In this thesis we will use Random Forests to define a trading strategy. Using this powerful machine learning technique, we will try to predict the daily price changes of financial products that move similarly over the long term, so-called cointegrated pairs. We propose a way to adjust our portfolio based on these prediction, while limiting our risk. Firstly, we test our strategy on data generat...

Eling and Schuhmacher (2007) compared the Sharpe ratio with other performance measures and found virtually identical rank ordering using hedge fund data. They conclude that the choice of performance measure has no critical influence on fund evaluation and that the Sharpe ratio is generally adequate for analyzing hedge funds. Nevertheless, their analysis does not include the class of tailor-made...

In climatology, spatial representativeness can be measured as the degree to which an instrumental temperature record resolves the climatic variability across an area. Some station records may disproportionately resolve characteristics of their immediate surroundings and, therefore, have less utility in representing climate (or weather) over larger spatial scales. To evaluate spatial representat...

We propose to train trading systems and portfolios by optimizing objective functions that directly measure trading and investment performance. Rather than basing a trading system on forecasts or training via a supervised learning algorithm using labelled trading data, we train our systems using recurrent reinforcement learning (RRL) algorithms. The performance functions that we consider for rei...

Main academic criticism on the Sharpe ratio concerns its lack in incorporating skewness in performance evaluation. In this note we rewrite the classical Sharpe ratio for skew normal distributions. This new skew-normal Shape ratio consistently moves with skewness and no distorted information on performance is provided. An empirical investigation illustrates skew-normality of mutual and hedge fun...

Stocks market performance measurement has long been regarded as the most interesting part in investment. Many new methods emerge every year but most of these are rooted from Modern Portfolio theory by Harry Markowitz. In this research paper, we have used the efficient frontier from modern portfolio theory to determine the best stocks performance in KLCI index from 2006-2010. The data is compare...

In the present work we address the problem of evaluating the historical performance of a trading strategy or a certain portfolio of assets. Common indicators such as the Sharpe ratio and the risk adjusted return have significant drawbacks. In particular, they are global indices, that is they do not preserve any local information about the performance dynamics either in time or for a particular ...

Diversified models for portfolio selection based on uncertain semivariance Lin Chen, Jin Peng, Bo Zhang & Isnaini Rosyida To cite this article: Lin Chen, Jin Peng, Bo Zhang & Isnaini Rosyida (2016): Diversified models for portfolio selection based on uncertain semivariance, International Journal of Systems Science, DOI: 10.1080/00207721.2016.1206985 To link to this article: http://dx.doi.org/10...

To enhance the vegetation signal in remotely sensed data and provide an approximate measure of live green vegetation, a number of spectral vegetation indices have been developed to estimate biophysical parameters of vegetation. The sensitivity of the normalized difference vegetation index (NDVI) to the soil background and atmospheric effects has generated an increasing interest in the developme...