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## LTCM’s Analysis of Risk Management

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**LTCM’s Analysis of Risk Management**February 28, 2002 Frank Burke Larry Kissko Gurkan Salk Heather King**Agenda**• LTCM Background • Swap Spread Trading Strategy • Project Analysis • Comparison/measurement of LTCM’s Risk Assessment • Discussion on return and spread distribution, calculated implied std deviation • Estimate of LTCM’s Value-At-Risk • Proxy Tests • Take-aways**LTCM Background**• August 21, 1998, fund lost $550m mostly from swaps spreads and equity volatility bets. • LTCM believed this event would occur 1 in every 800 trillion years (or an 8.3 std dev move). • Swap spreads shot up from 60 bps to 80 bps intraday vs. an average daily move of 2 bps • LTCM’s swap position represented 2.4% of global swap market in December 1997 • Leverage ratios varied from 28:1 to a high of 55:1 in late 1998**LTCM Trading Strategy**We focused on of one of LTCM’s biggest trades: • Swap Spread Relative Value Trade • Swap spread – difference between the fixed rate on a fixed-for-floating swap and the yield on a coupon-bearing Treasury bond of comparable maturity • Speculative strategy that spread would converge to its historical mean • Long swap/short the treasuries (in 1998) • Crisis: Aug 21, spreads spiked 21 bps intra-day**Project Analysis**• Parametric VAR – assumes normal distribution • Historical VAR – based on actual data distribution • Proxy search – difficult to find a strong correlation • BAA- 10 year treasury • AAA- 10 year treasury • MBS - 10 year treasury • Forecasted daily variance Value At Risk – defined as the expected maximum loss over a target horizon within a given confidence interval**Value at Risk (VAR)**• Principal measure of risk at LTCM • LTCM parametric VAR measure • Capital (assume $1b) x daily std dev of returns (.02) x std dev of required confidence interval (3 = 99.85% 1-tail) • $1.0b x 2% x 3 = $60,000,000 • Our historical VAR measure • $ 1.0b x 9.5238% = $95,238,000**Take-Away Thoughts**• VAR not necessarily suspect – correct inputs are critical • Cannot blindly apply normal distribution • Dig into your data • If data is not complete consider: • Developing a risk proxy • Assuming fatter tails in distribution (Student’s T curve)**Appendix - charts**August 21, 2002**References**• Jorion, P., 2000 Risk Management Lessons from LTCM • Kolman, Joe, 1999, “LTCM Speaks”, Derivatives Strategy (April) p.12-17 • Lewis, Michael, 1999, “How the Egg-Heads Cracked” New York Times Magazine, January 24, p 24-77 • Anonymous, 1998, “Too Clever By Half”, The Economist Magazine, November 14 • Whaley, Robert, 2001, “Derivatives” Class Presentation • Scholes, Myron, 2000, “Crisis and Risk Management- The Near Crash of 1998”, AEA Papers and Proceedings Vol 90 No. 2, May. • Bloomberg – Swap spread data