Pullback Scale-in Within Price Range By Ken Hodor 10/19/11

Current Market The recent market looked choppy to me How can I effectively make money? Dust off my old scaling routines and improve them

Observation and experiment Markets are random If I can develop a strategy that make money here it will work everywhere. Only found one strategy style that works See Ken’s Stock Market presentation on XSProfits.com on 2/9/11 at: http://xsprofits.com/Presentations2011.aspx After investigating many different strategies over the past 4 years, I believe I finally found a style that works. This resulted from my exploration of “Ken’s Stock Market” presentation I made on 2/9/11 and archived on XSProfits.com. The problem was markets are basically random. By clicking on f9 in the above presentation spreadsheet you will see various market charts. If you look at enough of them you will find one that very closely reflects the current market. The basic concept of a winning strategy is to buy when a market pulls back and sell when it advances above your initial purchase price. This presentation is my latest attempt to make the most out of the trading style of buying on pull backs.

Objectives Minimize initial risk (drawdown) I hate losing money…especially mine Use Optimal f for position sizing Want the fastest possible gain Be able to apply this on any tradable equity Want to trade across various asset classes My emotional make up indicates extreme stress when I lose money on initial entry. Only when I start to play with the “house’s money” do I finally feel less stress. So the initial constraint of the trading system must have very little initial drawdown. I want to increase my gains as fast as I know possible. So I have chosen “optimal f” for my position sizing. The strategy automatically computes the trade size based on what it accumulates. Since I want to spread out my risk across 5 non-correlated asset classes I want this same strategy to work on any tradable equity. The 5 asset classes I have chosen are: Cash, Forex, gold or silver, SPY (general stock market) and bonds. Then utilize as much leverage as possible to improve my returns.

Basic Strategy Look for a number of lower highs--pullbacks Buystops to enter at yesterday’s high Look for a number of higher lows Sellstops to exit position Don’t buy when the market is selling off. So use the previous day’s high as an entry point for a buy—using buystops at yesterdays’ high. Then sell when there has been a significant rise in the price. Use sellstops at previous day’s low to exit.

Trading range Determined by historic high and low I want the computer to do as much for me as possible. When ever I can teach it to learn this minimizes the amount of thought and potential errors I introduce into the trading. So one of the first things it can learn is to develop a trading range.

Money Management My maximum market exposure for this asset class is based on funds I allocate Say…20% of my assets would be allocated to SPY Trade size is based on the allocated funds divided by scales based on distance between high and low If we have $10,000 and 10 scales there would be $1,000 available to buy at each scale

Artificial Intelligence Market conditions constantly change Let the strategy learn the best parameters to use.

General Idea The above daily chart shows the general idea of this style of trading. Buying at the previous day’s high using a buystop. Then selling at the low of the previous day’s low.

Basic Strategy Starting on 8/10, I let the software learn about the trading range. The green lines indicate the top of the range (resistance) and the red lines indicate the bottom of the range (support). So there is no slope to these lines—they are flat. The software then divides the current range (between the red and green lines) into 10 scales—which can be likened to the rungs on a ladder. Each time the price moves down it enables more shares to be purchased. When price moves up it sells proportionately more shares. If it gapped up above the green line it would sell all shares. Notice also the number of shares traded. The share counts are 8 then 24 then back down to 8 again, etc. So the number of shares traded was not very many with $10,000 of capital allocated to this equity. What is nice is it consistently makes money.

No Slope Equity Curve What I mean by no slope is the range lines are flat. Which we liken to support and resistance lines. The above backtest shows the return over approximately 2 months on $10,000. The return is approximately 8% or over 48% annualized.

No slope Performance This performance report shows the strategy has a 75% profitable success rate. Missing from the above is the open position which indicates a profit of about $200. This is the reason this report does not show the $800 profit from the previous equity curve. From these results the scaling strategy showed promise. So I continued to refine it.

0.01 Slope Factor I decided to look at narrowing the range automatically. This produces even better returns by trading in a narrower range. This chart shows a slope factor of 0.01 (slight narrowing). So I decided to optimize this variable and see if my profits would improve.

Optimize slope This chart shows how varying this one slope parameter changed the returns. The slope parameter varied between 0.01 and 0.50. It turns out all conditions are profitable. This generally implies the strategy is robust. It does not matter what you chose it will make money. The optimal profit happens when the slope parameter is 0.29. If the market conditions change I would expect this strategy to continue to make money with this parameter value.

Optimal Slope Factor This shows the trading effect of this optimal slope factor of 0.29 applied to SPY using this strategy. Once again this starts with $10,000 of capital. Notice the number of shares has increased. This is due to the optimal f money management together with the optimized strategy slope parameter.

Optimal Slope Factor Equity Curve This shows the returns for approximately 2 months. What I like about this is the very low initial drawdown (meeting my original objective). In addition the strategy continues to make money even with a slight downward price movement. If you remember with no slope the return on $10,000 was only about $800 over the same period of time. So the returns have improved by 3 times by changing the slope parameter.

Optimal Slope Factor Performance This shows the results trading with a maximum of 100 shares using this optimal value to the slope.

What if we used Options instead? Returns should improve Limit my downside risk Stops not necessary This strategy looks pretty good with equities. What about if we applied this to options? I always like to get the most bang for my bucks. We would expect the returns should improve dramatically. In addition the downside risk is limited by the value of the options. So no stops would need to be considered.

SPY 120 Strike Oct Option One addition I found when trading options is to take profit when you have it. So I added a profit target to enhance returns. In this backtest of the 120 strike call, the profit target was $160 and the initial capital stayed at $6,000. The bottom chart shows the drawdown to almost $20,000. Which remains nicely above the initial $6,000 starting capital. If you would have entered the market here you would have taken some major heat to the initial $6,000 capital.

SPY 120 Strike Oct Option Equity Curve Once again this equity curve shows very low initial drawdown. It also shows the very dramatic drawdown.

SPY 120 Strike Oct Perf Summary This was a particularly high success rate. I would not expect this high of a success rate typically. Although a bull market this would be expected.

Another way to look at comparison The bottom equity curve is plotted from $0. To graphically illustrate how $10,000 of equity grows trading SPY directly—about a 9% gain. To me this is not very exciting.

Compare SPY 115 to 120 Strikes The bottom of these charts also start at $0. Instead of a 9% gain as on the previous chart these returns are multiple 100s of percent over the same time period. Also notice the relative performance using the same strategy applied to the SPY 115 strike and the 120 strike. These both used the same $6,000 initial starting capital. Trading the 115 strike (top chart) grew to $39,030 and the 120 strike (bottom chart) grew to $165,562—4 times improvement in returns using 120 strike. So by choosing a strike near or just above the expected top of the trading range nets out the best returns. Also realize this works well because of the liquidity afforded by SPY and all its derivatives. Other equities may not have enough liquidity to take advantage of trading various option strikes. For example I would not trade any options on Ultra ETFs. The liquidity is far to low. This causes very wide spreads that make profit much less likely.

Manual Implementation Buy Side At the end of the day or before the market opens set up a buystop at previous days’ high Determine the trade size—example $10,000 allocation Subtract recent lowest low from highest high Divide this by 10 (steps) If $1 per step this would mean for each dollar drop buy 1/10 of the shares $10,000 would buy. If fall drops $5 then buy 5/10 of shares $10,000 would buy. This can be done on TOS manually. It works very well for someone that works and cannot be at their machines during the day. All setup can be done in after hours. Either at night after the market closes or in the morning before the market opens. The only thing you have to do is set up your buystops or sellstops based on the last close. The only major complexity is money management. This may require breaking out the old spreadsheet to make appropriate adjustments to the quantities bought or sold.

Manual Implementation Sell Side At the end of the day or before the market opens set up a sellstop at previous days’ low Determine the trade size—example $10,000 allocation Subtract recent lowest low from highest high Divide this by 10 (steps) If $1 per step this would mean for each dollar rise sell 1/10 of the shares the new equity position. If rise by $5 then buy 5/10 of shares equity position.

Caveat Emptor (Buyer beware) Always remember “the market can stay irrational longer than you can stay solvent.” The strategy works well in a sideways or slightly down market. It works extremely well in a bull market. However, if the market plunges unabated with lower highs you have nothing at risk. There is considerable “heat” if the market plunges with fits and starts that suck you in. “Caveat Emptor” is Latin for buyer beware. Although I have shown some very dramatic results, please be careful and limit your exposure—especially when trading options.

Conclusion This strategy works well on SPY and other equities But it works extremely well with options Work in progress: automated options trading