2. Option Pricing and Hedging Flashcards

1
Q

Describe binary calls and puts

A

Payoff = 1 when the option is in-the-money

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2
Q

Define gamma, theta, speed, vega, rho

A
  1. Gamma
    • Second derivative of the option price V w.r.t. the underlying S
    • Represents:
      • Sensitivity of delta w.r.t. the underlying
      • How much or how often a position must be rehedged to maintain a delta-neutral position
  2. Theta
    • Derivative of the option price V w.r.t. time t
    • Quantifies how much t contributes in a completely certain way
    • Option value decreases when T increases
  3. Speed
    • Third derivative of the option price V w.r.t. underlying S
    • Quantifies the rate at which gamma changes w.r.t. the underlying S
  4. Vega
    • Derivative of the option price V w.r.t. volatility parameter σ
    • Can add significant model risk because it relies on whether volatility is modeled correctly
    • Downfalls:
      • Only meaningful for options with single-signed gamma everywhere
      • Not as useful for analyzing binary options
  5. Rho
    • Sensitivity of an option value V w.r.t. parameter for interest rate r
    • Same model risk concern as vega, but less of it because r is easier to estimate than σ
    • Typically separated into buckets and term structure interest rates so r(t) can vary over time
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3
Q

Define portfolio insurance

A
  • Strategy when you:
    • Reduce stock holdings when prices fall,
    • Increase stock holdings when prices rise
  • Overall, option values due to portfolio insurance are balanced because of mean reversion
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4
Q

What are two types of hedging w.r.t. models?

A
  1. Model independent
    • Few and far in between
    • e.g., violations in Put-Call parity
  2. Model dependent
    • Most hedging strategies
    • Requires some kind of volatility model
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5
Q

What are some types of hedging w.r.t. greeks?

A
  • Delta
    • Exploits perfect correlation between option and underlying
  • Gamma
    • Reduces transaction costs, rebalancing needs
    • More accurate than delta hedging
  • Vega
    • Trading strategy that results in zero vega
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6
Q

Define static, margin and crash (platinum) hedging

A
  • Static hedging
    • Buying/selling a set of more liquid contracts to reduce the CFs of the original contract
    • Positions are left to expiry
  • Margin hedging
    • Portfolio set up such that margin calls are covered by refunds of hedging contracts
  • Crash (platinum) hedging
    • Minimizes worst possible outcome for the portfolio
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7
Q

Define implied volatility

A
  • Volatility of the underlying which, when used in B-S formula, results in market prices
  • Market consensus or estimate of volatility
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8
Q

Define actual volatility

A

Amount of randomness of a financial quantity that actually transpires at any given point

  • Amount of noise int he stock price
  • Wiener process coefficient in the stock returns model
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9
Q

Define historical, forward and hedging volatility

A
  1. Historical volatility
    • Backward-looking statistical measure
  2. Forward volatility
    • Actual or implied, for some time in the future
  3. Hedging volatility
    • What is plugged into the detla calculation
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10
Q

List types of models used for volatility

A
  • Econometric
    • Time-series analysis to estimate current and future expected actual volatility, e.g., GARCH
  • Deterministic
    • Deterministic volatility surface
    • Set σ(S,t) in the B-S model
    • Does not capture dynamics of volatility very well
  • Stochastic
    • Better captures the dynamics of traded option prices compared to deterministic
  • Poisson
    • Volatility jumps
  • Uncertain
    • Define a range of σ ⇒ range of prices
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11
Q

Compare and contrast pros/cons of hedging with actual and implied volatility

A
  1. Actual volatility
    • PROS:
      • Known profit at expiration, assuming continuous hedging
      • Most reasonable if mark-to-model strategy is followed
      • More leeway than implied volatility, as long as forecast is “good enough”
    • CONS:
      • Daily P&L volatility can be substantial ⇒ risks
      • Need to estimate actual volatility forecast for ∆
  2. Implied volatility
    • PROS:
      • Minimal local fluctuations in P&L (i.e., continual profit)
      • No need exact actual volatility estimation, just the right side of the trade
      • Easy to calculate because implied vol is observable
      • More reasonable if market value approach is used
    • CONS:
      • Final profit is unknown, just know that it will be positive
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12
Q

What are two trains of thought for the rationale behind option pricing movements?

What are some considerations when pricing options?

A
  1. Valuation (theory)
    • Prices are driven by B-S (theoretica, parameters, assumptions)
    • Option values are consistent with the price of the underlying
  2. Pricing (practice)
    • Prices are driven by supply and demand

Considerations:

  • OTM options sell at a premium
  • American options are difficult to price becasue early exercise is seldom done optimally
  • Embedded options are priced high because Σ parts > whole security
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13
Q

What is the power law survival function?

A

S(x) = K / xα

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14
Q

Compare/contrast normal and fractal distributions

A
  1. Normal/Gaussian
    • Nonscalable
    • Typical member is mediocre
    • Winner takes a piece of the pie
    • Ancestral environment
    • Not determined by a single instance
    • Tyranny of collective
    • Easy to predict from the past
  2. Fractal
    • Scalable
    • No typical member
    • Winnter takes all
    • Modern environment
    • Determined by a few events
    • Tyranny of accidental
    • Hard to predict from the past, need large window of observation
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15
Q

What is volatility smile?

How can it be built into pricing?

A
  • It is the graph of strike (K) vs. implied volatility, which may result in higher implied vol for OTM calls/puts
  • Can be built into pricing by:
    1. Deterministic volatility surface
      • May not describe actual dynamics very well
    2. Stochastic volatility models
      • Sources of randomness are stock returns and volatility
      • Greater potential to capture dynamics
    3. Jump diffusion model
      • Accommodate for excess kurtosis
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16
Q

What is vonma?

A
  • The second derivative of V w.r.t. σ
  • It is negative close to ATM, and >> 0 for ITM/OTM
    • Results in higher price and implied volatility for OTM options
  • If vonma > 0 ⇒ vega is positively related to volatility changes
  • If vonma < 0 ⇒ vega is inversely related to volatility changes
17
Q

What causes volatility smiles?

A

Due to:

  1. Supply and demand
    • ↑ OTM puts demand for insurance protection ⇒ ↑ price and σ of OTM puts
    • ↑ OTM calls supply to earn premium ⇒ ↓ price and σ of OTM calls
  2. Kurtosis / fat tails
  3. Correlation between stock prices and volatility
    • Dramatic ↓ in price ⇒ ↑ implied vol for puts with lower K
  4. Volatility gamma (vonma)
    • OTM puts have higher vonma ⇒ ↑ implied vol
18
Q

List 10 assumptions in B-S and how to take advantage of them

A
  1. Volatility is known
    • If σ ↑, buy a straddle/strangle
  2. No jumps
    • If expecting symmetric jumps, buy OTM options
  3. Constant rfr
    • If r ↑, buy calls/stocks and sell puts
  4. Borrowing = lending rates; infinite borrowing
    • If r > lending rates + borrowing limits ⇒ buy calls
    • If r < lending (no borrowing limits) ⇒ borrow instead of buy calls
    • If implied r ↑, buy options instead of stock
  5. Short sales can be invested
    • Instead of short stock, hold put or naked short call
  6. No transaction costs
    • Use arbitrage bands
  7. No taxes
  8. No dividends
  9. European options
  10. No early exercise or takeover events
    • May affect short-term OTM options dramatically
19
Q

List 7 assumptions in B-S and how to relax them

A
  1. Discrete hedging
    • Expected value is the same as continuous
  2. Transaction costs
    • Use volatility range to represent bid-ask spreads
  3. Time-dependent volatility
    • Use root-mean-square average variance over the remaining lifetime (T-t)
  4. Arbitrage opportunities
    • Use B-S to delta-hedge and determine how much profit you would like
  5. Non-lognormal underlying
    • Nothing to do
  6. Borrowing costs
    • Adjust drift, similar to dividend adjustment
  7. Non-normal returns
    • Nothing to do- only need finite variance of returns due to CLT
20
Q

What is the total PV of profit when hedging using actual volatility? And from time t to t + dt?

A

Va - Vi

e-r(t-t0) d(Va - Vi)

21
Q

What is the total PV of profit when hedging using implied volatility? And from time t to t + dt?

A

dVi = 1/2 (σ2 - σimp2) S2 Γi dt

dVi = 1/2 (σ2 - σimp2) ∫[t0, T] e-r(t-t0)S2 Γi dt

22
Q

What is the general total PV of profit formula?

A

V(S,t;σh) - V(S,t;σi) + 1/2(σ2 - σh2) ∫[t0, T]e-r(t-t0)S2Γh dt