Enhancing Capital Asset Pricing Analytics CAPM

[Virtual Presenter] Research Study Enhancing Capital Asset Pricing Analytics (C-A-P-M-) for Sustainable Investment Decisions The Case of the Iraq Stock Exchange University of Anbar Al Idrisi University College University of Al Maarif March 2020 May 2024 | 54 Listed Companies | 7 Market Sectors.

[Virtual Presenter] Introduction Research Overview Research Objective Sample Coverage Develop optimal portfolio selection models using C-A-P-M to facilitate investor decision making in the Iraq Stock Exchange 54 companies across all 7 traded sectors on the Iraq Stock Exchange with comprehensive market representation Data Period Analytical Tool Monthly observations from March 2020 to May 2024, providing 52 data points for robust statistical analysis EViews 12 statistical software for comprehensive C-A-P-M analysis and beta coefficient estimation.

[Audio] Challenge Research Problem Statement ⚠ ✓ Current Challenges Proposed Solution Difficulty in optimal asset selection Increased portfolio risk exposure Higher investment transaction costs Lack of standardized valuation framework Implement C-A-P-M methodology systematically Distinguish efficient from inefficient firms Facilitate evidence based investment decisions Provide standardized portfolio framework.

[Audio] Theoretical Framework Capital Asset Pricing Model (C-A-P-M-) Fundamental Equation Re = Rf plus β(Rm Rf) Sharp (1964) Portfolio Theory Foundation Re Rf β Rm Expected Return (Cost of Equity) Risk Free Rate (Safe Investment) Beta Coefficient (Systematic Risk) Market Return (Expected Market) Risk Premium (Rm Rf): Additional return required for bearing systematic market risk.

[Audio] Methodology Research Methodology Data Collection: Monthly stock prices for 54 companies across 7 sectors (52 observations) Beta Calculation: β = Cov(Ri,Rm) / σ²Rm using covariance and variance analysis CAPM Application: Calculate expected returns for each company using the C-A-P-M formula Stock Classification: Categorize as defensive (β 1) stocks Statistical Analysis: Comprehensive analysis using EViews 12 econometric software.

[Audio] Sample Study Sample Overview Sector Distribution Banking Industrial Hotels & Tourism Agriculture Insurance Services Investment 15 12 7 8 5 4 3 Companies Sectors Observations.

[Audio] Results Category I Defensive Stocks Analysis Definition & Characteristics Conservative stocks with return variance lower than market variance (β < 1). These securities exhibit limited risk exposure and provide stable, predictable returns for risk averse investors. Key Features Target Investors Beta Range Lower volatility Stable returns Limited downside risk Conservative investors Risk averse portfolios Long term holdings 0.019 0.792 Hnti To Hbag Investment Recommendation: Suitable for building defensive portfolios with minimal risk exposure despite lower expected returns.

[Audio] Results Category 2 Aggressive Stocks Analysis High risk stocks with return variance exceeding market variance (β > 1). These securities offer potential for higher returns but with significantly greater volatility and downside risk exposure. High volatility Variable returns Significant risk exposure Speculative investors Risk tolerant portfolios Growth oriented strategies 1.230 12.852 Imos To Hbay Investment Recommendation: Appropriate for building aggressive portfolios seeking higher returns with acceptance of substantial risk.

[Audio] Results Beta Coefficient Interpretation β < 1 β = 1 β > 1 Defensive Neutral Aggressive Key Findings Inverse Relationship No Response 7 Companies 4 Companies Weak Correlation Strong Response Majority (< 0.5) 10 Companies.

[Audio] Results Market Efficiency Market Information Efficiency Analysis Information Dissemination Findings Analysis reveals that most investment companies (majority) exhibited weak positive correlation with market returns (β < 0.5), suggesting: Market Inefficiency Delayed Response Information does not reach all investors simultaneously and directly Stock prices adjust gradually rather than immediately to new information Practical Implication The weak correlation patterns indicate opportunities for informed investors to exploit information asymmetries, while emphasizing the need for improved market transparency and information dissemination mechanisms in the Iraq Stock Exchange..

[Audio] Conclusions Key Research Findings CAPM Model Validity CAPM proves to be a suitable financial model for optimal asset mix selection and portfolio allocation based on investor risk preferences Positive Market Correlation Multiple companies demonstrated positive correlation between returns and market performance, indicating alignment with investor preferences Independent Performance Some companies showed no correlation between security returns and market returns, suggesting autonomous performance patterns Information Asymmetry Weak direct correlation (< 0.5) for most companies indicates information doesn't reach all investors simultaneously.

[Audio] Critical Finding Key Determinants of Asset Pricing Critical Factors in Capital Asset Pricing Risk Premium Beta Value plus Market Risk Premium Systematic Risk Measure (Rm Rf) (β) Any increase in either factor is directly reflected in company asset prices, establishing the fundamental pricing relationship in capital markets.

[Audio] Recommendations Investment Recommendations Utilize C-A-P-M for systematic asset pricing and portfolio construction Select assets from strong sectors with appropriate weights Diversify across asset classes and international portfolios Match securities to investor risk tolerance levels Ultimate Objective Achieve balanced portfolios optimizing returns while managing risk.

[Audio] Thank You Questions & Discussion Research Team University of Anbar Economics Al Idrisi University Finance & Banking University of Al Maarif Finance Sciences Contact [email protected].