Financial Economics I

This is a course on financial economics that I teach second--year Ph.D. students at IGIDR, Bombay.

Books

The course is based on the material covered in Investment science by David Luenberger. In addition, the following are highly recommended general reading:

1. The Economics of Financial Markets by Houthakker and Williamson (for market microstructure).
2. A random walk down Wall Street by Burton G. Malkiel.
3. Capital Ideas by Peter Bernstein.
4. India's financial markets: an insider's guide to how the markets work by Ajay Shah, Susan Thomas, Michael Gorham

Course syllabus

Course content

Introduction[Slideshow]

• Introduction to the questions in finance

Financial assets[Slideshow]

• Defining a financial asset
• Different asset classes by cashflow and maturity characteristics
• Approaches to pricing financial assets
• Who uses finance? Individuals, firms, government
• Types of firms

An introduction to debt and equity[Slideshow]

• Placing debt and equity in firm finances
• Debt vs. Equity
• Measurement of debt vs. equity - from the firm's balance sheet

Fixed income analytics: an introduction[Slideshow]

• Fixed income instruments
• Pricing fixed income instruments
• Term structure of interest rates -- zero coupon yield curve, ZCYC
• Spot and forward interest rates

Fixed income analytics[Slideshow]

• The Nelson-Siegel (NS) ZCYC
• Pricing GOI bonds using the NS ZCYC
  1. Interest rate changes and returns on bond
  2. Risk of bond returns and risk of interest rates
  3. Simplified bond risk measures: Duration and Convexity

Risk in bonds[Slideshow]

• Risks in bonds: interest rate risk and credit risk
• Defining credit risk
• Probability of default, Recovery ammounts
• Risk neutrality valuation

The flowchart in credit risk analytics

• Risk adjusted discount rate -- credit premium
• Putting together the credit risk problem
• Credit risk syntax.
• Analytics in creditrisk #1: estimating probability of default
• Data to estimate prob of default in India

Modelling the probability of default using statistical models

• Modelling framework: binary choice models -- probit, logit
• The Z-score
• Calculating and using the Odd's Ratio
• Diagnostics

Modelling the probability of default for Indian firms

• Building the CMIE credit model for Indian firms
• Diagnostics -- the power curve
• Selection of independent variables from accounting ratios

Risky cashflows: equity

• Expected future cashflows in equity == Dividends
• Sensitivity of price to errors in E(dividends) or equity risk premium
• Accounting data models for equity valuation: free cashflow/dividend discount models

Financial markets and their outcomes

• Functions of financial markets:
  1. Price discovery
  2. Liquidity provision
  3. Risk management
• Measuring outcomes of financial markets: prices, liquidity, risk
• Market microstructure: Different types of markets

The random walk of ``speculative market'' prices

• Definition and properties of random walk
• Definition and properties of the white noise process
• Simulating from a random walk process -- R program
• The Efficient Market Hypothesis (EMH)
• Tests of EMH: serial correlations
• Defining Variance Ratios (VR)
• Defining the null of VR for EMH
• Inference for VR
• VRs for the Indian Stock Market

Tests of EMH: Event studies

• Defining the event study framework
• Example: Do Indian stock market prices over-react to bonus issue announcemnets
• Inference for VR
• Example: Impact of the budget on Indian stock markets.

Microstructure of financial markets

• Products
• Trading systems
• Clearing systems
• Settlement
• Regulation/Governance
• Case study of the National Stock Exchange (NSE)
• Case study of the Muzaffarnagar Jaggery Futures Market

Introduction to derivatives

• Spot vs. Forwards transactions
• Payoff diagrams
• What are futures contracts?
• What are options contracts?
• Using derivatives
  1. Leverage and liquidity of derivatives compared to the spot
  2. Speculation using derivatives
  3. Hedging
  4. Arbitrage

Pricing derivatives

• Arbitrage to price forwards
• Pricing swaps on interest rates
• Arbitrage to pricing options: Putcall parity
• Mimicking assets using portfolios of options: exploring putcall parity

Exploring Put-Call Parity

• Portfolios mimicking asset payoffs
• Synthetic portfolios: replicating assets

Portfolio optimisation

• What is a portfolio?
• Portfolio inputs vs. portfolio outcomes
• Measuring expected returns
• Measuring expected risk
• The E(r)-sigma graph as the first step towards portfolio optimisation

Portfolio optimisation: Harry Markowitz

• Optimisation in a two risky-asset universe
• Special case of capital allocation: risk free vs. risky assets
• Leverage: negative weights on assets in a portfolio
• Harry Markowitz and the Portfolio Optimisation Framework
• Simulation of generating the efficient portfolio frontier using R
• Characteristics of the optimal portfolio solution
• Two fund separation
• Portfolio optimisation including the risk-free rate of return
• One fund theorem
• Operationalising the Markowitz framework

Portfolio optimisation: William Sharpe

• The Capital Asset Pricing Model
• Using CAPM as a pricing model
• Beta as the risk of an asset
• Re-evaluating diversification in the CAPM world
• Operationalising Markowitz using CAPM

Measuring portfolio performance

• Performance benchmarks: risk vs. returns
• Sharpe's measure, Treynor's measure
• Jensen's measure
• Information Ratio
• M-squared measure
• What to use when
• Examples

Risk in financial assets

• What is risk?
• Measuring risk.
• Value at Risk, VaR

Mechanics

• Susan Thomas can be reached at susant@igidr.ac.in. Office extension is 550.
• Students are expected to read the following newspapers the Mint, Financial Express, Economic Times, Business Standard. One student will be asked to make a 5-minute presentation on both Tuesday and Thursday on an important issue in Indian finance for the week.
• There will be a final examination (60% of the grade). It will cover the entire course content covered at the time of the exam.
• Students will have to take the NCFM Derivatives certification examination, and the score obtained in this exam will carry a 10% weightage. Only NCFM scores in the range of 75 to 100 will be accepted. The scoring will be as follows: 75% will start as 5 and the maximum score obtained in the class will be taken as 20.
• Three students will work together to write a paper on a topic out of a list of given topics. This will cover 30% of the grade, and is due by the end of March. The project paper is expected to be formatted using LaTeX and submitted as a PDF file. Evaluation will be based on the final draft of the paper as well as a presentation before the examination week.

Useful links

• Ajay Shah's website
• Ideas for computational tools.
• NSE
• SSRN

Back up to Susan Thomas' teaching page