Alessio Emanuele Biondo

Are Random Trading Strategies More Successful than Technical Ones

In this paper we explore the specific role of randomness in financial markets, inspired by the beneficial role of noise in many physical systems and in previous applications to complex socio-economic systems. After a short introduction, we study the performance of some of the most used trading strategies in predicting the dynamics of financial markets for different international stock exchange indexes, with the goal of comparing them to the performance of a completely random strategy. In this respect, historical data for FTSE-UK, FTSE-MIB, DAX, and S & P500 indexes are taken into account for a period of about 15–20 years (since their creation until today).

Reducing financial avalanches by random investments.

Building on similarities between earthquakes and extreme financial events, we use a self-organized criticality-generating model to study herding and avalanche dynamics in financial markets. We consider a community of interacting investors, distributed in a small-world network, who bet on the bullish (increasing) or bearish (decreasing) behavior of the market which has been specified according to the S&P 500 historical time series. Remarkably, we find that the size of herding-related avalanches in the community can be strongly reduced by the presence of a relatively small percentage of traders, randomly distributed inside the network, who adopt a random investment strategy. Our findings suggest a promising strategy to limit the size of financial bubbles and crashes. We also obtain that the resulting wealth distribution of all traders corresponds to the well-known Pareto power law, while that of random traders is exponential. In other words, for technical traders, the risk of losses is much greater than the probability of gains compared to those of random traders.

The Beneficial Role of Random Strategies in Social and Financial Systems

In this paper we focus on the beneficial role of random strategies in social sciences by means of simple mathematical and computational models. We briefly review recent results obtained by two of us in previous contributions for the case of the Peter principle and the efficiency of a Parliament. Then, we develop a new application of random strategies to the case of financial trading and discuss in detail our findings about forecasts of markets dynamics.

Modelling Financial Markets by Self-Organized Criticality

We present a financial market model, characterized by self-organized criticality, that is able to generate endogenously a realistic price dynamics and to reproduce well-known stylized facts. We consider a community of heterogeneous traders, composed by chartists and fundamentalists, and focus on the role of informative pressure on market participants, showing how the spreading of information, based on a realistic imitative behavior, drives contagion and causes market fragility. In this model imitation is not intended as a change in the agents group of origin, but is referred only to the price formation process. We introduce in the community also a variable number of random traders in order to study their possible beneficial role in stabilizing the market, as found in other studies. Finally, we also suggest some counterintuitive policy strategies able to dampen fluctuations by means of a partial reduction of information.

Micro and macro benefits of random investments in financial markets

In this paper, making use of recent statistical physics techniques and models, we address the specific role of randomness in financial markets, both at the micro and the macro level. In particular, we review some recent results obtained about the effectiveness of random strategies of investment, compared with some of the most used trading strategies for forecasting the behaviour of real financial indexes. We also push forward our analysis by means of a self-organised criticality model, able to simulate financial avalanches in trading communities with different network topologies, where a Pareto-like power law behaviour of wealth spontaneously emerges. In this context, we present new findings and suggestions for policies based on the effects that random strategies can have in terms of reduction of dangerous financial extreme events, i.e. bubbles and crashes.

A multilayer approach for price dynamics in financial markets

Abstract We introduce a new Self-Organized Criticality (SOC) model for simulating price evolution in an artificial financial market, based on a multilayer network of traders. The model also implements, in a quite realistic way with respect to previous studies, the order book dynamics, by considering two assets with variable fundamental prices. Fat tails in the probability distributions of normalized returns are observed, together with other features of real financial markets.

Order book microstructure and policies for financial stability

Purpose The purpose of this paper is twofold:- first, to introduce an innovative model of financial order book, less simplified than the existing literature and still able to replicate all statistical features of true markets;- second, to simulate realistically the effects of policies aimed to reduce the instability of financial markets. Design/methodology/approach The paper is based on an agent based model and the applied methodology is the computational simulation. Findings The policy-maker can actively reduce the instability of financial market by means of policies aimed to:- increase the heterogeneity of investors, both in terms of the behavioral attitude for market participation and of the differentiation of opinions;- favour investors who show insensibility with regards to market information;- limit the allowed number of counterparts for any market order;- reduce the time validity of orders;- maintain exibility and efficient bargaining, reduce transaction costs, and avoid Tobin taxes. Research limit...

Perfect Information vs Random Investigation: Safety Guidelines for a Consumer in the Jungle of Product Differentiation

We present a graph-theoretic model of consumer choice, where final decisions are shown to be influenced by information and knowledge, in the form of individual awareness, discriminating ability, and perception of market structure. Building upon the distance-based Hotelling’s differentiation idea, we describe the behavioral experience of several prototypes of consumers, who walk a hypothetical cognitive path in an attempt to maximize their satisfaction. Our simulations show that even consumers endowed with a small amount of information and knowledge may reach a very high level of utility. On the other hand, complete ignorance negatively affects the whole consumption process. In addition, rather unexpectedly, a random walk on the graph reveals to be a winning strategy, below a minimal threshold of information and knowledge.

Modelling surveys effects in political competitions

Abstract In this paper the impact of news media and surveys on electoral campaigns for political competitions is studied by means of an agent-based model, showing the dynamics of voters’ opinions before elections. A small community of people, connected among them as a realistic social network, is exposed to the effects of periodic surveys, in order to analyze how the electoral consensus varies time, in several scenarios of a two-parties configuration. Results of performed simulations provide support to the idea that surveys and news may play a relevant role in driving political orientation.

Disclosure of sexual orientation in the USA and its consequences in the workplace

Purpose Discrimination and hostility in the workplace prevents homosexual workers from performing their core functions on the job. Moreover, it introduces unnecessary costs by increasing absenteeism, lowering productivity, and fostering a less motivated, less entrepreneurial, and less committed workforce. By means of an agent-based model, the authors simulated the effects on unemployment rates of an increasing of sexual orientation (SO) disclosure in the workplaces. The authors tested the effects on workers’ utility, level of job satisfaction and segregation. The results show a complessive improvement of the firms’ performances and a better job satisfaction for undeclared and homosexual workers and employers. With a homosexual employer, the authors can observe an increasing homosexual utility and firm profit, with a low decrease in undeclared utility. Instead, with an undeclared employer, the firm’s profit decreases but the total effect is positive. The paper aims to discuss these issues. Design/methodology/approach An agent-based model applied. Findings Effects of sexual disclosure on unemployment rates, job satisfaction, and job segregation. Originality/value The economic literature on SO and job satisfaction is very meager.