Recently I finished reading a great book by Jack D. Schwager titled “Hedge Fund Market Wizard”. As a note to myself and traders interested to improve their system, here are some quotes that I found to be interesting.
Set stop loss level that would prove the hypothesis is wrong and then limit the position to desired capital at risk level
Find the best strategy to profit from the expected events, ideally the one with limited downside risk but unconstrained upside potential.
Economic Condition: Combination of growth expectation and inflation expectation
Countries classification: debtor/creditor and independent/non-independent monetary policy
Growth concern -> Negative correlation between bond and stock
Inflation concern -> Positive correlation between bond and stock
Eight years before the deleveraging that began in 2008, we had developed and implemented what we call a depression gauge. It was designed to indicate when a depression-like environment was in effect based on a number of conditions coinciding, such as interest rates below a certain low level, contractions in private credit growth, a declining stock market, and widening credit spreads.
The best policy would be to spread out the problems over a long period of time so that nominal interest rates stay below nominal growth rates.
Diversification to 15 assets is enough to decrease 80% of the volatility.
Look for various asset response in a crisis. The strongest defensive will lead the rebound and the weakest will rally only at the later part of the rebound.
Be a risk manager, not a trader. Know what you can lose
They would buy platinum as a proxy for gold because “it hasn’t yet made the move.” Whatever the reason, the point is that many traders buy platinum because they are bullish gold. Buying a laggard as a proxy for a leader is a bad idea
Never sell the strongest markets until they fail.
In selecting emerging market equities, Taylor looks for three essential characteristics:
1. Favorable macro outlook—There are two key ways in which Taylor’s macro assessment will influence the portfolio. First, Taylor will concentrate longs in countries with the most positive fundamentals. Second, the global macro outlook can influence the total portfolio net exposure. For example, in late 2008 to early 2009, the very negative global macro fundamentals kept net exposure significantly lower than it would have been based solely on the individual company fundamentals.
2. Supportive secular trend—Taylor looks for situations in which there is a strong fundamentally based secular trend that supports the trade. For example, the strong trend in increasing Russian mobile phone usage in the early 2000s was a key consideration that prompted Taylor to place a large and very profitable position in companies in this sector. As another example, Taylor’s expectation that Apple’s global market share of its products will trend steadily higher in coming years was the dominant reason why Apple was his largest holding at the time of this interview (April 2011).
3. Good company—Taylor looks for companies with attractive growth prospects priced at reasonable values relative to future expected earnings. He avoids what he calls “boring” companies (typically low-beta stocks) regardless of whether they are good values.
Taylor believes the best opportunities are those where you can identify a potential trend that the market does not appreciate because it is extrapolating history instead of looking forward.
Often, the longer the duration of the option, the lower the implied volatility, which makes absolutely no sense
Option models generally assume that forward prices are predictive of the future movements in the spot price. Academic research and common sense suggest that this relationship is often invalid. Forward option-pricing models can break down, particularly in interest rate markets with steep term structures and low volatility levels.
Forward-looking assumptions based on backward-looking statistical correlations are another source of some interesting opportunities
There are five main pillars to Mai’s investment strategy:
- Find mispricings in a theoretically priced world. Mai seeks to identify trade opportunities that arise because prices, particularly for derivatives, are based on one of a number of standard pricing assumptions that may be entirely inappropriate based on the specific circumstances applicable to the given market. When these assumptions are unwarranted, they create mispricings and trading opportunities.
- Select trades in which the probabilities appear to be significantly skewed to a positive outcome. As a general rule of thumb,
Cornwall requires that the estimated gain if the trade succeeds multiplied by the probability of a positive outcome must be at least twice as large as the estimated loss if the trade fails multiplied by the probability of a negative outcome. Of course, these gain-and-loss amounts and their respective probabilities must be based on subjective estimates. Nonetheless, the key point is that the probability-weighted gain must be lopsided relative to the probability-weighted loss.
The rigorous standard for qualifying trades will lead to a concentrated portfolio. Typically, Mai will have only 15 to 20 independent risks (consisting of one or more separate trades) at any one time. This concentrated portfolio approach should not be confused with the proverbial “put all your eggs in one basket, but watch that basket very closely.” The important distinction is that although Mai’s portfolio is very concentrated, the asymmetric construction of his trades assures that the downside is always severely constrained if he is wrong.
- Implement trades asymmetrically. Mai structures trades so that the downside is severely limited, while the upside is open-ended. One common way of achieving this type of return/risk profile is by being a buyer of options (of course, only at those times when a mispricing is identified).
- Wait for high-conviction trades. Mai is perfectly content to stay on the sidelines and do absolutely nothing until there is a trade opportunity that meets his guidelines. Having the patience to wait for high expected value trades greatly enhances the return/risk of individual trades.
- Use cash to target portfolio risk. Because most of the trades in the portfolio are derivatives, which require much smaller cash outlays than outright positions, Mai will hold a large cash component in the portfolio (typically, 50 to 80 percent). By increasing or decreasing this cash component, Mai can target his desired portfolio risk level.
Prices for derivatives, such as options, are determined by pricing five generally accepted assumptions that sometimes are invalid.
1 . Prices are normally distributed
2. The forward price is a perfect predictor of the future mean
3. Volatility scales with the square root of time
4. The trend can be ignored in the volatility calculation
5. Current correlations are good predictors of future correlations
Most of the trades that Platt stops himself out of never get to their stop-loss points. If a trade does not work within a reasonable amount of time, Platt will just liquidate rather than give it room to his original stop point. Platt also reevaluates each of his positions daily and asks himself whether he would still place the same trade today. If not, he will liquidate it.
Risk control is important for many obvious reasons, which include avoiding account-incapacitating losses, minimizing emotional pain, and constraining the adverse impact of compounding—large percentage losses require increasingly greater percentage gains to get back to even.
Platt, however, points out a far less obvious reason for avoiding losses: Losing trades mentally impede the trader and often result in missed winning trade opportunities. As Platt colorfully describes the trader’s mindset after incurring a foolish loss, “You feel like an idiot, and you’re not in the mood to put anything else on. Then the elephant walks past you while your gun’s not loaded.” Platt says that trading follows the 80/20 rule—80 percent of a trader’s profits come from 20 percent of the trades. If the psychological fallout from a trading loss causes a trader to miss a trade in the 20 percent, it can be a big deal. one way of knowing your position is too large is if you wake up thinking about it.
If I am 100 percent dedicated to managing your money, and I lose your money, I can look you in the eye and say, “I did my best,” and I could be okay with that. If I am not 100 percent engaged, however, and I’m not even sure I want to be in the business, then managing other people’s money is very hard. Once I was sure I wanted to manage money, it took away 80 percent of the angst.
The general principle is that we look for future revenue generation that can be reasonably anticipated but that is not reflected by the current market price. This idea is probably the single most important concept in our stock selection process.
Traders need to accept that a certain percentage of good trades will lose money. As long as a profitable strategy is implemented according to plan, a trade loss does not imply a trading mistake.
learned the danger in selling expensive stocks just because they are overpriced and buying value stocks just because they are underpriced.
Pricey stocks are always 30 percent pricier than they should be because people are willing to own them at 30 percent above what they should own them at. A good growth stock is always overvalued, and a lousy company is always undervalued. That is the danger of buying value
stocks. Until you get the turn where the market recognizes an improvement in the business model, they are always going to be undervalued. If you are going to short a growth stock because it is 30 percent overvalued, it is going to grow for the next five years always being 30 percent overvalued—until it finally breaks, and by that time, you are probably not going to be there.
Sometimes, though, it is best to just liquidate the entire position. It’s a good idea to harvest your losses because it forces you to revisit the trade. If you are in the trade, you are always defending it. Liquidating forces you to reevaluate the trade relative to other opportunities. You sold the position. Do you really want to buy it back? Or would you rather put the money in this other idea, which looks a lot better right now?
EV/EBIT (cap rate)—This ratio is a twist on the EV/EBITDA metric. However, instead of EBITDA we used EBIT, earnings before interest and taxes but after deducting depreciation and amortization. At my old firm, Hoefer & Arnett, we used to call EV/EBIT a “cap rate,” similar to a cap rate used to value real estate. We used to argue, why buy a piece of commercial real estate with a 6 percent cap rate or a bond with a 7 percent yield if you could buy a business like Macy’s with a 20 percent cap rate?
Daly’s stock investing methodology and philosophy can be summarized as follows:
Stick to businesses you understand.
Find companies in those businesses that are undervalued vis-à-vis the pertinent metrics or similar competitors.
Take profits when prices move up to fair valuation levels.
Sail into a cash harbor when the market seas turn stormy.
Stick to the basic process, and never take flyers.
Treat investments as a business, not as a gamble.
Greenblatt used earnings yield to represent cheapness and return on capital to represent goodness.1 The two measures were combined in a single ranking that worked even better than Greenblatt and Goldstein expected. Greenblatt named this combined ranking indicator the Magic Formula, a name that implicitly pokes fun at the hype accompanying market indicators, but also acknowledges the surprising efficacy of the measure (as empirically demonstrated).
There are a lot of ways of measuring cheapness. We used the earnings yield, which we defined as the ratio of earnings before interest and taxes (EBIT) to enterprise value. Return on capital was measured by calculating the ratio of pretax operating earnings (EBIT) to tangible capital employed (net working capital + net fixed assets). This ratio was used rather than the more commonly used ratios of return on equity (ROE, earnings/equity) or return on assets (ROA, earnings/assets) for several reasons.
If I wrote a book about a strategy that worked every month, or even every year, everyone would start using it, and it would stop working. Value investing doesn’t always work. The market doesn’t always agree with you. Over time, value is roughly the way the market prices stocks, but over the short term, which sometimes can be as long as two or three years, there are periods when it doesn’t work. And that is a very good thing. The fact that our value approach doesn’t work over periods of time is precisely the reason why it continues to work over the long term. Our formula forces you to buy out-of-favor companies, stocks that no one who reads a newspaper would think of buying, and hold a portfolio consisting of these stocks that, at times, may underperform the market for as long as two or three years. Most people can’t stick with a strategy like that. After one or two years of underperformance, and usually less, they will abandon the strategy, probably switching to a strategy that has done well in recent years.
It is very difficult to follow a value approach unless you have sufficient confidence in it. In my books and in my classes, I spend a lot of time trying to get people to understand that in aggregate we are buying above-average companies at below-average prices. If that approach makes sense to you, then you will have the confidence to stick with the strategy over the long term, even when it’s not working. You will give it a chance to work. But the only way you will stick with something that is not working is by understanding what you are doing.
Don’t fall in love with any position. Always keep a large margin of safety, even if you’re playing with house money.
To quote Howard Marks, “Experience is what you got when you didn’t get what you wanted.”
Over the short term, prices fluctuate due to emotion, but over the long term, they come back to value. Value investing is figuring out what a business is worth and paying a lot less.
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