Week 11 Flashcards
What does the Bengen 4% rule state? Is 4% a good value?
When you retire, extract 4% from retirement balance in the first year, then adjust that dollar withdrawal for inflation in the following years, keeping the withdrawal constant in real terms. This keeps you safe from money death. This rule is typically excessive, it should be lower in many cases, such as 2.5% for FIRE movement individuals before fees, or 2% after fees.
What is money death?
When our money runs out before we die.
What risk is the Bengen 4% rule most susceptible to?
sequence risk, the risk that the money withdrawal will start right before a year of bad returns.
What is “phase locking”?
During periods of market panic/stress, the correlation between returns on assets increases, this is known as “phase locking” and means our diversification will not work as well as usual, as such we should model a portfolios behaviour using higher correlations than seen during normal market periods in order to survive a panic.
Why does mean blur mean we cannot expect consistent outperformance of benchmarks?
Even in very talented fund managers there is simply too much noice in financial markets.
Is it easy to find good fund managers in America? What about Australia? What study showed this?
In America the markets are very efficient, leading to roughly 80-98% of US active equity managers underperforming their benchmarks after fees over a 15 year time frame, this could be just luck. When we look at the Australian data it is much more variable, showing it is not just luck, especially in small-caps, where roughly half of the Australian small-cap funds outperform their benchmarks at the 15-year mark. This shows that active investing struggles to work in efficient markets, but in less efficience markets it can work easier, particularly in small caps.
The study that showed this was known as S&P Index Versus Active (SPIVA)
What is one of the best creators of alpha opportunities?
inefficient markets.
What is the difference between Bachelier’s and Black-Scholes-Merton’s option pricing formula in terms of random walk model?
Bachelier assumes a simple random walk hypothesis. Black-Scholes-Merton option pricing assumes a more complicated random walk model known as geometric Brownian motion.
What is the return of a stock given by under simple random walk?
mean return * time + standard deviation * sqrt of time * a random variable from a normal distribution with mean 0 and standard deviation 1. This would mean that marginal distributions are normally distributed, and there should be no predictability in the time series of returns.
What is a marginal distribution? Why is this particularly relevant for stock returns?
A marginal distribution ignores the different potential states of a statistic and bundles them all together, this is particularly relevant for stocks, where some time periods are calm and some are volatile, but they all appear in the same time series.
What does the marginal distribution of stock returns look like? Why does this occur? What does this mean overall?
A bell shaped distribution, even though the return on calm days and volatile days is a normal distribution (though with different mean and standard deviation). The marginal distribution displayed peakednes and fat tails relative to a normal distribution with the same mean and variance.
This overall means at any given time stock returns are generated from a normal distribution, but the parameters vary over time, with the calm periods giving peakedness, and the volatile periods giving fat tails. This model of returns is sometimes called a model of stochastic volatility, because the bolatility is determined by a random process.
What is the NZSF? What are its themes? What do they all assume?
The NZ super fund is a sovereign wealth fund, owned by the government to help pay for future superannuation benefits. Its three broad investment themes are: resource sustainability, emerging markets segmentation, and evolving demand patterns. Each of these themse assumes there is a capital market inefficiency, which can be a problem if you believe in the efficient market hypothesis.
Why does the simple random walk process not hold for stock returns?
The marginal distribution of stock returns is not normally distributed, this means the first implication of the random walk hypothesis does not hold.
Also in some cases there is some time series predictability in stock returns, such as the auto-correlation in small-cap stock returns, and predictability in volatility.
Because neither of the implications of the simple random walk hypothesis hold it does not hold either.
When can we say markets are efficient?
If prices reflect information to the extent that consistent positive abnormal trading profits cannot be made after accounting for transaction costs, taxes, and risk aversion.
Does the efficient market hypothesis hold?
Why is it still useful?
It doesn’t hold, shouldn’t hold and isn’t easily testable.
It is still useful because it provides a practical framework for thinking about when stocks should be misprices, and therefore when/where active portfolio management might work.
Active management does not make sense in markets we expect the efficient market hypothesis to hold.
