activity
20172022
most citedOn Drawdown-Modulated Feedback Control in Stock Trading

19 citations · 62 across the 5 of their papers we have counts for

collaborators

9 papers

math.OC20225 cited

On Robustness of Double Linear Trading with Transaction Costs

Chung-Han Hsieh

A trading system is said to be {robust} if it generates a robust return regardless of market direction. To this end, a consistently positive expected trading gain is often used as…

math.OC2020

On Feedback Control in Kelly Betting: An Approximation Approach

Chung-Han Hsieh

In this paper, we consider a simple discrete-time optimal betting problem using the celebrated Kelly criterion, which calls for maximization of the expected logarithmic growth of w…

math.OC20206 cited

Necessary and Sufficient Conditions for Frequency-Based Kelly Optimal Portfolio

Chung-Han Hsieh

In this paper, we consider a discrete-time portfolio with assets optimization problem which includes the rebalancing~frequency as an additional parameter in the maximiza…

math.OC2019

The Impact of Execution Delay on Kelly-Based Stock Trading: High-Frequency Versus Buy and Hold

Chung-Han Hsieh, B. Ross Barmish, John A. Gubner

Stock trading based on Kelly's celebrated Expected Logarithmic Growth (ELG) criterion, a well-known prescription for optimal resource allocation, has received considerable attentio…

math.OC2019

On Positive Solutions of a Delay Equation Arising When Trading in Financial Markets

Chung-Han Hsieh, B. Ross Barmish, John A. Gubner

We consider a discrete-time, linear state equation with delay which arises as a model for a trader's account value when buying and selling a risky asset in a financial market. The…

q-fin.PM2018

Rebalancing Frequency Considerations for Kelly-Optimal Stock Portfolios in a Control-Theoretic Framework

Chung-Han Hsieh, John A. Gubner, B. Ross Barmish

In this paper, motivated by the celebrated work of Kelly, we consider the problem of portfolio weight selection to maximize expected logarithmic growth. Going beyond existing liter…