Algo-Trading using Statistical Learning and Optimizing Sharpe Ratio and Drawdown

Portfolio Benchmarking under Drawdown Constraint and Stochastic Sharpe Ratio

We consider an investor who seeks to maximize her expected utility derived from her terminal wealth relative to the maximum wealth achieved over a fixed time horizon, and under a portfolio drawdown constraint, in a market with local stochastic volatility (LSV). The newly proposed investment objective paradigm also allows the investor to set portfolio benchmark targets. In the absence of closed-...

An Algorithm for Trading and Portfolio Management Using Q-learning and Sharpe Ratio Maximization

A trading and portfolio management system called QSR is proposed. It uses Q-learning and Sharpe ratio maximization algorithm. We use absolute proot and relative risk-adjusted proot as performance function to train the system respectively, and employ a committee of two networks to do the testing. The new proposed algorithm makes use of the advantages of both parts and can be used in a more gener...

Nonlinear Trading Models Through Sharpe Ratio Maximization

While many trading strategies are based on price prediction, traders in financial markets are typically interested in optimizing risk-adjusted performance such as the Sharpe Ratio, rather than the price predictions themselves. This paper introduces an approach which generates a nonlinear strategy that explicitly maximizes the Sharpe Ratio. It is expressed as a neural network model whose output ...

The Sharpe Ratio, Range and Maximal Drawdown of a Brownian Motion

Maximum Drawdown and Directional Trading

Abstract In this paper, we introduce new techniques how to control the maximum drawdown (MDD). One can view the maximum drawdown as a contingent claim, and price and hedge it accordingly as a derivative contract. Trading drawdown contracts or replicating them by hedging would directly address the concerns of portfolio managers who would like to insure the market drops. Similar contracts can be ...