Topic 6: Methods for Alts Flashcards
What are the 4 key components of risk-neutral modelling?
- INFINITE sets of values (P measure prob, risk premium, recovery etc) consistent with particular derivative value
- ONE set of Q measures with inputs readily observable and easy to apply. In risk-neutral world, risk premiums = 0
- Values obtained from Q identical to no-arbitrage values in risk averse using P
- Q used in conditions in which actual Deriv. prices must match risk-neutral model prices
3 Fallacies due to Averaging Compounded Returns
Non-0 NPVs CANNOT be generated when assets are efficiently priced: e.g. leverage or inverse ETF
Rebalancing does not generate better performance due to better diversification, for efficient assets (when 0 NPV)
Which of the following most closely represents risk premiums of risk-neutral investors?
- 0%
- 100%
- -100%
0%. Risk-neutral investors do not require compensation for bearing risk. Therefore, they have zero risk premiums.
4 steps of fundamental strategy
- idea generation
- idea expression
- sizing
- trade execution
Define sentiment
Beliefs about future cash flows and risks NOT justified by objective analysis of facts.
According to Baker and Wurglur, what are the six sentiment indicators?
- discount on closed-end funds
- turnover of NYSE shares
- # of IPOs
- avg first day IPO returns
- equity shares in new issues
- dividend payment
The Golden Future Hedge Fund has conducted an internal study on the trading records of its senior traders. The trading record of Kano Gunma shows that he realized profits too quickly and held losing positions for a long time. To which of the following biases is Kano most likely subject?
Disposition effect: causes investors to realize profits too quickly and not cut losses in a timely fashion
What is Principal Component Analysis?
Linear statistical technique which identifies orthogonal (uncorrelated) statistical factors or principal components “PC” that maximise percentage of explained variation
What is factor analysis?
Identifies factors and their coefficients by optimising a model with statistical assumptions
Difference between Factor Analysis and Principal Component Analysis?
- FA makes assumptions about returns process; PCA does not require a model (simply maxes explained variance)
- FA generates different factor scores when model has different #s of factors; PCA loadings do not change when # of components change
- FA seeks factors that drive at least 2 securities; PCA can identify a factor driven almost entirely by one security
Challenge with Multiple Regression Models
Realised return may be correlated with factors
Factors may not have risk premium
CHALLENGE: selecting appropriate indepedent variable
THUS omitted factors falsely attribute to alpha = captured at intercept = inflated alpha
Add factors = higher r-square
Three factors for Fama French Model
- Market risk premium
- Size premium
- Value premium
Name the ways that data set could work against multiple regression models
- outliers
- autocorrelation
- heteroskedasticity
- multicollinearity = indep variables correlated with one another
What are the adverse effects of multicollinearity?
- slope estimates may be inaccurate
- standard error of the coefficient estimates (B) can be inflated
SOLUTION: create a new variable from 2 correlated explanatory variable
What is stepwise regression?
Finding an independent variables by keeping variables with greatest t-statistics and deleting with insignificant t-stats
What is stepwise regression used for?
Stepwise regression is used to determine the independent (explanatory) variables that should be included in a regression model. It involves adding or removing variables from a model based on their statistical significance (i.e., their t-statistics).
What is Positive conditional correlation
Positive conditional correlation refers an environment in which correlation in up markets exceeds correlation in down markets. Negative conditional correlation refers to correlations in down markets exceeding correlations in up markets.
Investors typically prefer positive conditional correlation, since this environment provides investors with greater participation in profitable opportunities in markets that rose and less participation in losses in markets that declined.
Laszlo Paul has developed a statistical method for hedge fund replication based on specialized market factors. Which of the following characteristics is this method most likely to have?
identifies factors based on how well they explain OVERALL MARKET or PARTICULAR HEDGE FUND’S return in order to replicate the hedge fund’s return based on these factors
identifies factors based on how well they explain particular hedge fund’s return in order to replicate the hedge fund’s return based on these factors
Dummy variable regression analysis is used to test
Market timing ability
Which of the following represents a way to estimate a first-order partial autocorrelation?
A.as the first factor in a principal component analysis
B.as the intercept of a multi-factor model
C.as the first variable selected in a stepwise regression
D.as the beta coefficient of the first regression factor
Partial autocorrelations (PAs) may be found as the beta coefficients of the factors in a regression model. The first-order PA corresponds to the beta of the first factor, the 2nd-order PA corresponds to the beta of the second factor, etc.
An individual hedge fund’s returns are generally best explained by which of the following?
Hedge fund’s trading style OR returns of funds using similar strategies
Trading style
Which of the following best represent characteristics of principal component analysis performed on a set of stock returns for several companies?
I. Resulting principal components are orthogonal.
II. Resulting factor loadings represent each stock’s return variance.
III. Resulting factors represents the smallest percentage of explained stock return variance.
I only
- A factor loading represents a stock’s RESPONSIVENESS to a particular factor (or principal component). Thus, factor loadings are similar to betas in regression models.
- Factors represents the greatest percentage of explained stock return variance.
Which of the following is considered an advantage of principal component analysis?
A.visualization
B.dimensionality reduction
C.factors with largest t-statistics
An advantage of principal component analysis is dimensionality reduction: it significantly reduces the dimensions of the original data set (from perhaps thousands of variables to a few), which results in a relatively small number of factors.
What is a typical crack spread
A crack spread is the spread created in commodity markets by purchasing oil futures and offsetting the position by selling gasoline and heating oil futures.
What is relative value strategies?
Long and short relatively misplaced instruments; deviated from stable relationship; profit when values converge and relationship re-established.
Strategy aims to hedge out directional risk
Commmodity Based RV strategies - three dimensions
- Time
- Correlation
- Location
Crack spread
Used by oil refineries - long crude oil futures, short gas and heating oil futures
Crush spread
Long soybean futures and short soybean oil futures and soy meal futures
Carry trade’s risks
- Funding ccy interest rate increases
- Funding ccy appreciates relative to target
- Target ccy does not provide expected yield
Covered Interest Rate Partity (CIP)
Borrowing in one currency and investing proceeds in another while hedging currency risk in forward market should not be profitable
Risks in Pairs Trading Strategies
- Noise Traders: mostly idiosyncratic, spread between co-integrated prices to widen
- Fundamental: idiosyncratic
- Corp Event:
- Synchronisation: pairs positions because price not converged in time (investors slow to react to divergence)
- liquidity risk - systematic
- short-sale risk - idiosyncratic, cover shorts at unattractive prices
- model risk - undiversifiable
- financing risk
Equity Market Neutral Strategies
Aim to exploit inefficiencies without much exposure to significant systematic risks.
Correlation and Beta are measures of market neutrality, but uncorrelated is not necessarily statistically independent.
Correlation: linear relationship
Three types of market neutrality
- Monetary: equal long/short exposures to ccy
- Beta: equal equity market betas of long/short
- Sector: returns uncorrelated with sectors
Co-integrated stock prices
Linear combination that is a stationary process
In a commodity substitution spread, the relative performance of the commodities is typically expressed as:
Natural log of the ratio of commodity prices.
This removes the effects of different specifications for each of the commodities, such as price and contract size.
A petroleum refiner executes a crack spread by buying crude oil futures and selling futures on the refined products. What is a ratio of a crack spread
Crack spreads are expressed as X:Y:Z, where X is the # of barrels of crude, Y is the # of barrels of gasoline, and Z is the # of barrels of heating oil; where X = Y + Z.
E.g., a 3:2:1 spread reflects 3 barrels of crude to produce 2 barrels of gasoline and 1 barrels of heating oil.
Threshold signal for pairs trading
historical standard deviation of the spread between the two stocks
In a commodity substitution spread, the relative performance of the commodities is typically expressed as
natural log of the ratio of commodity prices
Returns on successful pairs trading strategies have HIGH / LOW correlations with overall market changes
LOW correlations (low beta)’
Definition of arbitrage
- Textbook definition of arbitrage is earning virtually riskless profit while making little or no investment.
- Pure arbitrage involves a level of risk that is so close to zero that any risk can be ignored as inconsequential.
- Risk arbitrage refers to profit opportunities with enough risk that it is appropriate to explicitly indicate that the supposed arbitrage comes with nontrivial risk.
Four principles of Depreciation
- when an investment’s purchase price is depreciated at an ACCELERATED depreciation rate relative to true economic depreciation, its AFTER-TAX return is GREATER than its PRE-TAX RETURN, LESS TAX RATE (and less than its pre-tax return).
- depreciated at rate SLOWER than true economic depreciation, AFTER-TAX return is LESS than PRE-TAX RETURN
- When immediately expensed, after-tax IRR = pre-tax IRR
- When depreciated at rate = true economic appreciation, after-tax return is pre-tax reduced by tax rate
When does noisy pricing occur
Noisy pricing occur because a transaction price is selected from a range of reservation prices (i.e., lowest price at which potential sellers will sell a property, or highest price potential buyers will pay for a property) or because real estate appraisals are used, which vary (since they are based on appraisers’ opinions).
An analyst estimates the value of a real estate property, which results in a random estimation error. To reduce this error and improve the estimated value of the property, she performs the valuation again using a larger set of data. Which of the following most likely occurs as a result in her changed valuation process?
The temporal lag bias increases.
There is a trade-off between the random estimation error and the temporal lag bias - when one decreases, the other increases.
What are the key disadvantages of Hedonic Price Movement
- large data set
- sample selection bias
- specification error
What are the key advantages of Hedonic Price Movement
- uses all transactions - not just repeat sales
- versatile
- does not make backward adjustments of historical returns
