5: Hedge Funds Flashcards

1
Q

Risk-Return Benefits of CTAs

A
  1. Diversification
  2. Performance (better than long-only commodities)
  3. Access to multiple markets
  4. Transparency
  5. Liquidity
  6. Size
  7. No withholding taxes
  8. Low foreign exchange risk
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2
Q

Futures vs. Forwards

A

Futures

  1. Require daily cash settlement
  2. No net liquidating value
  3. Post collateral to cover daily losses
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3
Q

Advantages of systematic over discretionary strategies

A
  1. No emotional bias
  2. Lower key person risk
  3. More scalable
  4. More diversified
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4
Q

NFA and CFTC

A

NFA is responsible for introducing brokers, CTAs, CPOs and FCMs. It is an independent self-regulating body.

CFTC is a federal agency

The goal of both is to protect US investors trading on US or non-US exchanges.

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5
Q

Multi-currency and single-currency margining

A

If clients are moving numerous currencies in various global markets then their clearing broker (CB) is using multi-currency margining. Advantage: no transactions costs related to converting currencies. Disadvantage: exposure to change in FX gains or losses.

The CB can offer single currency margining, clients deposit one currency with the broker and CB is responsible for converting client’s money into collateral that is accepted at given exchanges.

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6
Q

3 terms for futures positions

A
  1. Trading level
  2. Funding level
  3. Notional level (1 - 2)
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7
Q

Margin to Equity ratio

A

Required Margin / Equity

The higher the ratio, the higher leverage levels, the higher the fund volatility

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8
Q

3 forms of market efficiency

A
  1. Weak form: claims that prices incorporate historical information
  2. Semi-strong: claims that prices incorporate historical and currently available public info
  3. Strong-form: claims that prices incorporate public and private info
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9
Q

Data mining

A

assessing numerous strategies to identify one that has worked in the past

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10
Q

Data snooping

A

being influenced by past findings and not using random samples for analysis

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11
Q

Over-reaction and Under-reaction mechanisms

A

Under-reaction (undershoot intrinsic value):

  1. Anchoring: bias to previous value or beliefs
  2. Disposition effect: closing profitable positions too quickly and holding onto losing positions for too long

Over-reaction (overshoot intrinsic value):

  1. Herding: join the crowd
  2. Confirmation bias: favor data that confirms a thesis
  3. Representative bias: look at past prices to form beliefs
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12
Q

3 technical analysis approaches for trend followers

A
  1. Moving average based systems: simplest and most popular, generates long. short position based on whether current price is above/below a given moving average. Ex: dual cross-over mov. avg. system which compares ST mov avg to LT mov avg.
  2. Price channels: aka trading range breakouts looks at new highs or lows (ex: 52 week highs) to find indication of a continued trend
  3. RSI: aka momentum oscillator system, ex: compare today’s price to price n days ago
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13
Q

Capital at Risk (CaR) ratio for managed futures

A

= Total loss if positions hit stop-loss price / NAV

this ratio represents the loss incurred if each position hits stop loss
can be used by investors who have managed account platforms b/c you need this level of transparency
CaR may underestimate the risk of loss if the stop-loss level is extremely close to the current market price, since volatility can lead the futures price to gap through the stop-loss level
CaR often overstates risk b/c it does not account for offsetting long and short positions

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14
Q

Value at Risk (VaR)

A

= (alpha x SD) + average return

alpha = 1.645 for 95% confidence interval
alpha = 1.96 for 97.5% confidence interval

VaR is a measure of potential loss in an investment portfolio for a given holding period and confidence level. Most often, returns are assumed to be normally distributed (parametric approach).

Ex: A 99% 1-month VaR of $5M indicates that there is a 99% chance that the portfolio’s losses over the next month will not exceed $5M and a 1% chance that they will

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15
Q

Omega Ratio (OR)

A

=average of upper partial movements / average of lower partial movements

ratio of the average realized return in excess of a target return relative to the average realized loss relative to the target return

OR < 1, the investment provides fewer opportunities to earn a return that exceeds the target level

In general, OR is lower for higher target return, higher volatility, lower skewness and higher skewness

Given a target of 0, OR for CTAs is 4 and OR for MSCI World is 2

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16
Q

Facts about CTA indices

A
  1. B/C CTA indices represent equally weighted portfolios of CTAs, their volatility, skewness, and kurtosis are not necessarily representative of the statistics of individual CTAs
  2. Both discretionary and systematic CTA indices have zero or positive skewness, likely due to CTAs’ use of stop-loss orders to reduce downside risk
  3. CTAs have little exposure to equity, interest rate, commodity, credit and volatility risk factors, this reflects diversification benefits of CTAs
  4. CTAs provide downside protection during periods of market stress (both discretionary and systematic indices generated positive returns in the post-internet bubble and financial crisis)
  5. Discretionary CTAs are more heterogeneous than systematic CTAs
  6. Discretionary CTA indices outperform systematic CTA indices but also have a higher SD

Sidey: Systematic CTA strategies outperform Discretionary CTA strategies (?)

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17
Q

Potential CTA database biases

A
  1. Selection Bias b/c managers voluntarily report their performances to databases
  2. Look back Bias: fund may stop reporting after period of poor performance and start reporting after a period of positive performance
  3. Survivorship Bias: occurs when databases removes performance of failed funds
  4. Backfill/Instant history Bias: fund reports from a date forward and then backfill returns with its past performance

Sidey: Published managed futures indices are not typically affected by look-back, survivorship or backfill bias

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18
Q

3 ways to benchmark performance of managed futures

A
  1. Use an index of long-only futures: not a good angle b/c futures traders are likely to be both long and short
  2. Peer Groups: can be benchmarked to active and passive indices. But, the active benchmarks may be exposed to selection bias b/c of selective reporting by some CTAs. Some benchmarks may not be investible and even the investible indices may suffer from “access bias” b/c some managers may elect not to be included in the index due to restrictions
  3. Passive benchmarks (PBs): passive indices have been constructed mainly for trend-following (TF) strategies (these can be active or passive). MLMI is a popular passive TF index. PBs are not the best approach for non-TF and relative value systems, due to the heterogeneity of the latter two.
    sidey: Portfolios of TF managers had significant explanatory power while those of non-TF managers had little. But, non-TF generated higher alphas than TF managers.
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19
Q

MLMI vs. active CTA indices

A
  1. MLMI, which is a passive TF index, is more correlated with the systematic TF CTA index than with the discretionary CTA index.
  2. The beta exposure to passive TF indices is responsible for < 50% of total excess return earned by TF CTAs
  3. The MLMI is not a reasonable benchmark for discretionary CTAs but is one for systematic CTAs
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20
Q

CTAs, volatility and gamma

A

CTAs are unlike the derivative holders of volatility swaps or a straddle who benefit from increased volatility

CTAs are long gamma (which measures the rate of change of an option’s delta as the value of its underlying asset changes), not volatility

CTAs perform well in down markets

Most CTA strategies generate their best performance when the SP500 volatility is extremely low and the next best when SP500 volatility is extremely high

CTA best performance is not observed when changes in SP500 volatility are very large, performance tends to be the worst when there are small changes in the SP500’s volatility

One reason CTAs may appear to be long volatility is b/c reported volatilities do not take into account emerging trends. Observers are often unaware of a price breakout and the emergence of a trend. This causes a delay in detection of identifying the new trend, so, reported volatility differs significantly from true volatility

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21
Q

Benefits of CTAs

A

Diversification
Downside protection in stressed markets
Zero or positive skewness

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22
Q

CTAs vs stocks and bonds

A

CTAs outperformed equities and had Sharpe ratios similar to that of bonds
CTAs had low correlations with equities and bonds

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23
Q

Costs associated with managing portfolio of CTAs

A
  1. Foregone loss carry forward: arises from CTAs assymetric fee structure in which managers only collect performance fees when the fund’s NAV exceeds the high watermark
  2. Costs of liquidation and reinvestment:
    lag 1: time to review and make a redemption decison
    lag2: several weeks betw notification and striking NAV
    lag3: time betw striking the NAV and receiving cash
    lag 4: time betw receiving 1st and last round of cash3 costs incurred from liquidating/reinvesting:
    • foregone interest on dormant cash
    • foregone excess returns on uncommitted cash
    • transaction/administrative fees for closing and opening positions
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24
Q

CTA funds vs. multi-CTA funds

A

Both have low maintenance, limited liability and no control over assets. But, only multi-CTA funds provide access to diversified portfolio of CTAs

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25
Q

Pros and Cons of Managed Futures accounts

A

Pros:

  • investors have control on their cash and can liquidate account anytime
  • investors have control of capital and can choose leverage
  • transparency of positions and trades which mitigates fraud

Cons:

  • many mangers do not accept managed accounts, so small pool of selection for investors
  • large minimum investments
  • oversight to maintain account
  • accounts do not have auditor or admin, unless secured by investor
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26
Q

3 types of HF replication products

A
  1. Factor Based: attempts to match HF’s monthly returns
  2. Payoff Distribution: attempts to replicate HF’s payoff distribution. Assumes that the returns on the clone portfolio is equal to the HF’s returns if their probability distributions are equal
  3. Bottom-up or algorithmic: good for well-defined strategies with systematic trading and no manager discretion as a source of return
27
Q

3 hypothesis for the decline in alpha and increase in beta in HF products

A
  1. Funds Bubble Hypothesis: entry of unskilled managers
  2. Capacity Constraint Hypothesis: oversupply of investment capital will reduce per capita alpha
  3. Increased allocation to active funds hypothesis: increased allocation to HF will increase correlation with traditional assets, especially in extreme cases like redemptions during stress periods
28
Q

Benefits of HF replication products

A
  1. Liquidity
  2. Transparency
  3. Lower DD and monitoring
  4. Lower fees (no carry!)
  5. Easy benchmarking
  6. Diversification
  7. Hedging capability b/c ETFs can be shorted
  8. Flexibility in terms of setting risk profiles

Still: factor based and payoff distribution models did not produce satisfactory results.

29
Q

View commonality

A

HF managers’ views are represented by their exposures, which are aggregated in an index. So, the index’s overall performance is driven by the managers’ common exposures

30
Q

Exposure Inertia

A

While individual HFs may change their exposure over time, a HF index’s overall position is more stable b/c its exposure corresponds to the aggregate of many single exposures.
Note that rapidly changing factor exposures will erode exposure inertia

31
Q

5 key steps of equity long/short strategy

A
  1. Idea Generation : look for good situations to invest
  2. Optimal idea expression: identify available instruments to execute idea, justifiable price ranges, possible future trends
  3. Size the position: higher conviction, larger position
  4. Execute the trade with minimal cost (ex: TWAP, VWAP) and determine liquidity of securities traded
  5. Manage the risk by conducting scenario analysis or stress testing
32
Q

2 sources of return to long/short managers

A
  1. firm based informational inefficiency

2. factor based informational inefficiency (ex: Fama French)

33
Q

4 components of HF long positions

A
  1. Cap gains/loss
  2. Dividends received
  3. Margin interest cost of longs if leveraged
  4. Interest earned on excess cash or cash posted as collateral
34
Q

4 components of HG short positions

A
  1. Cap gains/loss
  2. Interest earned on short sale proceeds
  3. Cost of borrowing shares (part of short stock rebate)
  4. Dividends paid to buyers of borrowed shares
35
Q

4 approaches of quantitative EMN strategies using technical analysis:

A
  1. Pairs trading : identify 2 stocks with a high LT correlation but with a temporary deviation from their normal relationship
  2. Mean reversion: assumes that returns mean revert or trend i.e. exhibit momentum
  3. Co-integration: prices are tied together by a common stochastic trend. Analogy of person walking his dog on a leash
  4. Statistical Arbitrage: involves advanced econometrics techniques
36
Q

Z scoring (technique used by quant hedgies)

A

standardizes a set of variables into dimensionless quantities. to cross analyze metrics such as P/E, P/TBV and P/S
Relatedly, winsorizing is a process that sets outlier z scores back to an acceptable range (what black swan?)

37
Q

10 step process for quant strategies

A
  1. Gather data
  2. Clean and Examine data
  3. Determine the model
  4. Define residuals, to mitigate noise/error
  5. Generate signals to decide when the algorithm should trade, this involves converting residuals into z-scores
  6. Convert the signal to positions
  7. Examine realized vs. forecasted performance
  8. Take the model live with real capital
  9. Monitor model
  10. Adjust model
38
Q

Sources of returns for quant hedgies

A
  1. Latency Arbitrage: exploit time lag in price discovery
  2. ETF Arbitrage: value deviation betw ETF and underlying NAV
  3. Momentum factor: note that momentum combined with value strategies is more effective
  4. Sharpe Ratio and Capacity: inverse relationship
39
Q

Fama French (used by quant EMN hedgies)

A

3 factors of the Fama French:

  1. excess returns above the markets, typically vs SP500
  2. size: long small-cap, short big-cap
  3. value: long high book-to-market, short low book-to-market

These are the F-F factors and they have low correlations to each other which allows them to improve risk-adjusted returns

40
Q

Great quant meltdown of 2007

A

Summer 2007, quants had bet on the continuation of positive drift of the F-F factors and their low correlation to each other.
Housing markets started to decline, subprime HFs suffered losses. Supposedly, a large multi-strategy HF liquidated while trying to post margins on subprime losses. This escalated liquidations of crowded quant strategies to meet demands for cash. The combo of size and speed of the liquidations led to significant losses in Aug. 2007.

And and Khandani research summary: firesale liquidations combined with widespread deleveraging and temporary withdrawal of risk capital led to the quant meltdown.

41
Q

Database biases that FoFs are exempt from

A
  1. No survivorship bias
  2. No selection bias
  3. No instant history bias
42
Q

Benefits of FoFs

A
  1. Diversification across managers and styles
  2. Economies of scale for smaller investors in pooling capital
  3. Information advantage
  4. Liquidity
  5. Access to top managers
  6. Bargaining power with fees
  7. Educational Role
  8. Leverage
  9. Professional Management
43
Q

Disadvantages of FoFs

A
  1. Double layer of fees
  2. Performance fees on pertion of portfolio
  3. Higher taxes possible due to offshore accounts in certain countries
  4. Lack of transparency
  5. Lack of control
  6. Lack of customization
  7. Exposure to other investor’s CFs
44
Q

2 ways to trade distressed securities

A
  1. Loan to own securities: secured loans with an equity stake or other equity-ownership rights, but no voting control
  2. Tender offers: bid by a company or third party to acquire a substantial % of a company’s debt securities. 8 suggested factors by US courts: firm terms, limited period offer, active solicitation of public shareholders, solicitation for substantial % of a class of shares, public announcement of a repurchase program, exertion of pressure upon security holders to sell stock
45
Q

2 key goals of Chapter 11

A
  1. Debtor rehabilitation

2. Return maximization for debtor’s creditors

46
Q

3 risk of distressed securities

A
  1. Headline/reputation risk
  2. Process risk
  3. Market liquidity risk
47
Q

Section 363 sale

A

Allows purchasers to acquire specific assets free of liens or liabilities. This provides a tool for distressed companies seeking to sell their assets and for buyers looking to purchase assets at potentially bargain prices

48
Q

Control vs. Non-Control investing

A

Non-control managers invest in senior levels of a distressed company’s capital structure (ex: senior secured debt), they have a low risk-reward profile given that they invest relatively late in the reorganization process or when credit risks can be minimized.

Control managers invest in relatively junior securities, are active in their investment style, making operational and managerial decisions, are longer term investors and have a high risk-reward profile. They obtain control at a discount to fair value and use such control to guide or arbitrage the reorganization process. They aim to take control either during bankruptcy or by targeting a particular class of security by identifying the “First Impaired Class”: this is the senior most tranche of claims that have the highest voting authority in bankruptcy proceedings and thus control the reorganization plan. This is related to the 1/3 blocking position in an impaired class which comes from the US bankruptcy code rule requiring 2/3 vote in favor of a plan by each of class of creditors receiving less than their claimed amount in a re-org plan.

49
Q

Hierarchy for liquidiation

A
Secured creditors
Bankruptcy admin costs
Post-petition bankruptcy expenses
Owed employee wages
Owed employee benefit plan contributions
Unsecured customer deposits
Taxes
Unfunded pension liabilities
Unsecured claims
Preferred Stockholders
Common Stockholders
50
Q

Conversion Price

A

Face Value of convertible bond / Conversion Ratio

51
Q

Conversion Premium

A

Convertible Price - Parity / Parity

52
Q

Parity

A

Stock Price x Conversion Ratio

53
Q

Delta

A

Measures the sensitivity of a convertible to the changes in the value of the underlying asset. Mathematically, it is the partial derivative of the value of the convertible bond to the stock price (dCV/dS)

The delta represents the number of shares the arbitrageur should sell short to hedge the long equity position

When the stock price is high and the convertible is deep-in-the-money, it behaves more like its underlying stock price, so the delta is close to 1. Conversely, when the stock priceis low the convertible behaves more like FI, so the delta is close to 0. ATM options tend to have deltas ~.50

54
Q

Factors associated with the price of a convertible bond

A
stock price
interest rates
volatility of underlying stock
time
credit spreads
55
Q

Gamma

A

Measures the amount by which a position’s delta changes when the stock price changes by one unit. It captures the the convexity (or nonlinearity) of the convertible bond price.

Gamma is largest for ATM convertibles and gets progressively smaller for in-and-out-of-money convertibles

When gamma is large, the portfolio needs to be frequently adjusted to maintain delta neutrality. By contrast, a small gamma indicates that delta changes slowly, so the portfolio needs less adjustment

Any change in volatility will also lead to changes in gamma

56
Q

Dodd Frank 1 (DF)

A

DF requires the SEC to oblige filers to report their short sales on Form 13F

DF replaced the private investment advisor exemption with a general requirement that an adviser to any private pool of capital must register with the SEC or a state regulator

There are a few exemptions, like for advisors who exlcusively advise VC funds or those who manage private funds with less than $150M AUM. So, DF is not for everyone

DF requires accredited investors to deduct value of their primary residence when calculation net worth

There was an exemption in place: private advisors with less than 15 clients in the past year did not have have to register with the SEC. DF eliminated this exemption

57
Q

Dodd Frank 2 (DF)

A

under DF, the following managers must register with the SEC:

  • manage funds 25 - 100M and maintain principle office in a state that does not require registration of investment advisors
  • manage funds 25 - 100M and maintain principle office in a state where the HF would be subject to examinations as an investment advisor by that securities commissioner
  • only manage HFs > 100M AUM and maintains managed accounts
  • manage HFs whose AUM > 150M and does not maintain managed accounts
58
Q

Section 13D

A

a person/entity must report to the SEC when it acquires > 5% of publicly traded equity security and this reporting must be completed within 10 days of purchase

59
Q

3 types of SEC inspections

A
  1. Regular
  2. Cause
  3. Sweep: focuses on a # of IAs in a specific region or engaged in certain activities (ex: soft dollars)
60
Q

Role of Chief Compliance Officer (CCO)

A
  1. Compliance testing/reporting
  2. Review of all marketing materials and other docs
  3. Record keeping
  4. Annual review
  5. Code of Ethics: draft, approve, distribute enforce and amend as needed
61
Q

FoFs. MSHFs and diversification

A

FoFs provide diversification benefits at the strategy level and the manager level

MSHFs only provide diversification at the strategy level

HF managers within different strategies have low correlations, this is an indication of diversification benefits. However, diversifying across managers offers significant risk-return measures. Reddy et al. research: going from a single manager to a 4-manager portfolio increased Sharp and Sortino ratios by ~90%

62
Q

Standard Portfolio Analysis of Risk (SPAN)

A

SPAN is used to determine margin requirements for futures contracts.
SPAN does not add the risk of individual positions to determine portfolio risk, but rather takes into account benefits of diversification by determining overall portfolio risk by calculating the maximum loss of a portfolio, based on which margin requirements are set.

63
Q

Recall spread

A

A recall spread is what is used to protect the credit value of a convertible asset swap against early call or conversion. A recall spread sets the price at which the credit seller is required to buy back the convertible security.