The profitability of algorithmic trading systems based on football sentiment

2020 ◽  
Vol 42 (1) ◽  
pp. 33-46
Author(s):  
Raúl Gómez-Martínez ◽  
Camila Marqués-Bogliani ◽  
Jessica Paule-Vianez

Behavioural finance has shown that investment decisions are the result of not just rational but also emotional brain processes. On the assumption that emotions affect financial markets, it would seem likely that football results might have a measurable effect on financial markets. To test this, this study describes three algorithmic trading systems based exclusively on the results of three top European football teams (Juventus, Bayern München and Paris St Germain) opening long or short positions in the next market season of the futures market of the index of each country (MIB (Milano Italia Borsa), DAX (Deutscher Aktien Index) and CAC (Cotation Assistée en Continu). Depending on the outcome of the last game played a long position was taken after a victory and a short position after a draw or defeat. The results showed that the algorithmic systems were profitable in the case of Juventus and Bayern whereas in the case of PSG, the system was profitable, but in an inverse way. This study shows that investment strategies that take account of sports sentiment could have a profitable outcome.

Author(s):  
Violeta Todorović ◽  
Aleksandra Pešterac ◽  
Nenad Tomić

The way in which financial markets operate has substantially been changed by the development of information technology. Automation of trading systems in financial markets represents the last phase of depersonalizing activities previously done by traders. Algorithmic trading development enabled computers to determine the moment and the way of executing sales orders. Computers still do not make autonomous decisions regarding the choice of instruments to be traded or trading criteria. They implement the strategy a trader has decided on, choosing a favorable moment. This reduces the impact of human emotions on decision making and enables overcoming possible problems which arise due to neglecting or lack of concentration. High-frequency trading enables the execution of algorithmic operations at a high speed. The main goal of the paper is to determine advantages and dangers produced by algorithmic stock trading.


2020 ◽  
Vol 11 (10) ◽  
pp. 2-20 ◽  

The main objective of the study is to investigate the impact of No-Mobile-Phobia (Nomophobia) on retail investors‟ investment decisions. The relationship was further analysed by incorporating the role of Investor related Fear-of-Missing-Out (I-FoMO) which is different from traditional FOMO in Indian Financial Markets. The information asymmetry is generated by the absence of a mobile phone coupled with the fear of missing important information in financial markets used for extensive investment decisions was determined by conducting a survey method. A total of 265 retail investors were used for analysing the data and to explore this new phenomenon by Partial Least Square Structural Equational Modelling (PLS-SEM) in SmartPLS version 3.3.2. Further, Importance Performance Map Analysis (IMPA) was applied to investigate the critical factors for determining investor behaviour. The results revealed that there is a tendency to exhibit overtrading by retail investors in the state of fear of no investment information and lack of convenience due to news in smartphones. The similar phenomenon was experienced where Nomophobia leads extensively to I-FoMO which mediates the relationship of No-mobiles and investor behaviour. The study provides a new dimension to the theoretical frameworks in behavioural finance where media studies and information dissemination through smartphones to understand investor behaviour. The study not only validates NMP Questionnaire in media studies but also investigates the new scale of I-FoMOin behavioural finance to understand the aspects of fear and anxiety among human behaviour in Information Systems (IS) Research.


2018 ◽  
Vol 11 (1) ◽  
pp. 87-102
Author(s):  
Cristian Păuna

Abstract Trading and investment on financial markets are common activities today. A very high number of investors, companies, public or private funds are buying and selling every day with a single purpose: the profit. The common questions for any market participant are: when to buy, when to sell and when is better to stay away from the market risk. In order to answer all these questions, many trading strategies are used to establish the best moments to entry or to exit the trades. Due to the large price volatility, a significant part of the trades is set up automatically today by computers using algorithmic trading procedures. For this particular field, special aspects must be met in order to automate the trading process. This paper presents one of these mathematical models used in automated trading systems, a method based on the Fisher transform. A general form of this method will be presented, the functional parameters and the way to optimize them in order to reduce the risk. It will be also suggested a method to build reliable trading signals with the Fisher function in order to be automated. Three different trading signal types will be explained together with the significance of the functional parameters in the price field. A code sample will be included in this paper to prove the simplicity of this method. Real results obtained with the Fisher trading signals will be also presented, compared and analyzed in order to show how this method can be implemented in algorithmic trading.


2021 ◽  
Vol 12 (1) ◽  
pp. 60-69
Author(s):  
Hiral D Mehta ◽  
◽  
Dr. Jitesh Parmar ◽  

Behavioural finance is a new theoretical field which seeks to apply the understandings of the psychologists to recognize the behaviour of both investors and financial markets. It concentrates upon how investor is aware and acts on information to take investment decisions and that their behaviours reason them to make changed Selection about their financial decisions. Investors do not act sensibly in taking verdicts relating to investment. They have positive weaknesses like cognitive and emotional which take a predominating function in taking investment decision of individuals. They have behavioral biases in the event of taking investment decision. In this present paper researchers examines “Effect of Behvioral Biases on Investor’s Preference Regarding 80C Tax Saving Instruments in Surat City.”. Researcher has studied behavioral biases of investors investing in 80C tax saving instruments by conducting the survey with sample size of 100 investors through a wellstructured questionnaire in Surat city. The sampling method used was convenient sampling through personal survey method by contacting investors of Surat city. The purpose of this study was to find out behavioral biases of investors while investing in tax saving 80C instruments in Surat City.


2018 ◽  
Vol 10 (1) ◽  
pp. 85-110 ◽  
Author(s):  
Syed Zulfiqar Ali Shah ◽  
Maqsood Ahmad ◽  
Faisal Mahmood

Purpose This paper aims to clarify the mechanism by which heuristics influences the investment decisions of individual investors, actively trading on the Pakistan Stock Exchange (PSX), and the perceived efficiency of the market. Most studies focus on well-developed financial markets and very little is known about investors’ behaviour in less developed financial markets or emerging markets. The present study contributes to filling this gap in the literature. Design/methodology/approach Investors’ heuristic biases have been measured using a questionnaire, containing numerous items, including indicators of speculators, investment decisions and perceived market efficiency variables. The sample consists of 143 investors trading on the PSX. A convenient, purposively sampling technique was used for data collection. To examine the relationship between heuristic biases, investment decisions and perceived market efficiency, hypotheses were tested by using correlation and regression analysis. Findings The paper provides empirical insights into the relationship of heuristic biases, investment decisions and perceived market efficiency. The results suggest that heuristic biases (overconfidence, representativeness, availability and anchoring) have a markedly negative impact on investment decisions made by individual investors actively trading on the PSX and on perceived market efficiency. Research limitations/implications The primary limitation of the empirical review is the tiny size of the sample. A larger sample would have given more trustworthy results and could have empowered a more extensive scope of investigation. Practical implications The paper encourages investors to avoid relying on heuristics or their feelings when making investments. It provides awareness and understanding of heuristic biases in investment management, which could be very useful for decision makers and professionals in financial institutions, such as portfolio managers and traders in commercial banks, investment banks and mutual funds. This paper helps investors to select better investment tools and avoid repeating expensive errors, which occur due to heuristic biases. They can improve their performance by recognizing their biases and errors of judgment, to which we are all prone, resulting in a more efficient market. So, it is necessary to focus on a specific investment strategy to control “mental mistakes” by investors, due to heuristic biases. Originality/value The current study is the first of its kind, focusing on the link between heuristics, individual investment decisions and perceived market efficiency within the specific context of Pakistan.


2016 ◽  
Vol 8 (3) ◽  
pp. 205-217 ◽  
Author(s):  
Scott Pirie ◽  
Ronald King To Chan

Purpose This study aims to find out how institutional investors use momentum in making investment decisions, and whether their actions are consistent with the Financial Instability Hypothesis of Hyman Minsky. Design/methodology/approach The study discusses the findings of interviews with 25 professional investors from the Hong Kong offices of five global financial institutions. All of the participants have several years of practical experience in global and regional markets. Findings Nearly all the managers interviewed said they use momentum in making investment decisions, and they do this in ways that are consistent with the Financial Instability Hypothesis, in which markets alternate between stable and unstable states. The participants are aware they may contribute to this, but they cannot avoid doing it because of short-term constraints in the present financial system. Originality/value This study adds to our knowledge of how professional investors use momentum in their investment strategies. It complements findings of quantitative studies that show momentum strategies have been profitable in many market settings. It also adds evidence that supports the Financial Instability Hypothesis.


2016 ◽  
Vol 11 (7) ◽  
pp. 83 ◽  
Author(s):  
Asif Siddiqui ◽  
Dora Marinova ◽  
Amzad Hossain

<p>The paper analyses the differences in venture capital (VC) firms, proposes a classification of the firms and<br />empirically investigates their investment and co-investment behaviour. The VC firms are not homogeneous and beside funds they possess a diverse set of nonfinancial resources which they optimize. A classification is developed based on VC firm resources and specialization represented by organizational form and affiliation. Based on Australian market data, we classify the VC firms in three categories, namely strategic, financial and independent using resource based theory, and highlight differences. Then the firms’ specialization is related to their portfolio characteristics to identify and analyse differences and complementarities in terms of investment strategies. The influence of specialization in investment and co-investment strategies is also analysed. This study shows that specialization influences investment decisions and co-investor selection. Implications of such investment practices on resource efficiency, financial viability and transition to sustainability are also discussed.</p>


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