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### Time Horizont for measuring market Risk

Posted: **September 10th, 2014, 11:25 am**

by **slacknoise**

Hi all,I would like to measure the risk of my equity portfolio via a VaR model incorporating a Student-T Copula and Extreme Value theory. What is an appropriate historical time span to consider for the equities in order to so? I appreciate any help. kind regards,

### Time Horizont for measuring market Risk

Posted: **September 10th, 2014, 11:39 am**

by **Samsaveel**

Basel recommends a historical time period of minimum 250 trading day's.your VaR metric computed with the following parameters-for general MR management : 1-day @ 95% quantile-for Trading Book Capital : 10-day @ 99% quantile.industry practice to apply square root of time rule to scale VaR in time and space.howeverit is Model dependent.

### Time Horizont for measuring market Risk

Posted: **September 10th, 2014, 11:42 am**

by **slacknoise**

thanks for the insight and the fast reply. very much appreciated

### Time Horizont for measuring market Risk

Posted: **September 10th, 2014, 12:52 pm**

by **MHill**

"It depends"What's in your portfolio, and what's your forecast horizon?If all your equities are US equities, then all the close-of business prices happen at the same time. You can look at calculating VaR based on daily return timeseries. You want a good number of observations to make the volatility estimate of any one stock reasonable. So maybe 252 days is good.If your equities are global, then close-of-business prices are staggered across time zones. You're probably better basing the calculation on weekly returns. So to keep a good estimate of individual stock volatilities, you're going to need a longer historical period (252 weeks?).If you're predicting a 1-day VaR, then you want to try & base it on the recent past to try and 'capture the current volatility regime'. Maybe 1 year of daily returns is good.If you're predicting a 1-month VaR, then maybe you want to use 5 years of data to allow for changing volatility regimes.If you use exponetially weighted observations in your model, you also need to use a time period that is consistent with your half-life. Riskmetrics gives a rule of thumb that your history shoul dbe 3 to 6 times your half life. This means that the earliest observation gets 0.13 to 0.02 times as much weight as the latest observation.

### Time Horizont for measuring market Risk

Posted: **September 10th, 2014, 1:39 pm**

by **slacknoise**

QuoteOriginally posted by: MHill"It depends"If your equities are global, then close-of-business prices are staggered across time zones. You're probably better basing the calculation on weekly returns. So to keep a good estimate of individual stock volatilities, you're going to need a longer historical period (252 weeks?).thanks for the advise. I am dealing with chileanen equities and ADR's and i am interested in 1day VaR and 1 month VaR so thats really helpful

### Time Horizont for measuring market Risk

Posted: **September 11th, 2014, 8:38 am**

by **DominicConnor**

It is worth trawling through to find the worst case that your data supports, not just what is required to keep risk management happy

### Time Horizont for measuring market Risk

Posted: **September 11th, 2014, 1:00 pm**

by **rmax**

Depends also on what you are measuring. I.e. I have seen 500 day historic, 250 day Stress with 250 day antithetic scenarios applied.

### Time Horizont for measuring market Risk

Posted: **September 11th, 2014, 1:02 pm**

by **Samsaveel**

how do you define antithetic scenarios ?

### Time Horizont for measuring market Risk

Posted: **September 11th, 2014, 2:32 pm**

by **DavidJN**

"how do you define antithetic scenarios ?"Say you have N observations of historical price changes.Extend the vector by multiplying each one of those changes by -1.Now you have 2*N observations.The same tactic is often used in Monte Carlo simulation - you draw your random number and then generate another one by multiplying it by -1.I am not sure "scenarios" is the right word to use here, what we are really talking about are historical observations, I suppose one could generously call them scenarios.

### Time Horizont for measuring market Risk

Posted: **September 11th, 2014, 2:37 pm**

by **slacknoise**

Has anyone here experience with real time VaR models concerning this topic?

### Time Horizont for measuring market Risk

Posted: **September 11th, 2014, 3:21 pm**

by **Samsaveel**

QuoteOriginally posted by: DavidJN"how do you define antithetic scenarios ?"Say you have N observations of historical price changes.Extend the vector by multiplying each one of those changes by -1.Now you have 2*N observations.The same tactic is often used in Monte Carlo simulation - you draw your random number and then generate another one by multiplying it by -1.I am not sure "scenarios" is the right word to use here, what we are really talking about are historical observations, I suppose one could generously call them scenarios.so in terms of P&L ,we are dealing with antithetic P/L ,and that is L/P , it makes VaR more intuitive as it becomes a positive number for a positive quantile under antithetictransformation. is this the correct logos ?

### Time Horizont for measuring market Risk

Posted: **September 11th, 2014, 3:32 pm**

by **rmax**

QuoteOriginally posted by: slacknoiseHas anyone here experience with real time VaR models concerning this topic?Not directly. I know a group at a large German Firm were looking into it, but I don't know how far they got. There were looking at using FPGA to get the necessary increase in performance. I don't know if it went anywhere.

### Time Horizont for measuring market Risk

Posted: **September 11th, 2014, 3:50 pm**

by **riskguru**

QuoteOriginally posted by: slacknoiseHas anyone here experience with real time VaR models concerning this topic?Incrementally, what are you trying to pick up with the "real time" version? Intraday trading? I would think this would be relatively straightforward if all you trade is cash equities? Going back to your original question on window length etc. I have two suggestions: First, use more than one (a lot of folks use short, medium and long horizon based VaR numbers) and second, backtest backtest backtest! That way you will have a bit of an early warning if the regime is changing. I hope this helps.

### Time Horizont for measuring market Risk

Posted: **September 11th, 2014, 4:51 pm**

by **slacknoise**

Going back to your original question on window length etc. I have two suggestions: First, use more than one (a lot of folks use short, medium and long horizon based VaR numbers) and second, backtest backtest backtest! That way you will have a bit of an early warning if the regime is changing. I hope this helps.thanks i will consider it in my model

### Time Horizont for measuring market Risk

Posted: **September 11th, 2014, 7:05 pm**

by **tula**

QuoteOriginally posted by: DavidJN"how do you define antithetic scenarios ?"Say you have N observations of historical price changes.Extend the vector by multiplying each one of those changes by -1.While this is useful to reduce noise in a Monte Carlo context, I dont see why this would make sense with historical data. Wouldn't it just distort your dataset?