We investigate how distraction affects the trading behavior of retail investors, and ultimately market liquidity. Exploiting episodes of sensational news exogenous to the stock market, we first document that investors stop trading altogether when they are distracted. We report further that these effects are more pronounced for more overconfident–i.e., single-male and active–investors, who are t...

Uninformed investors facing future carrying cost (liquidity) shocks determine primary market prices for asset-backed securities. A liquidity provider subsequently buys tendered securities in competitive secondary markets. Liquidity provision is distorted by a speculator receiving a private signal regarding cash flow. Optimal structuring minimizes total trading loss and carrying cost discounts d...

In recent years, algorithmic and high-frequency trading have been the subject of increasing risk concerns. A general theme that we adopt in this thesis is that trading practitioners are predominantly interested in risk-adjusted performance. Likewise, regulators are demanding stricter risk controls. First, we scrutinise conventional AI model design approaches with the aim to increase the risk-ad...

We study an economic model where agents trade a variety of products by using one of three competing rules: “need”, “greed” and “noise”. We find that the optimal strategy for any agent depends on both product composition in the overall market and composition of strategies in the market. In particular, a strategy that does best on pairwise competition may easily do much worse when all are present...

The observed transaction prices on a stock market at discrete time points are assumed to be a sample from a continuous time-value process. The theory of an efficient market is used as motivation for a random-walk type model. The fact that bid-ask spread and other microstructure phenomena exist is accounted for by adding a noise term to the model. Models for elementary detrending based on stocha...

A model of competitive stock trading is developed in which investors are heterogeneous in their information and private investment opportunities and rationally trade for both informational and noninformational motives. I examine the link between the nature of heterogeneity among investors and the behavior of trading volume and its relation to price dynamics. It is found that volume is positivel...

I n this paper, trading symbols of the 30 largest companies listed in the Tehran Stock Exchange (TSE) were ranked based on the asymmetry information risk. Using the Ersan and Alici (2016) modified clustering algorithm (EA), we estimated the probability of informed trading (PIN) to measure the asymmetry information among traders for each trading symbol and trading day through two-year...

In the classical Kalman-Bucy filter and in the subsequent literature so far, it has been assumed that the initial value of the signal process is independent of both the noise of the signal and of the noise of the observations. The purpose of this paper is to prove a filtering equation for a linear system where the (normally distributed) initial value X0 of the signal process Xt has a given corr...

We develop a new methodology to estimate the impact of financial transaction tax (FTT) on market outcomes. In our sequential trading model, there are price-elastic noise and informed traders. model through maximum likelihood for sample 60 NYSE stocks in 2017. quantify effect introducing an FTT given parameter estimates. An increases proportion trading, improves information aggregation, but lowe...