Theory of financial risks
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The duration for which protection from an identified risk is required is another factor in selecting an appropriate response. Consider a risk that has a medium probability of occurrence and moderate impact.
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If the imminent impact time horizon is only a week from now, its impact severity will not be the same as if we forecast it to occur anytime in the next three months. In three months, the project environment may vary so significantly that the medium probability has risen to a high probability or the moderate impact was downgraded to a low impact.
Any action taken to handle risk implicitly incorporate the estimated time within which it can materially impact the project. In addition, at any time during the risk management process, the project manager has the option to postpone the risk handling response. This carries a value because, as some risk parameters become clearer the project manager is positioned in a better shape to handle the risk at a later time. Traditional theories based on empirical evidence suggests a set of actions based upon the following guidelines:.
As we identity various risk factors and understand the risk better, we can see it as having additional dimensions, which will be positively correlated to each other and create a compounded effect. Investment finance deals mostly with future, and its associated uncertainty. Options are kind of financial instruments that could provide a hedge protection, at a cost, against future identified financial risks. Such risks, which occur in a continuum, are similar to project risks such as schedule slippage, cost overruns etc. The operational project risks can be equated to the market risks—the movement of prices based on external factors.
Here is the time to draw parallels from financial risk management principles. Historical simulation has been the technique of choice in many project risk management situations. Most of the risk analysis processes use historically identified causes and weights. This has worked reasonably well with many projects, and has been effectively understood by several project managers. This is one reason, why experience either firsthand or derived counts in several risk handling tasks. Monte Carlo simulation is another widely used method, particularly in computer aided project management situations.
In this technique a large number of possible paths are visualized based upon a predefined probability distribution. The result is a distribution of outcomes, based upon which a project manager can take an informed decision. Thus far, the usage of pure quantitative techniques has been minimal in several core project management areas except scheduling project tasks.
This is mainly because of the intense mathematical requirements and the nonavailability of usable data for the ensuing formulas. However, such knowledge could make a difference in the effectiveness of a project manager while dealing with future and uncertainty.
While none of the above three techniques is infallible, together they provide a good insight into the future. Each of the technique could be adapted for certain situations, with its own pros and cons. Assigning a dollar value to the risk is, of course, a common way to effectively compare risk responses. We saw, while ago, that the value of the risk is a variable, and factors that might affect its value include its probability distribution and the time frame. The expected value of the risk, at any time, is the mean value of the impact of the risk, estimated based on the risk factors, their probability of occurrence and their associated impact.
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The expected value of the risk can change over time, with the arrival of new information and better understanding of its root causes. These are random events that have unpredictable impact on the value of the risk. This uncertainty has to be modeled by assigning a probability distribution to the impact of the risk. However, unlike a financial market where trading activities affect prices, project risks are impacted mostly by the underlying causes that are beyond the control of the PM. Again, drawing parallels from the financial options, the following parameters help estimate the appropriate cost of obtaining coverage for a risky asset in our case the project.
The current value of the project is the budgeted cost plus the expected value of the identified risk. Since the value of the risk could vary over time, the cost of the project that assumes or accepts the risk is not fixed. This is the independent or the market variable, and depends upon the expected value of the risk. There is no prior knowledge of the exact value of the risk. The estimate to completion of the project as computed today is the exercise or strike price. This is the cost that has been budgeted for the project and this is the cost at which the project manager would like to complete the project.
In the absence of a risk mitigation strategy, the project cost could vary and is estimated as the budgeted cost plus today's estimate of the value of the risk. When a project manager mitigates or transfers a risk, effectively he or she buys an option, which will ensure that the costs will be fixed instead of being variable.
The cost of the risk response should be the premium expected to get a fixed cost instead of a variable and uncertain project cost. Now the total cost of the project is the budgeted cost plus the premium paid for the response. This premium would be different for each risk response, and hence is a useful measure to compare them.
Theory of Financial Risk and Derivative Pricing : Jean-Philippe Bouchaud :
The best way familiarize with a risk and to estimate its cost, is to analyze it into components and understand them in detail. Here too, we can borrow ideas from options theory to look at a project risk as having several components. The expected value of the risk is the mean estimated impact cost of the risk. This has to be estimated, using some qualitative or quantitative techniques. The value of the risky project is analogous to the price of a financial asset, which has the uncertainty in its future value.
The planned cost of work scheduled is the exercise or strike price. This is the cost that has been budgeted for the project and this is the cost at which the project should complete. The cost of the project assuming risk is a variable, and depends upon the expected value of the risk. An assumption we make corroborated by most real-life examples is that project risk factors are temporal and dynamic.
This implies that any value placed on a risk is correct only at the time it was estimated. As additional information is available, the risk factors change and the estimated value of the risk changes. This creates an uncertainty or volatility.
Introduction to Risk Theory
The volatility factor explains why two people view similar risks differently. They attach different volatility to the value of the risk. The volatility imbeds the variability in the estimate of the risk value. If the event has a high degree of unpredictability, its variance will be high.
On the contrary, if it can be estimated quite accurately, the variance will be low and the actual value of the risk converges toward the expected risk value. So how can we capture the impact of volatility while we value the risk and make some concrete decisions based on the information available today? Email Address.
Financial Risks: Cases Of Non-Financial Enterprises
Sign In. Access provided by: anon Sign Out. Generally speaking, in practice as well as in literature there is a considerable gap between China and Western developed countries. Therefore, how to push forward and improve project finance in theory as an academic guidance needs urgent explorations.
In the light of China's unique features, this paper, with the help of the game theory, has an overall analysis to the risks and solve the problem of how to make decisions under asymmetric information. This book has become a classic reference for graduate students and researchers working in econophysics and mathematical finance, and for quantitative analysts working on risk management, derivative pricing and quantitative trading strategies. Table of contents Foreword; Preface; 1.
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Probability theory: basic notions; 2. Maximum and addition of random variables; 3. Continuous time limit, Ito calculus and path integrals; 4. Analysis of empirical data; 5. Financial products and financial markets; 6. Statistics of real prices: basic results; 7.
Non-linear correlations and volatility fluctuations; 8. Skewness and price-volatility correlations; 9. Cross-correlations; Risk measures; Extreme correlations and variety; Optimal portfolios; Futures and options: fundamental concepts; Options: hedging and residual risk; Options: the role of drift and correlations; Options: the Black and Scholes model; Options: some more specific problems; Options: minimum variance Monte-Carlo;