Risk: Thinking creatively

Manage
21

I think this is a great topic and hope to learn some new techniques.

  I wanted to put in my 2 cents and share what has drastically improved my portfolio returns and lowed my risk(risk caused by emotion).

Studies on Human behaviour or trader psychology is not new but when I studied and applied a new way of thinking to my trading plan it stopped
unnecessary losses, draw downs and has increased my annual returns by about 10% a year. I believe studying and understanding human behaviour
when it comes to trading and risk management will increase portfolio returns in the long term.
A few examples.
-If you act on greed or fear emotions you will drastically reduce long term portfolio returns.
-If you don’t have a trading plan that is in line with your risk tolerance you will most
likely not be able to follow your plan.
-A lot of people don’t have realistic expectations and this may cause overtrading,
and poor portfolio performance.
etc…
So does the study of trader psychology belong in a risk management thread?
I believe it is a part of the bigger picture but a guide of techniques may be useful in portfolio risk management.
ie Think of your portfolio as a separate business and detach yourself emotionally from the portfolio. My only job is to follow my trading plan that I developed when I had a clear mind.

Most investors spend years losing money and learning lessons the hard way. Took me 7 years :frowning: A trader psychology guide may help beginners and some vets!

Thank you.

22

Marc, that is an interesting comment about operating leverage. Companies with high fixed cost to variable costs could be the first to nose dive when things slow down. I was focused on just debt. I am going to look at that further. Thanks for the idea.

23

I added a few items to the Google document.

If the goal is to have a view of ex-ante risk, then average or median portfolio characteristics may be a good place to start. For example, what is the weighted average sum of the portfolio’s ROE or debt-to-equity? Then a z-score can be calculated to determine the portfolio’s exposure versus the cap-weighted benchmark. Some basic metrics (e.g., ROE, ROI, P/B) can be calculated and grouped under various categories (e.g., Value, Quality).

Regarding diversification, some easy metrics are number of holdings, and sector weights. It would be great to compare sector weights versus the benchmark. While based on historical performance, I still think tracking error may also be a good (and simple) way to gauge diversification.

24

“Regarding diversification, some easy metrics are number of holdings, and sector weights.”

Quad - in the most recent drop in oil prices, my 30 stock R2G went down as fast as my 8 stock R2G, both with similar ranking systems. Thus I cannot conclude that number of holdings is of value to gauge diversification. Number of holdings helps against a single company collapse, but not against sensitivity to general market conditions / specific asset classes.

Furthermore, I don’t find that sector weighting is great tool for assessing diversification. What I have found is that our Ranking System - centric designs tend to pick similar types of companies even though they are in separate sectors. Again, many of my R2G models have sector weighting limitations that didn’t help with the oil price drop.

This is the reason why I think we need to get into the guts of how the individual holdings move in relation to each other. If the individual holdings are highly correlated throughout time then one can conclude that there isn’t significant diversification, and vice versa. It is much superior to using number of holdings and sector weights.

Steve

25

I agree that more holdings cannot immunize against a general market collapse, but some risks are systematic and cannot be diversified. My definition of diversification is to mitigate idiosyncratic risk, whether it be company, sector or factor specific. I would contend that trying to immunize a portfolio against any and all risks is unrealistic and potentially counterproductive. A portfolio that would have protected against the recent market decline (which can hardly even qualify as a “correction”) might be a portfolio without sufficient excess returns to be worthwhile.

26

There is another kind of risk requiring diversification that the quants have not discussed – yet – mainly because I don’t think they’ve figured out that it exists. It’s unique to our kind of data-driven investing; i.e., it hasn’t been very relevant in the past but it probably will become mainstream in the future. It’s a version of the mis-specified model.

It’s the risk of oddball phenomenon causing a factor (a growth rate, a debt ration, a valuation metric, anything) to not really mean what a quick glance at the number leads one to think it means.

This is not about data errors or database design or policy. It’s about the reality that data cannot fully capture the infinite variety that’s out there and can never be truly perfect. There’s a widespread impression that working with data involves precision. Actually, it’s quite the opposite. It requires us to embrace the adage that its better to be vaguely right than precisely wrong. It’s why contrary to quant best practices in other fields, for us, we’re better off using lots of factors and even embracing redundancy or correlations among factors. We need protection against oddball data readings. (So five ways to define growth are better than one.)

Similarly in portfolios, we have to recognize that despite our best efforts, our mode4ls will still pull in some stocks we don’t really want. A 20 stock portfolio based on a carefully constructed model gives us a better chance of properly implemented our idea than a five stock portfolio even with the same model.

So I think number of factors is relevant (although not in the way others discussing R2G have believed; to me, more is better from a risk control perspective), as is number of stocks (more is better – to a point, and figuring that out is the hard part). I’ll try to phrase it for the Google doc later.

27

Quad - we need to think about how to eliminate systemic risk at the book level. There is nothing more disconcerting than seeing all of one’s ports sinking at the same time. The diversification indicator that I propose will give a good deal of insight and may work in conjunction with market sensitivities such as interest rates, oil, USD, etc. And, if nothing else, the diversification indicator may provide early warning i.e. when one’s holdings start to become very correlated then it is time to think about protecting against a market bear.

At the port level the diversification indicator enlightens subscribers to the ease with which a port could be data mined. Human nature suggests that a model will be optimized as far as possible, despite claims to the otherwise. It should not be considered as a red flag at the port level, but an insight. At the book level it should be a red flag.

Steve

28

Everyone has failed to mention the most important risk factor–especially over the long term:

Performance

First, if you have doubled or tripled (maybe more) your money over the period of several good years you can tolerate a significant loss and still be ahead. Over a long period of compounded returns you are almost guaranteed to be ahead no matter what the draw down looks like.

Second, if you don’t get washed out you can recover quickly.

Third, there is a limit to how much you can control the draw downs on your long positions no matter how diversified you are.

Okay, it is debatable whether this is the most importance factor–but maybe.

29

Jim - the nemesis of performance is overconfidence/greed. As an example, there were many gold traders back in the early 80’s that made a fortune, then lost it all because they kept trading when they shouldn’t have. Great performance leads to overconfidence and greed. After a good run, one needs to be extra cautious and keep emotions in check. Don’t quit your day job, etc. So I would argue the exact opposite of your position.

“Third, there is a limit to how much you can control the draw downs on your long positions no matter how diversified you are.”

In this age of newfangled ETFs that offer short/inverse positions and exposure to various asset classes, hedge funds, etc. I believe that it is possible to control drawdowns. In any case, I don’t believe in blanket statements without any kind of evidence.

Steve

30

Steve,

You are probably right. I was trying not to take a position on hedging.

Still, to be safe with hedging you better do it all the time. And if you are sacrificing a lot of performance, I really am not sure about the reduction in risk over the long run.

BTW, did the gold traders you mentioned use any leverage: I would never recommend that. Also, I’m assuming almost none of us are in just one asset whether it be gold or oil or even airline stocks. Also, I’m not talking about options or futures. It goes without saying that one should stay about an order of magnitude away from gamblers ruin: even in theory. That would be the most important risk consideration.

31

If one wants to address systematic risk, I suspect hedging may be the only way, and as a practical matter, that probably means market timing because, as you said, the long-term reduction in return may prove to be too much.

32

I couldn’t agree more.

While it may be disconcerting to see all ports declining at the same time, equities have a risk premium for a reason. That being said, I agree that it would be great to have better insight into systematic risk, and I was reminded of the concept of market “turbulence” (see link below).

However, it would be difficult (if not impossible) to construct a more resilient portfolio without including other asset classes (e.g., credit, fixed income, currencies, commodities, international equities). Utilizing the current capabilities of P123, the only tool available to use this information is market timing, by selling equities and going to cash when systematic risk is elevated. So I would classify your proposed approach as market timing, not diversification of P123 equity strategies.

33

Quad - that is a very interesting paper.

"Utilizing the current capabilities of P123, the only tool available to use this information is market timing, by selling equities and going to cash when systematic risk is elevated. "

I believe that a book can be constructed that maximizes diversification without the use of market timing. This can be done by an appropriate mix of ETFs and stocks. However, market timing could in theory provide higher levels of return, albeit with higher risk. It really comes down to investor expectations. Some are quite happy to make 8% return per year provided it is reasonably low risk. Others aren’t happy with 50% return per year. If you are in the second camp then of course market timing is the only option as diversification won’t get you there.

Steve

34

I would agree that utilizing ETFs to diversify into other asset classes can help, but P123 is not necessarily the best tool (currently) to arrive at the strategic asset allocation. There are better (though not perfect) tools, such as mean-variance optimization models or Monte Carlo simulation, based on forward-looking capital market assumptions. That being said, I believe that allocation models are best used as directional indications only, since they are flawed (e.g., assuming normal distribution of returns, rebalancing every period), and often very sensitive to even slight changes in assumptions. I would never suggest “goal seeking” (i.e., optimizing) your way to an allocation.

How would you propose implementing an ETF portfolio? The ETF strategies that I have viewed on P123 seem to rotate into the “best” handful of ETFs (e.g., 1-2 ETFs at a time) based on historical performance (e.g., returns, volatility). How is this not market timing?

35

I’ve wasted way too much time on P123 threads in the past… so not wading in much, but the ‘diversification’ problem is fairly ‘simple’ at the book level. Invest in very conceptually different things/return drivers that have logical reasons for maintaining inverse/zero correlations in peak stress market environments. So, managed commodity futures and long-short trend following systems and short only stocks or short-term hi-quality gov’t bonds tend to exhibit this with long-only equity.

Can also hold ‘cash’ and, if you are willing to invest A LOT of time in learning, some dedicated ‘short only’ portions of the portfolio.

So, a simple port ‘book’ of a) personal income (from a job), b) cash, c) short-term, hi quality government bonds from the strongest economy nations, d) long only equity systems (can vary market cap, style, country, etc), e) managed futures or trend following long-short systems (long vol profile for the best managers in historical peak stress times), f) short term real estate or asset backed loans with margin of safety (short term senior credit investments, with collateral and say 60% LTV ratio), g) small’ish (or tactically varied) allocation to short only equity systems, and h) if you want, some market timing stuff… or (optional) i) selling vol through options selling after big vol spikes, with 2-3 year periods (or exit based on VIX levels) of investment followed by cash. There are some good market neutral traders out there as well, they can be added. Or rent generating real estate investments. It’s fairly good in many markets and offers inflation hedge as well. For pure returns, ‘angel investing’ is very good - if you begin at the bottom of an up cycle (we are now likely at the top).

The combination will give you a balanced overall portfolio that is very unlikely to all go down at once.

You can also build ‘simple’ binary systems - Bonds/cash, long-equity/cash, real-estate/cash, gold/cash etc. and allocate to some of these.

Many of these can be done in P123 with ETF’s and stocks if you invest the time, or can hire pro managers. Some can’t be done here no matter what.

A full discussion of ‘risk’ of any one system is something I’ve tackled in many threads in the past, so not gonna dive back in. But good luck.

As far as what is and isn’t ‘market timing’, it’s a giant ‘boogey man’ on this site. Any portfolio that differs from the market portfolio is ‘market timing’ in some way. Everyone market times. They just either do it intentionally or unconsiously.

36

Quad - would you agree that the traditional risk-based strategy of stocks/bonds/cash allocation based on age is a form of risk control? If so, then that is my answer. Yes it can be done. It can be done with stocks, bonds and cash, as a minimum. These can be put into ports without market timing and the book can do the % allocation. With the variety of options we have today I suggest it is possible to improve on that.

And if superior results depend on market timing, then so what? If the market timing can be done in a rational way (such as minimal correlation across securities) while adding more performance than risk, then isn’t that something that should be pursued? I think Marc’s mandate is to improve on what we have, not give up because we don’t already have it.

Steve

37

Tom - I agree with what you say but my position is that if there are tools that will help with the book-level diversification effort then why not have those tools available? I think you can make an educated guess about what to put into a book for minimum risk but you should be able to reduce the guess-work with good diversification tools. It is like driving a car. It may appear to be running well but you don’t know for sure without plugging in a diagnostics computer to tell you what is going on under the hood.

Steve

38

Changing the topic and thinking out loud a bit. We should have an “acid test” for company-level risk. Whatever Marc decides upon should be able to identify risk in various companies that have collapsed. A good example is FXCM , instantly put on life-support by government policy reversal. FXCM deals in FOREX which is high leverage, but is there anything on the books that would indicate such risk?

FXCM is also a good response for anyone that believes Black Swans are rare events.

Steve

39

Steve,

There are many things that can be done at the book level and I’ve posted on many of them in the past… there doesn’t seem to be any want or desire for them.

For example:
a) Allow people to create ‘rules driven’ books to auto adjust the total amount of cash invested in a book with mechanical rules - for example, this will allow risk targeting or beta targeting.
b) Allow developers to adjust the amount of hedging on a book based on rules - so, if there is a DD of 10-20%, can add X% hedge at the book level, if DD of 20% to 40% can adjust hedge amount, etc.
c) Allow developers to use buy and sell rules in a book with constraints, so we can set maximum position sector or asset class weights, or trailing period max correlation constraints, etc.
d) Allow for creation of long-short books, with ‘beta matching’ and total sector controls. This would allow professional-light type long-short systems.
e) Allow for user inputs on ‘total book level’ constraints - for example, cap size, long, short, position level, industry, etc.

I doubt many users would use these, but this is how professionals begin to use rules to drive books. As it is, if you don’t build the systems and someone else does, and subsystems are optimized, then combining them in books just makes it worse.

Best,
Tom

40

I also suggested year(s) ago that P123 save all launched R2G’s. Over time, can build real data driven models of what drives consistency over time in out of sample vs. in sample. Can look at things like total factors in ranking, number of hedges, total gross exposure, sector concentration, number of positions, etc. over several hundred systems from many designers. If no R2G’s are deleted, it’s valuable and can begin to extract ‘probabilities’ of certain factors driving consistency out of sample. However, this wasn’t followed, I think. And no need it should be, it’s not my company.

Something like Omega Ratio can be added (although it won’t detect overfit systems, it’s another useful - or Marc would say, useless ratio). I have seen studies of ‘ranking traders’ for 3,6 and 12 months go forward performance based on trailing period returns. Sharpe, Sortino and Omega all have some statistically significant positive results - although many multi-manager allocators claim to have much better proprietary models.

As far as ‘company level risks’… can identify the largest down day in a company’s history, as well as the largest down day (or 5 down days) in the past 20 years in the most closely correlated companies (on major factors such as size, financial quality, industry and ‘earnings misses / beats’ to this one). Can also look at ‘factor extraction’ to try to figure out which industry or company this company is most like on those factors and then look at the largest historical DD’s of the those most closely matched companies. Looking to create a multi-factor model that ‘predicts’ extreme events and ‘risk of ruin’ for this ‘type of company’ based on the companies ‘grouping’, not just the company’s history. Sorry, I don’t have more time to write more clearly now.