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Information in the term structure of variance swaps and CFO
predictions of volatility
Whit Graham, Josh Kaehler, Matt Seitz
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Agenda
• Variance Swaps– What is a variance swap?– Term structure– Initial analysis/ findings– Key questions/ ongoing analysis
• CFO Survey- volatility predictions– CFO survey data– Initial findings– Questions for further study
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Introduction to Variance Swaps
• Variance swaps are similar to an interest rate swap, except the cash flows are based on the volatility of an underlying asset. (in our case, the S&P 500)
• Variance swap has a set term (ranging from 1-24 months, a volatility “strike”, and a notional amount).
• The party “long” the variance swap agrees to pay the fixed strike price at maturity, and receives the realized variance (counterparty does the opposite).
• The strike price is typically higher than “fair”/ realized volatility, because variance swaps are convex to volatility.
Final Equity Payment = Variance Notional x (Realized Vol2 – Strike Price2)
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Variance Swaps- Term Structure
• Typical term structure- mildly upward sloping in “normal” times; downward sloping in times of crisis.
• Can change significantly over time!
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Variance swaps- initial analysis and findings• How well do variance swaps predict future realized
volatility?– Reasonably well in the short term (1-3 months), far less
accurate in the longer term.
• Does the “slope” of the curve have an impact?– Adding a “spread” or slope coefficient is always significant,
but does not necessarily add a lot of explanatory power
• Ability of S&P variance swaps to predict volatility in other markets?– Using the S&P 500 v/s rate to predict volatility in the FTSE,
DAX follows a similar pattern.
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Variance swaps- key questions & further analysis• Can we predict equity returns based on past volatility +
current v/s rates & term structure?
• If so, what would be the optimal trading strategy to capitalize? – How to determine how long to hold? Inclusion of “stop loss”
limits?
• Implications/ extension to international markets including FTSE, DAX
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Duke/CFO Magazine Global Business Outlook Survey Data
• Quarterly Survey of Financial Executives– Analysis uses data from Q2 2000 to present– Average of 350 respondents
• Gauges respondent’s opinion on important economic data– Asks for both short-term (1 year) and long-term (10 year)
market forecasts
• Study still relatively new with potential for untapped value
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Initial Areas for Study
• Does CFO volatility expectation have a relationship with what is realized in the market?– Responses Analyzed:
• Average of respondent standard deviations• Disagreement between respondent market risk premiums
• Does outlook CFO’s have for their own companies or the broader economy serve as an indicator of future volatility?– Responses Analyzed:
• Own firm optimism diffusion• Economy optimism diffusion
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Initial Takeaways
• Short-term CFO forecasts are better predictors of volatility
• Best relationships found with shorter horizon for realized volatility– i.e. “Disagreement” has better explanatory power for 1
month vol than 2 month vol
• Optimism of respondent’s own firm best indicator of short term volatility
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Ongoing Steps
• Testing best performers of first round of research on changes in implied volatility– Would allow for a quarterly VIX trading strategy
• Identify potential variance swap trading strategy based on current realized volatility research
• Address logistics of trading strategy– “Take profit” scenario, other signals