Abstract We analyze the predictive power of technical analysis with a novel data set based on news sentiment that allows to systematically examine indicators over an extensive time period. do not find much statistically significant relationships examined and future asset returns, we almost any alphas in trading strategies sentiment. evidence for contrarian‐based hypothesis: past market returns ...

In many applications it is necessary to use a simple and therefore highly misspecified econometric model as the basis for decision-making. We propose an approach to developing a possibly misspecified econometric model that will be used as the beliefs of an objective expected utility maximiser. A discrepancy between model and ‘truth’ is introduced that is interpretable as a measure of the model’...

The aim of this research is to analyse the different results that can be achieved using Support Vector Machines (SVM) to forecast the weekly change movement of the different simulated markets. The different simulated markets are developed by a GARCH model based on the S&P 500. These simulated markets are grouped by a main parameter: high volatility, bearish trend, bullish trend and low volatili...

In many applications it is necessary to use a simple and therefore highly misspecified econometric model as the basis for decision-making. We propose an approach to developing a possibly misspecified econometric model that will be used as the beliefs of an objective expected utility maximiser. A discrepancy between model and ‘truth’ is introduced that is interpretable as a measure of the model’...

Generating asset-specific trading signals based on the financial conditions of assets is one challenging problems in automated trading. Various asset rules are proposed experimentally different technical analysis techniques. However, these kind strategies profitable, extracting new from vast historical data to increase total return and decrease risk portfolios difficult for human experts. Recen...

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