Trading Performance & Evaluation Flashcards
4 categories of trade motivation
- Profit seeking
What is alpha decay and what does it do to urgency?
- Risk management
- cash flow needs
- corporate actions margin calls and index reconstitution.
Which type is a portfolio manager researching short and long term stocks to buy with an end of day client withdrawal?
- Profit seeking - Active manager seeks to outperform benchmark. Seeking undervalued or overvalued stocks.
Alpha decay is a function of how quickly a piece of information takes to be incorporated into a securities price. Information moving quickly into a price shows high alpha decay. Low alpha decay creates lower trade urgency)
- Risk management. Portfolio traded to maintain risk exposure such as target beta, duration or interest rate environment driven decisions.
- Cash flow needs. Margin calls would require immediate liquidation (high urgency). Fund redemptions (low urgency). Greater emphasis on time vs price.
- corporate actions and index reconstitution. Mergers and acquisitions or spinoffs may require trading. Income managers may need to sell holdings inf dividends are cancelled.
Short and long term research is profit seeking high and low urgency for the long term stocks. Cash flow needs low urgency is for end of day sales in liquid stocks.
4 Key factors dictate appropriate strategy
Order Characteristics
Security characteristics
Liquidity effect on impact?
Market conditions
Individual risk aversion
Order Characteristics = SIDE & SIZE - Side (buy or sell), Size (large amount transacted creates larger market impact), Relative size ( % of ADV)
Security characteristics - Security type, short term alpha for active managers experiencing high rate of alpha decay, price volatility and security liquidity (low liquidity = low market impact).
Market conditions - Mainly affecting trading cost due to volatility and liquidity levels. Liquidity crises where deviations from liqudity patterns occur due to periods of crisis.
Individual risk aversion - High risk aversion managers will trade more urgently.
4 categories for trade execution benchmarking to see how your price received compares to benchmark prices in a session for post trade evaluation:
Pretrade benchmarks
Intraday benchmarks
Which removes outliars?
Posttrade benchmarks
Price target benchmarks
Someone who wants to avoid outliars would pick which?
Short term alpha manager would choose which?
Index and mutual funds would choose which?
Pretrade - A reference price which is known before trading. Used by short term alpha managers.
Decision price = the security price at the time portfolio manager decided to trade.
Previous close ‘price target pegged at close the previous day’
Opening price
Arrival price (instruction price)
Intraday - VWAP (average price of all trades weighted by volume) and TWAP (equal weighted so removes outliars) (risk re-balance managers, client redemption)
Post trade - determined after trading is completed. CLOSING price is most often used. Used by mutual funds and Index funds who wish to execute at the end of the day.
Price target benchmark - Perceived fair value of a stock ie if you believe shares are undervalued you’d keep buying them below your price target benchmark price. (short term alpha managers)
High touch approach trades implementation 2
Principal trades:
Agency trades:
High touch for less liquid, low urgency fixed income markets such as MBS.
Principal trades: Required for large block trades. Quote driven, OTC or off-exchange markets. Plus request for quote (RFQ).
Agency trades where broker finds the other side of the trade.
When is each of the below algorithms appropriate regarding urgency and order size?
Liquidity seeking
POV Algorithm
Arrival Price
Liquidity seeking = Large orders with high urgency. Large trades relative to ADV can be managed well.
POV Algorithm = Low urgency traded over a trading session. 10% participation of ADV.
Arrival Price = High urgency in LIQUID stocks only.
Scheduled algorithms—percent-of-volume (POV), VWAP, and TWAP algorithms
POV algorithms (a.k.a. participation algorithms)
3 reasons to choose a scheduled algorithm.
Which one is most likely to complete a trade within a trading day?
POV algorithms (a.k.a. participation algorithms) trade more (less) when volume increases (decreases) (e.g., “participate as 10% of traded volume will participate in 10% of market volume until trade completes”).
Advantage: They automatically exploit increased liquidity when available. Good for large low urgency equity trades.
Disadvantage: They continue to trade at any (potentially adverse) price, and may not fill the order in a specified time if there is a lack of trading.
TWAP releases over a specified time period.
+ ENSURES shares trade within a time period
+ ignores outliars
- Shares trade evenly during times of low liquidity
VWAP releases over a specified time
+ time slicing based on volume means higher volumes at open and close. May NOT complete an illiquid trade.
Useful for trades who do not expect adverse price movements during a trade horizon
Traders who have greater risk tolerance.
Relatively small trades relative to daily volume (no more than 5-10%)
Which one is most likely to complete a trade within a trading day? TWAP
SFDL Buy $8.50 10,000 20,000 Urgency: High
TWEL Buy $32.31 5,000 100,000 Low
UDSL Sell $2.05 1,000,000 1,000,000 Low
Liquidity seeking, scheduled algo or high touch?
SFDL should be purchased using a liquidity-seeking algorithm. The low liquidity in the market and the high order size make minimization of market impact a key consideration. Plus high urgency.
TWEL should be purchased using a scheduled algorithm. The low urgency, With low order size and relatively high liquidity, a scheduled algorithm such as POV, VWAP, or TWAP is most appropriate
UDSL should be sold using a high-touch principal approach. This order represents 100% of the ADV; hence, using an algorithm is not appropriate due to the high possibility of information leakage
Best execution
Best execution seeks the best possible result for clients
Execution price.
Trading costs.
Speed and likelihood of execution and settlement.
Order size and liquidity.
Nature of the trade (e.g., urgency of the trade).
Not necessarily lowest cost. It could be distressed shares sold at a discount by a CFO who wants to avoid leakage.
Evaluating a firms trading procedure, four key areas:
- Meaning of best execution
- Factors that determine the optimal execution approach.
- List of eligible brokers and execution venues
- Process for monitoring execution arrangements
- Meaning of best execution - general term used by regulators to describe the duty of asset managers to seek the best possible result for clients
- Factors that determine the optimal execution approach. Urgency and size of order, Liquidity of security, available venues, reason for trades.
- List of eligible brokers and execution venues - best practice is to establish a best execution monitoring committee (BEMC)
- Process for monitoring execution arrangements - The approved broker list should be constantly monitored for representational issues, trading error frequency, criminal actions, and financial stability.
When is each of the below trade styles appropriate?
Open auction
Closing auction
Passive trading over the day?
Open auction - for high urgency short term alpha trades trying to capture a mispricing.
Closing auction - mutual funds seeking the NAV of a fund to meet redemptions.
Passive trading over the day - low urgency when not attempting to capture short term alpha
Comment on the below algorithms (order size, liquidity of stock, volume)
Dark strategies/liquidity aggregators
Smart orders routing (SOR)
Direct Market Access
Arrival price
Liquidity seeking
Darks strategies = Illiquid stocks. Trade on opaque dark pools. They are used to reduce information leakage. Used when order size is large relative to market volumes, with ‘wide bid-ask spreads’.
Smart orders routing will search everywhere on lit and dark markets in order to execute at the best price. Best for small orders less than the quantity posted on bid or offer or stocks which trade on multiple venues.
Direct Market Access - low touch, smaller liquid trades.
Arrival price = Liquid stocks, little market impact expected (Instruction price) These algorithms ‘front load’ volume when the trade is entered in order to stay near to the instruction price.
Liquidity seeking = Large orders looking for low market impact. Used for stocks with sizable liquidity. Aims to reduce informaiton leakage. Can also be appropriate for thinly traded stocks where liquidity is EPISODIC.
3 stages of performance evaluation
1.Performance measurement
- Performance attribution =
- Return attribution
- Risk attribution
Effective attribution =
- Performance appraisal =
What performance did the fund achieve during the period (performance measurement)?
Performance attribution = Identified drivers of investment returns and explains HOW excess performance or risk was achieved. Should account for ALL of a portfolios return or risk exposures.
- Return attribution = analyses impact of active investment decisions
- Risk attribution = analyses the risk consequences of those decisions
Effective attribution = Reconciliation of the total portfolio return or risk exposure
Performance appraisal = Uses results of risk, return and attribution analyses to asses the QUALITY of a portfolios performance.
The three main approaches to conducting performance attribution:
- Returns-based attribution
Different to Returns based style analysis - Holdings-based attribution
- Transactions-based methods attribution
Which is used when holding detail is unavailable?
Which is a beginning of period measure and which is measured over a period?
Which is most complex and accurate?
(Analogous to returns and holdings based style analysis)
Which struggle with illiquid assets?
- Returns-based attribution- regresses total portfolio returns OVER A PERIOD against major risk factors (for example, systematic risk, size, value) Least accurate because does not consider underlying holdings. fundamental factor-based model.
A returns-based style analysis is a top-down approach that is used to estimate a portfolio’s sensitivities to security market indices. It uses objective risk exposures that are derived from the manager’s actual return series. Appropriate when underlying portfolio information is unavailable. - Holdings-based - uses a snapshot of a portfolio at a single point in time and is subject to window dressing. It is a bottom up look through of portfolio holdings to assess the active sector/stock selection bets of the manager and their contribution to active return. More accurate than returns-based because it considers underlying holdings.
- Transactions-based methods - improves upon the holdings-based attribution by including the impact of any trades executed during the evaluation period. Most accurate method. Highest data requirements.
Highest complexity
Both struggle with illiquid assets
Macro attribution.
Micro attribution
Performance attribution on the decisions made by the ASSET OWNER and FUND SPONSOR is called a macro attribution. Evelyn Partners Asset Allocation Committee. (Together, the investment committee and the internal investment staff would be referred to as the fund sponsor.)
PORTFOLIO MANAGER level decisions is called micro attribution. Jersey Investment team.
Which risk attribution technique?
A EMN systematic scoring stocks on proprietary risk factors with absolute return target
Bottom up stock picker with relative return target
Market timer using technical analysis top down and absolute return target
Marginal contribution to total risk
Marginal contribution to tracking risk
Factor’s marginal contribution to total and specific risk
A EMN systematic scoring stocks on proprietary risk factors = Marginal contribution to total risk if using an absolute return target.
Bottom up stock picker = Marginal contribution to tracking risk with a relative return target.
Market timer using technical analysis = Factor’s marginal contribution to total and specific risk and absolute return target
Seven primary types of benchmarks Advantages and Disadvantages
Absolute
Broad market indexes
Style indexes
Factor-model-based.
Returns-based
Manager universes
Custom security-based
absolute benchmark is a return objective that aims to exceed a minimum target return. Adv Simple and straightforward benchmark. Disadvantage:
Absolute return objective is not an investable benchmark
Broad market indexes - S&P 500 adv = well recognized dis = manager style may deviate
Style indexes - (1) large-capitalization growth, (2) large-capitalization value, (3) small-capitalization growth, and (4) small-capitalization value. adv - They are widely available, widely understood by clients. Dis = Some style indexes can contain weightings in certain securities and sectors that may be larger than considered prudent.
Factor models involve relating a specified set of factor exposures to the returns on an account. CAPM, Adv - It provides managers and sponsors with insight into the manager’s style by capturing factor exposures that affect an account’s performance. Dis - Focusing on factor exposures is not intuitive to all managers or sponsors. The data and modeling are not always available and may be expensive to obtain.
Returns-based benchmarks are constructed using (1) the managed account returns over specified periods and (2) corresponding returns on several style indexes for the same periods. adv - Useful where the only information available is account returns. Generally easy to use and intuitive. dis - Will not work when applied to managers who change style.
Manager universes. The median manager or fund from a broad universe of managers or funds (that follows a similar investment process) is used as the benchmark. The median manager is the fund that falls at the middle when funds are ranked from highest to lowest by performance. Advantage: It is measurable. Dis - Manager universes are subject to “survivor bias,” as underperforming managers often go out of business and their performance results are then removed from the universe history.
Custom security-based benchmarks are designed to reflect the manager’s security allocations and investment process. Adv - Allows fund sponsors to effectively allocate risk across investment management teams. Dis - It can be expensive to construct and maintain.
A portfolio return can be broken up into three components: market, style, and active management.
Portfolio return equation M, S A
Style return (S) =
Active management return (A)
P = M + S + A
S = B - M
A = P - B
portfolio return = return on market index + excess return from style + overall portfolio return surplus to the benchmark
P = portfolio manager return
M = Market return
S = incremental return due to investment style
B = return of managers style benchmark
A = incremental alpha (manager value added)
Three hedgefund benchmarks
Rf rate -
broad market indexes - Broad market indexes are not appropriate to use as a benchmark for hedge funds because hedge funds cover a wide range of investment strategies.
hedge fund peer universes - not likely to match those of a specific hedge fund.
Real estate benchmarks issues
Benchmark returns are self-reported, so some subjectivity and/or bias may be present.
Benchmarks that are value-based could be biased toward the most expensive properties or geographical areas.
There is a lack of comparability with benchmark returns given that some benchmarks use leverage while others do not.
PE benchmark issues
The metric used is usually IRR, taking into account all investment cash flows since inception plus the ending investment value. Key problems with such benchmarks include managers using different methods of valuation, which makes comparison more difficult. In addition, IRR may be biased by losses or gains occurring near the beginning of an investment.
Commodity benchmark issues
Benchmarks for commodity investments are usually based on futures as opposed to actual assets. This may result in significant differences between the benchmark and the commodity investments portfolio, which reduces the comparability. Similar to other alternative investments, the different amounts of leverage employed by portfolios versus benchmarks
Managed Derivatives
Distressed Securities
Peer-group benchmarks are similar to those used for hedge funds and will potentially exhibit the same issues as hedge fund peer-group-based benchmarks such as survivorship bias.
Given the illiquidity and severe lack of marketability of distressed securities, it is almost impossible to determine an appropriate benchmark. Should the financial state of a distressed company become better, it may become more liquid. A significant amount of time to occur
Quantitative Analysis should be evaluate objectively through what?
Qualitative Analysis of manager selection includes investment and operational due diligence.
What is performance attribution used for? Does it show quality of decisions or performance?
Which type of risk assessment is used for Top Down approaches to risk?
Quantitative Analysis should be evaluated through performance ATTRIBUTION and APPRAISAL through capture ratios.
Qualitative analysis of manager selection includes investment and operational due diligence.
Performance attribution breaks down HOW performance was achieved by breaking it down into explanatory components. It shows quality of performance but not quality of a managers decisions.
Risk allocation based on sector allocations and security selection, which is TOP DOWN, would assess tracking risk relative to a benchmark.
Qualitative Analysis? Investment due diligence. Two important issues
Operational due diligence
Qualitative analysis and Investment due diligence = philosophy, process, people and portfolio. 1) What is the likelihood that the same level of returns will continue in the future? 2) Does the manager’s investment process account for all the relevant risks?
Operational due diligence = process & procedures. Firm. Terms. Vehichle. Monitoring.