Quantitative Investing: Multiple Technical Indicator Trading Strategy Introduction - Technical indicators are frequently used tools by investors and traders. They implement mathematically based formulas to analyze past data to identify future trading opportunities. Through analyzing historical data, technical analysts use indicators to try and create trading strategies. In this article, we use Python to explore a specific trading strategy based on a combination of 7 of the most commonly used indicators. We generate trading signals based on a defined set of rules, backtest our strategy, and form an optimally weighted portfolio. Our goal is to outperform a standard buy-and-hold strategy of the SPY ETF over a defined period of time. Dataset - Nasdaq-100 company daily data for each ticker from January 2000-01-01 to the present. In addition, daily SPY ETF data is used for benchmark stats. Factors/Performance Indicators - We selected 7 technical indicators for further strategy construction based on research: - Simple Moving Average (Price) - Simple Moving Average (Volume) - Average True Ra

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