scholarly journals Predicting Futures Price And Contract Portfolios Using The ARIMA Model: A Case of Nigeria’s Bonny Light and Forcados

2020 ◽  
Vol 1 (4) ◽  
pp. 237-248
Author(s):  
Arnold Adimabua Ojugo ◽  
Rume Elizabeth Yoro
Keyword(s):  
Capital Market ◽  
Arima Model ◽  
Real Life ◽  
Optimal Solution ◽  
Supply Curve ◽  
Price Rise ◽  
Market Participants ◽  
Oil Market ◽  
Futures Price ◽  
Previous Prediction

Market prediction has been the goal of many study as investors sought traded assets since the inception of the capital market. With each asset exchanged for money, investors seek to stay ahead the market trend in the hope of amassing profits. Businesses’ growth (rise/fall) is evident upon their response to market behaviour. Thus, accurate prediction of the market often offers as its reward, enlarged financial portfolio. Market participants thus, seek to manage the risks associated with asset prices and its volatility, which can be rippled with chaos and complex tasks arising from a demand-supply curve. We seek to model the Oil market and forecast its price direction supported with empirical evidence using ARIMA model to analyze inputs in search of an optimal solution. We adopt the OPEC model to: (a) predict spot/futures-prices, (b) investigate why previous prediction was poor and price plummeted, and (c) compares value(s) from Ojugo and Yoro (2020) and Ojugo and Allenotor (2017). Results shows demand-supply curve rise (and a price rise) even though the policies and trend in real life scenario is currently experiencing a price plummet.

ANALISA PREDIKSI INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN METODE ARIMA

2020 ◽  
Vol 2 (2) ◽  
pp. 454
Author(s):  
Julkifli Purnama ◽  
Ahmad Juliana
Keyword(s):  
Capital Market ◽  
Stock Price ◽  
Time Series Data ◽  
Arima Model ◽  
Secondary Data ◽  
Actual Data ◽  
Series Data ◽  
Analysis Technique ◽  
The Right ◽  
The Capital Market

Investment in the capital market every manager needs to analyze to make decisions so that the right target to produce profits in accordance with what is expected. For that, we need a way to predict the decisions that will be taken in the future. The research objective is to find the best model and forecasting of the composite stock price index (CSPI). Data analysis technique The ARIMA Model time series data from historical data is the basis for forecasting. Secondary data is the closing price of the JCI on July 16 2018 to July 16 2019 to see how accurate the forecasting is done on the actual data at that time. The results of the study that the best Arima model is Arima 2.1.2 with an R-squared value of 0.014500, Schwarz criterion 10.83497 and Akaike info criterion of 10.77973. Results of forecasting actual data are 6394,609, dynamic forecast 6387,551 selisish -7,05799, statistics forecas 6400,653 difference of 6,043909. For investors or the public can use the ARIMA method to be able to predict or predict the capital market that will occur in the next period.

Computationally Simple and Efficient Method for Solving Real-Life Mixed Intuitionistic Fuzzy 3D Assignment Problems

2022 ◽  
Vol 14 (1) ◽  
pp. 0-0
Keyword(s):  
Assignment Problem ◽  
Graphical Representation ◽  
Real Life ◽  
Optimal Solution ◽  
Future Research ◽  
Assignment Problems ◽  
3 Dimensional ◽  
Intuitionistic Fuzzy ◽  
Comparison Results ◽  
Future Research Directions

This article addresses the 3-dimensional mixed intuitionistic fuzzy assignment problems (3D-MIFAPs). In this article, firstly, the author formulates an assignment problem (AP) and assumes the parameters are in uncertainty with hesitation. Secondly, based on the nature of the parameter the author defines various types of solid assignment problem (SAP) in uncertain environment. Thirdly, to solve 3D-MIFAP the PSK method for finding an optimal solution of fully intuitionistic fuzzy assignment problem (FIFAP) is extended by the author. Fourthly, the author presents the proofs of the proposed theorems and corollary. Fifthly, the proposed approach is illustrated with three numerical examples and the optimal objective value of 3D-MIFAP is obtained in the form of intuitionistic fuzzy number and the solution is checked with MATLAB and their coding are also given by the author. Sixthly, the author presents the comparison results and their graphical representation, merits and demerits of the proposed and existing methods and finally the author presents conclusion and future research directions.

The Capital Market Authority Effectiveness in the Regulation of Financial Markets perspectives from the financial sector actors

2012 ◽  
Vol 02 (11) ◽  
pp. 15-24
Author(s):  
Charles Kombo Okioga
Keyword(s):  
Financial Markets ◽  
Financial Market ◽  
Capital Markets ◽  
Capital Market ◽  
Financial Regulation ◽  
International Standards ◽  
Market Regulation ◽  
Financial Market Regulation ◽  
Market Participants ◽  
New Business

Capital Market Authority in Kenya is in a development phase in order to be effective in the regulation of the financial markets. The market participants and the regulators are increasingly adopting international standards in order to make the capital markets in sync with those of developed markets. New products are being introduced and new business lines are being established. The Capital Markets Authority (Regulator) is constantly reviewing existing regulations and recommending changes to regulate the market properly. Business lines and activities are being harmonized by market participants to provide a one stop solution in order to meet the financial and securities services needs of the investors. The convergence of business lines and activities of market intermediaries gives rise to the diversity of a firm’s business operations to meet multiplicity of regulations that its activities are subject to. The methodology used in this study was designed to examine the relationship between capital markets Authority effective regulation and the performance of the financial markets. The study used correlation design, the study population consisted of 30 employees in financial institutions regulated by Capital Markets Authority and 80 investors. The study found out that effective financial market regulation has a significant relationship with the financial market performance indicated by (r=0.571, p<0.01) and (r=0.716, p≤0.01, the study recommended a further research on the factors that hinder effective financial regulation by the Capital Markets Authority.

scholarly journals Decision Support Tool for Offshore Wind Farm Vessel Routing under Uncertainty

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2190 ◽  
Author(s):  
Rafael Dawid ◽  
David McMillan ◽  
Matthew Revie
Keyword(s):  
Wind Farm ◽  
Real Life ◽  
Synthetic Data ◽  
Optimal Solution ◽  
Decision Support Tool ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Support Tool ◽  
Trade Offs ◽  
The Impact

This paper for the first time captures the impact of uncertain maintenance action times on vessel routing for realistic offshore wind farm problems. A novel methodology is presented to incorporate uncertainties, e.g., on the expected maintenance duration, into the decision-making process. Users specify the extent to which these unknown elements impact the suggested vessel routing strategy. If uncertainties are present, the tool outputs multiple vessel routing policies with varying likelihoods of success. To demonstrate the tool’s capabilities, two case studies were presented. Firstly, simulations based on synthetic data illustrate that in a scenario with uncertainties, the cost-optimal solution is not necessarily the best choice for operators. Including uncertainties when calculating the vessel routing policy led to a 14% increase in the number of wind turbines maintained at the end of the day. Secondly, the tool was applied to a real-life scenario based on an offshore wind farm in collaboration with a United Kingdom (UK) operator. The results showed that the assignment of vessels to turbines generated by the tool matched the policy chosen by wind farm operators. By producing a range of policies for consideration, this tool provided operators with a structured and transparent method to assess trade-offs and justify decisions.

scholarly journals Managing cost uncertainties in transportation and assignment problems

1998 ◽  
Vol 2 (1) ◽  
pp. 65-104 ◽  
Author(s):  
V. Adlakha ◽  
H. Arsham
Keyword(s):  
Time Lag ◽  
Real Life ◽  
Optimal Solution ◽  
Global Market ◽  
Solution Algorithm ◽  
Assignment Problems ◽  
The Stability ◽  
Order Assignment ◽  
Cost Parameters ◽  
The Cost

In a fast changing global market, a manager is concerned with cost uncertainties of the cost matrix in transportation problems (TP) and assignment problems (AP).A time lag between the development and application of the model could cause cost parameters to assume different values when an optimal assignment is implemented. The manager might wish to determine the responsiveness of the current optimal solution to such uncertainties. A desirable tool is to construct a perturbation set (PS) of cost coeffcients which ensures the stability of an optimal solution under such uncertainties.The widely-used methods of solving the TP and AP are the stepping-stone (SS) method and the Hungarian method, respectively. Both methods fail to provide direct information to construct the needed PS. An added difficulty is that these problems might be highly pivotal degenerate. Therefore, the sensitivity results obtained via the available linear programming (LP) software might be misleading.We propose a unified pivotal solution algorithm for both TP and AP. The algorithm is free of pivotal degeneracy, which may cause cycling, and does not require any extra variables such as slack, surplus, or artificial variables used in dual and primal simplex. The algorithm permits higher-order assignment problems and side-constraints. Computational results comparing the proposed algorithm to the closely-related pivotal solution algorithm, the simplex, via the widely-used pack-age Lindo, are provided. The proposed algorithm has the advantage of being computationally practical, being easy to understand, and providing useful information for managers. The results empower the manager to assess and monitor various types of cost uncertainties encountered in real-life situations. Some illustrative numerical examples are also presented.

scholarly journals Is this time really different? Flight-to-safety and the COVID-19 crisis

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251752
Author(s):  
Celina Löwen ◽  
Bilal Kchouri ◽  
Thorsten Lehnert
Keyword(s):  
Financial Crises ◽  
Price Volatility ◽  
Equity Market ◽  
Gold Price ◽  
Sharp Drop ◽  
Market Participants ◽  
Oil Market ◽  
Causality Tests ◽  
Safety Effect ◽  
The One

During periods of market stress, risk-averse investors reallocate their investments from stocks to gold in a bid to hedge risks. Market participants interpret the induced gold price increase as an indication of safe-haven purchases and a signal of increased uncertainty in the general economic and financial conditions, thereby causing higher gold price volatility. The aim of this paper is to analyze whether this flight to safety effect can be observed during the COVID-19 crisis, which is considered to be a one-of-a-kind crisis and obviously of different origin compared to previous (financial) crises. By examining the interactions between the (option-implied) volatilities of the stock market (VIX) and of the gold (GVZ) and oil (OVX) markets, the main findings indicate that there is a granger causality in general between the equity market and the gold as well as the oil market. During the COVID-19 crisis, a stronger influence of the equity market on the oil market can be observed. Based on symmetric causality tests that are typically employed in the literature, this cannot be observed for the gold market. However, once we control for asymmetric causal interactions, we find that positive shocks in VIX cause positive shocks in GVZ. Hence, the typical flight to safety effect, similar to the one observed during other (financial) crises can also be identified for the COVID-19 crisis. The causality between the equity and oil market is triggered by political factors as well as the economic impact of the crisis which induces a sharp drop in demand for oil.

Methods for Solving Fully Fuzzy Transportation Problems Based on Classical Transportation Methods

2013 ◽  
pp. 328-347 ◽  
Author(s):  
Amit Kumar ◽  
Amarpreet Kaur
Keyword(s):  
Transportation Problem ◽  
Fuzzy Numbers ◽  
Real Life ◽  
Optimal Solution ◽  
Fuzzy Linear Programming ◽  
Programming Formulation ◽  
Transportation Problems ◽  
Fuzzy Optimal Solution ◽  
Linear Programming Formulation ◽  
Fuzzy Transportation Problem

There are several methods, in literature, for finding the fuzzy optimal solution of fully fuzzy transportation problems (transportation problems in which all the parameters are represented by fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings, two new methods (based on fuzzy linear programming formulation and classical transportation methods) are proposed to find the fuzzy optimal solution of unbalanced fuzzy transportation problems by representing all the parameters as trapezoidal fuzzy numbers. The advantages of the proposed methods over existing methods are also discussed. To illustrate the proposed methods a fuzzy transportation problem (FTP) is solved by using the proposed methods and the obtained results are discussed. The proposed methods are easy to understand and to apply for finding the fuzzy optimal solution of fuzzy transportation problems occurring in real life situations.

Behavioral Study of Drosophila Fruit Fly and Its Modeling for Soft Computing Application

2016 ◽  
pp. 32-84 ◽  
Author(s):  
Tapan Kumar Singh ◽  
Kedar Nath Das
Keyword(s):  
Real Life ◽  
Optimal Solution ◽  
Fruit Fly ◽  
Linear Constraints ◽  
Behavioral Study ◽  
Search Optimization ◽  
Life Problems ◽  
Decision Variables ◽  
Wide Range ◽  
Real Life Situation

Most of the problems arise in real-life situation are complex natured. The level of the complexity increases due to the presence of highly non-linear constraints and increased number of decision variables. Finding the global solution for such complex problems is a greater challenge to the researchers. Fortunately, most of the time, bio-inspired techniques at least provide some near optimal solution, where the traditional methods become even completely handicapped. In this chapter, the behavioral study of a fly namely ‘Drosophila' has been presented. It is worth noting that, Drosophila uses it optimized behavior, particularly, when searches its food in the nature. Its behavior is modeled in to optimization and software is designed called Drosophila Food Search Optimization (DFO).The performance, DFO has been used to solve a wide range of both unconstrained and constrained benchmark function along with some of the real life problems. It is observed from the numerical results and analysis that DFO outperform the state of the art evolutionary techniques with faster convergence rate.

scholarly journals PSK Method for Solving Intuitionistic Fuzzy Solid Transportation Problems

2018 ◽  
Vol 7 (4) ◽  
pp. 62-99 ◽  
Author(s):  
P.Senthil Kumar
Keyword(s):  
Real Life ◽  
Optimal Solution ◽  
Transportation Problems ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Optimal Solution ◽  
Fuzzy Representation ◽  
Objective Value

This article proposes a method for solving intuitionistic fuzzy solid transportation problems (IFSTPs) in which only the transportation costs are represented in terms of intuitionistic fuzzy numbers (IFNs). The remaining parameters, namely: supply, demand and conveyance capacity, are all considered into crisp numbers. This type of STP is called a type-2 IFSTP. When solving the real life solid transportation problems (STPs) those tend to face the uncertainty state as well as hesitation due to many uncontrollable factors. To deal with uncertainty and hesitation many authors have suggested the intuitionistic fuzzy representation for the data. In this article, the author tried to categorise the STPs under the uncertain environment. He formulates the intuitionistic fuzzy STPs and utilizes the triangular intuitionistic fuzzy number (TIFN) to deal with uncertainty and hesitation. The PSK (P.Senthil Kumar) method for finding an intuitionistic fuzzy optimal solution for fully intuitionistic fuzzy transportation problem (FIFTP) is extended to solve the type-2 IFSTP and the optimal objective value of type-2 IFSTP is obtained in terms of TIFN. The main advantage of this method is that the optimal solution of type-2 IFSTP is obtained without using the basic feasible solution and the method of testing optimality. Moreover, the proposed method is computationally very simple and easy to understand. A case study is presented to illustrate the procedure of the proposed method.

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