Advanced Topics in Corporate Reporting:
Accounting for Financial Instruments under IFRS
Georgi Nikolov, PhD
The accounting treatment of financial instruments is considered one of the most difficult and controversial financial reporting areas. The purpose of this academic course is to broaden and deepen students’ theoretical and practical knowledge of the entire financial reporting process for transactions with financial instruments undertaken by the entity. The course is of highly specialized nature. It is designed for PhD students willing to gain in-depth knowledge and understanding of the economic characteristics of financial instruments and their accounting implications - an area highly sought after by corporations, financial institutions, auditing firms and financial analysts.
An integrated approach is being followed in designing the structure of the course material. The course combines an outline of the main theoretical concepts and financial reporting requirements with lots of illustrative practical examples and mini cases. The key general aspects of accounting for financial instruments are discussed first - classification, initial recognition and measurement, subsequent measurement, impairment, derecognition, hedge accounting, etc. Then the accounting treatment of specific financial instruments is separately considered - stocks, bonds, options, forwards, futures, swaps, etc. The course is based on the requirements of International Financial Reporting Standards (IFRS).
Contents:
1. NATURE OF FINANCIAL INSTRUMENTS
2. CLASSIFICATION OF FINANCIAL ASSETS AND FINANCIAL LIABILITIES
3. RECOGNITION AND INITIAL MEASUREMENT OF FINANCIAL INSTRUMENTS
4. SUBSEQUENT MEASUREMENT OF FINANCIAL INSTRUMENT
5. IMPAIRMENT OF FINANCIAL ASSETS
6. DERECOGNITION OF FINANCIAL ASSETS AND FINANCIAL LIABILITIES
7. CLASSIFICATION OF FINANCIAL INSTRUMENTS BY THEIR ISSUER
8. ACCOUNTING FOR ISSUED DEBT INSTRUMENTS
9. ACCOUNTING FOR INVESTMENTS
10. BASIC AND DELUTED EARNINGS PER SHARE
11. SHARE BASED PAYMENTS
12. АCCOUNTING TREATEMENT OF OPTIONS
13. АCCOUNTING TREATMENT OF FUTURES AND FORWARD CONTRACTS
14. ACCOUNTING TREATMENT OF SWAPS
15. FINANCIAL RISK MANAGEMENT USING DERIVATIVES
16. HEDGE ACCOUNTING AS A RISK MANAGEMENT TOOL
SOFT DECISION ANALYSIS METHODS
Assoc. prof. Galya Illieva
This course introduces the principles of soft decision analysis methods. In particular, the course provides students with the educational background to the inaccurate approximate methods for decision making often with non-polynomial complexity. Tasks solved with these methods arise today in the fields of biology, medicine, humanities, robust control, and management. The methods are oriented toward loosely coupled management objects and use techniques from the fuzzy sets theory (fuzzy sets, fuzzy logic, fuzzy controllers, etc.). Different methods of soft decision analysis can complement each other and often work together.
Course Outline:
1. Decision problems
2. Utility theory
3. Analytical Hierarchy Process. TOPSIS, DEMATEL, VIKOR methods
4. Decision making under uncertainty
5. Classical fuzzy sets and systems
6. Aggregation operators
7. Intuitionistic, hesitant, rough, ordered fuzzy sets - state of the art and future directions
MONTE CARLO SIMULATIONS AND REAL OPTIONS ANALYSIS
Assoc. prof. Stanimir Kabaivanov, PhD
The purpose of this course is to present new ways of addressing a wide range of corporate finance research problems which include complex real options. Covered topics are not limited to typical cases but also include more complex scenarios that require decomposition of the available options. Monte Carlo simulations are discussed not only as a powerful valuation method but also as a standalone risk assessment approach.
Main topics
1. Introduction to real options and the importance of flexibility.
2. Analytic solutions for typical real option types.
3. Advanced option types – properties and valuation methods.
4. Use of exotic option types in real options analysis.
5. Introduction to Monte Carlo and mathematics behind it.
6. Simulation approach for derivative pricing and risk assessment.
7. Specific issues with Monte Carlo methods – estimation and callibration.