Title:

Stochastic modeling and methods for portfolio management in cointegrated markets

In this thesis we study the utility maximization problem for assets whose prices are cointegrated, which arises from the investment practice of convergence trading and its special forms, pairs trading and spread trading. The major theme in the first two chapters of the thesis, is to investigate the assumption of marketneutrality of the optimal convergence trading strategies, which is a ubiquitous assumption taken by practitioners and academics alike. This assumption lacks a theoretical justification and, to the best of our knowledge, the only relevant study is Liu and Timmermann (2013) which implies that the optimal convergence strategies are, in general, not marketneutral. We start by considering a minimalistic pairstrading scenario with two cointegrated stocks and solve the Merton investment problem with power and logarithmic utilities. We pay special attention to when/if the stochastic control problem is wellposed, which is overlooked in the study done by Liu and Timmermann (2013). In particular, we show that the problem is illposed if and only if the agent’s riskaversion is less than a constant which is an explicit function of the market parameters. This condition, in turn, yields the necessary and sufficient condition for wellposedness of the Merton problem for all possible values of agent’s riskaversion. The resulting wellposedness condition is surprisingly strict and, in particular, is equivalent to assuming the optimal investment strategy in the stocks to be marketneutral. Furthermore, it is shown that the wellposedness condition is equivalent to applying Novikov’s condition to the marketprice of risk, which is a ubiquitous sufficient condition for imposing absence of arbitrage. To the best of our knowledge, these are the only theoretical results for supporting the assumption of marketneutrality of convergence trading strategies. We then generalise the results to the more realistic setting of multiple cointegrated assets, assuming risk factors that effects the asset returns, and general utility functions for investor’s preference. In the process of generalising the bivariate results, we also obtained some wellposedness conditions for matrix Riccati differential equations which are, to the best of our knowledge, new. In the last chapter, we set up and justify a Merton problem that is related to spreadtrading with two futures assets and assuming proportional transaction costs. The model possesses three characteristics whose combination makes it different from the existing literature on proportional transaction costs: 1) finite time horizon, 2) Multiple risky assets 3) stochastic opportunity set. We introduce the HJB equation and provide rigorous arguments showing that the corresponding value function is the viscosity solution of the HJB equation. We end the chapter by devising a numerical scheme, based on the penalty method of Forsyth and Vetzal (2002), to approximate the viscosity solution of the HJB equation.
