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cfa level iii > Session 15 - Trading, Performance Evaluation, and Manager Selection > Flashcards

Session 15 - Trading, Performance Evaluation, and Manager Selection Flashcards

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1
Q

Motivations to Trade

A

1/ Profit Seeking
2/ Risk Management
3/ Cash Flow Needs
4/ Corporate Actions/Index Reconstitution/Margin Calls

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2
Q

Profit Seeking (under Motivations to Trade)

A
  • active managers are trading based on information that is not reflected yet, believe securities are mispriced
  • will try to hide their trades to prevent information leakage (executive in multiple or less transparent ventures)
  • trade urgency is high when ST profit opportunity
  • tries to execute close to the market
  • occurs when alpha decay is high
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3
Q

Lit vs dark venues

A

lit - better execution likelihood

dark - less transparency, but higher likelihood of going unfilled

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4
Q

Risk management/hedging needs (under Motivations to Trade)

A
  • may involve derivatives or just trades in the underlying securities
  • investment mandate may not allow derivatives
    • use ETFs or the underlying security
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5
Q

Cash flow needs (under Motivations to Trade)

A

➝ may involve high or low trade urgency
- collateral/margin calls ➝ high
- redemption ➝ low
- inflows from dividends and cash can be equitized using ETFs/futures to min. cash drag and until next rebalance or UL positions can be established
– client redemptions are based on NAV
- NAV based on closing prices
∴ trading at the closing price reduces redemption price risk

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6
Q

Corporate Actions/Index Reconstitution/Margin Calls (under Motivations to Trade)

A
  • cash dividends/coupons need to be reinvested
  • margin or collateral calls have high levels of trade urgency
  • index tracking portfolios ➝ trades usually done ‘on close’ to minimize tracking error
  • active managers with a benchmark may choose to rebalance with index reconstitution
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7
Q

Factors to consider for Trade Strategy Inputs

A

1/ Order characteristics
2/ Security characteristics
3/ Market conditions
4/ Individual risk aversion

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8
Q

Order characteristics (under Trade Strategy Inputs)

A

a) side of the order
- if buying in a rising market or selling in a falling market ➝ market risk exposure order may take longer to execute, or cost more
b) size of the order - large order sizes create market impact (i.e. adverse price movement in a security as a result of trading an order)
- larger orders take longer to trade
- will usually be traded with lower trade urgency to reduce market impact

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9
Q

Security characteristics (under Trade Strategy Inputs)

A

a) security type - liquidity and trading costs will vary by exchange
b) short-term alpha - the expected movement in the security price over the trading horizon (i.e. appreciation, depreciation, reversion)
c) price volatility - affects execution risk
d) security liquidity - greater liquidity ➝ lower execution risk & trading costs
- bid-ask spreads will indicate both costs and market depth
- larger trades ➝ broken down, traded more slowly

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10
Q

Alpha decay

A

➝ results from price movement in the direction of the trade forecast
➝ if information is reflected in prices quickly, decay is fast - requires faster trading

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11
Q

Execution risk

A

➝ risk of an adverse price movement over the trading horizon

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12
Q

Market conditions (under Trade Strategy Inputs)

A
  • during market events or crisis ➝ volatility increases and liquidity decreases
  • security liquidity may change bc of market liquidity
  • lower market liquidity ➝ longer trading horizon but/ - higher volatility may heighten trade urgency
  • longer trading horizons increase execution/market risk
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13
Q

Individual risk aversion (under Trade Strategy Inputs)

A
  • high level of risk aversion, more concern about market risk, trade with greater urgency
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14
Q

Market Impact and execution risk

A

· temporary market impact cost - temporary, short-lived impact on security price from trading
- usually price reversion after the order is complete
· permanent component of price change associated with trading is the market impact caused by the information content of the trade
· execution risk lowers with faster trading
- trade too fast ➝ increased market impact
- trade too slow ➝ increased execution risk/market risk

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15
Q

Types of Reference Prices

A

1/ pre-trade benchmarks
2/ Intraday benchmarks
3/ Post-trade benchmarks
4/ Price-target benchmarks

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16
Q

Pre-Trade Benchmark

A

a/ opening price
b/ arrival trade
c/ decision price
d/ previous close

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17
Q

Decision price

A

security price at the time the PM makes the decision to buy and sell the security

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18
Q

Previous Close

A

often specified by quantitative PMs

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19
Q

Opening Price

A
  • used by PMs who trade from the open
  • used as the ‘decision price’ by fundamental PMs
  • opening price does not have overnight risk
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20
Q

Arrival Price

A
  • price of the security at the time the order is entered into the market for execution
  • typically used by short-term alpha traders
  • goal is to transact at or close to current
    market prices
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21
Q

Intraday benchmarks

A
  • for funds that trade passively over the pay, see liquidity or rebalancing
  • do not expect the security to exhibit any ST price momentum
    1/ VWAP
    2/ TWAP
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22
Q

VWAP (Volume weighted average price)

A
  • volume-weighted average price of all the trades executed over the day or trading horizon
  • usually when PM wants to participate with volume
    patterns
  • works well when PM is executing buy and sell orders
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23
Q

TWAP

A
  • time-weighted average price - the average price of trades executed over the trading day or trading horizon
  • used when outlier trades make VWAP unreliable
    i. e. large buy orders at the day’s low or large sell orders at the day’s high
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24
Q

Post-Trade Benchmarks

A
  • most common is closing price
  • funds valued at end of day (NAV) will ‘buy on close’ to minimize tracking error
  • typically used by index & mutual funds
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25
Q

Price-target benchmarks

A
  • PMs seeking short-term alpha

- purchase shares at or below some target price

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26
Q

Large Block Trades + Urgent (Trade Execution)

A
  • principal trade or broker risk trades
  • dealer is the counterparty
  • buy/sell from their own inventory
  • if the security is less active, the dealer will quote a wider bid-ask spread
  • called quote-driven, OTC or off-exchange markets
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27
Q

Large block trades ➝ non-urgent or very illiquid (Trade Execution)

A

➝ agency trade
- dealer attempt to arrange trades as a broker
- attempt a cross ➝ matching with other client orders
- then open market ➝ split order up
RFQ - Request for quote ➝ PM requests quotes from dealers

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28
Q

Liquid, standardized securities with order-driven markets

A
  • trading done electronically w/ multiple venues

- for trades other than large orders

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29
Q

Large orders, liquid, standardized (Trade Execution)

A

➝ algorithmic trading (DMA) - high-touch generally inefficient
- subject to front-running

30
Q

Algorithmic Trading

A

slice orders into smaller pieces and
trade across venues and overtime to reduce the
the price impact of an order
- 2 purposes
➝ execution - PM determines what to buy/sell
➝ profit-seeking - algorithm determines what to buy/sell

31
Q

Scheduled Execution algorithm classifications

A

1/ Scheduled:

a) POV - percent of volume (a.k.a. participation algorithms)
b) VWAP/TWAP

32
Q

POV - percent of volume (a.k.a. participation algorithms)

A
  • as volume increases, the algorithm trades more
  • trader specifies a participation rate
    e. g./ 10%, for every 10K shares traded, algorithm trades 1000
33
Q

VWAP/TWAP

A
  • VWAP ➝ follows a time slicing schedule based on historical volume profiles
  • higher percentage traded at the open and close
  • may not be optimal for illiquid stocks (may not complete order)
  • TWAP ➝ follows an equal-weighted time schedule - same number of shares per time period
34
Q

Scheduled algos. appropriate for:

A
  • PM has no expectations of momentum (adverse price moves)
  • PM has greater risk tolerance for longer execution time periods - minimizing market impact
  • relatively small order size (5%-10% of expected volume)
  • relatively liquid or balanced buy/sell orders
35
Q

Liquidity seeking (opportunistic algorithms)

A
  • trade faster when liquidity shows up across multiple venues
  • will use exchanges, ATS, and dark pools (for larger quantities)
    · appropriate for
    · large orders with high trade urgency while avoiding market impact
    · printing limit orders would reveal information (minimizes information leakage)
    · less liquid, thinly-traded, or when liquidity is episodic
36
Q

Arrival price (Execution algorithm)

A
  • trade more aggressively at beginning of order - called front-loaded strategy
  • used when momentum is expected in prices
  • appropriate for · PM who are risk adverse and
    wish to trade more quickly to reduce execution risk
  • security is relatively liquid, order is not out-sized (i.e. < 15% expected volume)
37
Q

Dark Strategies/liquidity aggregators (Execution algorithm)

A
  • used to avoid any information leakage volume
  • order size is relatively large and may have a significant market impact
    appropriate for:
    · illiquid securities
    · wide bid-ask spreads
    · PM does not require full execution (low trade urgency)
38
Q

Smart order routers

A
  • SOR determines the destination with the highest probability of executing a limit order
  • used with small market or limit orders that will have no market impact
  • best used for orders that require immediate execution or for
    limit orders for which printing the order will not leak information
  • appropriate for · securities traded on multiple markets
39
Q

Trade Executions for Equities

A
  • exchanges and dark pools (ATS or MTF – multilateral
    trading facilities)
  • most trades are electronic, algo. trading is common
    large & urgent trades ➝ high touch (especially illiquid securities)
    large & non-urgent ➝ trading algorithms
    small trades - electronic trading
40
Q

Trade Executions for Fixed Income

A
  • primarily OTC, quote-driven
  • sourcing liquidity relies heavily on dealers
  • except for on-the-run U.S. Treasuries, bond/interest rate futures
  • small trades and large urgent trades ➝ principal trades
  • large, non-urgent ➝ agency trades
41
Q

Trade Executions for Exchange-Traded Derivatives

A
  • electronic trading widespread
  • algo.-trading ➝ mostly futures
  • large, urgent trades ➝ liquidity seeking algos.
42
Q

Trade Executions for OTC Derivatives

A

– dealer market, trade sizes usually large

  • large, urgent trades ➝ principal trades
  • non-urgent ➝ agency trades
43
Q

Trade Executions for Spot forex (currency)

A
  • primarily electronic trading

- large, urgent trades ➝ RFQ

44
Q

IS decomposes total cost into

A 
- measures total costs associated with implementing the investment decision
IS = Paper return - Actual Return
where: Paper return = (𝐏𝐧−𝐏𝐝) 𝐒
Actual return = ∑𝐬𝐣(𝐏𝐧) − ∑𝐬𝐣𝐩𝐣 − 𝐅𝐞𝐞𝐬
- IS decomposes total cost into 
1/ Execution cost ∑𝐬𝐣𝐩𝐣 − ∑𝐬𝐣𝐩𝐝
- shares that were transacted
- market impact + price drift
2/ Opportunity cost ^𝐒 − ∑𝐬𝐣a(𝐏𝐧−𝐏𝐝) – unexecuted shares 
3/ Fixed Fees – explicit fees
45
Q

Exp

A

➝ execution cost divided into delay and trading cost
- delay cost = (p0-pd)Sj
p0 = price when the order is placed
- trading cost = Sj(pj-Po)
- the time from receiving the order from the PM to actually placing the order
- often resulting from the time required to determine the trading strategy (broker or algorithm choice)

46
Q

Improving Execution Performance

A

· have a process in place that provides traders with broker performance metrics (reduce delay)
· determine proper order size for the market
- rather than typing up funds/time trying to fill a difficult trade, reduce the size and concurrently trade something else (reduce lost opportunity)
- typically the result of adverse price movement and/or illiquidity

47
Q

Evaluating Trade Execution

A
  • measure execution quality of a trade
  • measure overall performance of the trader/broker/algo.
    𝐂 𝐨 𝐬 𝐭 ( $ ) = 𝐒 𝐢 𝐝 𝐞 × ( 𝐏1 − 𝐏 ∗ ) × 𝐒 𝐡 𝐚 𝐫 𝐞 𝐬
    𝐂𝐨𝐬𝐭 ($/𝐬𝐡) = 𝐒𝐢𝐝𝐞 × (𝐏1 − 𝐏∗)
    𝐂𝐨𝐬𝐭(𝐛𝐩𝐬)=𝐒𝐢𝐝𝐞 ×9 𝐏∗ : 𝟏𝟎,𝟎𝟎𝟎
    𝐏 = average execution price of order
    𝐏∗= reference price can be: arrival price, VWAP, TWAP, market-on-close
48
Q

Mark Adjusted Cost

A

Adjusts for general market movement
MAC = Arrival cost (bps) – 𝛃 · Index Cost (bps)
𝐈𝐧𝐝𝐞𝐱 𝐜𝐨𝐬𝐭 (𝐛𝐩𝐬) = 𝐒𝐢𝐝𝐞 × ( 𝐈𝐧𝐝𝐞𝐱 𝐕𝐖𝐀𝐏 - 𝐈𝐧𝐝𝐞𝐱 𝐚𝐫𝐫𝐢𝐯𝐚𝐥 𝐩𝐫𝐢𝐜𝐞) / 𝐈𝐧𝐝𝐞𝐱 𝐚𝐫𝐫𝐢𝐯𝐚𝐥 𝐩𝐫𝐢𝐜𝐞 × 𝟏𝟎, 𝟎𝟎𝟎

49
Q

Added Value

A
  • compare arrival cost with estimated pre-trade cost

- Added Valued (BPS) = Arrival cost (BPS) - estimated pre-trade cost (BPS)

50
Q

Trade governance

A
  • all asset managers should have a trade policy
    a document that articulates the firms trading policies
    (mandated by major market regulators, e.g. SEC)
    ➝ objective of a trade policy ➝ ensure execution and order-handling procedures are in line with the duty of best execution owed to clients
51
Q

Meaning of best execution

A

· not just best price at lowest cost
- involves identifying the most appropriate trade-off between:
· execution price
· trading costs
· speed of execution
· likelihood of execution and settlement · order size
· nature of trade

52
Q

Factors determining the optimal execution approach

A

· urgency of order
· characteristics of the securities traded
· rationale for a trade
· characteristics of the execution venue used
· investment strategy objectives

53
Q

List of eligible brokers and execution venues

A 
· quality of service 
· reputation
· speed of execution
· financial stability
· settlement capabilities · cost competitiveness
· willing to do principal trades
54
Q

Process used to monitor execution arrangements

A
  • all brokers and execution venues used should be subject to ongoing monitoring for reputational risk, irregularities, criminal actions and financial stability
  • use of a ‘Best Execution Monitoring Committee’
  • firm-wide responsibility for trade execution monitoring
  • trading records stored and accessible for several years
55
Q

Performance measurement

A
  • absolute return ➝ what the portfolio achieved over a specific period
  • excess return ➝ portfolio return - benchmark return
  • also involves measuring the risk incurred to achieve that return
56
Q

Performance Attribution

A
  • how that performance was achieved or how the risk was incurred
  • explain absolute or relative return
  • what portion was driven by active mgr. decisions - decompose excess return into component sources - decompose risk
57
Q

Performance Evaluation

A
  • draw conclusions regarding the quality of performance - distinguish manager luck from skill
58
Q

An effective performance process must

A

1) account for all the portfolio’s return or risk exposure 2) reflect the investment decision-making process
3) quantify the active decisions of the PM
4) provide a complete understanding of the excess
return/risk of the portfolio

59
Q

Return attribution

A

– analyzes the impact of active investment decisions on returns

60
Q

Risk attribution

A
  • analyzes the risk consequences of those decisions (absolute or benchmark relative terms)
61
Q

Micro attribution

A
  • understanding the drivers of a manager’s returns and whether those drivers are consistent with the stated investment process
62
Q

Macro attribution

A
  • measures the effect of the asset owner’s (sponsor’s) choice to deviate from the SAA
  • also measures the effect of the manager selection and
    timing decisions
63
Q

Returns-based attribution

A
  • uses only total portfolio return
  • most appropriate when underlying portfolio information is not available at the required frequency or detail
  • easiest to implement
  • least accurate
  • vulnerable to data manipulation
64
Q

Holdings-based attribution

A
  • used actual holdings (beginning of period)
  • all transactions are assumed to occur at end of the day
  • accuracy improves when data has shorter time intervals
  • most appropriate for investment strategies with little turnover
65
Q

Transactions-based attribution

A
  • uses both the holdings and the transactions during the evaluation period
  • most accurate, but most difficult and time-consuming to implement
66
Q

Brinson Model Equity Attribution

A

➝ Allocation (𝑷 −𝑩 )(𝑹 −𝑹o )➝∆𝐰(𝐑 −𝐑o )
➝ Security (𝑹𝑷−𝑹𝑩)𝑩𝒘 ➝ 𝑹𝑨𝒊 · 𝑩𝒘𝒊
➝ Interaction (𝑷𝒘 − 𝑩𝒘)^𝐑𝐩 − 𝐑𝐁a➝ ∆𝐰𝐢 ⋅ 𝑹𝑨𝒊

67
Q

Factor-Based Equity Attribution

A
  • fundamental factor models
  • decompose contributions to excess returns from factors
  • market, size, value, momentum
  • size (<0 = Lg. Cap)
  • value (>0 = value)
    RMRF = 1 = broad-based market index
68
Q

Exposure decomposition – top-down approach (under Fixed Income Attribution)

A

Benchmark
➝ Duration
➝ Yield curve positioning
➝ Sectors (i.e. gov’t., corporate)
Portfolio
- active decisions to deviate from benchmark exposures
e.g./ active duration bets ➝ increase duration relative to the benchmark in anticipation of falling rates
yield curve positioning ➝ barbell for a flattening curve
sectors ➝ overweight credits in anticipation of spreads narrowing
· how well, relative to the benchmark, did these active decisions work out, what contribution to active return
- used primarily for client reports, easy to understand

69
Q

Fixed Income Attribution Approaches

A

1/ Exposure decomposition – top-down approach
2/ Yield curve decomposition - duration based
3/ Yield curve decomposition - full repricing

70
Q

Yield curve decomposition - duration based (under Fixed Income Attribution)

A
  • can be either top-down or bottom-up
    ➝ estimates the returns based on duration
    % total return = % Income return + % Price change
  • ModDur × ∆𝐲𝐢𝐞𝐥𝐝
  • applied to both the portfolio and the benchmark
  • difference = effect of active PM decisions
  • requires more data points than exposure decomp.
  • typically used in reports for analysts & PMs
71
Q

Yield curve decomposition - full repricing (under Fixed Income Attribution)

A
  • instead of using estimates
  • prices out each security
  • most complex attribution of the three

cfa level iii (12 decks)

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