The qualities of a model’s results depend heavily on the quality of the data feed.
Garbage in, garbage out (GIGO) is the law in risk management. Therefore, all data
inputs to a model should always be checked and validated carefully. Typically, should
you use a bid, an ask, or a mid-price? To discount, should you build a zero-coupon
curve, a swap curve, or a government bond curve? The difference can be quite
substantial on illiquid securities, and can impact all the subsequent computations.
Data sources should also be reduced to a minimum. For instance, on a liquid
market such as US Treasuries, the end of the day pricing can differ by up to 5 basis
points across sources. Added to a little leverage, this can result in a 2% valuation
error for a simple 10-year position. Another important problem is data synchronicity,
particularly if you are dealing with multiple currency or different time zone portfolios.
Where should you get the US dollar–Swiss franc exchange rate? In New York or in
Zurich at the close? Using non-simultaneous price input can lead to wrong pricing,
or create artificial arbitrage opportunities.
Hiç yorum yok:
Yorum Gönder