Be greedy when others are fearful: Evidence from a two-decade assessment of the NDX 100 and S&P 500 indexes
This study explores the profitability of trading range breakout (TRB) trading rules and
commonly used moving average (MA) trading rules in the NDX 100 and S&P 500 indices. Its …
commonly used moving average (MA) trading rules in the NDX 100 and S&P 500 indices. Its …
The profitability of technical analysis during the COVID-19 market meltdown
C Lento, N Gradojevic - Journal of Risk and Financial Management, 2022 - mdpi.com
This article explores the profitability of technical trading rules around the COVID-19
pandemic market meltdown for the S&P 500 index, Bitcoin, Comex gold spot, crude oil WTI …
pandemic market meltdown for the S&P 500 index, Bitcoin, Comex gold spot, crude oil WTI …
Mean–variance vs trend–risk portfolio selection
In this paper, we provide an alternative trend (time)-dependent risk measure to Ruttiens'
accrued returns variability (Ruttiens in Comput Econ 41: 407–424, 2013). We propose to …
accrued returns variability (Ruttiens in Comput Econ 41: 407–424, 2013). We propose to …
Using multivariate stochastic dominance to enhance portfolio selection and warn of financial crises
N Kouaissah - The Quarterly Review of Economics and Finance, 2021 - Elsevier
In this paper, we develop a portfolio optimization methodology that significantly improves
upon conventional portfolio selection problems. In particular, we propose a two-step …
upon conventional portfolio selection problems. In particular, we propose a two-step …
Mastery of “Monthly Effects”: Big Data Insights into Contrarian Strategies for DJI 30 and NDX 100 Stocks over a Two-Decade Period
In contrast to finding better monthly performance shown in a specific month, such as the
January effect (ie, better stock price performance in January as opposed to other months) …
January effect (ie, better stock price performance in January as opposed to other months) …
Distributionally robust portfolio optimization with linearized STARR performance measure
We study the distributionally robust linearized stable tail adjusted return ratio (DRLSTARR)
portfolio optimization problem, in which the objective is to maximize the worst-case …
portfolio optimization problem, in which the objective is to maximize the worst-case …
Implementation of machine learning in -based sparse Sharpe ratio portfolio optimization: a case study on Indian stock market
Constructing the optimal portfolio by determining and selecting the best combinations of
multiple portfolios is computationally challenging due to its exponential complexity. This …
multiple portfolios is computationally challenging due to its exponential complexity. This …
Dynamic Return Scenario Generation Approach for Large-Scale Portfolio Optimisation Framework
In this paper, we propose a complex return scenario generation process that can be
incorporated into portfolio selection problems. In particular, we assume that returns follow …
incorporated into portfolio selection problems. In particular, we assume that returns follow …
Portfolio selection using multivariate semiparametric estimators and a copula PCA-based approach
N Kouaissah, S Ortobelli Lozza, I Jebabli - Computational Economics, 2022 - Springer
This paper investigates the implications for portfolio theory of using multivariate
semiparametric estimators and a copula-based approach, especially when the number of …
semiparametric estimators and a copula-based approach, especially when the number of …
Systemic risk detection using an entropy approach in portfolio selection strategy
This paper focuses on the investigation and detection of systemic risk. Such risk significantly
affects the financial markets and the banking sector, and is fundamental for macro-prudential …
affects the financial markets and the banking sector, and is fundamental for macro-prudential …