Sunday, April 23, 2017

Alpha Prime Trading Model


Program Objectives: The Alpha Prime algorithmic trading platform a discretionary portfolio dedicated to providing superior returns on investments in all market conditions.  The objective is capital appreciation and growth. The portfolio aims to achieve a high absolute rate of return by utilizing proprietary metrics in applied mathematics and technical analysis. 

This is a long / short strategy, buying highly liquid securities to achieve our desired performance results. Taking into consideration concentration risk, we will be utilizing a mix of long/short securities to mitigate systemic and idiosyncratic risk.

The Alpha Prime algorithmic trading platform is based on the belief that a diligent and nimble investor can take advantage of short- and medium-term market inefficiencies. Opportunistic trading can produce profits for our investors and manage the risk of overall market movements.

Program Rules: The basic underlying mathematical premise behind the trading methodology assumes a highly mean-reverting strategy and directional momentum bias. We intend on deploying a maximum of 5% of the total portfolio buying power per trade to mitigate concentration risk. We will maintain stop-losses per trade that equate to no more than 0.5% of the unlevered portfolio value. Margin will be used. To mitigate portfolio volatility, we will maintain a downside beta neutral strategy. Our profit objective is a gain within 5 - 15 days.

Security Selection Criteria: We will only buy those securities that are highly liquid and trade above a certain dollar amount. For the purposes of this program we will be buying securities that trade more than 1,000,000 shares daily at a price above $20.00.

Momentum Bias: The decision to be long or short the security will depend on its individual momentum bias and that of the momentum bias of the general market (S&P 500).

Long Candidates

The securities to be considered are as following:

·        20-day exponential moving average > 50-day exponential moving average

·        50-day exponential moving average > 200-day exponential moving average

·        Slope of the 200-day exponential average > 0

·        SCTR > 90 (will go as low as 75 if warranted)[1]

The momentum indicators in the SCTR used to determine directional bias include:

·        Percent above/below its 200-day exponential moving average

·        125-Day rate-of-change

·        Percent above/below 50-day exponential moving average

·        20-day rate-of-change

·        3-day slope of PPO-Histogram

·        14-day RSI

We prefer to see a security rank in the strongest 10% of its peers prior to going long. For short candidates, we prefer the security to rank in the bottom 10% of its peers. 

 

Short Candidates

The securities to be considered are as following:

                    20-day exponential moving average < 50-day exponential moving average

                    50-day exponential moving average < 200-day exponential moving average

                    Slope of the 200-day exponential average < 0

                    SCTR < 10 (will go as high as 25 if warranted)

We prefer to see a security rank in the strongest 10% of its peers prior to going long. For short candidates, we prefer the security to rank in the bottom 10% of its peers. 

Target Candidates

A security will be targeted as a potential trade depending on the slow stochastics %K (5,1)[2] reading.

%K (5) = ((Current Close - Lowest Low)/ (Highest High - Lowest Low) * 100) t-5

%D (1) = 1-day SMA of %K



Lowest Low = lowest low for the look-back period

Highest High = highest high for the look-back period

%K is multiplied by 100 to move the decimal point two places



If the above listed long criteria are met, then a long candidate is targeted when slow stochastics %K (5,1) < 20.

If the above listed short criteria are met, then a short candidate is targeted when slow stochastics %K (5,1) > 80.

The Trigger

Buy a long candidate near the close of trading when slow stochastics %K (5,1) rises above 20.

Sell a short candidate near the close of trading when slow stochastics %K (5,1) falls below 80.

Exiting the Trade

The following rules will be used to exit a trade.

For long positions:

Sell the position when the daily slow stochastic %K (5,1) rises above 80 and the stock price is below the 20-day exponential moving average.

or

If above the 20-day EMA, sell 1/2 position when the daily slow stochastics %K (5,1) rises above 80. The 20-day EMA becomes your stop for the remainder of the position. Sell on the open of the day after it breaches to the downside if the stock opens lower than the 20-day EMA. If it opens higher than the 20-day EMA, the 20-day EMA becomes your intra-day stop.

or

When the stock closes below the predetermined stop loss. Sell at the start of the next trading day if the stock opens below the stop loss. If the stock opens above the stop loss level, sell intra-day if the level is breached.



For short positions:

Cover the position when the daily slow stochastic %K (5,1) falls below 20 and the stock price is above the 20-day exponential moving average.

or

If below the 20-day EMA, sell 1/2 position when the daily slow stochastics %K (5,1) falls below 20. The 20-day EMA becomes your stop for the remainder of the position. Cover on the open of the day after it breaches to the upside if the stock opens higher than the 20-day EMA. If it opens lower than the 20-day EMA, the 20-day EMA becomes your intra-day stop.

or

When the stock closes above the predetermined stop loss. Cover at the start of the next trading day if the stock opens above the stop loss. If the stock opens below the stop loss level, cover intra-day if the level is breached.

Maintaining a market neutral position.

At the close of trading each day we examine our total beta-neutral long/short bias within the portfolio. We will utilize overnight protection against adverse price swings using derivatives or ETF’s. This will mitigate systemic risk versus unforeseen events when the market is closed. 

On an intraday basis, we will close the beta-neutral hedge if the market (S&P 500) opens higher. 

If the 200-minute simple moving average is breached to the downside and the S&P 500 is turns negative during trading, beta-neutral hedges will be redeployed. They will be removed should the market recover above the 200-minute simple moving average and the market goes positive. 

If the market (S&P 500) opens lower we will maintain the over-night downside beta-neutral hedge until the point where the market goes positive on the day and a break to the upside on the 200-minute simple moving average occurs.


The breach above or below the 200-minute moving average will be confirmed by a movement in the MACD Histogram (1,200,20) one standard deviation above or below the mean over a 200-minute time span.

Position Size.

We will calculate the 90-day variance for each security that we add to the portfolio. We will deploy assets to the position equal to the minus one standard deviation downside that coincides with our total portfolio downside risk of 0.5% of the unlevered portfolio value.

Trade Example:






Joseph S. Kalinowski, CFA

No part of this report may be reproduced in any manner without the expressed written permission of Squared Concept Asset Management, LLC.  Any information presented in this report is for informational purposes only.  All opinions expressed in this report are subject to change without notice.  Squared Concept Asset Management, LLC is a Registered Investment Advisory and consulting company. These entities may have had in the past or may have in the present or future long or short positions, or own options on the companies discussed.  In some cases, these positions may have been established prior to the writing of the report. 
The above information should not be construed as a solicitation to buy or sell the securities discussed herein.  The publisher of this report cannot verify the accuracy of this information.  The owners of Squared Concept Asset Management, LLC and its affiliated companies may also be conducting trades based on the firm’s research ideas.  They also may hold positions contrary to the ideas presented in the research as market conditions may warrant.

This analysis should not be considered investment advice and may not be suitable for the readers’ portfolio. This analysis has been written without consideration to the readers’ risk and return profile nor has the readers’ liquidity needs, time horizon, tax circumstances or unique preferences been considered. Any purchase or sale activity in any securities or other instrument should be based upon the readers’ own analysis and conclusions. Past performance is not indicative of future results.



[1] The StockCharts Technical Rank (SCTR) is a numerical score that ranks a stock within a group of stocks. The methodology for these rankings comes from the wisdom of John Murphy, author of many books on technical analysis and contributor to the Market Message at StockCharts.com. Stocks are assigned a score based on six key indicators, which cover different timeframes. These indicator scores are then sorted and assigned a technical rank.
[2] Developed by George C. Lane in the late 1950s, the Stochastic Oscillator is a momentum indicator that shows the location of the close relative to the high-low range over a set number of periods. According to an interview with Lane, the Stochastic Oscillator “doesn't follow price, it doesn't follow volume or anything like that. It follows the speed or the momentum of price. As a rule, the momentum changes direction before price.” As such, bullish and bearish divergences in the Stochastic Oscillator can be used to foreshadow reversals. This was the first, and most important, signal that Lane identified. Lane also used this oscillator to identify bull and bear set-ups to anticipate a future reversal. Because the Stochastic Oscillator is range bound, is also useful for identifying overbought and oversold levels.

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