Quantitative trading strategy - Assignment Example

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For quantitative investing purposes, value and quality signals among others are used to forecast relative stock returns (Fabozzi et al, 247). Value signals are…
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Quantitative trading strategy
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Lecturer’s Introduction Organizations measure and evaluate returns on their investment portfolios to ensureprofessional equity management. For quantitative investing purposes, value and quality signals among others are used to forecast relative stock returns (Fabozzi et al, 247). Value signals are powerful because they use market price information whereas quality signals are based on financial statements. The signals of my trading strategy are explained as follows:
1. Value.
It is based on valuation ratios namely; price/dividends, price/earnings, price/cashflow, enterprise value/EBITDA and prices/book. These ratios have conceptual difficulties so the need to combine them to explore additional information contained in each one of them.
2. Quality.
There are namely four signals; gross profitability, Piotroski score, Accruals and Beinish Score.
a) Gross profitability = (Revenue-Cost of Goods Sold)/Total Assets

b) Piotroski Score = F1+F2+F3+F4+F5+F6+F7+F8+F9;where F are binary variables(0=weakness,1=strength)
F1: Positive Net Income
F2: Positive Operating Cash Flows
F3: Increasing Return on Assets: ROAt > ROAt‐1
F4: Negative Accruals: Operating Cash Flow > Net Income
F5: Decreasing long term debt
F6: Increasing Current Ratio
F7: Negative Net Equity Issues
F8: Increasing Gross profit margins
F9: Increasing Asset Turnover
Stocks with higher Piotroski Score have higher returns.
c) Accruals =(earnings before extraordinary items-cash flow from operations)/Total assets
Stocks with lots of accruals have lower returns
d) Beneish Score = – 4.84 + 0.92 DSR + 0.528 GMI + 0.404 AQI + 0.892 SGI
+ 0.115 DEPI – 0.172 SGAI + 4.679 Accruals – 0.327 LEVI
Stocks with high Beneish scores tend to have lower returns
It refers to combing all the useful signals (value, quality, risk, price trends and information) to get additional information about the signals (Fabozzi et al, 247). From the analysis of my Trading Strategy in comparison with UM Super Combo the following can be concluded:
i. The performance over time of my trading strategy beats the UM super Combo by a large margin over 1999-2015
ii. The returns of the portfolio of my trading strategy are higher compared to the UM Super Combo.
The annualized return of my trading strategy is much larger than market portfolio’s (23.15% to 5.75%) compared to (20.83% to 5.75%).
The Sharpe ratio much larger than market portfolio (0.91 vs. 0. 09) compared to (0.88 vs. 0.99).
Alpha is positive and large.18.14% for my trading strategy compared to 15.95%
Maximum drawdown is close to market portfolio’s (-55.08% to -55.66%) compared to (-56.42% to -55.66%)
My trading strategy in summary beats UM Super Combo both in terms of consistency and risk-adjusted basis.
Work cited
Fabozzi, Frank J, Sergio M Focardi, and Petter N Kolm. Quantitative Equity Investing: Techniques And Strategies. Hoboken, N.J.: John Wiley, 2010. 247-250. Print. Read More
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