by Steve Kern
on June 8, 2015
by Steve Kern
on June 5, 2015
Part IX: Appendices
Appendix B: Types of Orders and Other Trader Terminology
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- All or None (AON)
- Ask
- Bid
- Day Order
- Downtick
- Fill or Kill (FOK)
- Good ‘Til Canceled Order (GTC) or Open Order
- Immediate or Cancel (IOC)
- Leaves
- Limit, Limited Order, or Limited Price Order
- Liquidity
- Long
- Market on Close (MOC)
- Market Order
- Not Held
- Odd Lot
- Offer
- Opening Only or OPG
- Pegged Market
- Pull Back
- Quote
- Relative
- Round Lot
- Scale
- Scale Order
- Seat
- Short
- Short Covering
- Short Sale
- Stock Ahead
- Stop Limit Order
- Stop Order
- Time in Force
- Uptick or Plus Tick
- VWAP
- An Order Ticket usually includes the following:
- Contract Description
- Underlying
- Exchange
- Security Type: Stock, Option, Future, Future Option, Warrant, Cash, Index, Bond
- Currency
- Expiration Date
- Strike Price
- Option Type: Call/Put
- Action: Buy/Sell
- Order Description:
- Order Type: Limit, Stop, Stop Limit, Market, MOC, MOO, IOC, FOK, AON, etc.
- Quantity
- Limit Price
- Stop Price
- Time in Force: Day/GTC, Good after Time, Expiration Date and Time, Regular Trading Hours Only?
Proceed to Appendix B: Types of Orders and Other Trader Terminology (in Kirkpatrick and Dahlquist)
Chapter list for Kirkpatrick and Dahlquist
by Steve Kern
on June 5, 2015
Part IX: Appendices
Appendix A: Basic Statistics
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- Appendix Objectives
- The difference between descriptive and inferential statistics
- How to calculate common measures of central tendency and dispersion
- The process of regression
- The basic premises and statistics related to MPT
- Intro
- Returns
- Probability and Statistics
- Independence
- Permutations
- Combinations
- Descriptive Statistics
- Intro
- Descriptives statistics merely tries to describe or characterize data in a shorthand manner
- Inferential statistics tries to infer various statements about data based on observed outcomes or assumptions about outcomes
- Measures of Central Tendency
- Intro
- Mean (arithmetic mean)
- Median
- Mode
- Geometric Mean
- Also called “compound rate of return”
- Measures of Dispersion
- Intro
- Variance
- Standard deviation
- sample
- population
- unbiased estimate
- degrees of freedom
- Relationship Between Variables
- variance – one variable
- covariance – two-variable version of variance
- time series
- time series variable
- time series data
- observations of a variable at consecutive timer intervals
- r-squared
- Also called “Coefficient of determination”
- error term
- also called “residual”
- the portion of the unexplained Y variable in each period
- Autocorrelation
- also called “serial dependence”
- when the error terms themselves are correlated with each other
- Durbin-Watson test
- statistical test that helps detect autocorrelation
- Dependent variable
- the variable being explained
- Independent variable (“explanatory variable”)
- the variable doing the explaining
- Multiple regression
- We can extend the idea of regression to more than one independent variable
- multiple regression
- Logically, two explanatory variables are better than one, three are better than two, etc.
- Virtually any additional explanatory variable we include in a regression will improve the r-squared
- but using additional variables to improve r-squared is not always good
- Adjusted r-squared value penalizes the r-squared value as more independent variables are added to the regression equation. Is it beneficial to add a particular variable?
- Multicollinearity
- occurs when there is a reasonably strong correlation between two or more of the independent variables
- Multicollinearity clouds the picture concerning which independent variables are statistically significant
- Statistically significant = How likely is it tha tI would observe this outcome purely based on chance alone?
- Statistically significant threshold of 5% if often used. If we observe something that we would expect to see less than 5% of the time based strictly on chance alone, then it might be deemed statistically significant.
- Threshold of 1% would be a more stringent test.
- Statistically significant doesn’t always mean economically significant. Some trading systems might be statistically significant but because of transaction costs and other factors, might not be profit producing.
- Inferential Statistics
- Modern Portfolio Theory
- Performance Measurement
- Sharpe performance (or Sharpe Ratio)
- Treynor measure of performance
- Jensen’s alpa
- Advanced Statistical Methods
- Time series modeling
- ARCH and GARCH
- Generalized autoregressive conditional heteroskedasticity
- volatility of a series is not generally constant or consistent
- Maximum likelihood
- work backward from the observed data to make inferences about the probability distribution that produced those outcomes
- try to find the distribution that was most likely to be the source of the outcomes
- can be applied to many different statistical problems
- can even be an alternative to least squares in performing regression
- Artificial Intelligence
- Review Questions
Proceed to Appendix B: Types of Orders and Other Trader Terminology (in Kirkpatrick and Dahlquist)
Chapter list for Kirkpatrick and Dahlquist
by Steve Kern
on June 5, 2015
Part VII: System Testing and Management
Chapter 23: Money and Risk Management
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- Chapter Objectives
- Definitions and measurements of risk as it relates to money management
- The martingale betting strategy
- Diversifiable versus correlated risk
- Methods for testing money-management strategies
- The use of various types of stops to manage risk
- Methods for determining the minimum capital needed for a system
- Methods for determining the percentage of capital to allocate toward one system
- Intro
- Risk and Money Management
- Testing Money-Management Strategies
- Money-Management Risks
- Concepts
- Drawdown and Maximum Drawdown
- Theory of Runs
- Martingale Betting System
- Reward to Risk
- Normal Risks
- Positions size
- Number of Shares or Contracts
- Determining Optimal Position Size
- Risk of Ruin Formula
- Theory of Runs
- Optimal f and the Kelly Forumula
- Final Position Size
- Initial Capital
- Initial Capital– Monte Carlo Simulation
- Monte Carlo simulation projected equity
- Leverage
- Pyramiding
- Unusual Risks
- Psychological Risk
- Knowledge of the Market
- Diversifiable Risk
- Trade Frequency
- Temporal
- Security Quality
- Money-Management Risk Strategies
- Intro
- Protective Stop
- Hard Money or Dollar Stop
- Maximum Winning Adverse Excursion
- Trailing Stop
- Breakeven Level and Breakeven Stop
- Technical Point Versus Money Point
- Volatility Stop
- Maximum Winning Favorable
- Trend Line
- Adaptive
- Other Kinds of Stops
- Targets
- Execution
- Monitoring Systems and Portfolios
- If Everything Goes Wrong
- Conclusion
- Review Questions
Proceed to Appendix A: Basic Statistics (in Kirkpatrick and Dahlquist)
Chapter list for Kirkpatrick and Dahlquist
by Steve Kern
on June 5, 2015
Part VII: System Testing and Management
Chapter 22: System Design and Testing
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- Chapter Objectives
- The importance of using a system for trading or investing
- The difference between a discretionary and a non-discretionary system
- The mind-set and discipline required to develop and trade with a system
- The basic procedures for designing a system
- The role that risk management plays in system design
- How to test a system
- Standard measures of system profitability
- Why are systems Necessary?
- Discretionary Versus Non-discretionary Systems
- Benefits of a Non-discretionary, Mechanical System
- Pitfalls to a Non-discretionary, Mechanical System
- How Do I Design a System?
- Requirements for Designing a System
- Understanding Risk
- Initial Decisions
- Types of Technical Systems
- Trend Following
- Moving Average Systems
- Breakout Systems
- Problems with Trend-Following Systems
- Pattern Recognition Systems
- Countertrend Systems
- Exogenous Signal Systems
- Which System Is Best?
- How Do I Test a System?
- Special Data Problems for Futures Systems
- Testing Methods and Tools
- Test Parameter Ranges
- Designing a System– The “Nerves of Steel System”
- System Statistics
- Net profit
- Gross profit and gross loss
- Profit factor
- Number of trades
- Percent profitable
- Average trade net profit
- Largest winner or loser versus gross profit or gross loss
- Maximum consecutive losing trades
- Average weeks in winning and losing positions
- Buy-and-hold return
- Return on account
- Average monthly return and standard deviation
- Sharpe ratio
- Maximum drawdown
- Net Profit as Percentage of Maximum Intraday Drawdown
- Optimization
- Methods of Optimizing
- Whole Sample
- Out-of-Sample (OOS)
- Walk Forward Optimization
- Optimization and Screening for Parameters
- Measuring System Results for Robustness
- Intro
- Robustness simply means how strong and healthy our results are
- Robustness refers to how well our results will hold up to changing market conditions
- Components
- Profit Measures
- Profit factor
- Outlier-adjusted profit
- Percentage winning trades
- Annualized rate of return
- Payoff ratio
- Length of the average winning trade
- Efficiency factor
- Risk Measures
- Maximum cumulative drawdown
- Net profit to drawdown ratio
- Also called “recovery ratio”
- Maximum consecutive losses
- Large losses
- Longest flat time
- Time to recovery
- Maximum favorable and adverse excursions
- Sharpe ratio
- Other risk measures in the literature:
- Return Retracement ratio
- Sterling ratio (over three years)
- Maximum loss
- Sortino ratio
- Smoothness and the Equity Curve
- Equity curve
- Underwater curve
- What Is a Good Trading System?
- From the book: Beyond Technical Analysis, by Tushar Chande
- Positive expectation
- Small number of robust trading rules
- Less than ten each is best for entry and exit rules
- Able to trade multiple markets
- Can use baskets for determining parameters, but
- Rules should work across similar markets
- different stocks
- different commodities
- different futures, etc.
- Incorporates good risk control
- Maximum risk should not be more than 20% drawdown
- 20% drawdown should not last more than 9 months
- Conclusion
- Review Questions
Proceed to Chapter 23: Money and Risk Management (in Kirkpatrick and Dahlquist)
Chapter list for Kirkpatrick and Dahlquist
by Steve Kern
on June 5, 2015
Chapter 14: Moving Averages
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- Chapter Objectives
- What Is A Moving Average?
- How Is a Simple Moving Average Calculated?
- Length of Moving Average
- Using Multiple Moving Averages
- What Other Types of Moving Averages Are Used?
- The Linearly Weighted Moving Average (LWMA)
- The Exponentially Smoothed Moving Average (EMA)
- Wilder Method
- Geometric Moving Average (GMA)
- Triangular Moving Average
- Variable EMAs
- Strategies for Using Moving Averages
- Determining Trend
- Determining Support and Resistance
- Determining Price Extremes
- Giving Specific Signals
- What Is Directional Movement?
- Constructing Directional Movement Indicators
- Using Directional Movement Indicators
- What Are Envelopes, Channels, and Bands?
- Percentage Envelopes
- Bands
- Bollinger Band
- Keltner Band
- STARC Band
- Trading Strategies Using Bands and Envelopes
- Channel
- Conclusion
- Review Questions
Proceed to Chapter 15: Bar Chart Patterns (in Kirkpatrick and Dahlquist)
Chapter list for Kirkpatrick and Dahlquist
by Steve Kern
on June 5, 2015
Chapter 12: Trends– The Basics
- Chapter Objectives
- Know why identifying trends is paramount to profits in securites
- Be able to recognize an uptrend, downtrend, and a trading range
- Understand the concept of support and resistance
- Be familiar with the major methods of determining trends
- Be familiar with the major signals that a trend is reversing
- Trend– The Key to Profits
- 3 Steps
- Determine when a trend has begun, earliest time and price
- Enter a position in the trend
- Close the position when the trend is ending
- Trending is simple in concept but difficult in practice
- Why? Because determination of trend and trend reversal is a subjective decision that depends on one’s skill and experience and one’s ability to control one’s own emotions.
- All market participants make mistakes, but the regimented professionals correct theirs quickly
- All patterns are a combination of trend lines– up, down, or sideways (See Chapter 15: “Bar Chart Patterns)
- Trend Terminology
- Uptrend
- Downtrend
- Sideways trend – trading range or neutral area
- Support
- Resistance
- Basis of Trend Analysis– Dow Theory
- See Chapter 6: “Dow Theory” for review
- Charles Dow was one of the first of the modern technicians to write about the fact that stock market prices trade in trends
- Investors and traders must concentrate on the time horizon most favorable to their circumstances
- Trends are fractal
- Their behavior is the same regardless of the period
- minute-to-minute trends behave exactly like day-to-day trends with only minor differences:
- variation in liquidity over shorter periods can cause differences in this fractal behavior
- Dow proposed 3 principal time horizons
- primary (“tides”)
- intermediate (“waves”)
- minor (“ripples”)
- Dow didn’t have computers, so he focused on the first two. Today technicians focus on more trends than Dow observed
- Dow’s most important observation:
- Trends tend to continue rather than reverse
- Otherwise there would not be a trend
- Otherwise the trend could not be used for profit
- This second statement seems silly, but it underlies everything the technician assumes when looking for the beginning or end of trends
- Vexes the academic theoretician who believes that price changes are random
- Any particular trend is influenced by its next larger and next smaller trend.
- Within a rising trend can be many smaller trends, both down and up
- There are several smaller down- and uptrends within these
- This is the fractal nature of trends
- Any analysis of a trend of interest must include analysis of the longer and shorter trends around it.
- The longer trends will influence the strength of the trend of interest
- The shorter trends will often give early signs of turning in the longer
- Short-term trends reverse before medium-term, and medium-term trends reverse before long-term.
- Arbitrary trend categories
- Primary trend – measured in months or years
- Secondary or intermediate trend – measured in weeks or months
- Short-term trend – measured in days
- Intraday trend – measured in minutes or hours
- Dow – advanced the primary, secondary/intermediate, and short-term trends
- Dow identified technical means of determining when the primary trend had reversed direction
- Dow – “Father of Technical Analysis” (see Chapter 3 – History of Technical Analysis)
- How Does Investor Psychology Impact Trends?
- Supply and demand determine the price of any good
- When prices travel in a trend, they remain headed in one direction
- imbalance of demand and supply
- What makes a trend is the power of the buyers or sellers
- Do they have enough stock or money?
- aggressiveness or anxiousness of buyers and sellers
- do they have specific information or deductions, rational or irrational?
- are emotions of fear or greed propelling their action?
- positive feedback mechanism maintains that trend
- In an uptrend, buyers who have profited tend to continue being buyers and new buyers, seeing what they have missed, also buy
- In a downtrend, sellers must have stronger negative expectations and larger positions to sell
- How is the Trend Determined?
- Intro
- The trend is a direction rather than a line
- Price oscillates back and forth in smaller trends along its travel in the larger trend
- Any signs of reversal may only be for smaller trends within the larger trend.
- Securities occasionally “rest” during a trend and move sideways as the earlier rise or fall is “digested” by all the different players
- Peaks and Troughs
- Look for peaks and troughs
- Uptrend – the peaks tend to be higher than the earlier peaks, and the troughs tend to be higher than the previous troughs. It’s that simple.
- Downtrend – peaks are lower than previous peaks, and troughs are lower than previous troughs
- Determining a Trading Range
- Trading ranges (or sideways trends) occur when peaks and troughs appear roughly at similar levels.
- The peaks cluster at a certain price level
- The troughs cluster at a certain price level below the peaks.
- The configuration usually occurs after a larger trend has come to a temporary halt.
- A trading range is also called a:
- consolidation
- congestion area
- rectangle formation
- line formation
- Charles Dow used this term and had very specific rules to use this designation
- What is Support and Resistance?
- Resistance point:
- The highest point in the rise
- the level at which the advance has met with selling “resistance.”
- Sellers (supply) become more powerful and aggressive than the buyers (demand)
- Result: price decline from the peak.
- A single, high-volume, price peak often defines a resistance point
- But the price where large sellers actually begin to enter the market is unclear, especially if the high volume is preceded by a sharp price rise
- Resistance zone
- when more than one resistance level occurs at roughly the same price
- Support point
- Opposite of resistance point
- Single trough
- Buyers become as powerful or aggressive as the sellers and halt a price decline
- Remembered psychological barrier
- Support and resistance presumes that in the future, price will stop at these recorded levels or zones
- These zones will become barriers to future price action
- These zones will carry through time
- Once these zones are broken, they will switch functions
- Previous support will become resistance
- Previous resistance will become support
- Why Do Support and Resistance Occur?
- Have you ever bought a stock, watched it decline in price, and yearned to sell out for what you paid for it?
- Have you ever sold a stock, watched it go up after you sold it, and wished you had the opportunity to buy it again?
- Support
- Those who sold short near resistance will be covering at support because they have seen price halted before at the support zone and do not want to take the risk that price will rally again to the resistance zone
- Those who had been watching the stock but did not buy it at the support level earlier will be satisfied that the newest decline to the support level price is back to where they earlier had wanted to purchase it but “missed it.”
- Those who sold the stock at the low support level price when it declined from the high resistance price, saw the price immediately rise thereafter, and wish to reenter a position at the price they sold it earlier.
- The reasons are purely psychological, not fundamental or informational
- The presumption is that the more frequently prices halt at a zone, the stronger and more important that zone will likely be in the future
- Resistance
- Sellers who missed the high resistance price before
- Sellers who bought at the resistance level and want their money back
- Sellers who want to short the stock at resistance where it halted earlier
- Support and resistance zones, are price levels where supply and demand reach equilibrium for unusual but persistent psychological reasons
- What About Round Numbers?
- People think in terms of round number and act accordingly in the securities market as well
- Problem with this concept: the concept of round numbers is that knowledge of the tendency is widespread
- It is best to determine entry and exit points based on the technical situation rather than worry about round numbers
- How Are Important Reversal Points Determined?
- DeMark or Williams Method
- Tom DeMark and Larry Williams
- Bullish reversal: In a low bar, the analyst may look for two bars with higher lows directly on either side of the suspected trough bar
- The number of bars on either side can be increased to increase the importance of the trough
- but the number of troughs will be sacrificed
- The higher the number of confirming lows necessary, the more important the trough
- Bearish reversal: In a high bar, look for two bars on either side of it with lower highs
- At right edge of chart, it might not be possible to see the two bars on the right because they haven’t occurred yet
- Percentage Method
- Using 1% for example:
- Any time the price declines more than 1%, makes a low, and then rallies more than 1%, will define a significant trough
- The larger the percentage used, the more important but less frequent the reversal point
- Gann Two-Day Swing Method
- W.D. Gann swing method is very similar to the DeMark or Williams method
- Identify low bar
- Observe the two following trading days
- If these two days have higher highs than the low bar
- then the low bar is a support point
- originally Gann used three following trading days to determine a support point, but more recently it has been switched to two days.
- Identify high bar
- A resistance point is defined as any high bar during an uptrend that is followed by two successive bars with lower lows.
- Gann vs DeMark/Williams
- Sometimes the Gann rule reversal points do not occur at the DeMark/Williams reversal points
- Reasons
- The days of the actual reversal points were not followed by the required two successive days
- By Gann’s rule, the reversal may not occur on the actual high or low bar
- High Volume Method
- Very large volume can also identify a significant reversal point
- High volume indicates that larger than usual activity occurred on that trading day
- Can be one-day or two-day reversal pattern at peaks or troughs
- Stage of high emotion– signify either a panic or speculative bubble
- the actual price level at which the reversal took place is not identifiable on a large bar chart
- sometimes intraday action must be inspected to see at just what price level the majority of buying and selling occurred
- How Are Support and Resistance Zones Drawn?
- Draw a horizontal line through each significant trough (or peak) into the future
- lows of each bar
- close of each bar
- Extend these lines into the past to see if earlier price declines stopped at the same price level
- Where these horizontal lines bunch together, sometimes overlapping at the same price level is a support or resistance zone.
- Zones are usually stronger the more horizontal lines there are within it.
- The more times the price level has halted previous advances or supported previous declines, the stronger will be the resistance or support in the future
- Zone is constructed between the highest and lowest horizontal line
- Zone defines the actual support or resistance area clearly
- If a horizontal line is by itself with no other horizontal lines close to it, it is likely an independent support or resistance level.
- Such levels, unless accompanied by extraordinary volume, usually do not have the same strength in the future that a combination of horizontal lines might have within a zone.
- Prices will often enter the zone but will not break out of the outer horizontal line of the zone.
- If they do break that level, we have a “breakout” that has important consequences
- There can be a downward breakout too, when prices break below a support zone
- If there is another support zone at some distance below the current broken zone, prices will generally trade down to that next lower zone.
- A support zone in a declining market can become a price objective once a higher support zone is broken
- Support zones exist at all horizons– day, week, even minute-to-minute
- As time goes on, the importance of past horizontal lines diminishes for both support and resistance zones
- More recent price reversals are more important
- Human memory fades quickly
- How Do Analysts Use Trading Ranges? (Check back soon for more detailed outline– sign up for email list updates)
- Intro
- Range Trading
- Breakout Trading
- Directional Trends (Up and Down)
- Intro
- What is a Directional Trend?
- How Is an Uptrend Spotted?
- Using a Regression Line
- Using Trend Lines
- Scale and Trend Lines
- Accelerating Trend Lines
- Decelerating Trend Lines
- General Rules for Trend Lines
- Channels
- Internal Trend Lines
- Retracements
- Pullbacks and Throwbacks
- Other Types of Trend Lines
- Trend Lines on Point-and-Figure Charts
- Speed Lines
- Andrews Pitchfork
- Gann Fan Lines
- Conclusion
- Review Questions
Proceed to Chapter 14: Moving Averages (in Kirkpatrick and Dahlquist)
Chapter list for Kirkpatrick and Dahlquist
by Steve Kern
on June 5, 2015
Part III: Trend Analysis
Chapter 11: History and Construction of Charts
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- Chapter Objectives
- The advantages of presenting price information in a picture, or chart, format
- The construction of line charts
- The construction of bar charts
- The construction of candlestick charts
- The construction of point-and-figure charts
- The differences between arithmetic and logarithmic scales
- Benefits of Using Charts
- Jack Schwager, book: Technical Analysis (1996)
- Concise price history
- good sense of the market’s volatility, useful in assessing risk
- useful to fundamental analyst, relating areas of major price moves to fundamental conditions of those periods
- timing tool, even for fundamentalists
- money management tool, by defining meaningful and realistic stop points
- reflect market behavior that is subject to certain repetitive patterns
- chart concepts help develop profitable technical trading systems
- failed chart signals can lead to very profitable trading opportunities
- History of Charting
- What Data is Needed to Construct a Chart?
- What Types of Charts Do Analysts Use?
- Line Charts
- Bar Charts
- Candlestick Charts
- What type of Scale Should Be Used?
- Arithmetic Scale
- Semi-Logarithmic Scale
- Point-and-Figure Charts
- One-Box (Point) Reversal
- Box Size
- Multibox Reversal
- Time
- Arithmetic Scale
- Logarithmic Scale
- Conclusion
- Review Questions
Proceed to Chapter 12: Trends– The Basics (in Kirkpatrick and Dahlquist)
Chapter list for Kirkpatrick and Dahlquist
by Steve Kern
on June 5, 2015
Chapter 10: Flow of Funds
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- Chapter Objectives
- Understand why knowledge of the flow of funds is important to determining stock market valuation
- Understand why liquidity plays an important role in potential stock market valuation
- Be familiar with measurements of market liquidity
- Understand the relationship between Federal Reserve policy and the cost of funds
- Funds in the Marketplace
- Money Market Funds
- Margin Debt
- Secondary Offerings
- Funds Outside the Security Market
- Household Financial Assets
- Money Supply
- Bank Loans
- The Cost of Funds
- Short-Term Interest Rates
- Long-Term Interest Rates (or Inversely, the Bond Market)
- Money Velocity
- Misery Index
- Fed Policy
- Fed Policy Futures
- The Federal Reserve Valuation Model
- Three Steps and a Stumble
- Yield Curve
- Conclusion
- Review Questions
Proceed to Chapter 11: History and Construction of Charts (in Kirkpatrick and Dahlquist)
Chapter list for Kirkpatrick and Dahlquist
by Steve Kern
on June 5, 2015
Chapter 9: Temporal Patterns and Cycles
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- Chapter Objectives
- The long (50-60-year) Kondratieff wave cycle
- The 34-year cycle
- The decennial cycle
- Four-year cycles, including the election year pattern
- Seasonal tendencies in stock performance
- The relationship between January stock market performance and the rest of the year
- The relationship between events and stock market performance
- Periods Longer than Four Years
- Kondratieff Waves, or K-Waves
- Decennial Pattern
- Periods of Four Years or Less
- Four-Year or Presidential Cycle
- Election Year Pattern
- Seasonal Patterns
- January Signals
- January Barometer
- January Effect
- Events
- Conclusion
- Review Questions
Proceed to Chapter 10: Flow of Funds (in Kirkpatrick and Dahlquist)
Chapter list for Kirkpatrick and Dahlquist
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