Predictions and Suggestions from a machine learning based Algorithmic trading

#MachineLearning #AlgortihmicTrading #StockMarketAutomatedTrading  #LogisticRegression #Boosting

Predictions and Suggestions from a machine learning based Algorithmic trading

An algorithm is a specific set of clearly defined instructions aimed to carry out a task or process.

Algorithmic trading (automated trading, black-box trading, or simply algo-trading) is the process of using computers programmed to follow a defined set of instructions for placing a trade in order to generate profits at a speed and frequency that is impossible for a human trader. The defined sets of rules are based on timing, price, quantity or any mathematical model. Apart from profit opportunities for the trader, algo-trading makes markets more liquid and makes trading more systematic by ruling out emotional human impacts on trading activities.

We can create a Regression formula like below :

The dependent variable is the Return on capital invested and can be run across all stocks.

Error term ei can be boosted using Boosting Algos and thus increasing the prediction accuracy.

Now how to choose your Variables and what can be the ideal STOCK Equation :

YOY Quarterly sales growth  > 15 and

YOY Quarterly profit growth  > 20 and

Net Profit latest quarter  > 1 and

G Factor >= 7 and

Net Profit latest quarter > .33 AND

Other income latest quarter < Net Profit latest quarter * .5 AND

Net Profit preceding year quarter <= 0 AND

Expected quarterly net profit > 0 AND

Sales latest quarter > Sales preceding year quarter   AND

Return on invested capital > 25 and

Earnings yield > 15 and

Book value > 0 AND

Market Capitalization > 15

AND

Graham Number > Current price AND

PB X PE <=22.50 AND

PEG Ratio >0 AND

PEG Ratio <1 .5="" and="" o:p="">

Altman Z Score >=2.5 AND

Sales growth 5Years >25 AND

Profit growth 5Years >15 AND

Current ratio >2 AND

Market Capitalization >250 AND

Sales >100  AND

Piotroski score > 7

AND

Dividend yield > 2 AND

Average 5years dividend > 0 AND

Dividend last year > Average 5years dividend AND

Profit after tax > Net Profit last year * .8 AND

Dividend last year > .35 AND

( Profit growth 3Years > 10 OR

Profit growth 5Years > 10 OR

Profit growth 7Years > 10 ) 

OR

(Market Capitalization > 3000) AND

(Average return on equity 10Years Years > 20) AND

(Debt to equity < 1.5) AND

(Interest Coverage Ratio > 2) AND

( PEG Ratio <= 1) AND

(Profit growth 5Years > 20) 

AND

YOY Quarterly sales growth  > 40 and

YOY Quarterly profit growth  > 40 and

Average return on capital employed 3Years >30 and

Price to Earning <6 o:p="">

OR

Sales growth 10Years > 10 AND

Profit growth 10Years > 12 AND

OPM 10Year > 12 AND

Debt to equity < 0.5 AND

Current ratio > 1.5 AND

Altman Z Score > 3 AND

Average return on equity 10Years > 12 AND

Average return on capital employed 10Years >12 AND

Return on invested capital > 15 AND

Sales last year / Total Capital Employed > 2 AND

Average dividend payout 3years >15

AND

PEG Ratio <1 and="" o:p="">

Sales > 500 AND

Price to Earning < 40 AND

Profit growth > 20 AND

Debt to equity < 0.2 AND

Price to Cash Flow > 5

OR

EPS last year >20 AND

Debt to equity <.1 AND

Average return on capital employed 5Years >35 AND

Market Capitalization >500 AND

OPM 5Year >15

AND

Net Profit latest quarter > Net Profit preceding quarter AND

Net Profit preceding quarter > Net profit 2quarters back AND

Net profit 2quarters back > Net profit 3quarters back

AND

EPS latest quarter > 1.2 * EPS preceding year quarter AND

EPS latest quarter > 0 AND

YOY Quarterly sales growth > 25 AND

EPS last year > EPS preceding year AND

EPS > EPS last year AND

Profit growth 3Years > 25 AND

Return on equity > 17 AND

Down from 52w high < 15 AND

Market Capitalization > 100

AND

Price to Earning >0 and Price to Earning <10 5years="" and="" equity="" growth="" on="" return="">10 and Dividend yield >1 and Return on capital employed >10

AND

Profit growth 5Years > Sales growth 5Years AND

Sales growth 5Years > 3 AND

Return on equity > 15 AND

Working capital 5Years back < 0

AND

Price to Earning >0 and Return on equity 5years growth > 5 and Dividend yield >0  

Note : DEBT reacts inversely to the equation . Term period will be a spread over last 15 to 20 Years. 

Now , applying boosting algorithm ( like XGBoost) you can reduce the error coefficients.

Based on the above equation and a little variation choosing a flattened NN( Neural Network ) below stocks can be looked upon for Indian stock market.

1)  RELIANCE INDUSTRIES

2)  DCB BANK

3)  KAJARIA CERAMICS

4)  INFOSYS

5)  INDO COUNT INDUSTRIES