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2020 CFA LEVEL II > Portfolio Management > Flashcards

Portfolio Management Flashcards

1
Q

AP

A

+ shares by delivering the creation basket

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2
Q

ETFs trades in _ market(s)

A

primary & secondary

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3
Q

Tracking Error

A

Annualized std of daily tracking diff.

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4
Q

ETF Premium/discount

A

(ETF Price -NAV)/NAV

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5
Q

Risk of investing in ETF

A
  1. Counterparty risk
  2. fund closures
  3. expectation-related risk
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6
Q

APT

A

describes equilibrium relationship b/w EXPECTED returns for well-diversified portfolios and their multiple sources of systematic risk

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7
Q

APT assumptions

A
  1. unsystematic risk can be diversified away
  2. returns are generated in a factor model.
  3. no arbitrage opp. exist

APT is based in part on the assumption that as assets are added to a portfolio, the portfolio becomes well diversified and asset-specific risk is eliminated. Therefore, adding assets to a diversified portfolio should decrease its specific risk.

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8
Q

expected return formula

A

rf + factor sensitivity * factor risk

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9
Q

Macroeconomic factor model

A

assume asset returns are explained by SURPRISES in macroeconomic risk factors

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10
Q

Fundamental factor model

A

assume asset returns are explained by returns from multiple firm-specific factors

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11
Q

statistical factor model

A

use multivariate statistics to identify statistical factors that explain the COVARIATION among asset returns, weakness: no economic interpretation

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12
Q

active risk squared

A

active factor risk (factor tilt/weight) + active specific (asset selection)

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13
Q

Information ratio

A

Active return/active risk;
altered by the addition of cash or use of leverage;
for an UNCONSTRAINED portfolio, the information ratio is unaffected by the aggressiveness of active weights

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14
Q

multifactor models

A

good for active and passive

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15
Q

factor model

A

factor sensitivity of 1 to 1 factor and 0 to all other, used for speculation or hedging

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16
Q

VAR

A
  1. minimum loss
  2. given prob
  3. specific period
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17
Q

var model - parametric

A

use est. var and cov of securities to est the distribution of possible values, assuming normal distribution

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18
Q

var model - historical

A

use historical over prior LOOKBACK period

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19
Q

var model - monte carlo simulation

A

draws each risk factor change from an assumed distribution and calculates portfolio values based on a set of changes in risk facts, repeated 1000 times

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20
Q

Adv of VAR

A
  1. widely accepted
  2. simply to understand
  3. expresses risk as a single number
  4. useful for comparing the risk of portfolios, portfolio components, and business units
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21
Q

disadv of VAR

A
  1. Subjective to time and probability by choice
  2. sensitive to est. and assumption
  3. focuses only on left-tail outcome
  4. vulnerable to misspecification by user
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22
Q

conditional var

A

expected loss given that the loss exceeds VaR

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23
Q

INCREMENTAL VAR

A

est change in var from a specific change in the size

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24
Q

marginal var

A

est of the change in var for a small change in position, use as an est of contribution to overall var

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25
risk measure by bank
asset-liability, market, leverage, duration, convexity, overall risk to economic capital
26
risk measure by asset manager
return vol, prob distribution of absolute losses or losses relative to benchmark
27
risk measure by pension fund manager
mismatch b/w A/L, volatility of the surplus
28
risk to p&c
sensitivity of investment portfolios to risk factors, var, scenarios incorporate market and insurance risks as stress tests
29
risk to life insurers
market risk, mismatch b/w a/l
30
Short-term interest rates
positively related to GDP growth and expected volatility in GDP growth; In recession, short-term policy rates tend to be low. Positive slope of yld curve.
31
BEI
expected inflation and risk premium for uncertainty in inflation; yld on no-inflation-index - yld on inflation-indexed bonds
32
Credit spreads
widen during economic downturns, narrow during expansion. Credit spread = Yield - BEI - R
33
Sharpe Ratio
(Rp-Rf)/ vol(p)
34
Unconstrained portfolio optimial active risk*
IR/SRb*VOL(b) optimal weighht = optimal active risk*/active risk
35
Sharpe ratio comprised of an optimal proportion of bmk and active portfolio
sqr(SRb^2+IRp^2)
36
Fundamental law of active portfolio management
1. IC measures manager's skill 2. The breadth measures number of independent active bets 3. the transfer coefficient measures the degree of constrains on manager's active management
37
IR = (TC)(IC)SQR(BR)
E(Ra), for unconstrained portfolio TC=1
38
IC of market timer
2*(%correct)-1
39
Limitation of fundamental law
bias in measurement of the ex-ante information coefficient | and lack of true independence while measuring the breadth of an active strategy
40
Explicit trading costs
brokerage, taxes, fees, implicit costs include bid-ask spread, price impact, slippage, and opportunity cost
41
Effective bid-ask spread
2*(per share effective spread transaction cost) | 2*(trade price - midpoint of the trade)
42
VWAP transaction cost for buy/sell order
trade size * direction * (trade VWAP-benchmark VWAP)
43
Impementation shortfall
diff in value b/w a hypothetical portfolio (no cost) and the value of actual portfolio
44
drivers of development of electronic trading system
lower cost, higher accuracy, provision for audit trails, fraud prevention, and a continuous market during trading hours
45
market fragmentation
when a security trades in multiple markets | smart order routing seek to overcome the challenges posed by it
46
Latency
time lapse b/w the occurrence of an event and execution of a trade based on that event; electronic trading system allow low-latency traders to gain competitive advantage
47
Hidden orders (impact of electronic trading)
hidden from the market except for the exchange receiving them; seek to remove the valuable option that exposed standing orders provide to the rest of the market
48
Leapfrog (impact of electronic trading)
beating the best bid or ask price, narrows the inside spread
49
flickering quotes (impact of electronic trading)
exposed limit orders that are submitted and cancelled almost immediately
50
Runaway algorithms (systemic risk of electronic trading systems)
a series of unintended orders, cause increase in volatility
51
fat finger errors (systemic risk of electronic trading systems)
input error
52
overcharge orders (systemic risk of electronic trading systems)
demand liquidity significantly higher than what's available in the market
53
malevolent orders (systemic risk of electronic trading systems)
created to specifically manipulate the market
54
front running (surveillance and monitoring)
low latency trading ahead of known large trades
55
``` market manipulation (surveillance and monitoring) -trading for market impact ```
activities that produce false market data, including price and volume data
56
-rumormongering
- dissemination of fake information about fundamental values or about other trades' trading intentions in an attempt to alter investor's value assessments
57
-wash trading
create false liquidity
58
-spoofing/layering
- fake limit orders posted to create fake optimism/pessimism about the security
59
-bluffing
-preying on momentum order
60
-gunning the market
- forces other traders into bad trades (rapid short selling triggering stop loss)
61
-squeezing/cornering
- obtaining control over resources needed to settle contracts and then withdrawing triggering default
62
inside bid-ask
highest bid - lowest ask
63
market impact relating to a trade
price of trade 2 - trade 1 from two different time
64
discount rate
1. rf 2. expected influation 3. risk premium reflecting the uncertainity about cash flows
65
inter-temporal rate of substitution = m
marginal utility of consumption 1 unit in the futures/ | marginal utility of consumption 1 unit today
66
taylor ruls
set policy rates to 1) maintain price stability 2) achieve maximum sustainable level of employment r= Rn +pai + 0.5(pai-pai*) + 0.5(output-output*)
67
term spread
LT bond yld - short term bond yld
68
P/E, P/B & expected earnings growth rate
positive related
69
P/B, P/B & required returns
negative related
70
growth stock
- high p/e - low dividend yld - economic expanision
71
value stock
- low p/e - high dividend yld - stable earnings perform well during & immediate following recession
72
Return of capital distribution
amount paid out in excess of ETF's earnings and serve to reduce and investor's cost basis by the amount of the distribution -not taxable
73
good hedge
short-term bond
74
Soft closures entail
creation halts and changes in investment strategy
75
When a bank ETN issuer is no longer interested in additional borrowings
, the resulting creation halts may cause those ETNs to trade at a premium.
76
Portfolio liquidity management
entails equitizing excess cash
77
Portfolio completion strategies
use ETFs to fill temporary gaps in portfolio allocation.
78
Arbitrage gap
is the band around NAV at which the ETF should trade at and is not affected by the in-kind creation/redemption process.
79
Liquidity aggregation refers to
the process of monitoring a number of trading venues and then compiling the data into a "super book" that summarizes price and liquidity across these markets. This allows trades to be routed appropriately.
80
A dark pool is
a trading venue that is only open to certain clients, and that does not publish its liquidity.
81
A parent order is
a large order (e.g. buy 1 million shares of Facebook) that is divided up by an execution algorithm into smaller child orders that are less likely to move the market.
82
VAR Calculation
=E(r)-critical value * volatility | 5% = 1.65
83
purpose of ap procession
lower cost tax efficiency market prices in line with NAV
84
Arbitrage Gap
ETF trades within a bank | wider for iliquid, trading with time zone diff
85
Maximum spread
creation/redemption fees +trading cost +spread of underlying securities +risk premium for carrying until close of day +ap's normal profit margin -discount based on probability of offsetting the trade in a secondary market
86
Low-latency traders
include news traders who subscribe to high-speed electronic news feeds reporting news releases made by corporations, governments, and other aggregators of information. They can quickly analyze these releases to determine whether the information will move markets and can profit when they can execute against stale orders that do not yet reflect the new information.

2020 CFA LEVEL II (15 decks)

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