to perform contrarian (momentum) strategies and trade frequently (infrequently) with small (large) amounts of money and short (long) holding periods.     

Optimizing a portfolio of mean-reverting assets with transaction costs via a feedforward neural network

Optimizing a portfolio of mean-reverting assets under transaction costs and a finite horizon is severely constrained by the curse of high dimensionality. To overcome the exponential barrier, we develop an efficient, scalable algorithm by employing a feedforward neural network. A novel concept is to apply HJB equations as an advanced start for the neural network. Empirical tests with several practical examples, including a portfolio of 48 correlated pair trades over 50 time steps, show the advantages of the approach in a high-dimensional setting. We conjecture that other financial optimization problems are amenable to similar approaches.     

Contracts for dummies? The performance of investors in contracts for difference

Investors widely use contracts for difference (CFDs) to leverage and short sell underlying financial assets. We investigate the after cost performance of investors in Australian Securities Exchange listed share CFDs, and find that market order CFD trades earn small positive returns at the daily horizon, with negative returns reported for one month to one year horizons due to financing costs. Market orders also net sell positions, which suggests that investors use CFDs for shorting opportunities. Overall, we find that liquidity demanders in CFDs obtain favourable execution, which is inconsistent with the view that CFDs are used by naive individuals.     

What factors affect behavioral biases? Evidence from Turkish individual stock investors

This paper investigates behavioral biases among Turkish individual stock investors during 2011. Using transaction data, we analyze how common disposition effect, familiarity bias, representativeness heuristic, and status quo bias are, what factors affect these biases and how these biases relate to each other including overconfidence and return performance. We find that biases are common among investors. Male, younger investors, investors with lower portfolio value, and investors in low income, low education regions exhibit more familiarity bias. Female, older investors and investors with high portfolio values are more subject to disposition effect and representativeness heuristic. Individuals in the opposite edge of overconfidence are subject to status quo bias. Overconfidence is positively correlated with familiarity bias. Representativeness heuristic deteriorates wealth while status quo bias results in higher trade performance. Familiarity bias has a nonmonotonic effect on return; lower (higher) levels of familiarity bias have a negative (positive) effect on return. To the best of our knowledge, this is one of the few studies that focus on nationwide data and analyze the biases simultaneously. Using a unique dataset, we extend the findings of the behavioral finance literature to emerging markets. Besides, analysis of multiple biases helps us better understand the relationship among biases.     

Realization utility

A number of authors have suggested that investors derive utility from realizing gains and losses on assets that they own. We present a model of this “realization utility,” analyze its predictions, and show that it can shed light on a number of puzzling facts. These include the disposition effect, the poor trading performance of individual investors, the higher volume of trade in rising markets, the effect of historical highs on the propensity to sell, the individual investor preference for volatile stocks, the low average return of volatile stocks, and the heavy trading associated with highly valued assets.