Strategic Risk Management and Product Market Competition

1. Strategic Risk Managementand Product Market Competition Tim R. Adam National University of Singapore & RMI Amrita Nain McGill University Comments welcome!

2. Theory of Corporate Risk Management Firm-specific factors • Taxes (Smith and Stulz, 1985) • Financial distress costs (Smith and Stulz, 1985) • Information asymmetries & agency costs (Froot, Scharfstein and Stein, 1993, DeMarzo and Duffie, 1991, …) • Risk-aversion of stakeholders (Smith and Stulz, 1985) Industry-specific factors • Degree of competition, hedging decisions of competitors (Mello & Ruckes, 2006, Adam, Dasgupta and Titman, 2007) • Derivatives decisions are not made in isolation but take the decisions of competitors into account.

3. Empirical Literature • Nance, Smith and Smithson (1993), Mian (1996), Dolde (1993) Geczy, Minton and Schrand (1997), Tufano (1996), Haushalter (2000), Allayannis and Ofek (2001), Brown (2001), Graham and Rogers (2002), Adam and Fernando (2006), Lel (2006), … • Most variation in derivatives strategies cannot be explained by traditional models of hedging / firm-specific factors. • Brown (2001) studies risk management at a major durable goods producer (HDG). • Earnings management and competitive concerns in the product market motivate HDG’s FX risk management rather than the traditional models of hedging. • HDG tracks the hedging programs of its major US-based competitors.

4. Objective • Are industry-specific factors likely to be important in determining a firm’s derivatives strategy? • Do the derivatives strategies of competitors matter? • Does the degree of competition affect derivatives strategies? • Derive testable hypotheses based on the models by Adam, Dasgupta and Titman (2007), and Mello and Ruckes (2006).

5. The ADT Model • Analyze firms’ hedging decisions within the context of an industry equilibrium. • n identical firms, Cournot competition • Common cash flow (cost) shocks • Firms hedge their cash flows as in FSS (1993) • Cost effect: Hedging reduces expected costs • Flexibility (real option) effect: Volatility in cash flows is beneficial because firms can choose output after observing their cash flows. • Low cash flow → high marginal cost → reduce production • High cash flow → low marginal cost → increase production • Shleifer and Vishney (1992) effect: Firms benefit if their cash flows are high when their competitors have low cash flows and vice versa. • Low agg. cash flow → high price → high investment opportunities • High agg. cash flow → low price → low investment opportunities

6. Why Symmetric Equilibria Don’t Exist • Suppose all firms hedge their cash flows • Constant cash flows  constant costs  constant output  constant price • A financially constrained firm benefits from volatility in its cash flow (marginal cost) because when its cash flow is high it produces more and when its cash flow is low it produces less. (Flexibility effect) • Suppose no firm hedges • Variable cash flows  variable costs  variable output  variable price • Firms have high cash flows when prices are low and vice versa. • A financially constrained firm benefits from shifting cash from states with low marginal productivity (high cash flow states) to those with high marginal productivity (low cash flow states). (Shleifer and Vishney (1992) effect)

7. Testable Hypotheses Do derivatives strategies of competitors matter? • Is the sensitivity of output prices (to FX shocks) affected by aggregate hedging decisions? • Is a firm’s exposure affected by aggregate hedging decisions? • Most firms hedge • Exposure of a hedged firm is low • Exposure of an unhedged firm is high • Most firms do not hedge • Exposure of an unhedged firm is low • Exposure of a hedged firm is high Degree of competition • Does the degree of competition affect aggregate hedging decisions?

8. Data • Derivatives data • Search all SEC 10-K filings for year of 1999 for text strings such as “hedg”, “swap”, “cap”, “forward”, etc. • Match sample with Compustat firms. Exclude financial firms and utilities. • Collect gross notional amounts of FX derivatives (forwards, swaps, options). • Ex-ante exposure data • We classify firms as having ex-ante FX exposure if they disclose foreign assets, foreign sales, foreign income, foreign taxes, exchange rate effect, or foreign currency adjustments.

9. Firm Characteristics Firms with ex-ante FX exposure only.

10. Industry Characteristics (6-digit NAICS)

11. Estimating the Sensitivity of Producer Prices to FX shocks • Following Feinberg (1989), we estimate the following model using monthly data from 1996 to 2000. RPPIjt = real producer price index EXCHt = real trade-weighted value of the U.S. dollar against its major trading partners FRACTIONjt = market value-weighted fraction of FCD users • Price sensitivity may be a function of FRACTION (endog.) Instrument: fraction of IR derivatives users (2SLS); model is estimated in log changes; Newey-West standard errors.

12. Price Sensitivity to FX Shocks

13. Key Results • When the USD depreciates (EXCH ↓) and the cost of imports rise, domestic producer prices increase. • A real depreciation of the US$ by 10% increases real domestic producer prices by 0.77%. • The price sensitivity (pass-through) is lower • in industries in which FX derivatives usage is more widespread • in industries that use fewer foreign inputs • in industries that export more • in less concentrated (more competitive) industries

14. Determinants of Exposure • Is a firm’s exposure affected by aggregate hedging decisions? • Estimate firms’ ex-post FX exposures. • Analyze the exposures of FCD users and non-users.

15. Estimating the FX Exposure of Firms • For each firm we estimate the following market model using monthly returns from 1996 to 2000. rit = firm i’s stock return rmt = value-weighted market return ΔEXCHt = change in trade-weighted value of the U.S. dollar against its major trading partners • The FX exposure estimates ßixrange from -1.03 to 1.22. Out of 3,036 firms 344 firms have significant exposures to the trade-weighted value of the U.S. dollar.

16. Comparison of FX Exposures Top figures denote means, bottom figures denote medians. FCD users have lower exposures to the trade-weighted value of the U.S. dollar than FCD non-users.

17. FCD USERS FCD NON USERS Distribution of Exposure Coefficients Avg. FRACTION of FCD Users = 0.42 Avg. FRACTION of FCD Users = 0.35 Avg. FRACTION of FCD Users = 0.33 Avg. FRACTION of FCD Users = 0.39

18. Aggregate Hedging and FX Exposures

19. Aggregate Hedging and FX Exposures

20. Key Results • FCD users have lower ex-post FX exposures than FCD non-users. • As the fraction of derivatives users increases, the exposure • of FCD users declines • of FCD non-users increases.

21. Derivatives Usage and Competition • Allayannis and Ihrig (2001) • Exposures increase as mark-ups fall.  Firms that operate in more competitive industries face larger exposures and therefore are more likely to hedge. • Mello and Ruckes (2006) • Firms hedge less if competition is more intense in order to gain a competitive advantage (market share) if prices move favorably. • Adam, Dasgupta and Titman (2007) • Competition can have a positive or negative impact on the number of firms that hedge in equilibrium, depending on whether hedging or not hedging is optimal in the absence of any competitive interaction between firms.

22. Testable Hypotheses Degree of competition • Does the degree of competition affect aggregate hedging decisions? • Do firms hedge less in more competitive industries? Fraction of FCD users ½ # of firms (competition)

23. Equilibrium In equilibrium EΠh(w) – EΠu(w)  0 The proportion of firms that use derivatives is given by • Flexibility effect dominates • cost reduction effect • Small market share (a - α) • Cost reduction dominates • flexibility effect • Large market share (a - α) Fraction of firms hedging 0 ½ 1

24. Measuring the Degree of Competition

25. Fraction of FCD Users

27. Extent of FCD Usage

28. Summary • Output prices are less sensitive to FX shocks (lower pass-through) if more firms use derivatives. • Firms’ FX exposures appear to be a function of the prevalence of derivatives usage. • If derivatives usage is widespread, FCD users exhibit relatively low exposures, while FCD non-users exhibit relatively high exposures. • If derivatives usage is less common, FCD users exhibit relatively high exposures, while FCD non-users exhibit relatively low exposures. • In more competitive industries fewer firms use derivatives. • In more competitive industries the average size of derivatives positions is lower.