Investors are becoming more sensitive about returns and losses, especially when the investments are exposed to downside risk potential in the financial markets. Despite the computational intensity of the downside risk measures, they are very widely applied to construct a portfolio and evaluate...

This paper proposes a novel approach to the portfolio management using an AutoEncoder.In particular, the features learned by an AutoEncoder with ReLU are directly exploited to the portfolio construction.Since the AutoEncoder extracts the characteristics of the data through the non-linear...

Classical asset allocation methods have assumed that the distribution of asset returns is smooth, well behaved with stable statistical moments over time. The distribution is assumed to have constant moments with e.g., Gaussian distribution that can be conveniently parameterised by the first two...

We address how value relevance of accounting information evolved as the new economy developed. Prior research concludes accounting information—primarily earnings—has lost relevance. We consider more accounting amounts and find no decline in combined value relevance from 1962 to 2014. We...

Financial advisors typically recommend that a long-term investor should hold a higher percentage of his wealth in stocks than a short-term investor. However, part of the academic literature disagrees with this advice. We use a spatial dominance test which is suited for comparing alternative...

This paper develops a new estimation procedure for characteristic-based factor models of security returns. We treat the factor model as a weighted additive nonparametric regression model, with the factor returns serving as time-varying weights, and a set of univariate nonparametric functions...

Purpose: This article deals with the retail investors' decision-making under risk, firstly addressing several theories of decision-making under risk. Following this theoretical framework, an analysis on investment strategies on the Croatian capital market has been conducted....

We introduce a novel application of support vector machines (SVM), an important machine learning algorithm, to determine the beginning and end of recessions in real time. Nowcasting, forecasting a condition in the present time because the full information will not be available until later, is...

Research study is a comparative study of the returns of the two mutual funds which are close ended and open ended mutual fund, quarterly data of Net Asset Values NAV of both the funds from 2008-2012 (inclusive) was taken and the return on those NAVs was calculated through natural log (LN)...