In this series, we’ve asked Covestor managers: “What is the single most important lesson you’ve learned about being a successful investor, and how do you try to apply that today?”
Author: Hengfu Hsu, Analytic Investment LLC
Covestor models: Focus Value, Dividend, Enterprise Value, Deep Value, Opportunistic Value, Earnings Growth
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I was born and raised in Taiwan, a beautiful island known for its high tech industries. I received double bachelor degrees in Electrical Engineering and Power Mechanical Engineering from National Tsing Hua University in 1990. I came to the US to study in 1991 and received a master’s in Computer Engineering from USC in 1992. After graduation from USC, over the next 10 years period I worked for two early stage startup companies as a key software engineer, producing software used to design complex semiconductor integrated circuits. Both companies went public – in 1998 and 2002 respectively – and then were acquired by other companies.
Like many engineers in Silicon Valley with stock options grants, I started participating in the stock market in the mid ’90s. I went through the boom and bust of technology companies and experienced significant loss in my hard-earned 401k account. Following this, I started seriously searching for better, more systematic investment and risk management approaches. Through my own terrible experience, I came to the realization that many financial advisors sell mutual funds or insurance products to meet their own personal goals, not to achieve my financial goals.
Without millions in hand to hire the best hedge fund managers, I had to take matters into my own hands. I read over countless investing and trading books, subscribed to numerous newsletters, pieced together all kinds of indicators and programs, and traded many complicated strategies of stocks, options, Forex, and futures with my own money. After many failures, I finally found my approach with the relative value strategy described in the 1998 book “What Works On Wall Street” by James P. O’Shaughnessy. This approach fits my trading style best, and it can be programmed algorithmically to develop a consistent methodology over the long run.
By late 2007, I quit a full-time engineering job at Sun Microsystems (which was acquired by Oracle in 2009) to start my own advisory firm, to focus on the research and development of strategies based on the relative value approach and to manage accounts.
The years from 2008 to 2010 were a once-in-a-lifetime learning experience for me to have the opportunity to actively manage accounts during a financial crisis. I would not have learned anything if I were still a full-time engineer watching 401k statements losing huge portions of their value for the second time in a decade.
Unless you parked money in a bank savings account, you experienced all asset classes suffering significant drawdown during this period. The harsh lesson was that drawdown simply cannot be avoided, regardless how well a portfolio is diversified.
Although I had sound risk management strategy in place to limit accounts’ maximum drawdown during the financial crisis, the length of the drawdown period was more than expected from a historical point of view. I therefore hesitated to put money back into value stocks as my algorithm instructed me, so I missed periods with favorable market conditions for the relative value approach. In hindsight, I let my emotion override the pre-programmed computer decision.
In summary, just like any investment or trading approach, drawdown within the relative value approach is unavoidable, as the market does not stay in favor of any one approach forever. To reduce the emotional toll, I do extensive back testing based on historical data to try to limit drawdown in the effort to maintain capital until favorable market conditions return. The cost of becoming emotional with investment decisions is very high.
The unprecedented volatility, the simultaneous massive drawdown of global asset classes, the collapse of large institutions, and the impressive V-shape recovery of many stocks and assets during the financial crisis provide a good data set to analyze. Based on additional volatility and credit risk data, I tried to improve the risk management part of my program to further limit the account drawdown if a similar financial crisis were to happen again in the future.
However, the most challenging part of investing is that the market is always changing, and the next crisis will be most likely differ from the previous one. There have been never two identical bear/bull markets in history. What I do to prepare for the next crisis is to replay 2008, 2009, and 2010 data repeatedly to feel the fear of the market during the panic periods and inevitable fast recovery of deep discounted value stocks after most investors have capitulated.
And writing it down in this article serves the best reminder for me to remember the lesson forever.
