A hybrid stock trading system using genetic network programming and mean conditional value-at-risk

Development of an inexact risk-aversion optimization model for regional carbon constrained electricity system planning under uncertainty

“…Based on a series of analysis, it was found that the distribution of CVaR is uniformed, thus, in this paper, a is the considered equal to 0.95 [34,35]. In the model, k is a nonnegative trade-off coefficient representing the exchange rate of mean cost for risk, which is specified by decision makers according to their risk preferences, and it can be chosen as any real numbers.…”

“…where k is the weighting factor presenting the tradeoff between the expected cost and CVaR; n ± denotes the value of VaR; a is confidence level, usually it could be set as 0.90, 0.95 and 0.99 [34,35]. subject to:…”

MGP-INTACTSKY: Multitree Genetic Programming-based learning of INTerpretable and ACcurate TSK sYstems for dynamic portfolio trading

“…Furthermore, a fuzzy rule based expert system has been developed for this problem [13]. The models proposed by [10,12,13] support portfolio managers in their middle term stock evaluation and portfolio construction decisions. They used two distinct models for single stock price forecasting and evaluation and portfolio management.…”

“…The GNP model is extended to consider the risk of trading in terms of conditional value at risk [9,10]. Also, a fuzzy rule based system has been developed using an artificial evolutionary process for portfolio trading considering transaction cost and risk [11].…”

A Survey on Financial Applications of Metaheuristics

“…Their proposed method is shown to outperform a buy-and-hold strategy, and it is found that the constructed forecasts predict better the prices of small rather than large stocks. Chen and Wang [2015] combine a GA with a risk model that aims at building up portfolios. The effective risk attitude is computed taking into account not only the investor risk aversion but also the fluctuating market conditions (bull market vs. bear market).…”