Second order Stochastic Dominance (SSD) has a well recognised importance in portfolio selection, since it provides a natural interpretation of the theory of risk-averse investor behaviour. Recently, SSD-based models of portfolio choice have been proposed; these assume that a reference distribution...

Robust optimization is a tractable alternative to stochastic programming particularly suited for problems in which parameter values are unknown, variable, and their distributions are uncertain. We evaluate the cost of robustness of the robust counterpart to the maximum return portfolio...

Recently considerable attention has been given to downside risk control in the context of portfolio choice; see Sortino and Satchell (2005). We propose an integrated model for portfolio choice in which downside risk is considered explicitly at the stage of the scenario generation which describes...

This paper considers long-short portfolio optimization in the presence of two risk measures: variance and Conditional Value at Risk (CVaR) and asset choice constraints of (i) buy, sell and holding thresholds (ii) cardinality restrictions on the number of stocks to be held in the portfolio. The...

The paper aims to illustrate that the lack of a sharp distinction between grammatical categories causes certain verbal structures to oscillate between them. During a three-phase evolution cycle the meaning of these constructions suffers important changes due to the semantic shifts they undergo....

Computer trading in financial markets is a rapidly developing field with a growing number of applications. Automated analysis of news and computation of market sentiment is a related applied research topic which impinges on the methods and models deployed in the former. In this chapter we have...

We investigate how “news sentiment” in general and the “impact of news” in particular can be utilized in designing equity trading strategies. News is an event that moves the market in a small way or a big way. We have introduced a derived measure of news impact score which takes into...

Multifactor models are often used as a tool to describe equity portfolio risk. Naturally, risk is dependent on the market environment and investor sentiment. Traditional factor models fail to update quickly as market conditions change. It is desirable that the risk model updates to incorporate...

The field of natural language processing (NLP) has evolved significantly in recent years. In this chapter we consider two leading and well-established methodologies, namely, those due to Loughran McDonald, and FinBERT. We then contrast our approach to these two approaches and compare our...