I am currently a retired Aerospace Engineer. I am married with three children and eight grandchildren. I was born in San Francisco, CA in 1949 and moved to Newport News, VA in 1951 where I lived until I went to college. By God's grace, I received a B.S. degree from Virginia Tech (1972), a M.S. degree from Caltech (1973), and a M.A. - Biblical Studies degree from Birmingham Theological Seminary (2013). I worked at Pratt & Whitney (1973-1986) and CFD Research Corporation (1987-2008). Now in retirement and trying to preserve (and grow) my life savings, I currently have a strong interest in tactical asset allocation strategies, and have studied them extensively. I have developed a number of tactical strategies involving the periodic trading of ETFs and, more recently, mutual funds. These strategies have been extensively backtested using the Portfolio Visualizer (PV) software. My goal is to earn 10% annually with no negative years, to have maximum drawdowns (on a monthly basis) less than 5%, and to have monthly win rates over 80%. The strategies include purchasing a limited number of funds with the highest growth and lowest volatility, and minimizing risk using dual momentum, relative strength, moving average and risk parity methods. I have developed strategies for equity as well as bond assets, although most of my current strategies involve bonds. My most popular bond strategy is known as ELVS (Enhanced Low Volatility Strategy) that features short duration timing periods and very low volatility mutual funds traded on a monthly schedule. Another popular strategy is known as the Modified Defensive Bond Strategy (MDBS) that utilizes bond ETFs and trades on a weekly schedule. I publish a free monthly article on SA Instablog that presents each month's selections of the strategies I invest in. I provide PV links to all of my strategies, and a spreadsheet that determines what asset to hold each month (PV selections are sometimes in error because end-of-month distributions of bond mutual funds are not included in the adjusted data until later).