The Opening Bell Deviation Theory Overview The Trade Possibility Analysis Results & Conclusions Trade Possibility: Percent Change Heat Map This experiment was to a sensitivity analysis to examine price deviations of 20% or more shortly after the opening bell to determine if significant same day profits can be made consistently. Though observation, stocks that rose more than 20% shortly after the opening bell seemed to rise substantially within the next few hours leading to tremendous profits. The experiment’s hypothesis is that stocks that rise more than 20% shortly after the opening bell will lead to tremendous profits within the hour Project Vision: To prove statistically if this pattern would produce consistent returns by capturing Alpha and modeling the pattern with intraday data Value Proposition: Determine a pattern that would provide consistently high returns to investors who are willing to take on higher than normal risk for higher returns The procedure had four phases. First, every trade possibility was located in TC2000 and recorded in excel from 1/4/2017 to 4/17/2017. Following this, 1.2 million rows of historical minute stock data was downloaded from Thomson Reuters into excel. Second, code was written to simulate the stock market in which stocks were bought and sold depending upon 22,500 combinations of independent variables. Third, data from each scenario was analyzed to determine which scenario produced the most consistent and profitable results. Fourth, a conclusion was drawn based on the analysis of the results of the experiment. The hypothesis was proven as multiple profitable and consistent trading patterns were discovered from the 22,500 combinations of independent variables that were run in the stock market simulation. The hypothesis was proven, multiple profitable and consistent patterns were found. The Good Scenario produced amazing results. This Scenario turned $30,000 into $45,000 in 4 months The best weekly yield was 70% on $10,000 High Stop Percent greatly impacts profits Most of the stock that were gathered were penny stocks which are very volatile. A Stop Percent of -5% was to high and would result in almost every trade stopping out. Higher stops are needed in trading penny stocks A trade possibility is a U.S equity that had a high of greater than or equal to 20% of the previous close on a day and had volume greater than or equal to 100000 on a day The Heat Map Each cell in the heat map represents the percent change for the combination of independent variables (for ranges see legend above). Results are grouped into four categories: Best, Moderate, Loser, Big Loser Two Scenario examples are shown below, one good one bad This is not the full Heat map as it would not fit on the board Example: Good Scenario The Good Scenario had a PctOBD of 30%, Tick Range from 10 to 60, Price Range from 4 to 8, Target Percent of 40%, and Stop Percent of -10%. This Scenario turned $30,000 into $45,000 in 4 months. Bad Scenario The Bad Scenario had a PctOBD of 30%, Tick Range from 10 to 120, Price Range from 2 to 4, Target Percent of 40%, and Stop Percent of -5%. This Scenario turned $30,000 into $12,000 in 4 months. Obstacles/Weakness Data Minute data for specific stocks on specific dates was hard to gather Data bases with minute tick data can be hard to gain access to A unique program had to be made just to gather the specific data Programs Five different programs were used to gather and analyze the data. This includes TC2000, RStudio, Thomson Reuters, Microsoft Access and Microsoft Excel This can make it difficult to move and analyze data Trade Volume Volume was not accounted at time of buying stocks to see if their were enough share strading at the minute you would buy Control Variables Date Minute Open Minute High Minute Low Minute Close Volume Exchange Independent Variables Starting Cash BlockSize Transaction Cost PctOBD Tick Range Price Range Target Percent Stop Percent Dependent Variables Net Profit Dollars Per Trade Number of Trades Apricus Biosciences, Inc. is a San Diego based biopharmaceutical company APRI had a drug that was approved by the government APRI opened at 20% and reached a high of 178% Great profit could have been made though trading this stock Question Can significant and consistent returns be made shortly after the opening bell though trading penny stocks? Additional Study Areas Areas for Additional Study Expand the number technical indicators used (like Bollinger Bands) Expand the number of independent variables Compare the best pattern to a benchmark Verify statistically the extent impact of various variables Areas for Improvement Include fundamental analysis as part of the approach Find tools that are better than Excel for analysis Gather more data to be certain of results Good Scenario Program Collect Independent Variables: By testing every combination of independent variables, 22,500 scenarios were run to find the best results. Each cell on the heat map on the right represents a combination of the seven independent variables listed below. Good Scenario from 1/4/2017 to 4/17/2017. Orange Line: Cash steadily increased because of regular profits. Blue Line: This scenario was fairly profitable resulting in spikes on the blue line Hypothesis TC2000 was used to locate stocks that had a high of greater than or equal to 20% of the previous close and had volume greater than or equal to 100000 based upon the hypothesis TC2000 was also used to capture the previous day close for every trade possibility RStudio was used to connect to the Tomson Reuters and gather a full day worth of minute tick data (High, Low, Open, Close, Volume) for all 993 different trade possibilities from 8 exchanges Data from 1/4/2017 to 4/13/2017 100 Calendar Days 68 Trading Days Microsoft Access was used to store the 7944 excel files Access was also used to create the weighted averages for the minute High, Low, Open, and Close Data was then brought from Access into Excel for analysis Stocks were bought when the percent change crossed though the PctOBD and when the other independent variables were within range Stocks were sold once the target percent or stop was hit If the target and stop were not hit the stock would sell at the end of the day It was assumed that the Transaction Cost was 16 dollars per trade It was assumed that the Starting Cash was $30,000 It was assumed that the BlockSize, cash used per trade, was $10,000 Bad Scenario Stocks that rise more than 20% shortly after the opening bell will lead to tremendous profits within the hour Acknowledgments PctOBD Tick Low Price Low Target Percent Stop Percent This project took began as just a observation and became so much more. I would like to thank Professor Calhoun, Professor Kaufman, Professor Anderson, and Professor Bozdog on their help and recommendations through out this experiment. Tick High Price High Buy “This experiment was run 22,500 times” PctOBD Tick Low Tick High Price Low Price High Bad Scenario from 1/4/2017 to 4/17/2017. Orange Line: Cash steadily decreased because of constant losses. Blue Line: The Stop Percent of -5% was to high so 88% of the trades stopped out resulting in a flat blue line 20% 60 .01 1 30% 10 120 .50 2 Procedure 40% 30 390 1 4 50% 2 8 4 ∞ Collect Downloaded a full day of minute tick data from 8 exchanges for 4 months for every trade possibility Trade possibility: high of the stock for the day is greater than or equal to 20% Combinations of independent variables resulted in profits and losses as shown in the heat map at right Outcome Only 34% of the trades were profitable in this Scenario. However the Target Percent was 4 times greater than the Stop Percent so profits were bigger than losses resulting in a good Scenario Develop & Execute Simulated the stock market in excel using the historical data in which stocks were bought and sold depending upon the variables Sell Develop & Execute Analyze Analyzed data from experiment in Microsoft Excel Reviewed profits based upon combinations of independent variables Target Percent Stop Percent 5% -5% 10% -10% 20% -20% Conclude Organized scenarios from best to worst Determined the variables that impacted how well a scenario performed Outcome 88% of trades were losses because the Stop Percent was to high at -5%. The stocks traded were to volatile and often hit the stop before it could take a profit 30% -30% 40% -40%