The paper studies arbitrage opportunities and possible speculative opportunities for diffusion mean-reverting market models. It is shown that the Novikov condition is satisfied for any time interval and for any set of parameters. It is non-trivial because the appreciation rate has Gaussian distribution converging to a stationary limit. It follows that the mean-reverting model is arbitrage-free for any finite time interval. Further, it is shown that this model still allows some speculative opportunities: a gain for a wide enough set of expected utilities can be achieved for a strategy that does not require any hypothesis on market parameters and does not use estimation of these parameters.Diffusion market, mean-reverting model, arbitrage, te...
Statistical analysis on various stocks reveals long range dependence behaviour of the stock prices t...
This article introduces the concept of a statistical arbitrage opportunity (SAO). In a finite-horizo...
Which pricing kernel restrictions are needed to make low dimensional Markov models consistent with g...
The paper studies arbitrage opportunities and possible speculative opportunities for diffusion mean-...
In this article we study discrete time mean-reverting market models. We show that certain choices of...
Mean reversion is a feature largely recognized for the price processes of many financial securities ...
In this paper we consider a general class of diffusion-based models and show that, even in the absen...
Market making refers broadly to trading strategies that seek to profit by providing liquidity to oth...
This paper focuses on mean reversion on international stock markets and explores whether this empiri...
We consider a model in which any investment opportunity is described in terms of cash flows. We don'...
We consider a market in which traders arrive at random times, with random private values for the sin...
Stock prices are well known to exhibit behaviors that are difficult to model mathematically. Individ...
This thesis analyzes models of financial markets that incorporate the possibility of arbitrage oppor...
This thesis examines the predictability of asset prices for an Australian\ud investor. Evidence supp...
grantor: University of TorontoThis dissertation is a combination of three chapters on thre...
Statistical analysis on various stocks reveals long range dependence behaviour of the stock prices t...
This article introduces the concept of a statistical arbitrage opportunity (SAO). In a finite-horizo...
Which pricing kernel restrictions are needed to make low dimensional Markov models consistent with g...
The paper studies arbitrage opportunities and possible speculative opportunities for diffusion mean-...
In this article we study discrete time mean-reverting market models. We show that certain choices of...
Mean reversion is a feature largely recognized for the price processes of many financial securities ...
In this paper we consider a general class of diffusion-based models and show that, even in the absen...
Market making refers broadly to trading strategies that seek to profit by providing liquidity to oth...
This paper focuses on mean reversion on international stock markets and explores whether this empiri...
We consider a model in which any investment opportunity is described in terms of cash flows. We don'...
We consider a market in which traders arrive at random times, with random private values for the sin...
Stock prices are well known to exhibit behaviors that are difficult to model mathematically. Individ...
This thesis analyzes models of financial markets that incorporate the possibility of arbitrage oppor...
This thesis examines the predictability of asset prices for an Australian\ud investor. Evidence supp...
grantor: University of TorontoThis dissertation is a combination of three chapters on thre...
Statistical analysis on various stocks reveals long range dependence behaviour of the stock prices t...
This article introduces the concept of a statistical arbitrage opportunity (SAO). In a finite-horizo...
Which pricing kernel restrictions are needed to make low dimensional Markov models consistent with g...