More than a decade after the letdown of risk management in cases such as Barings PLC, Metallgesellschaft and Orange County, risk management has evolved a lot, but there is still a long way to go. From Bernoulli’s experiment to Miller and Modigliani’s Portfolio Theory and Fama and French’s 3 factor model, the latest trend in risk management is Value-at-Risk.

Most of the existing research focuses on a single area of risk management. There exists a need to establish the missing links between these risk management techniques in application. This thesis attempts to do just that. It evaluates the performance of selected portfolios by calculating performance measurements such as Treynor Ratio, Sharpe Ratio, Jensen’s Alpha, Fama & French 3 factor model and Value-at-Risk. This thesis examines the period from 2003-2010 using the companies listed on the Karachi Stock Exchange. The benchmark used in this analysis is the KSE-100 index.

The purpose of the study is to determine which portfolios would be better investments in terms of risk and return. Also, through the application of a variety of methods, drawbacks and pitfalls of these methods will become more apparent when comparing and contrasting.

The main objectives are firstly to identify risk assessment techniques, and secondly to classify portfolios according to risk and return. Last but not least, comparison of results will prove the consistency and validity of the research.

INTRODUCTION

Risk

The Oxford dictionary defines the word risk as “hazard; chance of bad consequences, loss, etc.; exposure to mischance; to expose oneself, or be exposed to loss.” Traditionally, risk is viewed negatively. The Chinese symbol for crisis gives a more complete picture of what risk represents:

Of the two symbols, the former represents danger, while the latter signifies opportunity. This shows that it is important to manage risk in good times in order to plan for possible crises and in bad times so that you can look for opportunities. Above all, risk must be dealt with calmly. “Risk management is not just about minimizing exposure to the wrong risks but should also incorporate increasing exposure to good risks.”(DAMODARAN, Aswath)

Since risk implies uncertainty, risk assessment is largely concerned with uncertainty in connection with probability. In essence, risk assessment is a method of examining risks so that they can be controlled, reduced or evaded. In order to lend meaning to any form of risk assessment, the results must be compared against a benchmark or similar assessment (WILSON,  Richard and Crouch,  E. A. C., 1987).

Interpretations of Risk

Risk vs. Probability: Probability involves only the likelihood of an event occurring, whereas risk encompasses both the likelihood along with the consequences of the event. The practice of making probability centric decisions about risk leads to ignoring new risks or unusual risks which may not be numerically quantifiable.

Risk vs. Threat: A threat may be defined as “an indication of coming evil” or a low probability event with very large negative consequences whose probability is difficult to determine. A risk is a higher probability event whose probability and consequences can be determined.

All outcomes vs. Negative outcomes: A focus on negative outcomes relates to downside risk. But variability in risk should include both the good and the bad i.e. all outcomes should be taken into account when determining risk. The practice of making negative outcomes the highlight of risk assessment tends to narrow risk management to simply hedging. (DAMODARAN, Aswath)

Evolution of risk assessment

The idea of measuring performance has appealed to both investors and financial analysts alike. The process of doing so has evolved over time. Initially it involved evaluation based on total returns. When the concepts of efficiency and benchmarks were added to the mix, it further refined the process. With every passing day new methods and hybrid methods are tested in an effort to develop an accurate method of assessment (MODIGLIANI, Franco and Modigliani, Leah, 1997). The following table depicts the evolution of risk assessment:

Period

Risk Measure

Key Event

Pre-1494

None or gut feeling

Fate or divine providence

1494

Computed probabilities

Luca Pacioli’s coin tossing game

1654

Pascal and Fermal’s Probability Estimation Theory

1662

Graunt’s Life Table

1711

Sample-based probabilities

Bernoulli’s Law of Large Numbers

1738

The birth of the normal distribution

1763

Bayes contributions

1800s

Expected loss

The development of the insurance business

1900

Price variance

Bachelier’s random walk hypothesis

1909-1915

Stock and bond ratings

Moody’s, Fitch and Standard Statistics Bureau

1952

Variance added to portfolio

Markowitz’s efficient portfolio theory

1964

Market beta

The birth of CAPM

1960s

Power law, Asymmetric and Jump process distributions

1976

Factor betas

Ross’s Arbitrage pricing model; introduction of multiple market risk factors

1986

Macroeconomic betas

Macroeconomic Multifactor m