WHY TRADE OPTIONS?
There’s No Edge In Stock Picking – Efficient Market Hypothesis:
Those that subscribe to the efficient market hypothesis believe that there’s no edge or advantage when it comes to picking stocks. Thus, stock picking is a binary event and boils down to a 50/50 probability or simply chance. Everything that can be possibly known about a stock is known and all the available information, technical analysis and fundamental analysis is priced into the underlying stock price. The efficient market theory may be the Achilles heel of professional money mangers’ performance and their inability to outperform their benchmarks. A staggering 92% of actively managed funds do not outperform their benchmark hence the massive inflows into passive index investing and ETFs. Furthermore, when looking at The Russell 3000 Index over a 26-year timeframe (1983 to 2006) which comprises the largest 3000 U.S. companies, 39% of stocks were unprofitable investments, 64% of stocks underperformed the Russell 3000 and 25% of stocks were responsible for all the market’s gains. Taken together, only 36% of stocks outperformed the Russell 3000 index. If the efficient market theory is correct, is stock picking a useless endeavor? If stock picking boils down to chance, is there a strategy that places the statistical odds of success in one’s favor?
Efficient Market Hypothesis:
Markets aren’t always functioning in an efficient manner. Markets can be irrational and become overbought or oversold. Outside of these extremes however, markets are efficient and over the long-term the vast majority of actively managed funds are unsuccessful at beating their benchmarks. Everything that can possibly be known about a stock is known and there’s no edge in stock picking. As of Q1 2019, for the ninth consecutive year, the majority (64.5%) of large-cap funds lagged the S&P 500 last year. The longer the timeframe the poorer the performance, after 10 years, 85% of large cap funds underperformed the S&P 500, and after 15 years, nearly 92% are underperforming the index (Figures 1 and 2). These dismal results hold true across large-cap, mid-cap and small-cap funds. Even if these actively managed funds happen to outperform their index, it’s due to chance and this margin of outperformance is largely negated by hefty management fees, rendering stock picking useless. To further emphasize this point, for the Russell 3000, 39% of stocks were unprofitable investments, 64% of stocks underperformed the index and 25% of stocks were responsible for all the market’s gains. Taken together, only 36% of stocks outperformed the Russell 3000 index.
Figures 1 and 2 – Time based underperformance of actively managed funds relative to the S&P 500 (Active Fund Managers Trail S&P 500)
Figures 3 and 4 – Data summarizing performance of individual stocks relative to the Russell 3000 index. Highlighting the fact that only 36% of stocks had a higher return than the index and 25% of stocks accounted for all of the market’s gains. (The_Capitalism_Distribution)
Even Distribution of Returns:
If the fact that 92% of actively managed funds do not outperform their index and that only 25% of stocks accounted for all the market’s gains wasn’t compelling enough, the distribution of returns also supports the efficient market hypothesis. The S&P 500 moves in a standard distribution over time, the number of daily moves is evenly distributed. There’s an equal and even number of days where the market moved up 0.6% as it moved down 0.6% (Figure 5). The market has fluctuated between a 2% loss and a 2% gain 94% of the time. Markets move in a standard distribution over time, there is no pattern or predicable cycles over the long-term which renders stock picking to random chance or a 50/50 probability. Interestingly, the market does move up over time due to a positive skew in these data attributable to the fact that indexes are capitalization weighted. This means that successful companies receive larger weightings in the index. Conversely, unsuccessful companies receive smaller weightings and are inevitably removed from the index. This disproportionally favors successful, growing companies hence the fact that only 25% of companies account for all the market gains.
Figure 5 – Standard distribution of daily market moves of the S&P 500 for 65 years
Options Provide Statistical Edge:
The only way to consistently and reliably profit from this even distribution and market behavior is via options trading. Options trading allows one to profit without predicting which way the stock will move. Options trading isn’t about whether or not the stock will move up or down, it’s about the probability of the stock not moving up or down more than a specified amount. Options allow your portfolio to generate smooth and consistent income month after month without predicting which way the stock market will move. Options are betting on where stocks won’t go, not where they will go. Running an option-based portfolio offers a superior risk profile relative to a stock-based portfolio while providing a statistical edge to optimize favorable trade outcomes. Options trading is a long-term game that requires discipline, patience, time, maximizing the number of trade occurrences and continuing to trade through all market conditions. Put simply, an options-based approach provides a margin of safety with a decreased risk profile while providing high-probability win rates.
Life Insurance Parallels:
Insurance companies sell policies based on risk factors, then price these polices to their advantage. Insurance companies are betting on probabilities and sell overpriced polices above their expected losses. The insurer agrees to pay out a specific amount of money for a specific loss (i.e. death). In return, the insurance company is paid monthly premiums based on this risk-based revenue model. Insurance companies sell polices with a premium cost level that maximizes a statistical edge to the insurance company’s benefit. The goal is to collect premiums over the course of the policy and never pay out on the policies they sell. So, the probability of paying out on the policy is very low while the premiums received, over the policy lifespan will exceed your total benefit. In terms of life insurance, it’s the probability that you won’t die before your predicted lifespan so the insurance won’t have to pay. In order to spread the potential payout risk, the insurance company will sell as many polices as possible to collect as much premium income as possible.
Options trading is much like insurance. I receive premium payments (policy payments) in exchange for selling options (insurance). I sell these options with a statistical edge (underwriting) and a high-probability of winning the trade (insurance won’t have to pay). Occasionally, options move against you (death occurred) and you’re assigned stock (insurance is paid out) however in order to spread the risk of being assigned shares, options (insurance) are sold across a diversity of tickers that include both stocks and ETFs with varying expiration dates and optimal sector exposure. Additionally, risk is mitigated by appropriate capital allocation, position sizing and holding cash reserves in the portfolio.
Markets are efficient and over the long-term the vast majority of actively managed funds are unsuccessful at beating their benchmarks. A staggering 92% of actively managed funds do not outperform their benchmark. Options trading allow one to profit without predicting which way the stock will move. Options allow your portfolio to generate smooth and consistent income month after month without predicting which way the stock market will move. Options are betting on where stocks won’t go, not where they will go and provide a statistical advantage. Options fundamentals provide long-term durable high-probability win rates to generate consistent income while mitigating drastic market moves. Taken together, options trading is a long game that requires discipline, patience, time, maximizing the number of trade occurrences and continuing to trade through all market conditions with the probability of success in your favor.