ABHRA BASAK

KRISHNA KARNANI

FINANCIAL MARKET PREDICTION AND PORTFOLIO OPTIMIZATION USING FUZZY

DECISION TREES

SECURITY SCREENING AND SELECTIONSecurity Screening and Selection

Stock Classification

Stock Ranking

Stock Selection

STOCK CLASSIFICATION

• Security Evaluation using Technical Indicators

• Moving Average Convergence Divergence (MACD)

• Relative Strength Indicator (RSI)

• Commodity Channel Index (CCI)

• Bollinger Bands

• Momentum Oscillators

STOCK RANKING

• Corporate Evaluation using Fundamental Indicators

• Profitability – Returns on Assets and Equity

• Management Performance – Assets and Inventories Turnover

• Capital Structure – Assets to Liabilities, Liabilities to Equity

• Sales, Profit, Transaction Volume, Marginal Account

STOCK SELECTION

• Select 3 different stocks – one each showing uptrend, downtrend, and steady state

• Attempt to display different profit making strategies in stock trading

• All subsequent processes are applied on these 3 stocks

TRAINING PHASETraining Phase

TRAINING PHASE

• Gather Historical Stock data

• Obtain financial time series and price charts from data

• Determine technical indicators and momentum oscillators from charts

Historical Data

Financial Time Series

Price Charts

PIECEWISE LINEAR REPRESENTATION METHOD

Training Phase

PIECEWISE LINEAR REPRESENTATION METHOD

• Mining of trading points

• Points of begin (P) and end (Q) on a term of closing prices in the ascending order of dates

• Point K having longest straight line distance between P and Q

• K is the turning point resulting in 2 segments.

• Apply recursively in the resulting segments till minimum distance threshold

PIECEWISE LINEAR REPRESENTATION METHOD

• Trading signals transformation

• Convert PLR segments into trading signals

• Uptrend segment

• I <= L/2 : 0.5 – (I – 1) / L

• I <= L/2 : I / L – 0.5

• Downtrend segment

• I <= L/2 : 0.5 + (I – 1) / L

• I <= L/2 : 1.5 – I / L

• Ranges from 0 to 1

• Can also act as a potential technical indicator

STEPWISE REGRESSION ANALYSIS METHOD

Training Phase

STEPWISE REGRESSION ANALYSIS METHOD

• Data Preprocessing for Feature Selection

• Used to select important factors which affect forecasting results

• Sort out affecting variables to leave more influential ones in the model

• Adding or removing factors to find the fittest combination, decided by F-test statistical value (takes into account the PLR)

FUZZY RULES AND DECISION TREESTraining Phase

FUZZY RULES AND DECISION TREES

• Fuzzification

• Set of indicators selected by SRA fed into data fuzzification module

• This module transforms technical indicators to fuzzy values

• Adopt triangular and trapezoidal membership functions for the module

• Output decision is obtained as a Gaussian membership function

Fuzzy Inference

I3

I2I1

FUZZY RULES AND DECISION TREES

• Defuzzification

• Output from fuzzy inference scheme is transformed into a meaningful decision

• Implemented using the popular Center of Area (COA) methods in the Fuzzy Control Module’s algorithm

FUZZY RULES AND DECISION TREES

• Examples of Fuzzy decision rules

• If MACD above signal line, then BUY

• If RSI increases above 70, then market is BULLISH

• If Price increases above BBupper then market is BULLISH

• If MACD is LOW and RSIupper goes HIGH to LOW, then SELL

• If MACD is HIGH and CCIupper goes LOW to HIGH, then BUY

GENETIC ALGORITHMS AND REFINEMENT

Training Phase

GENETIC ALGORITHMS AND REFINEMENT

• Evolving the decision tree using GA

• Fitness function set as forecasting accuracy of the model

Selection

Crossover

Mutation

Replace

Termination

RESULT

• Decision of Stock price and transaction will be determined by the decision tree on the basis of trends and indicators

• Uptrend if hike in price is greater than 0.5%

• Downtrend if fall in price is less than -0.5%

• Steady state / hold if y is between -0.5% and 0.5%

CREDITS

• A Collaborative Trading Model by Support Vector Regression and TS Fuzzy Rule for Daily Stock Turning Points Detection – Wu, Chang, Chang, Zhang

• Evolving and Clustering Fuzzy Decision Trees for Financial Time Series Data Forecasting – Lai, Fan, Huang, Chang

• A Fuzzy Logic Based Trading System – Chueng, Keymak

• Nigerian Stock Market Investment using a Fuzzy Strategy – Neenwi, Kabari, Asagba

• Common Stock Portfolio Selection: A multiple criteria Decision making Methodology and an application to the Athens Stock Exchange – Xidonas, Askounis, Psarras