2. Option Pricing and Hedging Flashcards
Describe binary calls and puts
Payoff = 1 when the option is in-the-money
Define gamma, theta, speed, vega, rho
- 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
- 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
- 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
- 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
- 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
Define portfolio insurance
- 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
What are two types of hedging w.r.t. models?
- Model independent
- Few and far in between
- e.g., violations in Put-Call parity
- Model dependent
- Most hedging strategies
- Requires some kind of volatility model
What are some types of hedging w.r.t. greeks?
- 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
Define static, margin and crash (platinum) hedging
- 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
Define implied volatility
- Volatility of the underlying which, when used in B-S formula, results in market prices
- Market consensus or estimate of volatility
Define actual volatility
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
Define historical, forward and hedging volatility
- Historical volatility
- Backward-looking statistical measure
- Forward volatility
- Actual or implied, for some time in the future
- Hedging volatility
- What is plugged into the detla calculation
List types of models used for volatility
- 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
Compare and contrast pros/cons of hedging with actual and implied volatility
- 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 ∆
- PROS:
- 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
- PROS:
What are two trains of thought for the rationale behind option pricing movements?
What are some considerations when pricing options?
- Valuation (theory)
- Prices are driven by B-S (theoretica, parameters, assumptions)
- Option values are consistent with the price of the underlying
- 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
What is the power law survival function?
S(x) = K / xα
Compare/contrast normal and fractal distributions
- 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
- 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
What is volatility smile?
How can it be built into pricing?
- 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:
- Deterministic volatility surface
- May not describe actual dynamics very well
- Stochastic volatility models
- Sources of randomness are stock returns and volatility
- Greater potential to capture dynamics
- Jump diffusion model
- Accommodate for excess kurtosis
- Deterministic volatility surface
What is vonma?
- 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
What causes volatility smiles?
Due to:
- 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
- Kurtosis / fat tails
- Correlation between stock prices and volatility
- Dramatic ↓ in price ⇒ ↑ implied vol for puts with lower K
- Volatility gamma (vonma)
- OTM puts have higher vonma ⇒ ↑ implied vol
List 10 assumptions in B-S and how to take advantage of them
- Volatility is known
- If σ ↑, buy a straddle/strangle
- No jumps
- If expecting symmetric jumps, buy OTM options
- Constant rfr
- If r ↑, buy calls/stocks and sell puts
- 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
- Short sales can be invested
- Instead of short stock, hold put or naked short call
- No transaction costs
- Use arbitrage bands
- No taxes
- No dividends
- European options
- No early exercise or takeover events
- May affect short-term OTM options dramatically
List 7 assumptions in B-S and how to relax them
- Discrete hedging
- Expected value is the same as continuous
- Transaction costs
- Use volatility range to represent bid-ask spreads
- Time-dependent volatility
- Use root-mean-square average variance over the remaining lifetime (T-t)
- Arbitrage opportunities
- Use B-S to delta-hedge and determine how much profit you would like
- Non-lognormal underlying
- Nothing to do
- Borrowing costs
- Adjust drift, similar to dividend adjustment
- Non-normal returns
- Nothing to do- only need finite variance of returns due to CLT
What is the total PV of profit when hedging using actual volatility? And from time t to t + dt?
Va - Vi
e-r(t-t0) d(Va - Vi)
What is the total PV of profit when hedging using implied volatility? And from time t to t + dt?
dVi = 1/2 (σ2 - σimp2) S2 Γi dt
dVi = 1/2 (σ2 - σimp2) ∫[t0, T] e-r(t-t0)S2 Γi dt
What is the general total PV of profit formula?
V(S,t;σh) - V(S,t;σi) + 1/2(σ2 - σh2) ∫[t0, T]e-r(t-t0)S2Γh dt