Editing Value at risk (section)

== VaR risk management ==
{{further|Financial risk management#Investment banking}}
Supporters of VaR-based risk management claim the first and possibly greatest benefit of VaR is the improvement in [[systems]] and modeling it forces on an institution. In 1997, [[Philippe Jorion]] [https://web.archive.org/web/20170706074507/http://www.derivativesstrategy.com/magazine/archive/1997/0497fea2.asp wrote]:<ref name="Jorion I">{{cite conference|first1=Philippe|last1=Jorion|title=The Jorion-Taleb Debate|publisher=Derivatives Strategy|date=April 1997}}</ref><blockquote>[T]he greatest benefit of VAR lies in the imposition of a structured methodology for critically thinking about risk. Institutions that go through the process of computing their VAR are forced to confront their exposure to financial risks and to set up a proper risk management function. Thus the process of getting to VAR may be as important as the number itself.</blockquote>

Publishing a daily number, on-time and with specified [[Statistics|statistical]] properties holds every part of a trading organization to a high objective standard. Robust backup systems and default assumptions must be implemented. Positions that are reported, modeled or priced incorrectly stand out, as do data feeds that are inaccurate or late and systems that are too-frequently down. Anything that affects profit and loss that is left out of other reports will show up either in inflated VaR or excessive VaR breaks. "A risk-taking institution that ''does not'' compute VaR might escape disaster, but an institution that ''cannot'' compute VaR will not."<ref name="Einhorn I">{{cite journal|author=Aaron Brown|title=Private Profits and Socialized Risk|journal=GARP Risk Review|date=June–July 2008|author-link=Aaron Brown (financial author)}}</ref>

The second claimed benefit of VaR is that it separates risk into two regimes. Inside the VaR limit, conventional [[statistical]] methods are reliable. Relatively short-term and specific data can be used for analysis. Probability estimates are meaningful because there are enough data to test them. In a sense, there is no true risk because these are a sum of many [[Statistical independence|independent]] observations with a left bound on the outcome. For example, a casino does not worry about whether red or black will come up on the next roulette spin. Risk managers encourage productive risk-taking in this regime, because there is little true cost. People tend to worry too much about these risks because they happen frequently, and not enough about what might happen on the worst days.<ref name="Haug" />

Outside the VaR limit, all bets are off. Risk should be analyzed with [[stress testing]] based on long-term and broad market data.<ref name="Zask">{{Citation|author=Ezra Zask|title=Taking the Stress Out of Stress Testing|publisher=Derivative Strategy|date=February 1999}}</ref> Probability statements are no longer meaningful.<ref name="Roundtable II">{{cite journal|first1=Joe|last1=Kolman|first2=Michael|last2=Onak|first3=Philippe|last3=Jorion|first4=Nassim|last4=Taleb|first5=Emanuel|last5=Derman|first6=Blu|last6=Putnam|first7=Richard|last7=Sandor|first8=Stan|last8=Jonas|first9=Ron|last9=Dembo|first10=George|last10=Holt|first11=Richard|last11=Tanenbaum|first12=William|last12=Margrabe|first13=Dan|last13=Mudge|first14=James|last14=Lam|first15=Jim|last15=Rozsypal|title=Roundtable: The Limits of Models|journal=Derivatives Strategy|date=April 1998}}</ref> Knowing the distribution of losses beyond the VaR point is both impossible and useless. The risk manager should concentrate instead on making sure good plans are in place to limit the loss if possible, and to survive the loss if not.<ref name="Jorion" />

One specific system uses three regimes.<ref name="Size">{{cite journal|author=Aaron Brown|title=On Stressing the Right Size|journal=GARP Risk Review|date=December 2007|author-link=Aaron Brown (financial author)}}</ref>

# One to three times VaR are normal occurrences. Periodic VaR breaks are expected. The loss distribution typically has [[Kurtosis|fat tails]], and there might be more than one break in a short period of time. Moreover, markets may be abnormal and trading may exacerbate losses, and losses taken may not be measured in daily [[financial statements|marks]], such as lawsuits, loss of employee morale and market confidence and impairment of brand names. An institution that cannot deal with three times VaR losses as routine events probably will not survive long enough to put a VaR system in place.
# Three to ten times VaR is the range for [[stress testing]]. Institutions should be confident they have examined all the foreseeable events that will cause losses in this range, and are prepared to survive them. These events are too rare to estimate probabilities reliably, so risk/return calculations are useless.
# Foreseeable events should not cause losses beyond ten times VaR. If they do they should be [[Hedge (finance)|hedged]] or insured, or the business plan should be changed to avoid them, or VaR should be increased. It is hard to run a business if foreseeable losses are orders of magnitude larger than very large everyday losses. It is hard to plan for these events because they are out of scale with daily experience.

Another reason VaR is useful as a metric is due to its ability to compress the riskiness of a portfolio to a single number, making it comparable across different portfolios (of different assets). Within any portfolio it is also possible to isolate specific positions that might better hedge the portfolio to reduce, and minimise, the VaR.<ref name=PHIRS>[http://www.tradinginterestrates.com The Pricing and Hedging of Interest Rate Derivatives: A Practical Guide to Swaps], J H M Darbyshire, 2016, {{ISBN|978-0995455511}}</ref>