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MindMap Gallery Portfolio CFA Level 2
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Portfolio CFA Level 2
Portfolio CFA Level 2 mind map, covering ETFs, multi-factor models, measuring and managing market risk, backtesting and simulation, economics and investment markets, active portfolio management, transaction costs and electronic markets.
Edited at 2023-09-13 19:58:07
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Portfolio CFA Level 2
- bacteria
This is a mind map about bacteria, and its main contents include: overview, morphology, types, structure, reproduction, distribution, application, and expansion. The summary is comprehensive and meticulous, suitable as review materials.
- Plant asexual reproduction
This is a mind map about plant asexual reproduction, and its main contents include: concept, spore reproduction, vegetative reproduction, tissue culture, and buds. The summary is comprehensive and meticulous, suitable as review materials.
- Reproductive development of animals
This is a mind map about the reproductive development of animals, and its main contents include: insects, frogs, birds, sexual reproduction, and asexual reproduction. The summary is comprehensive and meticulous, suitable as review materials.
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- Outline
portfolio
ETF
value
Net asset value, NAV
weighted average settlement price
Net asset value per share NAV per share
market
Primary market: OTC
participants
fund manager
authorized participants, AP
Brokerage firm responsible for
Subscription and redemption in the primary market, buying and selling on behalf of customers in the secondary market
Subscription and redemption
Function: Forming primary and secondary market interconnection
In-kind creation: buying securities in exchange for shares
Physical redemption: APs give their shares to the fund manager, exchange them for securities, and the ETF shares are reduced.
Advantage
ETF prices are stable
Reasonable allocation of transaction costs
Low management costs
Secondary market: on-site
APs role
market maker
Broker
Clearing and settlement
American model
British model
More complexity, high spreads and costs
cost
management fee
Low
bid-ask spread
Affected by the market structure, for example, bond ETF spreads are high and inter-market and inter-time spreads are high.
Affected by the liquidity of component bonds
The liquidity of the ETF itself
Premium & Discount
ETF trading price – NAV per share
source
Time Difference: Investing in Cross-City Markets, Matrix Calculated Bond Prices
Stale pricing: low liquidity
Hidden costs
tracking differences tracking differences
Tracking error tracking error, the annualized standard deviation of the difference between the index and the benchmark return
12-Month Rolling Tracking Difference
Tax
capital gains distribution
tax fairness
ETF sales and redemptions have no tax impact on investors
tax effectiveness
stock dividends
Income from lending securities
Selling ETFs on the secondary market
risk
Track risks
cost
Representative sampling representative sampling, or optimization
Error caused by sampling the index
Index Baseline Changes
Changes in constituent stocks
Fund accounting operations
Valuation Time Difference
Regulatory and tax risks
Gains from lending securities, resulting in errors
Although it is a good thing, it is indeed an error
counterparty riskcounterparty risk
ETN Exchange Traded Notes, Default Risk from Issuing Bank
settlement risk
The bottom layer of ETF is swap, and the OTC market faces settlement risks
Fund closure risk
regulatory requirements
compete
mergers and acquisitions
Investment strategy changes
Leverage risk
Go long XXX n times
Use in investment portfolios
Liquidity management
Solve the cash drag, use cash to buy ETFs
Reduce costs, use ETFs to deal with redemptions, ETF selling costs are low
portfolio rebalancing
Portfolio Integrity Management
Fill the investment gap in a certain direction
transition management
Investment manager quits to use ETFs to maintain exposure in one direction
Asset allocation
Tactical asset allocation: short term
Strategic asset allocation: long term
Active investment strategy
smart beta ETFs
Bringing alpha through weight allocation and stock selection
ETF Disadvantages
Large ETF holdings need to be disclosed, and flexibility is poor
multifactor model
Arbitrage Pricing Theory, APT
theoretical research
APT special case: CAPM model
hypothesis
Asset returns can be described by the linear relationship of the factor model
Construct portfolios to eliminate asset-specific risk
There are no arbitrage opportunities between fully diversified portfolios
balanced
definition
sum of risk premiums
example
Carhart four-factor model
There is one more trend factor than the Fama-French three-factor model: the returns of winners in the previous year minus the returns of losers in the previous year.
multifactor model
Empirical Research
Macroeconomic factor model
The sum of returns that exceeded expectations
fundamental factor model
ai is the return under market equilibrium, the mean; followed by the degree of deviation from the mean
The sum of returns one standard deviation away from the mean
Fundamental factor classification
company fundamental factors
Financial Statements
Factors related to company shares
Market value, price-to-earnings ratio, dividend rate, etc.
macroeconomic factors
statistical factor model
Features
Advantages: no strict assumptions required
Disadvantages: difficult to explain
Model
Factor analysis models: explaining covariances among returns
Principal Component Analysis Model: Explaining the Variance of Returns
application
revenue attribution
risk attribution
information ratio
excess return for one unit of tracking error
Portfolio build
Hedging out the influence of a certain factor
strategic portfolio decisions
Measure and manage market risk
VaR
Definition: Under a certain level of confidence, the maximum amount of loss in a certain event in the future
Example: The securities portfolio has a 5% probability of losing at least 5 million on the next trading day.
Measurement
Parametric method (variance-covariance method)
The advantages are simple; disadvantages: covariance sensitivity, unreasonable assumption of normal distribution, dependence on input data accuracy
historical simulation
5%VaR=take the 5th one with the lowest return among 100 data
The advantage is actual data and no assumptions; the disadvantage is that history does not represent the future.
The weight of data is equal. In fact, the weight of data that is closer to the present should be greater.
Monte Carlo simulation
Advantages: Flexible and accurate; Disadvantages: Complex dependence on assumptions
advantage
Simple
comparable
Intuitive guidance for investment decisions
Excellent performance evaluation indicators
Backtesting proves effectiveness
Widely used
defect
Subjectivity: assumptions can be defined
Underestimating the frequency of extreme events: the normal distribution assumption is unrealistic
Liquidity problems can lead to more serious losses and VaR underestimation
Ignore the correlation, everyone falls together, and underestimate VaR
Vulnerable to trends and volatility
Misunderstanding of VaR, please note that VaR is not the worst case scenario
Ignoring right-tail events: the front
Improvement of VaR
Condition Var, CVaR
Also known as expected shortfall, ES: the expected or average loss when the loss exceeds the value at risk
Incremental value at risk, IVaR
The VaR before the position change in the portfolio minus the VaR after the change
Marginal value at risk, marginal VaR
A small change in the weight of an asset causes a change in the value at risk
Relative VaR
ex ante tracking error, combined VaR-baseline VaR
sensitivity risk measuressensitivity risk measures
Beta in equity, duration convexity in fixed income, Greek letters in derivatives
Disadvantages: Suitable for comparison with small changes; unable to identify assets with different volatility
Scenario Risk Measurement - Scenario Analysis
Classification
historical scenario method
What-if scenario approach
Stress Testing: Extreme Cases
Advantage
Pay more attention to extreme situations and are not constrained by parameters and distributions
Focus on positive events
Disadvantages
Assumptions may not be reasonable. If they are not true, they do not represent the future. It is difficult to implement hypothetical scenarios.
application
bank
VaR
sensitivity coefficient
lever
Scenario analysis
risk indicators
liquidity gap
economic capital
Measuring the asset-liability mismatch problem
asset management company
Business model: decentralized, no leverage, long only
Limit position size
sensitivity analysis
Scenario analysis
Active share: the difference between a certain type of asset in the portfolio and the proportion of similar assets in the benchmark
Pre- and post-tracking error
value at risk
redemption risk
fluidity
Hedge Fund
Business model: centralization, increased leverage, long-short strategy, absolute return
sensitivity analysis
Total exposure: the sum of the absolute values of each exposure
lever
VaR
situational risk
retracement
pension
Pursuit: Surplus on assets and liabilities, money for investors
Surplus in risk: VaR of the difference between long position and liability
Glide path: manage the surplus at risk and adjust the situation of serious excess or shortage of funds.
Interest rate and interest rate curve risk
Liability Hedging Exposure & Return Generating Exposure
sensitivity analysis
insurance company
non-life insurance
sensitivity analysis
Economic Capital&VaR
Scenario analysis
life insurance
sensitivity analysis
Matching assets and liabilities
Scenario analysis
Capital Allocation Constraints
risk budget
Position limits
situational constraints
Stop loss limit
Backtesting and Simulation
backtesting
step
Design Strategy
Historical data simulation
Analyze output results
index
average return
fluctuation
Downside risks
VaR
Maximum downside risk to CVaR
Sharpe Ratio & Sortino Ratio
Visualization
offset
survivorship bias
look ahead bias
Historically unavailable data was used during backtesting
A special case is survivorship bias
data snooping, data mining bias
Optimizing data makes results better
p-hacking
a selection bias
simulation
Historical Simulation & Monte Carlo Simulation & Sensitivity Analysis
Economics and Investment Markets
Tactical asset allocation, when should you allocate more and less?
discounted cash flow model
inter-temporal rate of substitution, mt
Utility from current consumption - Utility from future consumption
The real risk-free rate is inversely proportional to the intertemporal substitution rate
The higher the investment return, the smaller the intertemporal substitution rate, and investors focus on current consumption.
It doesn’t feel like spending money when it’s easy to make money
risk-free rate
Inflation and the nominal risk-free rate
actual value
Positively related to GDP growth rate, and positively related to the volatility of GDP growth rate
nominal value
break-even inflation rate break-even inflation rate
θexpected inflation
π error in expected inflation
economic cycle impact
policy rate
Taylor's rule
neutral real interest rate
current inflation rate
target inflation rate
Log real GDP
Log potential GDP
yield curve slope
During a recession, short-term risk-free interest rates decrease and long-term risk-free interest rates increase; long-term uncertainty is high and the yield curve is steep.
Late expansion, recession, short-term interest rates are high, long-term interest rates are low
credit spread
The economy is high and credit spreads are small
Non-cyclical industries and high-rated companies have small credit spreads
equity risk premium
Relative to bonds, equity cash flows are highly uncertain
Consumption hedging characteristics
Assets that yield high returns during economic downturns
Earnings growth expectations
Procyclical
Economic prosperity and profit growth
Non-cyclical industries are non-cyclical-defensive industries that are not strongly related to the economic cycle.
valuation multiple
Increases with economic expansion and decreases with recession
Investment Strategy
Value vs growth strategy
Value stocks are good in recessions
Large Cap vs Small Cap Strategy
Small cap stocks are good when expanding
Cyclical vs. Defensive Stock Strategies
Cyclical stocks do well during expansion
commercial estate
Dual attributes of stocks and bonds
Active Portfolio Management
Added value: what exceeds the baseline
Risk vs. reward comparison
Sharpe ratio
Portfolio leverage does not affect Sharpe ratio
Weight changes affect Sharpe ratio
information ratio
ex-anti IR is based on expected returns
ex-post IR based on realized gains
Leverage affects information ratio
Changes in benchmark weights do not affect the information ratio
optimal combination
active risk
Basic Rules: Assessing the Active Investment Management Capabilities of Investment Managers
single decision
Information coefficient: predictive power
core
Correlation coefficient between normalized actual active return and expected active return
The larger the IC, the stronger the investment manager’s predictive ability and the ability to add value to the investment portfolio.
transfer coefficient transfer coefficient: practical ability
The extent to which forecasts are translated into active investment asset allocation
Correlation coefficient between predicted active returns and actual active weights
TC=1, the investment manager has no restrictions on weight allocation when constructing a portfolio.
TC=0, no freedom
Value added: excess return capability
Comprehensive Basic Laws
multiple decisions
WidthBreadth
Number of independent positive decisions made per year
market timing
defect
IC is the core, but investment managers often overestimate their own abilities, and their predictive abilities are limited by uncertainty.
It is difficult to make independent decisions in fixed income and equity strategies
Transaction costs and electronic markets
transaction cost
Classification
explicit cost explicit cost
Commissions, stamp duties, etc. generated by transactions
implicit costimplicit cost
bid-ask spread
Market Maker Quote
market shock
delay cost
opportunity cost
measure
effective spreads effective spreads
Measuring transaction costs
The effective spread is less than the market spread, and there is a price improvement to the market price.
On the contrary, price shock
Volume Weighted Average Price VMAP
Measuring hidden costs
implementation shortfall
The difference between the income of the hypothetical paper portfolio and the actual portfolio
Measure all costs
electronic market
Advantages: In the command-based trading market
low cost
Enforce discipline well
anonymous
continuous trading
not affected by weather
electronic system
speed
Importance of trading speed: For low-latency traders or high-frequency traders
Advantage of speed
Get trading opportunities
Submit Order
cancel order
electronic communication system
High-speed data services to receive information and understand events
electronic computer system
Minimize decision time
programming
Situation analysis table contingency table, default plan
electronic trading strategies
hidden orders hidden orders
Orders that only brokers and exchanges can see, immediate or cancel orders to discover
leapfrog quote leapfrog
Market making strategy, increase the price to increase the buying price
flicking quotes
Place an order and cancel it quickly, sending a message to the market
electronic arbitrage
machine learning
electronic broker
Advanced Order: Floating Limit Order
Trading tactics: Submit multiple orders with one command and discover hidden instructions
Algorithm: Split orders to reduce market impact
Market segmentation fragment
One security multi-market trading
Liquidity pooling technology
Providing liquidity for a security in different markets
Intelligent order routing technology
Send orders to the market with the best price
electronic trader
electronic news trader
electronic market maker
electronic arbitrageur
electronic front runner
predict
Electronic quote matcher
Limit losses with matching instructions
Electronic trading risks
systemic risk
Trading system failure
Excess orders
runaway algorithm
Oolong finger
Very large orders: difficult to close
Malicious orders malevolent: disrupting the market
Illegal transactions
Front-running: Obtaining information illegally
market manipulation
manufacturing market shock
spread rumors
Wash trading: Frequent trading creates fake liquidity
Cheating spnoofing/layering
market manipulation strategies
bluffing
First pull and then smash pump and dump
gunning the market
Smash the stock price, force others to trigger stop losses and buy in large quantities
squeezing and cornering
short squeeze strategy short squeeze