Trading Cryptocurrencies Using Second Order Stochastic Dominance

This research is the first attempt to customize a trading system that is based on second order stochastic dominance (SSD) to five known cryptocurrencies’ daily data: Bitcoin, Ethereum, XRP, Binance Coin, and Cardano. Results show that our system can predict price trends of cryptocurrencies, trade them profitably, and in most cases outperform the buy and hold (B&H) simple strategy. Our system’s best performance was achieved trading XRP, Binance Coin, Ethereum, and Bitcoin. Although our system has also generated a positive net profit (NP) for Cardano, it failed to outperform the B&H strategy. For all currencies, the system better predicted long trends than short trends.

Investigation of the Calendar Effect

This chapter aims to examine calendar anomaly in selected sample countries by using second-order stochastic dominance (SSD) approach. Day-of-the-week and month-of-the-year effects are analysed for a group of 5 developed and 5 developing country indexes to estimate efficient (inefficient) weekdays and months for the period between 1988 and 2016. Then, back-testing procedure is applied for each sample country to compare performance of index returns for 2017-2019 with the strategy arisen by estimation results. Findings suggest that Monday and Friday returns are inefficient and efficient respectively in all developing countries where different results obtained for developed ones. In monthly analysis, December returns found efficient in 8 indexes including S&P 500. However, October is inefficient for all indexes. Positive January effect seems disappeared in most cases. Back-testing results indicate that in a bearish market condition SSD strategy outperforms index returns in general for daily and monthly comparison.

Pension fund management with investment certificates and stochastic dominance

This paper considers an extension of the common asset universe of a pension fund to investment certificates. Investment certificates are a class of structured products particularly interesting for their special payoff structures and they are acquiring relevancy in the worldwide markets. In fact, some subclasses of certificates offer loss protection and show high liquidity and, thus, they can be very appreciated by pension fund managers. We consider the problem of a pension fund manager who has to implement an Asset and Liability Management model trying to achieve a long-term sustainability. Therefore, we formulate a multi-stage stochastic programming problem adopting a discrete scenario tree and a multi-objective function. We propose a technique to price highly structured products such as investment certificates on a discrete scenario tree. Finally, we solve the investment problem considering some investment certificate types both in term of payoff structure and protection level, and we test whether they are preferred or not to standard hedging contract such as put options. Moreover, we test the inclusion of first-order and second-order stochastic dominance constraints on multiple stages with respect to a benchmark portfolio. Numerical results show that the portfolio composition reacts to the inclusion of the stochastic dominance constraints, and that the optimal portfolio is efficiently able to reach several targets such as liquidity, returns, sponsor’s extraordinary contribution and funding gap.

CAPM, Dominancias Estocásticas & Diversificación

El artículo expone de forma aplicativa a la teoría de diversificación del portafolio, cuyos cimientos se trasladan a Markowitz (1952). Acorde a esto, inicialmente se expusieron a grandes rasgos las bases de Capital Asset Pricing Model (CAPM), así como de la diversificación. Además, se explican ideas como las de dominancia estocástica, de primer orden; y, dominancia estocástica, de segundo orden, que plantean una forma alternativa y previa de evaluación de las opciones de inversión. Se utilizan cuatro acciones en el presente estudio, las cuales, pertenecen a: Banco de Chile (BCH), Banco Santander (BSANTANDER), Parque Arauco (PARAUCO) y Falabella (FALABELLA); estas acciones pertenecen a la Bolsa de Comercio de Santiago, Chile. Los resultados, respecto a CAPM, muestran que la mayoría se comporta en forma similar a como lo hace el mercado; es decir, tienen un beta cercana a 1. El análisis de Dominancias no permitió establecer Dominancia Estocástica de Primer Orden, no obstante, sí Dominancia Estocástica de Segundo Orden; FALABELLA domina estocásticamente en segundo a tanto a PARAUCO como BSANTANDER. Finalmente, se encontró un portafolio óptimo compuesto por las cuatro acciones; a pesar de que se permiten ventas cortas, la composición del portafolio óptimo no muestra acciones con proporciones negativas. Esta técnica serviría muy bien para valoración de diferentes proyectos, reemplazando los rendimientos de las acciones por los de los proyectos.Palabras clave: CAPM, Diversificación, Finanzas, Markowitz, Portafolio Óptimo. ABSTRACThe article introduces the reader in applicative way to the theory of portfolio diversification, the foundations of which were transferred to Markowitz in 1952. According to this, initially they were exposed to great features the CAPM (Capital Asset Pricing Model) and diversification foundations. In addition, ideas such as the first-order stochastic dominance and the second-order stochastic dominance were explained, as one previous and alternative way of evaluating investment options. Four actions were used in this study, they all belong to: Banco de Chile (BCH), Banco Santander (BSANTANDER), Parque Arauco (PARAUCO) and Falabella (FALABELLA); These shares belong to the Santiago Stock Exchange, Chile. The results, with respect to CAPM, showed that the majority behave similarly to how does the market; that is to say, they have a beta around 1. Dominance analysis does not allow you to establish the First-Order Stochastic Dominance, however yes second-Order Stochastic Dominance; FALABELLA dominates stochastically in second order, to both PARAUCO and BSANTANDER. Finally, an optimal portfolio was found, consisting of the four stocks; Although short sales are allowed, the optimal portfolio composition does not show stocks with negative proportions. This technique would be very useful for evaluating different projects, replacing the returns of the shares for those of the projects.

Whale Optimization Algorithm for Multiconstraint Second-Order Stochastic Dominance Portfolio Optimization

In the field of asset allocation, how to balance the returns of an investment portfolio and its fluctuations is the core issue. Capital asset pricing model, arbitrage pricing theory, and Fama–French three-factor model were used to quantify the price of individual stocks and portfolios. Based on the second-order stochastic dominance rule, the higher moments of return series, the Shannon entropy, and some other actual investment constraints, we construct a multiconstraint portfolio optimization model, aiming at comprehensively weighting the returns and risk of portfolios rather than blindly maximizing its returns. Furthermore, the whale optimization algorithm based on FTSE100 index data is used to optimize the above multiconstraint portfolio optimization model, which significantly improves the rate of return of the simple diversified buy-and-hold strategy or the FTSE100 index. Furthermore, extensive experiments validate the superiority of the whale optimization algorithm over the other four swarm intelligence optimization algorithms (gray wolf optimizer, fruit fly optimization algorithm, particle swarm optimization, and firefly algorithm) through various indicators of the results, especially under harsh constraints.

Stochastic dominance relations for generalised parametric distributions obtained through composition

Investigating stochastic dominance within flexible multi-parametric families of distributions is often complicated, owing to the high number of parameters or non-closed functional forms. To simplify the problem, we use the T–X method, making it possible to obtain generalised models through the composition of cumulative distributions and quantile functions. We derive conditions for the second-order stochastic dominance and for the increasing convex order within multi-parametric families in two steps, namely: (i) breaking them down via the T–X approach and (ii) checking dominance conditions of the (more) manageable distributions composing the model. We apply our method to some special distributions and focus on the beta-generated family, which enables the comparisons of order statistics of i.i.d. samples from (possibly) different random variables.