system summary

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System Summary A short to midterm trading strategy that seeks to buy large caps stocks that are making new highs and exhibiting price action that is outside what can be considered a “Normal Range” based on a weekly chart..

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System Summary. A short to midterm trading strategy that seeks to buy large caps stocks that are making new highs and exhibiting price action that is outside what can be considered a “Normal Range” based on a weekly chart. Description. - PowerPoint PPT Presentation

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Page 1: System Summary

System Summary

A short to midterm trading strategy that seeks to buy large caps stocks that are making new highs

and exhibiting price action that is outside what can be considered a “Normal Range” based on a

weekly chart..

Page 2: System Summary

Description• The elegance of RLCO is that it applies to any time frame, and

the same lens in one time frame may be used to identify the opportunity while a shorter term lens can be used to manage the trade. I view all of the trades in my shorter term accounts through a RLCO/SQC Lens. An in depth discussion of RLCO may be found in Mastermind Basecap Projects. RLCO uses the Regression Line Cross Over to identify trends, and SQC identifies breakouts. The system identifies breakouts of stocks using Bollinger Bands set at 1standard deviation of the previous 30 periods so as to be statistically significant. During this period, stocks were selected from target indicies which included the NASDAQ 100, THE S&P 500, and the Russell 1000.

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General Comments• This system was developed as an extension of the original work done by Dr. Ken Long and

the Regression Line Cross Over System.• The original thesis was that the RLCO Concepts could be adapted across multiple time

frames, and could be used for swing trading as well as longer term trend following systems.

• The rules developed here are rules that are;– Simple – Yet provide a degree of flexibility– Can be executed entirely when the market is closed using condition orders – Facilitates non emotional responses because the decisions are made when the market is closed.– Can be modified to fit the personality of the trader– Stresses Money Management techniques that:

• Encourage the trader to exit losing trades quickly– 1R is an expression of maximum risk – Not a design goal

• Encourage the trader to exit non-productive trades quickly– Non Productive trades tie up capital that can be used somewhere else

• Encourage the trader to be bold when the system is working well, and to be cautious when it is not.

Page 4: System Summary

Why RLCOUnambiguous in any timeframe – This trade looks pretty good from across the room…..

Page 5: System Summary

Inspiration/Background• As part of the RLCO ®EVOLUTION – How well would RLCO work as a Longer Term Trading

System – Swing and Beyond• Background: Initial back testing used a Worden product called Stockfinder to conduct

rudimentary backtests on how well a RLCO weekly system might work. (I view this as a “same way same day” backtest to see if it warrants further interest).

• Tested the S&P 500, NAS 100, the DJ30, the Mid Caps and the Small Caps over the period 1/1/2002 through 1/13/2013. – Entry criteria was go long when the weekly bar crossed above the BB top, exit when the weekly bar

closed below the BB top. Additional Stop Loss of 4%. (1Weekly ATR)• Win rates ranged from a low of 72% for the DJ-30 up to 76% for the small caps. • Avg Win is 3X the Avg Loss, with an overall system expectancy ranging from .86R on the Dow to

1.63 on the Small Caps. • Average winning trade lasts about 3.5weeks while the average loser is about a week and a half.

Calendar Days • The total number of trades was 52523, although some are duplicates based on index

membership. • No allowances made for pyramid positions or conversions of stops from hard to trail. There

were no heat restrictions and every trade is taken.

Page 6: System Summary

Logic, concepts, definitions– A short to midterm trading strategy that seeks to buy large cap stocks that are making new highs

and exhibiting price action that is outside what can be considered a “Normal Range” based on a weekly chart.

– Normal Range is defined as one standard deviation of the price action over the past 30 weeks– In this system, a target becomes eligible when the current close is outside the previously defined

normal range on a weekly chart.– We want to buy strength. We prefer targets that are gathering momentum and that will fuel

collective greed as the price action moves higher out of its normal range. – The system uses the weekly chart as the “eligibility” chart and the daily chart as the “decision”

chart. Trades are entered when the price action of the daily chart is taking out the highs of the weekly chart.

– The most important belief in this strategy is that the price can continue to rise outside of the statistically defined normal range. It behaves this way out of greed, herd behavior, and the desire to not be left behind. This belief is tempered with the knowledge that the trade will be exited at the first sign the price action may be returning to its’ normal range.

– The entry is not critical. Normally there will be multiple opportunities to enter once the trade is eligible. While it is certainly desirable to enter as early in the trend as possible, exits and trade management are key to trading this system successfully.

– Initial Stop – 1 Weekly Average True Range

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Logic, concepts, definitions

– Efficient Stock : An equity that is trending in an efficient manner. We define efficient as a stock whose ADX is above 20, whose price action is rising steadily and is generally touching or near touching the 20 period linear regression line on each successive day.

– Portfolio heat: The total amount or capital at risk based upon current positions and stops.

– Available Portfolio Heat: The total heat minus the total heat associated with any negative position

– The risk reward ratio based on current resistance levels is greater than 3:1.– When this trade works it typically works quickly. When it does not work, the same is

true. Exiting quickly makes subsequent re-entry much easier– If the trade hasn’t worked after five trading days, it probably won’t. Many times, an

equity will continue in a consolidation phase for sometime before breaking out either high or low. Staying in the trade during consolidation hoping for the breakout is a misuse of equity. Exit with a small profit or loss, re-enter when it’s appropriate. Consider plus or minus .2R as an exit target. If it is still at that level after five days, exit.

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Trading Targets

• Primarily Large Cap Stocks– S&P 500– Russell 1000– NASDAQ 100

Page 9: System Summary

Historical PerformanceLive trades were conducted 4 January 2013 – 31 Dec 2013

• Number of Trades 329• Winners 175 - Average Winner .91R• Losers 148 – Average Loser - .55R• Scratch – 6 • Expectancy per trade .24R• Standard Deviation of Completed Trades 1.02• System SQN 100 = 2.35 SQN = 5.57• Max Drawdown 10%• Total R = 79• Commissions expressed as R = 7.8R• Margin Interest expressed as R = 9.2R• Net = 62R

Normalized as 1% of the average account balance for the trading period

Page 10: System Summary

Entry rules• Trades are identified using the weekly RLCO charts and are

managed using the daily RLCO charts: • Rules:

– Price closes above BB (30,1)on a weekly chart. Stock is eligible to trade– Enter on a positive day when the previous close is above the BB top and

the open is above the previous close. • Doesn’t have to be the first day – it can be any day conditions exist

– Risk Reward Ratio is 3:1 based on Overhead Resistance– Set a hard stop of one weekly ATR. – Exit the trade when the stock closes below the upper BB boundary on a

weekly chart, when the stop is hit, or discretionary exit for poor performance. • Stops are adjusted according to trade management rules

Page 11: System Summary

Exit rules• Always let the market take you out of the trade (Exception is 3%/3R/50%) or discretionary

exit based on non performance• Never expose more than 1R of risk based on initial risk• First Stop is a hard stop based on 1 Weekly ATR, then change to trail it at ½ R Profit• Add to a position only after 1R is achieved, and only in ½ R increments. • General Rules for stop adjustments – Rules are based on the aggregate position (initial plus

add): Hard Rule 1R exposure based on most recent trade entry– ½ R – Hard stop to Trailing Stop – Original R Amount– 1R Continue – Add if appropriate (1/2 Initial R amount)- Good Momentum – efficient stock -

trader judgment– 2R Change stop from Weekly ATR to 1.5 Daily ATR (2R based on initial R amount)– 3R – Scale position back to 1R open profit with a weekly ATR trailing stop (start cycle over) (3R

based on Current R Amount) This allows a winning position to run but ensures that no single position becomes overbalanced in the account.

– When a position open profit reaches 3% of account value, reduce the position to 1R open profit.– If a single position accounts for 50% of the entire open profits, reduce that position to 1R open

profit

Page 12: System Summary

Position sizing rules• Position size uses .05% to 1.25% of the account equity plus an adjustment for market money

based on core equity . – Core equity is defined at the beginning of the month and is based upon trader discretion. Once it is

defined it is the equity reference point for the rest of the month. Core equity may be adjusted up during the month if the account size increases 15% or more. It may not be adjusted down

– Market Money is defined as the difference between core equity and current account value. Market Money can be positive or negative and is defined as any amount greater than core equity, or less than core equity. • During periods of gains, market money increases position size and during periods

of losses, the negative market money figure reduces the position size. Max Position size for swing trades is 1% of acct value plus 10% of market money value. – (Example: Core equity =$50K, current account value =$52K, market money = +$2K.

Position size will then be 1% of account equity ie $520+ 10% of market money $200 for a total position size of $720.) (Example 2 Core equity = $50K, current account value = $48K, Position size = 1% account equity $480 + 10% market money ie $50K – 48K = -2K x10% = -$200) = Total position size of $280.

• If losses persist, the system will reduce the position size to zero forcing a trading ban at a loss figure of about 8-10% core equity

• Minimum position size is .5R. Stop trading if market money drives position size below 0.

Page 13: System Summary

Margin/Money Management Rules

– Core Equity: The equity you define as the “floor” of the portfolio. This is the amount that will cause you to reduce your position size if it is violated. It can be adjusted on a regular basis – weekly, monthly, semi annually at trader discretion. It is an personal number established by the trader based upon individual beliefs and risk tolerance.

– The system performs well at a maximum portfolio heat of 12%. Portfolio heat is the total amount or capital at risk based upon current positions and stops.

– Available Portfolio Heat: Available Portfolio Heat is the total heat minus the total heat associated with any negative position. Example: Using a 1% position size, Let’ you have 7 open positions and 3 of them are currently negative, your total available portfolio heat would be 9% minus the existing heat of the 4 remaining positions.

– Market Money: This is normally a portion of money/profit beyond core equity that the trader is willing to risk. It is meant to increase position size during times when the system is working well. There are many formulas for increased position size, but normally a trader will risk an additional percentage of market money in addition to the core position size. Example: A trader has determined that her core equity is $50000. She determines that in addition to a 1% normal position size, she will risk 10% of the market money per trade. Her account has grown to $53000. She would risk 1% x $53000=$530, plus 10% of market money which is 10% x (53000-50000)=$300, for a total position size of $830 ($530+$300).

– Negative Market Money: This is defined as the amount of money below core equity which will cause the trader to reduce position size. This method will force the trader to reduce risk and the use of margin. Using the same example as above; Our trader has $50000 Core equity and 10% market money. She finds that her account has fallen to $48000. Her position size would be 1% x $48000=$480 plus 10% market money which is 10% x ($50000-$48000)= -$200. Position size =$480-$200=$280. If equity continues to fall, market negative market money will exceed 1% core equity and this is a signal to stop trading. I have a rule that says position size will not be less than .05%. When negative market money has driven the position size below .05% but>0, I use .05%. If the market money mandated position size falls below zero, stop trading and examine your system, rules, market type and psychology. Adjust core equity and resume trading only when you are confident you understand you system’s drawdown.

Page 14: System Summary

How to start the system from cash

Paper trade this for 3 months or until you are comfortable with the number and type of signals you receive, and that you are comfortable that you can respond to the signals and set the buy/sell orders and trailing stops. Consider trading at a reduced equity size with real money at a deep discount broker in order to build confidence and professionalism with real money before increasing size.

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Set-up samples - COP

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MO

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ACC

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RNR

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KR

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ESS

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ESS

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SNDK

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POM

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VLO

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DPS

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Closed trades– The Biggest Loser

Two Mistakes 4R Loss

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SPLS

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EA

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CSE

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GME

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ALSN

2nd biggest losing trade

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AWAY

3rd biggest loser Required discretionary exit

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IBKR

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Psychology TestDid you laugh or cry??

Page 35: System Summary

Final Thoughts/Lessons Learned•

– The entries in this system don’t need to be precise to be effective. Exits Do!– Earnings dates can be toxic. Make sure you are out five days prior – Post earnings are not so bad, but consider a choice

not to trade the gaps that are a result of an earnings beat as they tend to “RTM” or flat line.– Keep the money real. Consider paying yourself – As an example, any day the account makes more than 1%, you could pay

yourself 50% of the difference between 1% and total profit. Ex 1% = $500 Profit= $800, ½ the difference ($300) transfers out of the account.

– Looking at charts every day is important – It trains your inner voice– 1R is not a design goal. Get out as soon as you see the trade is not working. Consider choosing a discretionary exit such as

-.5R. 1R exits are typically gaps– The faster you get out the easier it is to get back in – it minimizes the psychological baggage– Don’t hedge within a market type

• A hedge technique was tested that put on a hedge when the daily and weekly charts fell back into the river - and got whacked each time. Wait for the signal that the market has changed

– The system will tell you when its time to stop trading (no eligible set ups) – Listen to it.– Scale in quickly when the trade is moving, but consider keeping your open exposure less than 1R. (A technique would be

to scale in 1/2R increments, and do not scale in more than twice).– Have a profit taking target, but stay in the game. When the trade profit exceeds ____% of account value, or 50% of total

profit, scale it back to initial position size and start over.(I used 3% and 50%, but will go to 5% and 50% in 2014). – If you are trading on margin, make sure you have a money management system that manages the margin exposure.

Page 36: System Summary

Learning JournalThe A HA Moment What I think

about/how does it connect

What will do about it

Results

RLCOW needs a mechanism to followup on closed trades for additional opportunities. Why not use existing swing systems that capitalize on temporary weakness.

What would I be comfortable with and what can I believe in.

Review closed trades from 2013 and 2014 and see how many times

Core Turbo Principles apply to this system

A sensible, professional way to utilize day trading buying power

Develop a ruleset and trade a reduced position size as proof of concept