CMT Level 3 Exams ( Updates STUDY BUNDLE
PACKAGE) The Integration of Technical Analysis |
Questions and Verified Answers| Grade A| 100%
Correct
Ch.1 System Design and Testing - A Complete Trading System - ANSWER1. Markets—
What to buy or sell
2. Position Sizing—How much to buy or sell
3. Entries—When to buy or sell
4. Stops—When to get out of a losing position
5. Exits—When to get out of a winning position
6. Tactics—How to buy or sell
Ch.1 System Design and Testing - Types of Technical Systems - ANSWER1. Trend
Following
1a. Moving Average Systems
1b. Breakout Systems
2. Pattern Recognition Systems
3. Reversion to the Mean
4. Exogenous Signal Systems
Ch.1 System Design and Testing - Problems with Trend-Following Systems -
ANSWER1. Popularity strains liquidity, increases slippage
2. Whipsaws common during trading ranges
3. Lag entries and exits, missing profit potential
4. Small losses awaiting new trends
5. Drawdowns from consecutive losses
6. Large drawdowns from small consecutive losses
7. Extreme volatility in equity curve
8. Parameter shifts decrease adaptability
Diversification into multiple systems helps
Countertrend systems can offset losses
Complexity if pyramiding signals added
Ch.1 System Design and Testing - Data - ANSWER- data must be sufficient to provide
at least 30 to 50 trades (entry and exit) and cover periods where the market traveled
up, down, and sideways
- Cleanliness of data is a necessary requirement. Any anomalies or mispriced quotes
will have an effect on the system test
- To test a daily system, for example, two years or more of daily data is required at
the very least
,Ch.1 System Design and Testing - Special Data Problems for Futures Systems -
ANSWER1. Limited contract lifespan, insufficient for system testing
2. Price difference between expiration and rollover contract
3. Splicing contracts together is challenging
Ch.1 System Design and Testing - Perpertual/ Constant Forward Contract -
ANSWER1. Perpetual contracts interpolate between two contracts
2. Weighted by time to a fixed forward date
3. Favors near contract initially, then shifts weighting
4. Gives smooth price series without rollover gaps
But deviates from actual contract prices
Ch.1 System Design and Testing - Continuous Contract - ANSWER1. Adjusts contract
prices for rollover spread
2. Begins with nearby contract prices
3. Rollover date set before expiration
4. Spread accumulated over rolls
5. Adjusted prices match system trade costs
6. No price distortion, matches history.But adjusted prices differ from actual
7. Reflects price moves, not price levels
8. Gives realistic view for system designer
Tradeoff between accuracy and realism
Ch.1 System Design and Testing - Optimization - ANSWER1. involves changing system
parameters to improve performance
2. Can eliminate useless parameters that don't work historically
3. Test impact of stops and exit rules with optimization
4. decide what the optimization is looking for in the data, objective function
5 The out-of-sample results are theoretically what the system should expect in real
time. Invariably, the out-of-sample performance will be considerably less than the
performance generated in the optimization
Ch.1 System Design and Testing - Problems of Optimization - ANSWER1. Curve-fitting
optimizes to historical data, not future
2. Overfit systems often fail in live trading
3. Avoid over-optimization and false confidence
Ch.1 System Design and Testing - Objective function - ANSWERanalyst must decide
what the optimization is looking for in the data. Is it looking for net profit, maximum
drawdown, Sharpe ratio, percentage of winning trades, MAR ratio or any other.
Ch.1 System Design and Testing - Methods of Optimizing - ANSWERan optimization
should be done over a considerable period of price data and include those periods
when the prices are in trends and in trading ranges
Ch.1 System Design and Testing - Avoid Curve Fitting - ANSWER1. optimize only a
portion of the data, called in-sample (IS) data, and
,2. test the resulting parameters on another portion of the data, called out-of-sample
(OOS) data, to see if positive results continue in data not seen before by the
optimization process.
3. use more than one market as the out-of-sample test.. A reliable system should
work in most markets.
Ch.1 System Design and Testing - Selection of data - ANSWER1. Use basket of
securities, not just one
2. Generates sufficient trades for significance. More trades increases statistical
validity(over 30 trades)
3. Diversification reduces peculiarities
Ch.1 System Design and Testing - Walk Forward Optimization - ANSWER1. Optimizes
small initial dataset
2. Tests on subsequent out-of-sample data
3. Example: 1 year optimized, 6 months tested
4. Record resulting parameters
5. Optimize next year, include previous OOS
6. Test on new out-of-sample data again
7. Slide window forward through data
8. Each optimization has out-of-sample test
Analyze all results for consistency
Ch.1 System Design and Testing - Profit Measures - ANSWER1. Profit factor - ratio of
total profit to total loss. Better > 2
2. Outlier-adjusted profit factor - removes anomalies (largest profit). Less than 1 is a
bust.
3. Win percentage - frequency of profitable trades (30% - 50% for trend following).
>60% should be look for
4. Annualized return - versus a benchmark
5. Payoff ratio - average win/average loss
6. Win/loss duration ratio
7. Efficiency factor - net profit/gross profit
Stability - profit metrics should be robust
Screen initially with profit factor above 2
Win percentage usually 50-70%
Payoff ratio above 2 for trends
Duration ratio above 1, above 5 better
Efficiency factor 38-69% typically
Ch.1 System Design and Testing - Risk Measures - ANSWER1. Maximum drawdown -
largest loss from equity peak
2. MAR ratio - annual gain/max drawdown percentage
3. Max Consecutive losses - risk of extended drawdowns
4. Longest flat time - capital not in use
5. Time to recovery, from large drawdowns - recuperation ability
, 6. Max Favorable/adverse excursions - primary use is to give hints as to where
trailing stops should be placed to take advantage of favorable excursions and reduce
adverse excursions.
7. Sharpe ratio - return vs. volatility
Flaws: uses average return, equal up/downside
8. Return retracement ratio - return/max loss
9. Sterling ratio - arithmetic average of annual net profit divided by average annual
maximum drawdown
10. Maximum loss - worst possible loss from peak
11. Sortino ratio - same as Sharpe but downside volatility only
Ch.1 System Design and Testing - GOOD TRADING SYSTEM (from Tushar Chande) -
ANSWER1. Positive expectation—Greater than 13% annually.
2. Small number of robust trading rules—Less than ten each is best for entry and exit
rules.
3. Able to trade multiple markets
4. Incorporates good risk control—Minimum risk as defined by drawdown should not
be more than 20% and should not last more than nine months.
5. Fully mechanical—No second-guessing
Ch.2 Money and Portfolio Risk Management - Drawdown - ANSWERdrawdown. It is
defined as that amount by which the equity in an account declines from a peak.
Ch.2 Money and Portfolio Risk Management - Monte Carlo simulation - ANSWER1.
not use the rules, variables, or parameters in the original trading system. It uses only
the actual trades, entry and exit, and the profit or loss from each.
2. money-management test rather than a system test, although obviously the system
determines the trades.
3. done many times, usually at least 100 times and better if 1,000 or 2,000 times.
4. An equity curve is then created for each scrambled sequence of trades. The results
from each equity curve are then assembled to give the results and related to a
normal distribution curve
Ch.2 Money and Portfolio Risk Management - Theory of Run - ANSWERstates that
the probability of a series of independent events is the product of the probability of
each event occurring. Thus, if a system has a losing percentage of 40%, the odds of a
run of five losses in a row are (0.40 × 0.40 × 0.40 × 0.40 × 0.40) = .01 or 1%.
Ch.2 Money and Portfolio Risk Management - ROI - ANSWERcalculated as net profit
divided by initial capital at the beginning of the measured period.
Ch.2 Money and Portfolio Risk Management - Determining Optimal Position Size -
ANSWER1. risk of ruin formula
2. theory of runs formula
3. optimal f/ Kelly formula
Ch.2 Money and Portfolio Risk Management - Risk of Ruin - ANSWER3 data:
PACKAGE) The Integration of Technical Analysis |
Questions and Verified Answers| Grade A| 100%
Correct
Ch.1 System Design and Testing - A Complete Trading System - ANSWER1. Markets—
What to buy or sell
2. Position Sizing—How much to buy or sell
3. Entries—When to buy or sell
4. Stops—When to get out of a losing position
5. Exits—When to get out of a winning position
6. Tactics—How to buy or sell
Ch.1 System Design and Testing - Types of Technical Systems - ANSWER1. Trend
Following
1a. Moving Average Systems
1b. Breakout Systems
2. Pattern Recognition Systems
3. Reversion to the Mean
4. Exogenous Signal Systems
Ch.1 System Design and Testing - Problems with Trend-Following Systems -
ANSWER1. Popularity strains liquidity, increases slippage
2. Whipsaws common during trading ranges
3. Lag entries and exits, missing profit potential
4. Small losses awaiting new trends
5. Drawdowns from consecutive losses
6. Large drawdowns from small consecutive losses
7. Extreme volatility in equity curve
8. Parameter shifts decrease adaptability
Diversification into multiple systems helps
Countertrend systems can offset losses
Complexity if pyramiding signals added
Ch.1 System Design and Testing - Data - ANSWER- data must be sufficient to provide
at least 30 to 50 trades (entry and exit) and cover periods where the market traveled
up, down, and sideways
- Cleanliness of data is a necessary requirement. Any anomalies or mispriced quotes
will have an effect on the system test
- To test a daily system, for example, two years or more of daily data is required at
the very least
,Ch.1 System Design and Testing - Special Data Problems for Futures Systems -
ANSWER1. Limited contract lifespan, insufficient for system testing
2. Price difference between expiration and rollover contract
3. Splicing contracts together is challenging
Ch.1 System Design and Testing - Perpertual/ Constant Forward Contract -
ANSWER1. Perpetual contracts interpolate between two contracts
2. Weighted by time to a fixed forward date
3. Favors near contract initially, then shifts weighting
4. Gives smooth price series without rollover gaps
But deviates from actual contract prices
Ch.1 System Design and Testing - Continuous Contract - ANSWER1. Adjusts contract
prices for rollover spread
2. Begins with nearby contract prices
3. Rollover date set before expiration
4. Spread accumulated over rolls
5. Adjusted prices match system trade costs
6. No price distortion, matches history.But adjusted prices differ from actual
7. Reflects price moves, not price levels
8. Gives realistic view for system designer
Tradeoff between accuracy and realism
Ch.1 System Design and Testing - Optimization - ANSWER1. involves changing system
parameters to improve performance
2. Can eliminate useless parameters that don't work historically
3. Test impact of stops and exit rules with optimization
4. decide what the optimization is looking for in the data, objective function
5 The out-of-sample results are theoretically what the system should expect in real
time. Invariably, the out-of-sample performance will be considerably less than the
performance generated in the optimization
Ch.1 System Design and Testing - Problems of Optimization - ANSWER1. Curve-fitting
optimizes to historical data, not future
2. Overfit systems often fail in live trading
3. Avoid over-optimization and false confidence
Ch.1 System Design and Testing - Objective function - ANSWERanalyst must decide
what the optimization is looking for in the data. Is it looking for net profit, maximum
drawdown, Sharpe ratio, percentage of winning trades, MAR ratio or any other.
Ch.1 System Design and Testing - Methods of Optimizing - ANSWERan optimization
should be done over a considerable period of price data and include those periods
when the prices are in trends and in trading ranges
Ch.1 System Design and Testing - Avoid Curve Fitting - ANSWER1. optimize only a
portion of the data, called in-sample (IS) data, and
,2. test the resulting parameters on another portion of the data, called out-of-sample
(OOS) data, to see if positive results continue in data not seen before by the
optimization process.
3. use more than one market as the out-of-sample test.. A reliable system should
work in most markets.
Ch.1 System Design and Testing - Selection of data - ANSWER1. Use basket of
securities, not just one
2. Generates sufficient trades for significance. More trades increases statistical
validity(over 30 trades)
3. Diversification reduces peculiarities
Ch.1 System Design and Testing - Walk Forward Optimization - ANSWER1. Optimizes
small initial dataset
2. Tests on subsequent out-of-sample data
3. Example: 1 year optimized, 6 months tested
4. Record resulting parameters
5. Optimize next year, include previous OOS
6. Test on new out-of-sample data again
7. Slide window forward through data
8. Each optimization has out-of-sample test
Analyze all results for consistency
Ch.1 System Design and Testing - Profit Measures - ANSWER1. Profit factor - ratio of
total profit to total loss. Better > 2
2. Outlier-adjusted profit factor - removes anomalies (largest profit). Less than 1 is a
bust.
3. Win percentage - frequency of profitable trades (30% - 50% for trend following).
>60% should be look for
4. Annualized return - versus a benchmark
5. Payoff ratio - average win/average loss
6. Win/loss duration ratio
7. Efficiency factor - net profit/gross profit
Stability - profit metrics should be robust
Screen initially with profit factor above 2
Win percentage usually 50-70%
Payoff ratio above 2 for trends
Duration ratio above 1, above 5 better
Efficiency factor 38-69% typically
Ch.1 System Design and Testing - Risk Measures - ANSWER1. Maximum drawdown -
largest loss from equity peak
2. MAR ratio - annual gain/max drawdown percentage
3. Max Consecutive losses - risk of extended drawdowns
4. Longest flat time - capital not in use
5. Time to recovery, from large drawdowns - recuperation ability
, 6. Max Favorable/adverse excursions - primary use is to give hints as to where
trailing stops should be placed to take advantage of favorable excursions and reduce
adverse excursions.
7. Sharpe ratio - return vs. volatility
Flaws: uses average return, equal up/downside
8. Return retracement ratio - return/max loss
9. Sterling ratio - arithmetic average of annual net profit divided by average annual
maximum drawdown
10. Maximum loss - worst possible loss from peak
11. Sortino ratio - same as Sharpe but downside volatility only
Ch.1 System Design and Testing - GOOD TRADING SYSTEM (from Tushar Chande) -
ANSWER1. Positive expectation—Greater than 13% annually.
2. Small number of robust trading rules—Less than ten each is best for entry and exit
rules.
3. Able to trade multiple markets
4. Incorporates good risk control—Minimum risk as defined by drawdown should not
be more than 20% and should not last more than nine months.
5. Fully mechanical—No second-guessing
Ch.2 Money and Portfolio Risk Management - Drawdown - ANSWERdrawdown. It is
defined as that amount by which the equity in an account declines from a peak.
Ch.2 Money and Portfolio Risk Management - Monte Carlo simulation - ANSWER1.
not use the rules, variables, or parameters in the original trading system. It uses only
the actual trades, entry and exit, and the profit or loss from each.
2. money-management test rather than a system test, although obviously the system
determines the trades.
3. done many times, usually at least 100 times and better if 1,000 or 2,000 times.
4. An equity curve is then created for each scrambled sequence of trades. The results
from each equity curve are then assembled to give the results and related to a
normal distribution curve
Ch.2 Money and Portfolio Risk Management - Theory of Run - ANSWERstates that
the probability of a series of independent events is the product of the probability of
each event occurring. Thus, if a system has a losing percentage of 40%, the odds of a
run of five losses in a row are (0.40 × 0.40 × 0.40 × 0.40 × 0.40) = .01 or 1%.
Ch.2 Money and Portfolio Risk Management - ROI - ANSWERcalculated as net profit
divided by initial capital at the beginning of the measured period.
Ch.2 Money and Portfolio Risk Management - Determining Optimal Position Size -
ANSWER1. risk of ruin formula
2. theory of runs formula
3. optimal f/ Kelly formula
Ch.2 Money and Portfolio Risk Management - Risk of Ruin - ANSWER3 data:
