scholarly journals Market-neutral trading with fuzzy inference, a new method for the pairs trading strategy

2019 ◽  
Vol 30 (4) ◽  
pp. 411-421
Author(s):  
Mehmet Bayram ◽  
Muzaffer Akat
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Fuzzy Inference ◽  
Trading Strategy ◽  
Pairs Trading ◽  
Inference Model ◽  
Relative Pricing ◽  
Arbitrage Opportunities ◽  
Human Decision ◽  
Arbitrage Strategy

Financial pricing and prediction of stock markets is a specific and relatively narrow field, which have been mainly explored by mathematicians, economists and financial engineers. Prediction with the purpose of making profits in a martingale domain is a hard task. Pairs trading, a market neutral arbitrage strategy, attempts to resolve the drawback of unpredictability and yield market independent returns using relative pricing idea. If two securities have similar characteristics, so should their prices. Deviation from the acceptable similarity range in prices is considered an anomaly, and whenever noticed, trading is executed assuming the anomaly will correct itself.This work proposes a fuzzy inference model for the market-neutral pairs trading strategy. Fuzzy logic lets mimicking human decision-making in a complex trading environment and taking advantage of arbitrage opportunities that the crisp models may miss to acquire for the trade decision-making. Spread between two co-integrated stocks and volatility of the spread is used as decision-making inputs. Spread is a measure of the distance between two stocks and volatility is an indicator of how soon the spread would disappear. We conclude that fuzzy engine contributes to the profitability and efficiency of pairs trading type of strategies.

scholarly journals Factory Location Decision Making Based on the FUZZY Inference Model

2019 ◽  
Vol 7 (10) ◽  
pp. 968-978
Author(s):  
Alexandre Vieira de Oliveira ◽  
David Barbosa de Alencar ◽  
Alexandra Priscilla Tregue Costa ◽  
Manoel Henrique Reis Nascimento
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Case Studies ◽  
Fuzzy Inference ◽  
Location Decision ◽  
Production Engineering ◽  
Inference Model ◽  
The Subject

This paper introduces the concept of fuzzy logic, some terms used in this kind of logic, and uses it to evaluate and choose where to deploy factories and other enterprises. In addition, a model is made using the InFuzzy program to evaluate a choice of a location within the Manaus Industrial Pole - PIM, using objective and subjective criteria within the fuzzy logic. This article aims to present the fuzzy logic in the context of production engineering, select the parameters that define the best location, develop models that represent the subject in the study and verify the applicability by simulating other case studies and comparing results.

scholarly journals Aplikasi Pengambilan Keputusan dengan Metode Tsukamoto pada Penentuan Tingkat Kepuasan pelanggan

CAUCHY ◽  
2015 ◽  
Vol 4 (1) ◽  
pp. 10 ◽  
Author(s):  
Venny Riana Riana Agustin ◽  
Wahyu Henky Irawan
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Fuzzy Inference ◽  
Weighted Average ◽  
Fuzzy Rules ◽  
Quality Of Services ◽  
Inference System ◽  
A Value ◽  
Fuzzy Logic Analysis

Tsukamoto method is one method of fuzzy inference system on fuzzy logic for decision making. Steps of the decision making in this method, namely fuzzyfication (process changing the input into kabur), the establishment of fuzzy rules, fuzzy logic analysis, defuzzyfication (affirmation), as well as the conclusion and interpretation of the results. The results from this research are steps of the decision making in Tsukamoto method, namely fuzzyfication (process changing the input into kabur), the establishment of fuzzy rules by the general form IF a is A THEN B is B, fuzzy logic analysis to get alpha in every rule, defuzzyfication (affirmation) by weighted average method, as well as the conclusion and interpretation of the results. On customers at the case, in value of 16 the quality of services, the value of 17 the quality of goods, and value of 16 a price, a value of the results is 45,29063 and the level is low satisfaction

Recent Advancement in Fuzzy System

2014 ◽  
pp. 158-168
Author(s):  
İ. Burhan Türkşen ◽  
İbrahim Özkan
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Interdisciplinary Research ◽  
Decision Process ◽  
Fuzzy System ◽  
Research Field ◽  
Decision Under Uncertainty ◽  
Recent Advancement ◽  
Human Decision

Decision under uncertainty is an active interdisciplinary research field. A decision process is generally identified as the action of choosing an alternative that best suites our needs. This process generally includes several areas of research including but not limited to Economics, Psychology, Philosophy, Mathematics, Statistics, etc. In this chapter the authors attempt to create a framework for uncertainties which surrounds the environment where human decision making takes place. For this purpose, the authors discuss how one ought to handle uncertainties within Fuzzy Logic. Furthermore, they present recent advances in Type 2 fuzzy system studies.

A Fuzzy Logic-Based Approach for Supporting Decision-Making Process in B2C Electronic Commerce Transaction

2011 ◽  
pp. 1416-1429
Author(s):  
Fahim Akhter ◽  
Zakaria Maamar ◽  
Dave Hobbs
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Electronic Commerce ◽  
Decision Process ◽  
Human Reasoning ◽  
Critical Factors ◽  
Human Decision Process ◽  
Human Decision ◽  
Business To Consumer ◽  
B2c Electronic Commerce

The purpose of this article is to present an application of fuzzy logic to human reasoning about electronic commerce (e-commerce) transactions. This article uncovers some of the hidden relationships between critical factors such as security, familiarity, design, and competitiveness. We analyze the effect of these factors on human decision process and how they affect the Business-to-Consumer (B2C) outcome when they are used collectively. This research provides a toolset for B2C vendors to access and evaluate a user’s transaction decision process and also an assisted reasoning tool for the online user.

scholarly journals Regimes of Expectations: An Active Inference Model of Social Conformity and Human Decision Making

2019 ◽  
Vol 10 ◽  
Author(s):  
Axel Constant ◽  
Maxwell J. D. Ramstead ◽  
Samuel P. L. Veissière ◽  
Karl Friston
Keyword(s):  
Decision Making ◽  
Active Inference ◽  
Social Conformity ◽  
Inference Model ◽  
Human Decision

A Fuzzy Logic-Based Approach for Supporting Decision-Making Process in B2C Electronic Commerce Transaction

2009 ◽  
pp. 258-271
Author(s):  
Fahim Akhter ◽  
Zakaria Maamar ◽  
Dave Hobbs
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Electronic Commerce ◽  
Decision Process ◽  
Human Reasoning ◽  
Critical Factors ◽  
Human Decision Process ◽  
Human Decision ◽  
Business To Consumer ◽  
B2c Electronic Commerce

The purpose of this article is to present an application of fuzzy logic to human reasoning about electronic commerce (e-commerce) transactions. This article uncovers some of the hidden relationships between critical factors such as security, familiarity, design, and competitiveness. We analyze the effect of these factors on human decision process and how they affect the Business- to-Consumer (B2C) outcome when they are used collectively. This research provides a toolset for B2C vendors to access and evaluate a user’s transaction decision process and also an assisted reasoning tool for the online user.

scholarly journals Crop Recommender System for the Farmers using Mamdani Fuzzy Inference Model

2018 ◽  
Vol 7 (4.15) ◽  
pp. 277 ◽  
Author(s):  
Madhusree Kuanr ◽  
Bikram Kesari Rath ◽  
Sachi Nandan Mohanty
Keyword(s):  
Fuzzy Logic ◽  
Recommender Systems ◽  
Similarity Measure ◽  
Recommender System ◽  
Fuzzy Inference ◽  
Weather Condition ◽  
Cosine Similarity ◽  
Inference Model ◽  
Large Pool ◽  
Cosine Similarity Measure

Recommender systems provide suggestions to the users for choosing particular items from a large pool of items. The purpose of this study is to design a collaborative recommender system for the farmers for recommending giving prior idea regarding a crop which is suitable according to the location of the farmer based on weather condition of the previous months. The proposed system also recommends other seeds, pesticides and instruments according to the preferences in farming and location of the farmers while purchasing the seeds through online. It uses cosine similarity measure to find the similar user according the location of the farmer and fuzzy logic for predicting the yield of rice crop for Kharif season in state Odisha, India. The proposed system is implemented in Mamdani Fuzzy Inference model. The results reveal that it provides prior idea regarding a crop before sowing of seeds.  

scholarly journals Evaluation of dynamic cointegration-based pairs trading strategy in the cryptocurrency market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Masood Tadi ◽  
Irina Kortchemski
Keyword(s):  
Trading Strategy ◽  
Significant Finding ◽  
Pairs Trading ◽  
Content Type ◽  
Arbitrage Opportunities ◽  
Cointegration Tests ◽  
Look Back ◽  
Trading Period ◽  
Asset Selection ◽  
Binned Data

Purpose This paper aims to demonstrate a dynamic cointegration-based pairs trading strategy, including an optimal look-back window framework in the cryptocurrency market and evaluate its return and risk by applying three different scenarios. Design/methodology/approach This study uses the Engle-Granger methodology, the Kapetanios-Snell-Shin test and the Johansen test as cointegration tests in different scenarios. This study calibrates the mean-reversion speed of the Ornstein-Uhlenbeck process to obtain the half-life used for the asset selection phase and look-back window estimation. Findings By considering the main limitations in the market microstructure, the strategy of this paper exceeds the naive buy-and-hold approach in the Bitmex exchange. Another significant finding is that this study implements a numerous collection of cryptocurrency coins to formulate the model’s spread, which improves the risk-adjusted profitability of the pairs trading strategy. Besides, the strategy’s maximum drawdown level is reasonably low, which makes it useful to be deployed. The results also indicate that a class of coins has better potential arbitrage opportunities than others. Originality/value This research has some noticeable advantages, making it stand out from similar studies in the cryptocurrency market. First is the accuracy of data in which minute-binned data create the signals in the formation period. Besides, to backtest the strategy during the trading period, this study simulates the trading signals using best bid/ask quotes and market trades. This study exclusively takes the order execution into account when the asset size is already available at its quoted price (with one or more period gaps after signal generation). This action makes the backtesting much more realistic.

scholarly journals A Review: Artificial Intelligent Approach for Enhancing Adaptability in an Adaptive E-Learning Environment

2021 ◽  
Vol 10 (4) ◽  
pp. 37-42
Author(s):  
M.P.L. Perera
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Decision Making ◽  
Fuzzy Logic ◽  
Artificial Intelligent ◽  
Human Decision ◽  
Decision Making Processes ◽  
E Learning ◽  
Intelligent Approach ◽  
Learning Frameworks

Adaptive e-learning the aim is to fill the gap between the pupil and the educator by discussing the needs and skills of individual learners. Artificial intelligence strategies that have the potential to simulate human decision-making processes are important around adaptive e-Learning. This paper explores the Artificial techniques; Fuzzy Logic, Neural Networks, Bayesian Networks and Genetic Algorithms, highlighting their contributions to the notion of the adaptability in the sense of Adaptive E-learning. The implementation of Artificial Neural Networks to resolve problems in the current Adaptive e-learning frameworks have been established.

scholarly journals Floating Car Data and Fuzzy Logic for classifying congestion indexes in the city of Shanghai

2019 ◽  
Vol 2 ◽  
pp. 1-7
Author(s):  
Maja Kalinic ◽  
Jukka M. Krisp
Keyword(s):  
Fuzzy Logic ◽  
Traffic Congestion ◽  
Fuzzy Inference ◽  
Inference Model ◽  
Floating Car Data ◽  
The Individual ◽  
The City

<p><strong>Abstract.</strong> In this paper, we use Floating Car Data from the city of Shanghai and Fuzzy Inference model to detect congestion indexes throughout the city. We aim to investigate to which extent traffic congestion is severe during afternoon rush hour. Additionally, we compare our results to the ones obtained by calculating congestion indexes on conventional way. Although we do not argue that our model is the best measure of congestion, it does allow the mechanism to combine different measures and to incorporate the uncertainty in the individual measures so that the compound picture of congestion can be reproduced.</p>

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