Trendsetter or Trendfollower? February 3, 2009Posted by DustinRJay in stock market, stocks, Uncategorized, volatility.
Tags: bear markets, S&P 500, technical trading
The following analysis was performed to backtest the S&P 500 against two investment strategies. A common belief is that the 50 day moving average (SMA) is indicative of a resistance level or support level for the market. When the price crosses above it’s 50 day moving average it means that investors are willing to pay more for the stock than the average of the previous 50 days and is typically regarding as a technical bullish signal.
The trading strategies analyzed are:
- Buy and hold
- Only buy when the S&P 500 crosses above the 50 day moving average, sell when the price drops below the 50 day moving average.
The following graph shows the value of an initial $100 investment on a logarithmic scale, as it is easier to identify relative percentage changes. What this sort of analysis reveals are that:
- Investment returns are about the same over long periods of time: e.g. Buy and hold strategy had a 49 fold return versus the 44 fold return of the SMA strategy.
- SMA strategy is out of the market or allocated to cash over a significant period of time compared to the buy and hold strategy
- Risk profile is vastly different over the short term (especially in volatile bear markets): e.g. Buy and hold strategy lost 31% since the Lehman failure on Septeber 15, 2008 versus 5% for the SMA strategy
- Transaction costs add up and shouldn’t be ignored: The SMA strategy would have had resulted in 881 different transactions over the time period analyzed. At a ballpark cost of $5/trade, the SMA trading strategy would have cost $4405 resulting in returns being entirely eroded.
Based on this, different demographics may have different investment objectives. It makes sense in general for young people to have a more aggressive portfolio as to fully expose themselves to the full upside of the market over long periods of time, similarily it makes sense for older people to have a more conservative portfolio that is geared towards capital preservation. In the current market, I am looking to change my allocation from a moderately conservative portfolio to something more aggressive. Generational lows in US housing sales and vehichle sales should support a floor to certain sectors of economic growth. In addition, credit market spreads (leading indicator) have improved greatly since the Lehman bankruptcy in September and price to earnings ratios seem relatively close to fair value given the large expected drop in corporate earnings.
In summary, paying attention to the SMA may be useful for people looking to reallocate money into a higher returning investment with most of the upside exposure, yet wanting to avoid the potential for more drops in a volatile bear stock market.
Volatility in Housing Markets (Part 1 of 2) July 20, 2008Posted by DustinRJay in Calgary real estate, volatility.
Tags: Calgary real estate, volatility
In general, housing prices have a low volatility compared to other asset classes. This is due to the underlying fundamental value (rents) being a relatively stable cash flow. This compares against stocks which have larger variance in earnings and therefore larger volatility in price.
A lookback at historical real estate volatility can help to give a forecast probability cloud. By comparison, the S&P 500 has a VIX index which is representative of S&P 500 volatility over the next 30 day period and is referred to by some as the fear index.
A quarterly calculation of year over year price changes by histogram for Calgary real estate from Q3 1977 to Q1 2008 helps identify the scale of price changes that could occur in one year. The results are below:
- P90: -5.6% (90% chance of price growth being greater than -5.6%)
- P50: +5.9% (50% chance of price growth being greater than +5.9%)
- P10: +19.9% (10% chance of price growth being greater than +19.9%)
Furthermore, the probability of an event occurring that is above the P10 or below the P90 for 5 consecutive years is 1 in 100,000 for each (i.e.: (1/10)^5 = 1/100,000). The shortfall of this kind of approach to volatility is that this calculation is not statistically independent as bear and bull markets typically last between 2-10 years.
What this analysis demonstrates is that even if a bearish scenario is the right approach, Mr. Market could take a very long time to unwind. The following graph illustrates what 5 consecutive P10, P50 and P90 events would look like and is meant to represent the best case, best guess and worst case respectively.