Financial Modeling

The goal of this paper is to analyze the role that non-financial variables can play in assessing Smes creditworthiness and to compare their value in predicting business failure with the one of the most commonly used financial ratios. We investigate the importance for banks in modeling credit risk for Smes using non-financial variables able to describe the relationship company-banks. Our findings demonstrate that credit relationship information is better predictor of corporate failure than financial ratios. We also test the models on an out-of-time and out-of-universe sample to prove their accuracy and soundness. Our initial assumptions remained confirmed: non-financial variables allow to improve the accuracy and performance of banks’ credit rating models.

‘Atmanirbhar Gaushala’ project aims to make financially Gaushala viable. This project is unique and first of its kind, planned and made in the district of Hardoi. As Mahatma Gandhi National Fellow, I got the opportunity to be a part of the planning and implementation of the project.
In the first stage, District Magistrate explained the problem statement. I worked on defining the components, resources available, and constraints of the project. After rounds of discussion and field visits, I came up with the first set of financial estimates for all the Gaushalas.
In the second stage, I worked on detailed financial planning for a generic model. During the project appraisal stage, Bahar was taken up as the pilot project. Formation of the assessment team and continuous follow up on the plan helped in the finalization of the plan. For the implementation and monitoring stage, a concrete plan of action was formulated. Self Help Groups has been made an integral part of the project.
In future, this project will be an example where Gram Panchayats can generate their revenue by utilizing their land. It promotes making Gaushalas financial viable. Along with this, it ensures employment generation and capacity building for Self Help Groups. This will ensure a case study for revenue generation for Gram Panchayats. This paper describes the experience of Mahatma Gandhi National Fellow, Jaishri Rai in the district of Hardoi as part of the ‘Atmanibhar Gaushala’ Project.

The main contribution of the paper is to present hard evidence on risk exposure, hedging strategies, and agency problems resulting in speculation with derivatives, by focusing on the case of Aracruz Celulose. It highlights the failure of risk management systems in non-financial firms in the face of extreme events like the financial crisis of 2008. The company posted financial losses of U$2.1 billion due to currency derivatives trading in the third quarter of 2008. We show how the company‟s real hedge position deviated from its optimal hedge as a result of the speculation with OTC derivatives, permitted by weak governance structures that failed in preventing hubris and mistakes in risk management.

The depletion of fossil fuel forces the world to look for alternative ways for energy production. The most common way is the production of biodiesel from waste cooking oil. This paper presents a detailed cost analysis for a biodiesel plant with capacity 100,000 ton/year. The cost analysis basis depends on the optimum conditions obtained from the experimental work that achieves biodiesel conversion of ≈ 99%. The study concludes that the project will achieve a good income that around four million US $ every year and the total net income during the life cycle of project is 72.5 million US $. The production cost of one liter biodiesel from used cooking oil is 0.515 $ while the global price of petro-diesel is 0.678 $/ liter and global biodiesel current price is 1 $/liter.

Research paper that lists the sukuk issuance where default event took place
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Estimating Investor Losses in Sukuk Default Restructuring (Universiti Sains Islam Malaysia)

"The aim of the study is to estimate investor losses in case of sukuk default restructuring using government and corporate sukuk as a benchmark. The main findings suggest that the average investor losses ranging from 2.01% - 3.14% (for less than or equal to 1 year remaining tenure) to 18.15% - 18.94% (for more than 5 years remaining tenure). The findings indicate that investors will face relatively bigger losses if the defaulted sukuk have longer remaining tenure. This finding may be used by market participants as benchmark in restructuring process" 

A study conducted by Khnifer (2010a) is one of the early studies that discuss the sukuk default. In his paper, the author reports that there are at least 21 defaulted sukuk in last 20 months from Nov. 2010. Khnifer (2010b) further proposes three approaches to restructure defaulted sukuk based on Shari’ah principles namely haircut, rescheduling and debt-for-equity swaps.

In this work, assuming as a model the Multifractional Processes with Random Exponent (MPRE), we propose a simulation algorithm able to replicate financial time series, specifically pertaining to the FX market. We show how, properly choosing the functional parameter of the MPRE, the simulated series fit with significant accuracy the actual ones. It is worthwhile to underline that the sole knowledge of the functional parameter ensures by itself that the surrogates succeed in replicating the empirical data. The results can be used in scenario analysis as well as in forecasting.

In this paper we derive an analytical formula for the variance of the hedging error for European options when hedging discretely with equal time steps. The result is further generalized to a portfolio of options with different maturities and strikes.

This book introduces essential concepts, applications, and techniques in financial, investment, and risk intelligence yet takes an unorthodox approach to its readers. By directly practicing on and interacting with spreadsheet exercises that are packaged for easy understanding and maneuvering, the readers will have an opportunity to discover, and a flexibility to consult, the theory and evidence leading to any particular financial problem discussed herein or from other texts in the field. This on-the-job-training approach is analogous to learning how to communicate in a foreign language for the first time by actively mingling with local people and being assimilated into their culture instead of passively going through a series of grammatical lessons first. A novice would gradually become a fluent practitioner equipped with different flexible ways to cultivate her quantitative and computational finance knowledge while enhancing her financial modeling and business-solution development skills. The first use of this book is to assist the readers to jump-start their business and financial analysis careers by integrating this newly acquired knowledge and skills in financial modeling with their relevant business backgrounds. Accountants who traditionally collect, record, and report operating and financial data from their companies’ business activities could now perform advanced and more sophisticated analyses on valuation, investment, and risk management. Operation, distribution, and marketing managers whose production, logistic, and sale targets depend on the estimate of customer demands in different geographical areas and seasonal periods, or consumer preferences that are closely tied with their demographical profiles, could also perform various types of quantitative and statistical analysis through spreadsheet modeling similar to many practice exercises demonstrated in this book. Most importantly, the book allows its audience to be less reliant on any formal lecture without sacrificing the classroom’s rigor yet gain more control over their study pace and learning development. To a group of practitioners in the professional world, this book would help unify the team members’ interests to focus on the business and modeling problems at hand. In a consulting firm, for example, specific clients’ cases can be addressed based on their objectives, input data, and interface requirements within the constraints of their resource and timetables, combined with diverse experiences of the team members in problem prognosis and situational analysis as well as their expertise in intelligence gathering, data-mining and warehousing, and design of and training for customized business solutions. All they need to do is ascertain that coordination between the client and the team as well as among the team members themselves is carried out in a cost-effective manner. Like an instruction manual, this book shall direct the firm’s coordination efforts by keeping track of the progress of the team’s tasks in terms of what has been left out and which of them need to be accomplished along the priority list. Those who intend to employ this book as part of their finance instructions and training modules within the academic institution or professional setting will find it quite easy to adopt because the book encapsulates the main finance topics that are regularly taught everywhere. The benefit of assigning this book to the students lies on skill-building modeling exercises that will help in their preparation before attending classes and their review afterwards. Various technical problems they have encountered during their practices can be shared with and resolved through their instructors and classmates. Rather than providing unilateral lectures all the time, the instructors could welcome and entertain their students’ questions and comments while still focusing on relevant topics. When it comes to group or individual project assignments, the students will be able to apply different models they have practiced to their own projects without requiring constant assistance from their instructors. The expectations of both the instructors and students will be more aligned and better fine-tuned to each other. Clearly, the use of this book is not limited to just the above audiences it intends to serve. It is also recommended to any individual who would like to approach finance differently and gain insights into how to implement many finance formulae to exploit the vast opportunities in today’s financial markets.

index Scope & Topics 3 rd International Conference on Data Mining & Machine Learning (DMML 2022) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Data Mining and Machine Learning. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Big Data and Machine Learning. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Data Mining and Machine Learning.

— As we know that many water resources are polluted the environment by anthropogenic sources like agricultural and household. As matter of fact Public think that the environmental impact of wastewater pollution has increased day by day many conventional wastewater treatment techniques like chemical adsorption, activated sludge are applied to remove the pollution but there are still some limitations which has high operation costs. The use of waste water treatment in public and private works as a different medium is receiving increased interest so that its low operation and maintenance costs. As per as the water treatment is concerned it is easy to have a good effectiveness and ability for degrading contaminant. Hence, this paper reviews is the use of waste water treatment technologies to remove contaminants from wastewater like a high oxidant which represent the main pollutants in wastewater as per as a financial modeling of public private partnership of wastewater treatment.

This paper explores the foundations of the Fractal Market Hypothesis. It explores the theoretical framework that a fractal view of markets provides while critiquing the wisdom of modern efficient market theories. This paper also delves into the building blocks of Fractal Financial Theory by examining the theories of Chaos and Complexity and how these concepts manifest themselves in today’s financial markets.

The stock market is constantly changing with uncertainties. That's why the analysis of certain time series from the economic and financial world shows specific characteristics that are not theoretically taken
into account in ARIMA modeling Box Jenkins. The first characteristic concerned is the
dependence of the conditional variance of time, in other words, we are concerned by the heteroscedastic behavior of the variance. The second
characteristic concerns the probabilistic distribution of the series (the appearance of shocks is
not compatible with the normal law). Then for a more realistic modeling of these series,
ARCH / GARCH models are the most useful.
In this project my co-worker and I :

► We have studied the ARCH and GARCH models from a theoretical point ( properties and conditions
to be fulfilled by the models).

► We applied them to one of the indices (CAC40 ) using EVIEWS.

► We applied 3 different forecasting models to predict the conditional variance of CAC 40 stock indices.

► We finally compared the forecasts using multiple statistical tests.

1980'lerden itibaren başta gelişmiş ülkeler olmak üzere, birçok ülkede finansın önündeki yasal engeller kaldırıldı ve bilgisayar teknolojisindeki ilerleme sayesinde "sıcak para" olarak tanımlanan milyarlarca dolarlık portföy yatırımları bir ülkeden diğerine birkaç saniye içinde geçebilir hale geldi. Böylece, özellikle gelişmekte olan ülkeler (GOÜ) daha kolay kısa vadeli kaynak bulma olanağına kavuştular. Ancak, portföy yatırımlarının çok kısa sürede bir ülkeden diğerine geçebilmesi, GOÜ ekonomilerinin finansal krizlere karşı kırılganlığını da artırdı. Öte yandan, finansal enstrümanların çeşitlenmesiyle birlikte, finansa olan ilgi arttı. Giderek çeşitlenen finansal enstrümanların sağladığı yüksek getirinin cazibesine kapılan üretim şirketlerinde bile finansla ilgilenen departmanlar kuruldu. Finans yöneticileri gerek aldıkları ücretler, gerekse şirket içindeki önemleriyle ön plana çıktılar. Tüm dünyada finansla ilgili meslekler gözde meslekler arasına girdi. Bununla birlikte, 2007'nin ikinci yarısından itibaren ABD'de başlayıp tüm dünyaya yayılan "Mortgage Krizi" de, finansın yalnız finansla uğraşan profesyoneller için değil, toplumun tüm kesimlerini ilgilendiren önemli bir alan olduğunu hatırlattı.

The study analyzed challenges that came upon the financial and management consultancy business, solutions to those challenges as well as customer satisfaction as it impacts on the general survival and success of the firm during the ten year long recession experienced in the Zimbabwean economy. The concern of the study was centered on the establishing of these challenges in details as well as the possible solutions while still making profits.

Financial, Liquidity and of late the Global Financial crises impacted on the operations of the firm, as well as high taxation rates and the negative shift of demand adversely affected the business. If well implemented, turnaround strategies can result in enhanced revenue, reduced costs, increased profitability, customer satisfaction and a widened clientele base. Financial consultancy services tend to have an induced demand thus they need to be supported by strong client product markets in order to sustain the demand for them, marketing strategies being key instruments in increasing customer satisfaction in both product markets of customers and that of the financial consultants.

Questionnaires were used to collect the data from employees and customers while personal interviews were used to get information from management. The sample size of 16 non managerial employees and 4 customers was issued with questionnaires and 2 managers interviewed.

The major findings from the research indicate that turnaround strategies had to be formulated and implemented in order to combat the studied challenges, thus proving the paramount importance of organizational analysis in times of crisis.

Pickford Financial and Management Consultants (Private) Limited is recommended that it could improve customer satisfaction, process efficiency and employee competence in offering financial services through distributing resources evenly across all the critical success factors. It was also advised that customer satisfaction should be frequently measured and also everyone’s role within the organization that is all the departments’ responsibility.

Rural India presents a remarkable opportunity for banks and financial institutions to seek their fortunes and bring prosperity to the aspiring poor through financial inclusion. In a fast growing economy like India the poor are the middle class of tomorrow and banks could, therefore, ill-afford to ignore this segment. Banks, however, argue that while the benefits of financial inclusion can be easily understood, the costs of serving the poor can be significant in the short-term, thereby impacting profitability. Banks, therefore, need to take bold decisions and reach out to rural India with strategies and business models which are beyond the realm of conventional thinking. This paper looks at some of the business models and the essential elements of profitable models for financial inclusion.

Stock option pricing is a difficult but important problem. Traditionally options are priced using pa-rametric models such as Black-Scholes. In this pa-per we develop a machine learning approach to option pricing using neural networks. We investigate different attributes and their affect on accuracy.  One of the problems associated with investing is knowing when to buy and when to sell. In this paper, we also attempt to facilitate the accuracy of these decisions by way of machine learning applied to option securities. Using several Multilayer Perceptron models, results suggest that machine learning can be used as a basis for effective option investment strategies.

3
rd International Conference on Data Science and Applications (DSA 2022) will act as a
major forum for the presentation of innovative ideas, approaches, developments, and research
projects in the areas of Data Science and Applications. It will also serve to facilitate the
exchange of information between researchers and industry professionals to discuss the latest
issues and advancement in the area of Data Science & Applications.

3 rd International Conference on Data Mining & Machine Learning (DMML 2022) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Data Mining and Machine Learning. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Big Data and Machine Learning.

A stock market, equity market or share market is the aggregation of buyers and sellers (a loose network of economic transactions, not a physical facility or discrete entity) of stocks (also called shares); these may include securities listed on a stock exchange as well as those only traded privately.

"A COMPARATIVE STUDY OF DOLLAR COST AVERAGING VS. VALUE AVERAGING
Pawel S. Benedykcinski and Prof. Rick Goedde (Advisor)
Economics Department
St. Olaf College
Northfield, MN

My research compares three investment techniques, fixed and variable dollar cost averaging and value averaging to determine if any of the methods yield superior investment returns in the long run. Mutual funds, stocks, and exchange-traded funds were used to test the methods. Value averaging is a formula-based investment technique using a mathematical formula to guide the investment of money into a portfolio over time. With this method investors contribute to their portfolios in such a way that the portfolio balance increases by a set amount, regardless of market fluctuations. Dollar cost averaging invests equal amounts regularly and periodically over specific time periods in a particular investment or portfolio. By doing so more shares are purchased when prices are low, and fewer shares are purchased when prices are high.

After testing many mutual funds, ETFs, and individual stocks, I concluded that Value Averaging yields better Internal Rates of Return than fixed and variable Dollar Cost Averaging. The results also indicate that the three methods provide superior investment returns over extended investment time periods with little increase in risk, even if prices are volatile. One important difference between these three formula investment techniques is that value averaging requires larger sums of money to be invested at regular time intervals than fixed or variable dollar cost averaging do."

Asian options are options based on some average of the underlying asset price. Generally, an Asian option is an option whose payoff depends on the average price of the underlying asset during a pre-specified period within the option’s lifetime, and a pre-specified observation frequency. We implement Vorst’s method in valuing these options and give the relevant formulas for the Delta and Gamma. We also list some pseudo VBA code.

The aim and objective of this study is to model and forecast the stock index volatility of Shanghai and Shenzhen index. The volatility is estimated by employing three GARCH-type models standard GARCH, GJR-GARCH and the EGARCH. Their performance are compared based on three statistical errors, the mean absolute error, root mean squared and mean absolute percentage and then by the Mincer-Zarnowitz regression. The EGARCH outperforms its counterparts in all three statistical errors and by the regression based analysis. These empirical results are of important significance to portfolio management and risk management processes.

This paper presents a new approach to perform a nearly unbiased simulation using inversion of the characteristic function. As an application we are able to give unbiased estimates of the price of forward starting options in the Heston model and of continuously monitored Parisian options in the Black-Scholes framework. This method of simulation can be applied to problems for which the characteristic functions are easily evaluated but the corresponding probability density functions are complicated.

Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data.

This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the Journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only.

Can-do options are bespoke option structures listed on Safex and Yield-X. The JSE is the first exchange in the world to list, trade and clear exotic options. The first exotic was listed on 8 January 2007 with the onset of the financial crisis that played out during 2008. The option was on the FTSE/JSE Top 40 index and was a discrete look-back put spread with an averaging feature thrown in for spice. Since then, the types of exotics traded has grown in leaps and bounds, with many of them being complex in nature. Can-Dos are now also listed on Yield-X, with various currency pairs as underlyers. Every product listed on either
Safex or Yield-X needs to be marked-to-market, and risk managed on a daily basis. Initial margins need to be estimated for these complex products. This note will describe and explain the methodologies currently used to price these exotic Can-Dos, as well as the methodologies currently in use to determine initial margins for these instruments.

The Nobel laureates Fischer Black, Myron Scholes and Robert Merton revolutionised financial economics with the publication of their option valuation formula in 1973. The model, however, was devised for an elementary, ideal and frictionless world. Understanding the framework and underlying simplifying assumptions behind their formulation will help to minimize the risks in trading and managing derivative securities.

This article basically determines the assets in which water resources are polluted the environment by anthropogenic sources like agricultural and household formation.  As matter of fact Public think that the environmental impact of wastewater pollution has increased day by day many conventional wastewater treatment techniques like chemical adsorption  Hence the activated sludge are applied to remove the pollution but there are still some limitations which have high operation costs. The use of wastewater treatment in public and private works as a different medium is receiving increased interest so that its low operation and maintenance costs. As per as the water treatment is concerned it is easy to have a good effectiveness and ability for degrading contaminant. Hence, this paper reviews is the use of wastewater treatment technologies to remove contaminants from wastewater like a high oxidant which represent the main pollutants in wastewater as per as a financial modeling of the pu...

Brownlees, Engle and Kelly (2012) [BEK12] presented a volatility forecasting
comparative study within the autoregressive conditional heteroskedasticity
(ARCH)1 class of models. They considered 5 models chosen from the vast literature
on GARCH modeling for their simplicity and demonstrated ability to
forecast volatility over alternatives. Their natural starting point for model comparison
due to its ubiquity and progenesis of alternative models was the GARCH
(1,1) model by Engle (1982)2. In this article, we consider the application and
comparison of these models in forecasting volatility within the South African
financial context. We applied these models on the JSE Top 40 index closing
levels data ranging from 2009/01/02 to 2012/01/31 and explore the changes in
model parameter values that occurs due to consideration of different parameter
estimation window lengths. The data under consideration comprises of 771 data
points.

8
th International Conference on Data Mining (DaMi 2022) Conference provides a forum for
researchers who address this issue and to present their work in a peer-reviewed forum.
Authors are solicited to contribute to the conference by submitting articles that illustrate research
results, projects, surveying works and industrial experiences that describe significant advances in
the following areas, but are not limited to.

Applications of Quantum Tunneling effect have long gone beyond the traditional physical meaning. Initially created by Gamow to explain α-decay of nuclear particles, along the time, quantum tunneling found fertile domain of research in chemistry and recently in biology, where the new discipline of Quantum Biology emerges. The present paper extends the applicability of quantum tunneling to financial markets. In a recent paper [1] a time-independent equation for pricing the options having the underlying stock in a range bound markets is found. The equation is identical with a time-independent Schrodinger equation but incorporates elements of finance. The financial time-independent equation for option pricing is solved to explain a particular explosive violent movement of stock price in range bound markets. The aforementioned particular stock price movement is assimilated with a quantum tunneling effect. The probability of stock price to quantum tunneling out of the bounded region, known as transmission coefficient, is deduced. Quantum aspects of tunneling effect in financial markets are discussed. Recent evidences of price quantum tunneling in stock market are also shown.