Research
Working Papers
Working Papers
Transaction Risks in Intraday Trading with Subjective Beliefs
Transaction Risks in Intraday Trading with Subjective Beliefs
Abstract
Abstract
I propose an asset pricing and trading model that bridges the intraday trading literature and the subjective beliefs literature. In the model, two types of investors, i.e. retail investor and fund manager, both have recursive utility. The fund manager, as the informed party, updates her subjective beliefs by Bayesian learning with fading memory from the output data, and prices the equity asset with her own pricing formula. The retail investors, as the uninformed party, don't price the asset and take the market price as it is. The model is then taken to a thorough simulation analysis, which features intraday trading and transaction risk. The simulations show several important results. First, market is efficient due to the existence and functioning of the expert investor, but the efficiency is bounded when severe disaster takes place. Second, higher share of labor income stabilizes the market, which is potentially because of the more stabilized theoretical price in the fund manager's mind as the transaction success rate is higher and the return volatility is lower. Third, transaction risk has a positive premium compensation. Fourth, the equity is more severely overpriced when the fund controls more resources, or the share of labor income is higher. Finally, in peaceful times the market adjusts itself more smoothly with higher intraday trading frequency. However, during disaster times, the market becomes more volatile with higher intraday trading frequency.
I propose an asset pricing and trading model that bridges the intraday trading literature and the subjective beliefs literature. In the model, two types of investors, i.e. retail investor and fund manager, both have recursive utility. The fund manager, as the informed party, updates her subjective beliefs by Bayesian learning with fading memory from the output data, and prices the equity asset with her own pricing formula. The retail investors, as the uninformed party, don't price the asset and take the market price as it is. The model is then taken to a thorough simulation analysis, which features intraday trading and transaction risk. The simulations show several important results. First, market is efficient due to the existence and functioning of the expert investor, but the efficiency is bounded when severe disaster takes place. Second, higher share of labor income stabilizes the market, which is potentially because of the more stabilized theoretical price in the fund manager's mind as the transaction success rate is higher and the return volatility is lower. Third, transaction risk has a positive premium compensation. Fourth, the equity is more severely overpriced when the fund controls more resources, or the share of labor income is higher. Finally, in peaceful times the market adjusts itself more smoothly with higher intraday trading frequency. However, during disaster times, the market becomes more volatile with higher intraday trading frequency.
(The paper may be available upon request)
(The paper may be available upon request)
Reference Point for Volatility and Disposition Effect
Reference Point for Volatility and Disposition Effect
Abstract
Abstract
I exploit the brokerage data set of individual investors to identify the effect of volatility on trading volume. Both parametric and non-parametric estimates consistently show the existence of volatility threshold effect, i.e. individual investors tend to trade more when the volatility exceeds certain threshold. Motivated by this empirical result, I discuss a portfolio choice model in which I introduce the volatility reference point in addition to the conventional return reference point. This idea is new to the literature. Two possible setups of that model are discussed and simulated to capture the behaviors of mental accounting traders and reinvestment traders. The simulation results show that the disposition effect is generally better predicted in my model with volatility reference point. Finally, the implication of my model is empirically tested, and the fact is identified that investors with low financial sophistication are more susceptible to volatility threshold effect.
I exploit the brokerage data set of individual investors to identify the effect of volatility on trading volume. Both parametric and non-parametric estimates consistently show the existence of volatility threshold effect, i.e. individual investors tend to trade more when the volatility exceeds certain threshold. Motivated by this empirical result, I discuss a portfolio choice model in which I introduce the volatility reference point in addition to the conventional return reference point. This idea is new to the literature. Two possible setups of that model are discussed and simulated to capture the behaviors of mental accounting traders and reinvestment traders. The simulation results show that the disposition effect is generally better predicted in my model with volatility reference point. Finally, the implication of my model is empirically tested, and the fact is identified that investors with low financial sophistication are more susceptible to volatility threshold effect.
(The paper may be available upon request)
(The paper may be available upon request)