The Gold and The Silver Index
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Precious Metals: A Coiling Spring

Daily Speculations are for me (Alex) to share some quick thoughts on charts/trades I’m looking at, books and articles I find interesting, or maybe just some photos of my dog Mars. As the name states, I’ll be sharing something daily except for some days when I don’t.

I’ve been keeping a close eye on precious metal stocks. They’re coiling in a tight pattern and look set for an explosive move in one direction or another.

Below is XAU the gold and silver index on a weekly basis.

The Gold and The Silver Index

Here a quick rundown on how I think about precious metals.

  1. Like Ray Dalio has said, “Over the long run, the price of gold approximates the total amount of money in circulation divided by the size of the gold stock. If the market price of gold moves a long way from this level, it may indicate a buying or selling opportunity.”
    1. We can view gold and silver as anti-dollars. Since they are priced in US dollars they tend to move inversely to the greenback. And the fundamentals that drive the dollar higher tend to drive them lower.
  2. A big driver then is the relative changes in the cost of money or the real rate of interest (interest rates adjusted for inflation).
    1. Real interest rates move off of growth and inflation; both realized and expected.
  3. The performance of precious metals over cycles is largely dependent on whether we’re in a “core” driven rally or “periphery” driven rally.    
    1. A core driven rally is when the US (and typically other DMs) are the market leaders relative to emerging markets (periphery). This typically coincides with a global risk-off view where EMs are deemed too risky so capital pools into safer DM markets. This helps drive the dollar higher and keeps inflation low, both of which are bearish for precious metals.
    2. A periphery led rally is the opposite. It’s where EMs are seen as more stable and an attractive investment, at least on a relative basis to core markets. In this case, capital flows into EM countries which leads to a lower dollar, higher commodity prices, higher inflation, and thus lower real rates which is bullish for precious metals.
  4. So much of the movement in precious metals is centered around beliefs about the future value of the dollar. And as a result, beliefs and resulting actions about the risks in holding assets that are priced in currencies other than the dollar.
  5. One of the largest influencers on these beliefs is of course the Game Masters (the Federal Reserve).
    1. Since they control the cost of money and by extension the value of the dollar, what they do and what they signal they’re going to do, matter for precious metals.

We can see on the charts below via Deutsche Bank the relationship between the market’s pricing of future Fed rate hikes and the resulting moves in precious metals; which move inversely to these expectations.

Rate Hike Expectations and Gold

Where are precious metals likely headed from here, then?  

Well it depends on the market’s perception of the Fed’s aggressiveness in hiking interest rates during this tightening cycle.

If the Fed signals a return to a more dovish approach then the dollar will continue to sell off, EMs will continue to outperform DMs, inflation expectations will increase (and expectations over future real rates decrease) and precious metals will perform well; perhaps breaking out to the upside of their large coiling pattern.

If the Fed sticks to its current commitment of tightening in December and the market’s belief in this commitment grows, then the dollar should strengthen, DMs should outperform EMs, and precious metals should perform poorly.

What makes the immediate future of precious metals even more difficult to discern is the coming announcement of Trump’s pick for the next Fed chair. Who it ends up being and how the market reacts could have a dramatic impact on precious metals.

So for me, I’ll continue to watch from the sidelines and wait for more clarity or a strong signal from the market, in the form of a technical breakout, before I take a position.

Drop any questions/comments in the comment section below. And if you’d like to get my thinking, ramblings, and occasional trade ideas, then just put in your John Hancock along with your email below.

Thanks for reading,

Alex

 

 

The Distribution Of Returns
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The Distribution Of Returns & The Randomness Embedded In Them

Daily Speculations are for me (Alex) to share some quick thoughts on charts/trades I’m looking at, books and articles I find interesting, or maybe just some photos of my dog Mars. As the name states, I’ll be sharing something daily except for some days when I don’t.

As traders, one of the most important traits we can adopt is humility. We have to embrace our fallibility.

Markets are complex systems. We cannot know all the relevant variables and causal relationships. Therefore, when we make a market prediction or place a trade, we can’t truly know if the subsequent outcome occurred for the reasons we believed, for reasons we’re unaware of, or if it was all just random noise.

This presents us with a dilemma: We must act on incomplete information and then iterate off results where we can’t fully know the causes.

So we never really know if we were right for the right reasons, right for the wrong reasons (i.e., lucky), or a little bit of both. Hence the need to stay humble.

Where traders get into trouble is when they’re right a lot for the wrong reasons but they think they’re right for all the right reasons. They think they’re making money because they’re skilled but really they’re just lucky.

Nassim Taleb writes about this problem, saying:

At any point in time, the richest traders are often the worst traders. This, I will call the cross-sectional problem: At a given time in the market, the most successful traders are likely to be those that are best fit to the latest cycle.

Being aware of the randomness embedded in the distribution of markets returns keeps us from falling for the ego trap where we mistake skill for luck or information for noise. And since the two are difficult to distinguish over a short time frame, it forces us to focus on managing our risk in a way that tilts the odds for success in our favor over the longer term.

In his book Fooled by Randomness, Nassim Taleb offers a useful analogy of the “dentist investor” on the difference between noise and information. Here it is:

The wise man listens to meaning; the fool only gets the noise. The modern Greek poet C.P. Cavafy wrote a piece in 1915 after Philostratus’ adage “For the gods perceive things in the future, ordinary people things in the present, but the wise perceive things about to happen.” Cavafy wrote:

“In their intense meditation the hidden sound of things approaching reaches them and they listen reverently while in the street outside the people hear nothing at all.”

I thought hard and long on how to explain with as little mathematics as possible the difference between noise and meaning, and how to show why the time scale is important in judging a historical event. The Monte Carlo simulator can provide us with such an intuition. We will start with an example borrowed from the investment world, as it can be explained rather easily, but the concept can be used in any application.

Let us manufacture a happily retired dentist, living in a pleasant, sunnytown. We know a priori that he is an excellent investor, and that he will be expected to earn a return of 15% in excess of Treasury bills, with a 10% error rate per annum (what we call volatility). It means that out of 100 sample paths, we expect close to to 68 of them to fall within a band of plus and minus 10% around the 15% excess return, i.e. between 5% and 25% (to be technical: the bell-shaped normal distribution has 68% of all observations falling between -1 and 1 standard deviations). It also means that 95 sample paths would fall between -5% and 35%.

Clearly, we are dealing with a very optimistic situation. The dentist builds for himself a nice trading desk in his attic, aiming to spend every business day there watching the market, while sipping decaffeinated cappuccino. He has an adventurous temperament, so he finds this activity more attractive than drilling the teeth of reluctant old Park Avenue ladies.

He subscribed to a web-based service that supplies him with continuous prices, now to be obtained for a fraction of what he pays for his coffee. He puts his inventory of securities in his spreadsheet and can thus instantaneously monitor the value of his speculative portfolio. We are living in the era of connectivity.

A 15% return with a 10% volatility (or uncertainty) per annum translates into a 93% probability of making money in any given year. But seen at a narrow time scale, this translates into a mere 50.02% probability of making money over any given second as shown in Table 3.1. Over the very narrow time increment, the observation will reveal close to nothing. Yet the dentist’s heart will not tell him that. Being emotional, he feels a pang with every loss, as it shows in red on his screen. He feels some pleasure when the performance is positive, but not in equivalent amount as the pain experienced when the performance is negative.

Probability of Making Money

At the end of every day the dentist will be emotionally drained. A minute-by-minute examination of his performance means that each day (assuming eight hours per day) he will have 241 pleasurable minutes against 239 unpleasurable ones. These amount to 60,688 and 60,271, respectively, per year. Now realize that if the unpleasurable minute is worse in reverse pleasure than the pleasurable minute is in pleasure terms, then the dentist incurs a large deficit when examining his performance at a high frequency.

Consider the situation where the dentist examines his portfolio only upon receiving the monthly account from the brokerage house. As 67% of his months will be positive, he incurs only four pangs of pain per annum and eight uplifting experiences. This is the same dentist following the same strategy. Now consider the dentist looking at his performance only every year. Over the next 20 years that he is expected to live, he will experience 19 pleasant surprises for every unpleasant one!

This scaling property of randomness is generally misunderstood, even by professionals. I have seen Ph.D.s argue over a performance observed in a narrow time scale (meaningless by any standard). Before additional dumping on the journalist, more observations seem in order.

Viewing it from another angle, if we take the ratio of noise to what we call nonnoise (i.e., left column/right column), which we have the privilege here of examining quantitatively, then we have the following. Over one year we observe roughly 0.7 parts noise for every one part performance. Over one month, we observe roughly 2.32 parts noise for every one part performance. Over one hour, 30 parts noise for every one part performance, and over one second, 1,796 parts noise for every one part performance.

A few conclusions:

  1. Over a short time increment, one observes the variability of the portfolio, not the returns. In other words, one sees the variance, little else. I always remind myself that what one observes is at best a combination of variance and returns, no just returns (but my emotions do not care about what I tell myself).
  2. Our emotions are not designed to understand the point. The dentist did better when he dealt with monthly statements rather than more frequent ones. Perhaps it would be even better for him if he limited himself to yearly statements. (If you think that you can control your emotions, think that some people also believe that they can control their heartbeat or hair growth.)
  3. When I see an investor monitoring his portfolio with live prices on his cellular telephone or his handheld, I smile and smile.

George Soros once wrote, “I contend that taking fallibility as the starting point makes my conceptual framework more realistic. But at a price: the idea that laws or models of universal validity can predict the future must be abandoned.”

And market wizard Mark Weinstein would say, “Don’t be arrogant. When you get arrogant, you for sake risk control. The best traders are the most humble.”

So be humble. Take fallibility as your starting point. Be aware of the random nature of markets over various temporal cycles. Don’t mistake noise for information or skill for luck. And always focus on protecting your capital first.

Drop any questions/comments in the comment section below. And if you’d like to get my thinking, ramblings, and occasional trade ideas, then just put in your John Hancock along with your email below.

Thanks for reading,

Alex

 

 

Separating signals from noise in markets
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Separating Signal From Noise In Markets

There’s not much information to get. The most important variables in global macro are the economic conditions and how central banks respond to those conditions.

To get that information, I read the paper, look at the data, watch what the officials say, and try to read between the lines. From an actual trade point of view, it’s price action that determines when and where to put on a trade.

Otherwise, there’s a huge amount of noise in the world. Other people’s opinions are irrelevant. I can’t bear talking to salespeople because all they want to do is tell you something new, and things don’t change enough to warrant that. I don’t pick up the phone if I can avoid it.

– The Currency Specialist, from Drobny’s Inside the House of Money

My take:

A big part of successful trading is learning how to effectively separate wheat from chaff and signal from noise.

This is no easy task.

We live in a world of 24/7 information flow. It’s easy to drown in the constant firehosing of data, opinions, and hot takes.

Traders get into trouble when they mistake the noise for actionable intelligence. This happens because they don’t yet have a framework for which to filter out what’s useful and what’s not.

All a framework is is a set of mental models, broad first principles, and general truths that you stress test for robustness and which hold up through time.

The key is to start with the simple truths and build, slowly, while never sacrificing veracity for complexity.

Munger gave a killer speech about how to do this back in the 90’s. Here’s a cut from it (emphasis mine).

Well, the first rule is that you can’t really know anything if you just remember isolated facts and try and bang ’em back. If the facts don’t hang together on a latticework of theory, you don’t have them in a usable form.

You’ve got to have models in your head. And you’ve got to array your experience both vicarious and direct on this latticework of models. You may have noticed students who just try to remember and pound back what is remembered. Well, they fail in school and in life. You’ve got to hang experience on a latticework of models in your head.

What are the models? Well, the first rule is that you’ve got to have multiple models because if you just have one or two that you’re using, the nature of human psychology is such that you’ll torture reality so that it fits your models, or at least you’ll think it does. …

And the models have to come from multiple disciplines because all the wisdom of the world is not to be found in one little academic department. That’s why poetry professors, by and large, are so unwise in a worldly sense. They don’t have enough models in their heads. So you’ve got to have models across a fair array of disciplines.

You may say, “My God, this is already getting way too tough.” But, fortunately, it isn’t that tough because 80 or 90 important models will carry about 90% of the freight in making you a worldly-wise person. And, of those, only a mere handful really carry very heavy freight.

For the Currency Specialist, the framework he carried was focused on a few global macro and economic variables, how central bankers responded to these conditions, and then constantly testing his resulting assumptions against the truth mechanism that is the market.

At MO we apply a range of mental models from Capital Cycles to Investment Clocks to Game Masters and Liquidity Levers to name a few.

Like the Currency Specialist, these models help us distinguish the signal from the noise while keeping us from chasing something shiny that’s of little value.  

And more importantly, it gives us a framework from which to value these inputs and our responses to them.

This allows us to continuously refine our tools and mental models which hopefully drives us closer and closer to truth and profits.

Market Wizard Michael Marcus said the most valuable thing he learned at Commodity Corp (CC) was how “to see the signal, like the signal, follow the signal.”

Focus on developing your latticework of mental models and you’ll get better and better at seeing the signal.

Drop any questions/comments in the comment section below. And if you’d like to get my thinking, ramblings, and occasional trade ideas, then just put in your John Hancock along with your email below.

Thanks for reading,

Alex

 

 

 

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Samurai, Livermore, and Market Timeframes (Daily Speculations)

Daily Speculations are just a post for me (Alex) to share some quick thoughts on charts/trades I’m looking at, books and articles I find interesting, or maybe just some photos of my dog Mars. As the name states, I’ll be sharing something daily but some days I won’t because I’m lazy.

Here’s an excerpt from one of one of the weekly market Briefs I write each week for members of the Collective. I wrote this one last year some time. It’s about Samurais, Livermore and market timing, obviously. 

Enjoy.

There is timing in the whole life of the warrior, in his thriving and declining, in his harmony and discord. Similarly, there is timing in the Way of the merchant, in the rise and fall of capital. All things entail rising and falling timing. You must be able to discern this. In strategy, there are various timing considerations. From the outset you must know the applicable timing and the inapplicable timing, and from among the large and small things and the fast and slow timings find the relevant timing, first seeing the distance timing and the background timing. This is the main thing in strategy. It is especially important to know the background timing, otherwise your strategy will become uncertain. ~ Miyamoto Musashi

Miyamoto Musashi was a renowned Samurai and Ronin (meaning he served no master) in Japan during the early 17th century.

He had a unique style of fighting with double blades which was apparently quite effective; he racked up an undefeated record of 60 duels. In his later years, he wrote The Book of Five Rings — a work similar to Sun Tzu’s Art of War that covers strategy, tactics, and philosophy through the scope of sword fighting, but that’s also applicable to life in general.

In Five Rings, Musashi talks about the importance of timing and maintaining one’s awareness of the ebb and flow inherent in life and war.

Timing, as we know, is as critical an input to a deadly Ronin Samurai as it is to a Master Trader. Musashi’s wisdom on the differences of time and the warrior’s manipulation of such is a subject that every trader needs to understand and practice at the deepest levels.

I’ve been increasingly thinking about Musashi and timing because of the macro environment we now find ourselves in. It’s in this type of environment where understanding the difference of applicable and inapplicable, as well as, background and distance timing, becomes ever more crucial. Let me explain.

As traders operating in markets, we’re fighting in multiple timeframes. In these different timeframes, there are varying levels of signal to noise. We’re left to discern what timing is applicable to our trade objective and what’s not. We need to learn from experience which timeframes we can have relevant conviction in and which we simply can’t.

For instance, one cannot simply be bullish on stock XYZ. That is a meaningless statement. Are you bullish on the stock over the short term (ie, next 4-8 weeks) because of factors a, b, and c? Or do you really think the company is undervalued and price should rise at some point over the next couple of years, but you have no conviction on where it will go in the near term?

Discerning your trade objective and reasoning is vital to understanding what your “relevant timing” is. Meaning, you understand the relevant time and the factors applicable to your thesis — every timeframe has its own unique drivers.

Musashi talks about the importance of “first seeing the distance timing and background timing.”

The trading equivalent to these is price action and macro. Price action (distance timing) signals where things stand now and where they’re possibly headed in the near term (1-3 months). Macro (background timing) tells us where the larger forces and imbalances are. It provides us with a gauge of where the risks and opportunities lie in the future. Both sections of time affect one another, so the ebb and flow of the battlefield (market) is constantly evolving.

But, as Musashi says, it is “especially important to know the background timing” because that is the more powerful force that will eventually bend and dominate the near-term. It’s when these different time frames lineup that you get the most powerful and profitable trends.

Livermore (the Musashi of markets) understood the importance of timing in speculation better than anybody and talked about this lesson repeatedly in Reminiscences of a Stock Operator:

“The way to make money is to make it. The way to make big money is to be right at exactly the right time. In this business a man has to think of both theory and practice. A speculator must not be merely a student, he must be both a student and a speculator.”

“There is a time for all things, but I didn’t know it. And that is precisely what beats so many men in Wall Street who are very far from being in the main sucker class. There is the plain fool, who does the wrong thing at all times everywhere, but there is the Wall Street fool, who thinks he must trade all the time. “

“Obviously the thing to do was to be bullish in a bull market and bearish in a bear market. Sounds silly, doesn’t it? But I had to grasp that general principle firmly before I saw that to put it into practice really meant to anticipate probabilities. It took me a long time to learn to trade on those lines. “

“I think it was a long step forward in my trading education when I realized at last that when old Mr. Partridge kept on telling the other customers, ‘Well, you know this is a bull market!’ he really meant to tell them that the big money was not in the individual fluctuations but in the main movements — that is, not in reading the tape but in sizing up the entire market and its trend.”

“…the point is not so much to buy as cheap as possible or go short at the top prices, but to buy or sell at the right time.”

“I had made a mistake. But where? I was bearish in a bear market. That was wise. I had sold stocks short. That was proper. I had sold them too soon. That was costly. My position was right but my play was wrong.”

“That is what happened. I didn’t wait to determine whether or not the time was right for plunging on the bear side. On the one occasion when I should have invoked the aid of my tape-reading I didn’t do it. That is how I came to learn that even when one is properly bearish at the very beginning of a bear market it is well not to begin selling in bulk until there is no danger of the engine back-firing.”

The key to dealing with the various temporal frames (that’s a fancy way of saying lengths of time) is just to remain aware of your analysis and expectations and how they align with the march of time.

Don’t get tunnel vision and try to fit a long-term macro view into a short-term trade expectation.

Be flexible and know which timeframe you’re operating in and in which your edge lies.

Drop any questions/comments in the comment section below. And if you’d like to get my thinking, ramblings, and occasional trade ideas, then just put in your John Hancock along with your email below.

Thanks for reading,

Alex

 

 

 

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Ray Dalio’s Portfolio Allocation Strategy: The Holy Grail

Daily Speculations are for me (Alex) to share some quick thoughts on charts/trades I’m looking at, books and articles I find interesting, or maybe just some photos of my dog Mars. As the name states, I’ll be sharing something daily but some days I won’t because I’m lazy.

Here’s an excerpt from Ray Dalio’s recent book Principles recounting his biggest aha!” moment in investing. This epiphany is what helped Dalio develop the unmatched asset allocation strategy he uses in his investment portfolios (emphasis is mine): 

From my earlier failures, I knew that no matter how confident I was in making anyone bet I could still be wrong — and that proper diversification was the key to reducing risks without reducing returns. If I could build properly diversified (they zigged and zagged in ways that balanced each other out), I could offer clients an overall portfolio return much more consistent and reliable than what they could get elsewhere.

Decades earlier, the Nobel Prize-winning economist Harry Markowitz had invented a widely used model that allowed you to input a set of assets along with their expected returns, risks, and correlations (showing how similarly those assets have performed in the past) and determine an “optimal mix” of those assets in a portfolio. But his model didn’t tell you anything about the incremental effects of changing any one of those variables, or how to handle being uncertain about those assumptions. By then I was terribly fearful about what would happen if my assumptions were wrong, so I wanted to understand diversification in a very simple way. I asked Brian Gold, a recently graduated math major from Dartmouth who’d joined Bridgewater in 1990, to do a chart showing how the volatility of a portfolio would decline and its quality (measured by the amount of return relative to risk) would improve if I incrementally added investments with different correlations. I’ll explain it in more detail in my Economic and Investment Principles.

That simple chart struck me with the same force I imaging Einstein must have felt when he discovered E=MC2: I saw that with fifteen to twenty good, uncorrelated return streams, I could dramatically reduce my risks without reducing my expected returns. It was so simple but it would be such a breakthrough if the theory worked as well in practice as it did on paper. I called it the “Holy Grail of Investing” because it showed the path to making a fortune. This was another key moment in our education.

ray dalio's asset allocation strategy

As the Holy Grail chart showed, an equity manager could put a thousand 60 percent-correlated stocks into their portfolios and it wouldn’t provide much more diversification than if they’d picked only five. It would be easy to beat those guys by balancing our bets in the way the chart indicated.

Thanks to my process of systematically recording my investment principles and the results they could be expected to produce, I had a large collection of uncorrelated return streams. In fact, I had something like a thousand of them. Because we traded a number of different asset classes, and within each one we had programmed and tested lots of fundamental trading rules, we had many more high-quality ones to choose from than a typical manager who was tracking a smaller number of assets and was probably not trading systematically.

I worked with Bob and Dan to pull our best decision rules from the pile. Once we had them, we back-tested them over long time frames, using the systems to simulate how the decision rules would have worked together in the past.

We were startled by the results. On paper, this new approach improved our returns by a factor of three to five times per unit of risk, and we could calibrate the amount of return we wanted based on the amount of risk we could tolerate. In other words, we could make a ton more money than the other guys, with a lower risk of being knocked out of the game — as I’d nearly been before. I called it the “killer system” because it would either produce killer results for us and our clients or it would kill us because we were missing something important.

The success of this approach taught me a principle that I apply to all parts of my life: Making a handful of good uncorrelated bets that are balanced and leveraged well is the surest way of having a lot of upside without being exposed to unacceptable downside.

This is an important concept to understand.

Diversifying with over 15 uncorrelated return streams and balancing out your return per unit of risk, through sizing and leverage (ie, leveraging bonds to equal equity on a return per risk unit basis), can get you to a balanced global or market-neutral position.

This is where your risk is balanced out and you’re effectively clipping beta coupons from global markets and various asset classes.

An important note I should make is that to build this market-neutral book you really have to understand cross-asset correlation. It’s not correlation in the typical sense, where you use a market lookback period of say three years to see how much in line those asset classes have moved together.

The correlation has to do with the fundamental drivers of each asset class (ie, what are the economics that drive investors to buy and sell each asset class). At its most basic, this idea can be boiled down to two inputs of growth and inflation which when combined give you four stages.

Different asset classes will perform well in some stages and less well in others, as the graph to the right shows.

You can dive really deep into this and begin to do some interesting stuff — I’ll save that for another post on another day.

But, as a global macro trader, I love the idea of having a market neutral book that collects beta in a smart risk-adjusted way.

This gives me an excellent base from which to operate off of and build an alpha overlay by making what are typically low probability but high expected value (EV+) convex bets, preferably using leverage on top of my beta.

This takes the pressure off me as the trader to always be in the market with a position and allows me to focus my time on seeking out the fat pitches and asymmetric trades that only come around every so often.

I’ve long been a proponent of the old-school macro approach used by Soros and Druck where you’re highly concentrated. You have just a few eggs in your basket that you watch intensely. But a more optimal approach is a combination of the two. Use diversification to collect your beta and overlay that with a concentrated book for your alpha.

Make sense?

Drop any questions/comments in the comment section below. And if you’d like to get my thinking, ramblings, and occasional trade ideas, then just put in your John Hancock and email below.

Thanks for reading,

Alex