We develop a portfolio trading strategy that aims to achieve optimal performance against arrival prices by minimizing market impact and risk. We first lay the groundwork by formulating a single-security trading strategy and then generalize the framework to the portfolio trading context....

In recent years, Bitcoin has received substantial attention as potentially high-earning investment. However, its volatile price movement exhibits great financial risks. Therefore, how to accurately predict and capture changing trends in the Bitcoin market is of substantial importance to...

Modern Algorithmic Trading ("Algo") allows institutional investors and traders to liquidate or establish big security positions in a fully automated or low-touch manner. Most existing academic or industrial Algos focus on how to "slice" a big parent order into smaller child orders over a given...

We investigate the role algorithmic trading (AT) on days when the absolute value of the market return is more than two percent. We find that the abnormal return of a stock is related to the stock's AT intensity, that high AT intensity stocks experience less price drops (surges) on days when the...

We develop a high frequency (HF) trading strategy where the HF trader uses her superior speed to process information and to post limit sell and buy orders. By introducing a multifactor mutually exciting process we allow for feedback effects in market buy and sell orders and the shape of the...

Prior studies on algorithmic trading (AT) have mostly focused on a single exchange. The authors use a public dataset provided by the Securities and Exchange Commission (SEC) covering all major U.S. exchanges to study the impact of AT and its fragmentation on market liquidity. Using a proxy of AT...

Algorithmic traders acknowledge that their models are incorrectly specified, thus we allow for ambiguity in their choices to make their models robust to misspecification in: (i) the arrival rate of market orders (MOs), (ii) the fill probability of limit orders, and (iii) the dynamics of the...

We assume that the drift in the returns of asset prices consists of an idiosyncratic component and a common component given by a co-integration factor. We analyze the optimal investment strategy for an agent who maximizes expected utility of wealth by dynamically trading in these assets. The...

This Article argues that the rise of algorithmic trading undermines efficient capital allocation in securities markets. It is a bedrock assumption in theory that securities prices reveal how effectively public companies utilize capital. This conventional wisdom rests on the straightforward...