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Say you've been running an MI portfolio in a separate account for a while. What's a good definition and metric of success?
Anyone ever thought about that?

It's a tough question to quantify. Outperforming a reasonably chosen benchmark over a long period of time is the acid test, but it isn't a black and white one. How long do you wait? The longer you wait, the less likely the outperformance is due to chance, so it's more of a statistical measure of true value added. Outperforming for ten years is a lot more certainly due to skill than outperforming for one year. But there are still some people who say Warren Buffett has just been lucky. Nobody doubts Elan's 6/3 option portfolio though, it's older than some board members : )

One metric I have toyed with is this:
First, if the end-to-end performance lags the chosen benchmark, it's a fail. Sorry.
Second, the time period has to be long enough to include a bear market. And some bull times too. If not, don't try to see if it working, the answer won't be reliable. Wait a while.
Third, if and only if it looks better than the benchmark from inception to date:
Calculate the performance of the portfolio in all the rolling 6 month periods, as well as the performance of the benchmark in those same period. (Each period might be a month or quarter or half-year or year or two-year stretch...it doesn't really matter, but there should be at least 10 of them). Feel free to pick the interval that makes things look best.*

Some sort of metric of MI success could be seen in the following two numbers:
* The end-to-end CAGR advantage versus the benchmark, the measure of monetary success without regards to whether it was luck or skill;
* The percentage of those rolling subperiods that the portfolio outperformed the benchmark: an attempt to create a metric of how certain you are that the performance was non-random, not just a few lucky picks.

That notion is really only suited to a long-only portfolio. It wouldn't work with a portfolio doing long/cash timing, for which you'd want something more like measuring the improvement in the rolling year downside deviation with a hurdle rate (MAR). I usually test my screens based on two numbers, being "CAGR improvement" and "risk fraction", i.e., what the DDD3 risk metric is when divided by the DDD3 risk metric of the benchmark in the same interval.

Does anyone have any better thoughts? At what point can one be reasonably sure that good performance wasn't just the luck of the draw?

Jim

* why is this OK?
If you pick really short intervals the "beat the index" rate will tend towards 50%, making things look bad...though you do get lots of statistical support. If you pick really long intervals, getting towards the length of the whole history, the statistical support is terrible because of the high overlap but it's such a long period that it's really starting to measure your end to end CAGR...which is, in the end, the only thing that matters, so one can let it slide.

Some other random thoughts about what might constitute success, irrespective of returns.
- having a defined strategy that you can stick with
- the investment returns meet some goal, which may not be an index return (i.e., what is the benchmark?)
- enjoying the game of implementing an investing strategy (lol)
- helping the younger generation learn to become good investors

About the benchmark, we probably normally think of it as an index return, say the S&P500.
It could also be just a fixed value, say 10% CAGR, or 5% or 20%.
Benchmark could differ for folks interested in preservation vs folks interested in growth.

An MI success metric could easily be generated from backtests.
Real life would be an entirely different story.

At what point can one be reasonably sure that good performance wasn't just the luck of the draw

Hmm, maybe we also need to know when bad performance isn't just luck of the draw.


Mark

We aren't running multi-billion dollar mutual/hedge funds; I see no reason we should have to be limited by their concerns. You can buy an index fund essentially for free and have a risk of large drawdowns anyway. I for one am willing to have higher volatility for higher returns, and while there are no guarantees of future success based on backtests there is little else to use for data points than history. "Success" is having enough money to do what you want to do not beat a given metric; why should we be limited by a need to not take on any more risk than an index fund if the return is great? The trick is finding volatility that is acceptable to you personally. We don't need to match laws on diversified mutual funds nor professionals whom can't buy small stocks. Sure, reduced risk is nice; nice returns are better.

Jim wrote: What's a good definition and metric of success? Anyone ever thought about that?

Great question! Indeed, it is something that I think about all the time. And my thinking has changed quite a bit over the years. Back in the 90s my only consideration was whether my returns would beat out an average of the three primary indexes that I was tracking and comparing to. These three had to be total return indexes so these days one would simply use an ETF for that purpose, e.g. IWM for the Russell 2000, or QQQ for the Nasdaq 100.

Around 2005 or so I began to think more in terms of limiting exposure. So a winning strategy for me was one where my time exposed to risk was reduced. My aim was to limit time in the market to a range of ten to twenty-five percent of the time. The rest of the time I'd be in cash. Success would then be measured on how well I did achieving this goal, while also significantly surpassing the average of the three indexes.

Jim's creation of the DDD3 has been super helpful in this regard. Using my understanding of his indicator I come up with the following DDD3 values with a LTBH of these ETFs.

* QLD from 6/21/2006 - 15.96%
* QQQ from 4/12/2007 - 8.96%
* SPY from 1/29/1993 - 7.99%
* DIA from 1/20/1998 - 7.17%
* IWM from 5/26/2000 - 9.46%

My absolute bare minimum threshold is to cut these in half, but combining my limiting exposure approach along with methods to reduce the DDD3 I can typically bring this DDD3 number down to less than 1%.

My primary trading system has a DDD3 of 0.15%. Despite this, the maximum drawdown is still -28.35%. But this was in the middle of the March 2020 volatility.

Very long backtests that were the bread and butter of the Mechanical Investing board's approach I consider more or less irrelevant. Markets change too much based on macro factors to consider them to be predictive. What works in one macro environment falls completely apart in another. Consequently, investing has to be approached with a more nuanced strategy that considers these factors. Which factors exactly?

* Interest Rates
* FED's policies - quantitative easing and tightening
* Inflation Rates
* Multiple macroeconomic indicators that identify recessionary pressures
* Consumer sentiment

I could go on and on, but you get the idea. A long-term backtest based on fundamental data of stocks doesn't take any of these things into consideration. This is where MI investing has failed and will continue to fail.

In summary, a key measure of success in my book is the ability to limit exposure to black swan events, while continuing to produce respectable returns that beat out all the major indexes. If I need to be invested 100% of the time just to match and slightly beat the major indexes, that for me, is failure!

Jim wrote: Does anyone have any better thoughts? At what point can one be reasonably sure that good performance wasn't just the luck of the draw?

I'm disappointed that no one really is keen on digging deeper into this question. It used to be a distinguishing mark of the MI board of old. A willingness to slice and dice ideas in a quest for clarity and truth. Oh well.....

On the brk board I posted a spontaneous thought re "longterm performance and avoiding luck/purpose in choosing start/end points":

https://www.shrewdm.com/MB?pid=443488487

At what point can one be reasonably sure that good performance wasn't just the luck of the draw?

I'm disappointed that no one really is keen on digging deeper into this question.

The answer, to me, seems fairly obvious. Since we're dealing with probabilities, the answer is we can never be sure good performance wasn't just luck of the draw. All we can do is draw an arbitrary line in the dry, fine, wind-blown sand and say,"Beyond this point, I'm reasonably confident this algorithm's performance (or mine) is truly good and not merely lucky." And that line gets drawn not merely statistically but also where we're comfortable with the level of risk we're accepting.

Informing the objective part of that line-drawing is history, but there are too few cycles too assess, and too many macro factors to include, or arbitrarily exclude, or not recognize altogether, for those cycles, and--sometimes--"this time it really is different." With no way to tell in real time whether this is the time it's different.

And one more contaminant: since TMF ruined its site, a potful of folks who used to frequent, and contribute to, a Mechanical Investing board have simply left, rather than follow over to this site and this Mechanical Investing board.

Eric Hines

Say you've been running an MI portfolio in a separate account for a while. What's a good definition and metric of success?

Risk-adjusted return compared to a benchmark is the most important metric. But end-to-end performance only provides one data point. Smaller time periods provide more data, but will have more noise. I use monthly excess returns, and a chart of the 12-month average shows any changes in performance. Using independent monthly returns allows the use of standard statistical methods. For example, for the standard MI SIP screens, monthly excess return was:

 avg    sd     from       to     months
1.0%   3.2%  19970224  20100701    161
-0.3%  2.5%  20100802  20231206    161

Using 6-month rolling returns is probably similar, but I would be more interested in the chart than percent wins.

The win percent will go from 100% for the longest period to 50% to 1-day periods. For the screens I follow, win percentage was:

rolling period  average  min  max
    10-year       92%    56%  100%
    1-year        68%    56%  81%
    1-month       56%    51%  63%  

First, if the end-to-end performance lags the chosen benchmark, it's a fail. Sorry.

Extending this thought a bit further. If the chosen benchmark did not perform as well as other available benchmarks, was the chosen benchmark a fail? If so, the only acceptable benchmark is the one that performed the best.

Success is very subjective and as such, it may be difficult to use objective terms. I recall reading but could not find the reference, that on average, people who win a bronze medal in the Olympics are happier than those that win a silver medal.


Aussi

I believe the coding and data requirements to analyze as Jim suggested is beyond the skill level and available time of most denizens here.

For example, I am trying to build some kind of analysis of the "efficacy"? of my little timing signals dashboard in predicting the likelihood of market behavior over the next 1-6 months. Calling it predictive modeling would be an insult to data science, but that's very simplistically what it is. Simple "=CORREL..." or other statistical regression formulas available are probably not appropriate for the task.

So I've tried to learn and do some Python using Youtube U guides... several hours of work for a lapsed developer... training data set, predictive dataset, etc. etc.... which without a better understanding of statistics and R-squared and multi-variate equation results (ie data science) is difficult to interpret, and may still be inappropriate. For instance, I plugged in my guessed set of 4-5 independent variables. The model spit out a correlation factor of .8. Wow! But... which one or two or 3 of those has the most influence, is it a change of state from bull to bear, is it any 3 or more flipping state, or which are really irrelevant, what's the actual regression formula that may be how to generate some kind of forecast...

At the end of the exercise I know a little more about Python and its awesome capabilities, and modern IDEs like Jupyter (now hosted in the cloud and doesn't even require local installation, for free!)... but in terms of understanding whether my little signals tracking does me any good, I'm still at "So... what?"

I'd love to get some community counsel/training from anyone about this.

FC

I've always just tried to beat the S&P over reasonable periods of time (a few years). Given how easy it is to buy, if I can't beat it, I should join it, right? Cooking up another benchmark would feel like cheating the game.


For me success is not having to worry about money. But that can't be all there is to it, because if it was I wouldn't still be doing this. I suppose it's that I've been racing SPY for so long it would feel strange to stop.

Baltassar

Success could have a couple tiers.
One could be to beat SPY with less downside/drawdown, however you want to quantify that. DDDD3 probably.
Another could be to realize some fixed target return, say 15% CAGR (since no one can do 20%) over a period of say three or five years.

Probably those are high bars that few achieve.

Mark

The more I think about it, the more I think I'm pretty happy with downside deviation as the key metric to watch.

Traditionally I have used a threshold hurdle ("minimum acceptable return") of 10%/year, but I think I might revise that to be "inflation + 8%/year". That's pretty much the same thing in the average year of backtests in recent years, but much more meaningful over the long run.

To recap the way I calculate downside deviation:
For every rolling year ending on a month boundary, check to see the extent (if any) that the real returns were less than the MAR (in this case inflation + 8%). All observation periods over 8% therefore count as zero risk.
Take that set of numbers, including the zeroes, and calculate the RMS. (square them all, sum the squares, take the square root of the sum).
That is the risk metric: rolling year downside deviation with MAR= real 8%.
Any portfolio which returns inflation+8% or more in every rolling year will by construction have a risk metric of zero. Each observed shortfall below 8% adds a bit of penalty, with a squared function on the size of each shortfall. Missing the MAR by 2% in a single one-year period (having return = inflation + 6%) is deemed to be four times as bad as missing by 1% (return inflation + 7%).

Arguably using rolling two years would be even better, but that needs a whole lot more history before you learn anything, and I'm impatient.

The quant portfolio would still have to have a decent minimum amount of history. I'd say absolute bare minimum 3 years before even looking at the results, preferably 5 or more years. And, critically, the real world history would has to include a bear market stretch.

For a comparison benchmark, my preference is whatever equally weighted index best matches your quant portfolio's search universe. I'm no more likely to buy a position in a trillion dollar company than I am in a billion dollar company, so I don't think the S&P 500 is a suitable benchmark for trying to assess value added--it's really just measuring the performance of a dozen huge stocks these days. For my own current portfolio I am however tilted towards large caps, so RSP (S&P 500 equal weight) is fine. If I wanted to be fussy I could create a synthetic benchmark of maybe 60-80% RSP and 20-40% equal weight the VL universe. But the difference would be negligible, and a lot more work.

With all those caveats out of the way, my yardstick of MI success would simply be this: after a few years of real world results including a bear, which had a better downside deviation risk metric, my portfolio or RSP? The key idea is this: if you've taken good control of the bad times, the good times will take care of themselves. If it got down to a risk metric of zero I'd know only that it had a return of at least inflation + 8%/year in every rolling period---my risk metric wouldn't know by how much it beat that, but it would surely be by a wholly satisfactory amount. I usually express this as the fraction of the risk metric from RSP in the same stretch, calculated the same way.

This risk metric has some hidden charms. As mentioned, you don't get minimum risk without making a decent return all the time, so sitting in cash won't give you low risk. Making no money is a real kind of risk. It doesn't care about portfolio volatility in the short term. It works fine for systems using options or market timing or shorting, since flat spots or jagged spots don't affect the risk metric for better or worse unless they are long lasting. Thus it is much more tolerant of different investment styles than anything involving short term volatility as a a proxy for risk.

Once that's done, start-to-end CAGR is the logical companion metric, provided only that you have a long enough sample and the end date you calculate it isn't really atypical. For example, CAGR figures ending March 2009 are not going to give you a really good idea about what portfolio styles were really the best long run choices, since things were just too weird. With that caveat, end to end CAGR is the ultimate metric of success.

For example, I'd be very happy if my MI portfolio, after several years including a bear, ends up with (say) 85% of the risk metric of RSP and start-to-end CAGR of 2.0%/year better than RSP. The backtests are of course way better than that, but we know better than to believe backtests : )

As others have noted, you're never 100% sure if it was skill or chance. It's just a matter of becoming slowly more certain over time. There are those who still think that Mr Buffett has just been a lucky outlier playing a game of chance these last 60+ years. But with a good enough metric of how things have gone, I think it's possible to get the certainty of the answer down in a reasonable period of time. Wild guess: after maybe 8-10 years of passably good real world results, I think you might achieve maybe 80% certainty that the result was not entirely due to chance.

Jim

Take that set of numbers, including the zeroes, and calculate the RMS. (square them all, sum the squares, take the square root of the sum).

This downside deviation method is pretty similar to DDDD3 isn't it? I think DDDD3 used a fixed target.


Mark

Never mind, I refreshed my memory. While based on the same philosophy, they are certainly different.
DDDD3 is daily double downside deviation with triple weight on the year and fixed 10% target.


Mark

Take that set of numbers, including the zeroes, and calculate the RMS. (square them all, sum the squares, take the square root of the sum).
...
This downside deviation method is pretty similar to DDDD3 isn't it? I think DDDD3 used a fixed target.

Same idea, just a subset for simplicity.

The DDD3 uses both rolling quarter and rolling year figures, the 3 meaning a triple weight on the rolling year figures versus only single weight on the quarterly.
So this metric is basically 3/4 the same as DDD3.
I included the rolling quarter figures in the definition DDD3 to minimize emotional pain, not really to create the best portfolios--it's the longer term that really matters : )

DDDD3 is just the daily version of DDD3. The extra D is for "daily".

With daily calculation you get 252 hold period start dates per year instead of 12, but of course it's still only one year of real world results--the overlaps are so significant that it isn't really much more in the way of sample size. Going daily helps more in a backtest than when measuring the results of a real world portfolio, because in a backtest you could in theory have different picks every single day. In a real world portfolio your picks aren't changing during a hold period. (my portfolio is running a two month cycle).

All of the above are just particular instances of downside deviation, as written up by Mr Sortino. In essence, it's a measure of the probability that any one year interval of the portfolio will fail to make the return hurdle (with a squared penalty on the size of any shortfalls below the hurdle).

Side note: Being at heart a probability that something will happen in a time interval of a particular length, it can't meaningfully be annualized, since equity portfolio returns are not random walks as time frames get longer. In the general case, an options strategy might have a high probability of a given sized loss at the one month mark but a low probability at the one year interval: a slowly rising but jagged line. Annualizing the biggish monthly number would instead give you a huge annual number equating to a virtual certainty of failure, the exact wrong result.

Mr Sortino's key insight in his creation is that a positive return below your bare minimum is still a failure. If you need 8%/year to avoid eating dog food at age 80, or if you're a pension fund that needs 8%/year to make your payment commitments, then achieving only 7% every year is a true risk. But you have to remember that the threshold to choose for the calculation is NOT the number you want, it's the number you need: the number below which your portfolio has truly failed.

I picked a pretty aggressive 10% only because this is in the context of quant screens, where backtests are always way higher return than the resulting reality. So the original 10%/year minimum threshold I picked could be thought of as (say) 6%/year of actual return and 4%/year of exaggerated optimism in the backtest : )

Jim

I take into account that most people do horribly in the market. They buy at the top, sell at the bottom, etc. Therefore, success has two components.

1. 90% or more of the return of a 70-30 portfolio.
2. The process of doing it, has been enjoyable.

I have not calculated my exact results, but I like to think I have done about 1% better than the market with my stocks, and much better with my fixed income, since I use preferred stocks and closed end bond funds for income. It's much easier to beat the Barclay's aggregate bond market than it is to beat the S and P.

And one more contaminant: since TMF ruined its site, a potful of folks who used to frequent, and contribute to, a Mechanical Investing board have simply left, rather than follow over to this site and this Mechanical Investing board.

People were coming and going also earlier on. I can list quite a number of wonderful authors of the late 90s and early 2000s who had disappeared by 2010 or so, some earlier. Kuperman, moebruin, etc.

So to mitigate the above, that brings me to the vital 2 points:
1. Invite: Try to let others know about the excellent Mechanical Investing community here - along with the sister resource/tool sites. If inclined, don't be afraid to literally talk to your friends about the ideas here and provide a link. If you recall having a private email shared with an author you can't see now, look it up and let them know that Mechanical Investing board has been continued. Treat the board as your own - there is no funded body doing marketing, but if you view it as your own purposeful duty to get the word out, then with many authors/readers (*) the effect will be significant.
2. Post quality: Try to keep the posts friendly to beginners, even whilst not diluting the substance whatsoever. There is no contradiction between the two (avoiding unexplained jargon, and retaining substance). On the contrary, by emphasising clarity you may even find the regular audience can comprehend parts of your post that you thought were obvious, but were actually ambiguous. For example avoid too many abbreviations without ever explaining what the meaning is, be clear with your writing, re-read and if something sounds ambiguous then expand the sentence, if presenting some data provide a summary, and even more fun to read with analysis and/or conclusion. These are obviously not requirements but can be tendencies - in short, write in a manner that you would ideally want to read.
3. Not a problem here, but remember - be both kind, grateful to everyone else. Everyone likes love (even when they don't admit it!).

The recent posts by zeelotes and mungofitch are excellent in this regard - whilst filed with novel ideas and substance, they can also be read by someone with no, or almost no, knowledge of Mechanical Investing to start to make enquiries.

My wish was to allow the communities and friendships to endure, many of which go back more than 20 years, and I am working on the technology side. For the cultural side, if everyone can help with 1 and 2 above, though the culture will anyway be successful, this board will be in an even better state 10 years from that it otherwise will be. Seemingly small things have a large accumulative effect if repeated over time.

- Manlobbi

(*) You only see the authors, and not the pure readers (many also without being logged in) - so there are far more people here than you might think. The culture, in this way, is a little bit like an old fashioned community newspaper; the public contributed, but the overwhelming majority were reading. This contrasts social media where the ad revenue is in proportion only to observation time. The social media thus encourages shorter posts (even if mindless) to lower the effort-commitment-hurdle, which then hugely increases post volume. This is multiplied by maximising the notifications across the network. The goal, as with any company, is revenue, with aggregate cultural enlightenment a completely irrelevant secondary consequence. The goal here, by contrast, is purely cultural - and we can maximise this with 1-3 above.

OT: Manlobbi, thanks for your effort, philosophy, wisdom, grace...& for this site.
:-)Shawn

A few random thoughts to add to the discussion.

Period of Time Evaluating My Historical Portfolio Returns

When it comes to the period examined for evaluating my success I like it to reflect the normal period of the market which is historically at or around 70% bullish and 30% bearish. It doesn't really matter if you use any peak to trough move from 10% to 30% you'll still end up around 70% bullish. So in my evaluation of my past results I want to include a period of time that is reflective of that and includes a minimum of two 20% bear markets.

The Importance of Mitigating Bear Market Devastation

In the 90s I realized that the most important focus of my research had to be on avoiding the lion's share of devastation caused by a bear market. A significant amount of a bull market's gains are reclaimed by the bear market that follows. This table illustrates that point:

https://www.zeelotes.org/Training/SP500_Gains_Recl...

In light of this from the late 90s until today I've focused my attention on identifying major market peaks that have a high potential of a bear market following. Basically, it was creating a basket full of indicators that have historically done this well - breadth, macroeconomic, sentiment, etc. - and then combine them into a consensus score. When this score reaches fifteen or above there is a warning shot over the bow, but when it hits twenty or above it is time to take decisive action moving either completely to cash, or taking on inverse ETF positions or shorting stocks. Here is a chart showing what I'm talking about for 2007-2009.

https://www.zeelotes.org/Training/ST_Bearish_Score...

I also create a consensus score to identify bottoms/troughs in similar fashion.

When it comes to using the MI Screens developed over the years, if you use this sort of approach for avoiding bear markets you'll find that the returns from some of them are massively better than others during the bullish period. In fact, the Shorting screens developed do best when the bullish consensus score reaches a high number. But NOT as shorts, but held long! And the final capitulation period of a bear market sees these same screens do best held as shorts. That is just how the markets roll.

One further chart to illustrate how consensus scores work. I'll be showing the 2007-2009 once again. The cross from a high bullish score to bearish score occurs at ten. The date was 7/23/2007.

Bullish rose above bearish at ten on 3/2/2009.

https://www.zeelotes.org/Training/LT_Combined_Scor...

What would this look like if one acted on this?

              Close     Close     ROI     ROI   Cum ROI  Cum ROI
   Date        NDX       RUT      NDX     RUT                   
1/1/2007    $1,756.90  $787.66                                  
7/23/2007   $2,036.33  $835.62  15.90%   6.09%   15.90%    6.09%
3/2/2009    $1,076.67  $367.80  47.13%  55.98%   70.53%   65.48%
12/31/2009  $1,860.31  $625.39  72.78%  70.04%  194.64%  181.38%

My point is simple: It pays to study the markets because although they do not repeat, they often rhyme. There is truly nothing new under the sun. Historical precedent has a lot to say that can be helpful in avoiding major market drawdowns.

The more I think about it, the more I think I'm pretty happy with downside deviation as the key metric to watch.

Your astute and elaborate method is greatly appreciated, as is your thorough explanation.

For me it's much simpler. I've been doing MI for about 25 years and I have the battle scars to show for it. In hindsight, none of the drawdowns, bear markets, or whatever, matter. They are all forgotten squiggles in the past. In my mind drawdowns are not risks if they don't lead to permanent loss. If I had to do it all over again, there would be two simple choices, the method I've used and evolved over time, or setting it all in SPY and forgetting it (or some other index ETF, your mileage may vary). And the only measure of success is whether I'm richer today with one method or the other. Market timing has turned out to be a frustrating and distracting effort. There were two or three notable market downturns during the period. I tried to time two of them, in 2008-2009 and in 2020. Both times I got out of the market with reasonable timing, and ended up getting back in way-way too late. Overall, those were badly losing experiences. The bottom line for me is, do I have a better than 50-50 expectation that I can beat SPY by using MI screens? As long as I think I do, and have fun doing it, I'll keep doing it. Nothing else matters.

Elan

Using that RMS formula for downside deviation, I (think I've) come up with a downside deviation metric of 1.86 and a 12 year CAGR of 7.2% on my equity class-only allocated investments (GTAA, excluding cash and fixed-income categories.)

I calculated rolling 12 month deficits to 10% MAR (or 0 if >10% as stated), by month, squared those negative numbers, summed the squares, and sqrt'd the sum. 1.86. Seems... great result? Or did I miss something.

I did not (yet) do the DDD3 version which I understand from memory does a quarterly version, and a monthly version, triple-weights the monthly version. Correct?

FC

As long as I think I do, and have fun doing it, I'll keep doing it.

I think the fun part often is underrated. A friend's 90+ year old father has huge health problem and since years is close to dying, which could happen any second. The only fun left in his life is sitting for hours on his computer, watching and trading stocks, which keeps his highly intelligent and agile mind busy.

Similar for me when during Covid and (same time) a dramatic car accident for months I also couldn't do much. Trading kept me entertained when reading books became too boring.

For me it's much simpler. I've been doing MI for about 25 years and I have the battle scars to show for it. In hindsight, none of the drawdowns, bear markets, or whatever, matter. They are all forgotten squiggles in the past. In my mind drawdowns are not risks if they don't lead to permanent loss. If I had to do it all over again, there would be two simple choices, the method I've used and evolved over time, or setting it all in SPY and forgetting it (or some other index ETF, your mileage may vary). And the only measure of success is whether I'm richer today with one method or the other. Market timing has turned out to be a frustrating and distracting effort. There were two or three notable market downturns during the period. I tried to time two of them, in 2008-2009 and in 2020. Both times I got out of the market with reasonable timing, and ended up getting back in way-way too late. Overall, those were badly losing experiences. The bottom line for me is, do I have a better than 50-50 expectation that I can beat SPY by using MI screens? As long as I think I do, and have fun doing it, I'll keep doing it. Nothing else matters.


In fact I was going to cite your own results (in particular 6/3 work) as an example of a portfolio which has enough history under its belt that there is a clear conclusion: it works. (or to be more conservative, it worked).

My whole reason for the thread was to muse on how rapidly one can approach a reasonable level of confidence with a much shorter amount of history...what can you tease out of the numbers to date to get the highest level of certainty of your evaluation of whether it is "working"? As you come up on 25 years of experience, that is no longer a concern: as you note, at some point CAGR tells you everything you need to know, and other metrics are either useless or worse than useless.

I say "worse than useless" because a lot of people go to a lot of trouble to get a smooth ride, and hurt themselves thereby. As the old saying goes, a lot more money has been lost trying to avoid bear market losses than has ever been lost in bear markets. After all, a smooth ride won't get you any higher standard of living the day you retire: only the portfolio balance matters. There is no point at all in seeking a low-volatility, low-drawdown, or low-stress portfolio **EXCEPT** the barest minimum of those features that will allow you with your real-world foibles to stick with the strategy which will ultimately in real life get you the highest CAGR with the highest confidence. There is nothing wrong with a smooth ride per se, but one should not pick a strategy with a lower likely return in order to get it. Unless you absolutely know in your heart of hearts that the higher return/certainty portfolio choice is not one you will be able to stick with, solely because of its squiggly nature.

I'm convinced that the reason that so many funds exist (there are way more equity funds than stocks in the world, which makes no sense) is because those buying the funds don't see that they own stocks that are crashing all the time...the fund result, being an average, hides the real and large squiggles that the investor's money is experiencing. So one might argue that the biggest benefit of index investing is that it's easier to stick with it than buying individual stocks because it looks nicer, even though the purchase of a broad slate of individual stocks is almost certain to have a higher long run return than a typical cap weight index fund.

Jim

Using that RMS formula for downside deviation, I (think I've) come up with a downside deviation metric of 1.86 and a 12 year CAGR of 7.2% on my equity class-only allocated investments (GTAA, excluding cash and fixed-income categories.)

I calculated rolling 12 month deficits to 10% MAR (or 0 if >10% as stated), by month, squared those negative numbers, summed the squares, and sqrt'd the sum. 1.86. Seems... great result? Or did I miss something.

I did not (yet) do the DDD3 version which I understand from memory does a quarterly version, and a monthly version, triple-weights the monthly version. Correct?

1.86% does seem implausibly low. If it were a hedge fund, people would flock to your door.

Again, the steps, phrased a bit differently in case that helps--
Calculate all rolling year returns. (daily or monthly, makes surprisingly little difference)
Subtract 10% from all of the figures.
Replace all positive numbers with zeros, but keep them in the list.
Square all the numbers.
Sum the squares.
Take the square root of the sum.

My own new revised version, inflation adjusted:
Calculate the inflation-adjusted value of the portfolio at each date.
Calculate all rolling year after-inflation returns. (daily or monthly, makes surprisingly little difference)
Subtract 8% from all of the figures.
Replace all positive numbers with zeros, but keep them in the list.
Square all the numbers.
Sum the squares.
Take the square root of the sum.

The result should be very similar, except in times of high inflation lately.

Jim

do I have a better than 50-50 expectation that I can beat SPY by using MI screens? As long as I think I do, and have fun doing it, I'll keep doing it. Nothing else matters.

and

a smooth ride won't get you any higher standard of living the day you retire: only the portfolio balance matters. ... stick with the strategy which will ultimately in real life get you the highest CAGR

I believe that Elan is retired. I am retired. (I think we both retired much younger than the typical 65.) Jim, if not already functionally retired, could retire at whim.

Once retired, the main thing is having a portfolio large enough to easily tolerate Bengan's 4% (now revised to 4.5% - 5%) SWR withdrawals.

If it is large enough that your withdrawals get down to below 4%, you are golden. At that point, your focus can shift to HAVING FUN. The smoothness or bumpiness of the ride does not matter.

A FI asked me why we were nearly 100% stocks and literally 0.0% bonds when our portfolio had already "won the game". You know, “When you've won the game, stop playing.” We said back, "No, now we are running up the score. No reason to quit."
Quit would be boring. Running--or attempted running--up the score is fun!

Jim wrote: I say "worse than useless" because a lot of people go to a lot of trouble to get a smooth ride, and hurt themselves thereby. As the old saying goes, a lot more money has been lost trying to avoid bear market losses than has ever been lost in bear markets. After all, a smooth ride won't get you any higher standard of living the day you retire: only the portfolio balance matters. There is no point at all in seeking a low-volatility, low-drawdown, or low-stress portfolio **EXCEPT** the barest minimum of those features that will allow you with your real-world foibles to stick with the strategy which will ultimately in real life get you the highest CAGR with the highest confidence.

This chart illustrates well the typical individual investor who attempts what Jim describes.

https://www.zeelotes.org/Training/Individual_Inves...

All financial advisors strongly advocate for being invested 100% of the time. Hmmmm.... I wonder why?

Jim, if not already functionally retired, could retire at whim.

As it happens, I retired from day jobs in late '99. My only activity with the goal of earnings since then was the "hobby" of a small investment management firm. Running a small hedge fund for 6 years, and managing the portfolio of a public company for a fee.

Jim

All financial advisors strongly advocate for being invested 100% of the time. Hmmmm.... I wonder why?

Well, it could be a number of reasons, and they could even have a point in some situations, but never ask the barber if you need a haircut. "Broker economics" at work: it's always time to buy!

I don't really try to dodge bear markets as such. I used to, but that was mainly because my portfolio used to be more aggressive. Now I mostly just try to keep a handle on the valuation level of the assets I own. When they seem richly priced, I sell a little: the upside is lower and the downside is bigger, so a smaller position allocation makes sense. Sometimes I write a few calls, turning a long position into a covered call. This lightening is rarely near a market top, but that's OK, there's nothing wrong with having some dry powder for a rainy day.

When something I like gets cheap, I go shopping. Sometimes this is during a bear market, sometimes not. Sometimes my purchases even work out!

Jim



From an article by Mr Smithers in the FT in 2006 about stockbroker economics:
"The FT reports regularly on the views of economists and stockbrokers. Readers might be intrigued by the conflicts between them but they should not be surprised. The purposes of the two groups are completely different. Economists are in pursuit of the truth and stockbrokers of commissions.
"The first principle of stockbroker economics is that all news is good. In a weak economy, interest rates tend to fall and in a strong one profits usually rise. It has therefore become an item of stockbroker faith that falling interest rates and rising profits are both good for stock markets. Neither theory, however, seems robust under testing. For example, the US stock market has moved in the same direction as profits only 54 per cent of the time. As both shares and profits have a long-term tendency to rise, this suggests a purely random relationship.
"The second principle is that the stock market is always cheap. This requires more flexibility than the first principle and is achieved by inventing meaningless measures of value, such as the bond yield ratio, and using whichever one of these absurdities happens to give the most bullish answer at the time..." [and so on]

Probably requires a subscription
https://www.ft.com/content/9a3965a0-7c8c-11da-936a...

Jim wrote: I don't really try to dodge bear markets as such.

Just to be clear, I don't either. I try to capitalize on them. Dodging them by definition means going 100% to cash.

Let me illustrate from an article I write to start every year. This was released on 1/1/2022. It concerns the historical cases when inflation has reached six percent.

6.00%   Date        Date        S&P 500    S&P 500             S&P 500     S&P 500
Months  Begins      Ends        Max Price  Min Price  % Drop   Peak Date   Trough Date
4       4/30/1902   8/30/1902   $8.85      $6.26      -29.27%  9/30/1902   10/31/1903
6       10/31/1902  4/30/1903   $8.85      $6.26      -29.27%  9/30/1902   10/31/1903
1       2/28/1907   3/31/1907   $10.03     $7.45      -25.72%  9/30/1906   9/30/1907
6       5/31/1907   11/30/1907  $9.93      $6.25      -37.06%  11/30/1906  11/30/1907
14      4/30/1909   6/30/1910   $10.23     $8.64      -15.54%  10/31/1909  7/31/1910
12      4/30/1912   4/15/1913   $9.86      $8.12      -17.65%  9/30/1912   6/30/1913
2       4/15/1916   6/15/1916   $10.21     $6.80      -33.40%  11/30/1916  12/31/1917
55      7/15/1916   1/15/1921   $10.21     $6.27      -38.58%  11/30/1916  6/22/1921
24      9/15/1941   9/15/1943   $10.47     $7.47      -28.65%  7/28/1941   4/28/1942
28      8/15/1946   12/15/1948  $19.25     $13.55     -29.61%  5/29/1946   6/13/1949
12      2/15/1951   2/15/1952   $22.81     $20.96     -8.11%   5/3/1951    6/29/1951
3       1/15/1970   4/15/1970   $99.23     $68.61     -30.86%  11/10/1969  5/26/1970
3       5/15/1970   8/15/1970   $97.36     $68.61     -29.53%  11/17/1969  5/26/1970
34      9/15/1973   7/15/1976   $115.47    $60.96     -47.21%  3/15/1973   10/4/1974
66      4/15/1977   9/15/1982   $107.97    $86.45     -19.93%  1/3/1977    3/1/1978
4       10/15/1990  2/15/1991   $369.78    $294.51    -20.36%  7/16/1990   10/11/1990
14      11/10/2021  12/31/2022  $4,818.62  $3,491.58  -27.54%  1/4/2022    10/13/2022
17      Average     1900-2020                         -27.55%              

The average drop from 1900 to 2020 has been -27.55% in the S&P 500. The drop from the high in November of 2021 to the low in 2022 was -27.55%. It is pretty rare for a repeat to occur at this level of closeness, but it does happen. It makes no sense to me to know this information and then ignore it! Why do that?

historical cases when inflation has reached six percent

Zeelotes, what are you using for this inflation figure?

Tails

Now I mostly just try to keep a handle on the valuation level of the assets I own. When they seem richly priced, I sell a little.......... Sometimes I write a few calls........ When something I like gets cheap, I go shopping.

Don't pretend to be so "harmless". I've heard rumors you sometimes buy or sell an option, isn't it? Just one of course :-)

Tails asked: Zeelotes, what are you using for this inflation figure?

Consumer Price Index for All Urban Consumers: All Items in U.S. City Average

https://fred.stlouisfed.org//data/CPIAUCNS.txt

Consumer Price Index for All Urban Consumers: All Items in U.S. City Average

Zee

Are you looking at the 1 year change or some shorter period converted to an annual rate?

Aussi

Aussi asked: Are you looking at the 1 year change or some shorter period converted to an annual rate?

I've put the data and the calculations on my bog under downloads - timing indicators.

Zee

Since there is certainly not much interest in such things - like avoiding bear markets - as in the past, let me wrap up my comments with a study based on following the inflation warning I mentioned today. Here are all the MI Valueline screens returns over this time period.

MI Screen             CAGR     GSD     Sharpe  DDD3    BBW    % Winning  Drawdown
Net-Nets_Grahamified  -72.93%  141.07  -1.06   63.34%  -1.27  36%        -72.10%
Dilution_s            -69.54%  64.65   -2.26   59.36%  -1.29  36%        -67.32%
The_Mirror_s          -62.38%  81.24   -1.46   52.96%  -1.29  50%        -64.32%
Steady_Growth         -57.95%  93.3    -1.25   51.28%  -1.25  29%        -62.75%
Up_5%                 -54.30%  71.83   -1.27   46.85%  -1.26  29%        -60.61%
BETA                  -55.51%  61.05   -1.55   47.33%  -1.28  21%        -52.92%
PLOWBKLD              -49.89%  37.07   -2.2    42.33%  -1.3   43%        -52.24%
78RPM                 -43.95%  51.77   -1.26   37.95%  -1.27  21%        -51.33%
Microcap_Momentum     -49.46%  45.49   -1.67   41.28%  -1.3   36%        -49.50%
Quality_Earnings      -47.26%  40.88   -1.84   41.00%  -1.28  14%        -49.13%
RS13WK                -46.13%  37.51   -1.92   38.92%  -1.3   29%        -44.50%
EG5_AT                -41.12%  37.14   -1.64   35.13%  -1.29  36%        -42.67%
RS1WK                 -43.40%  45.04   -1.45   36.76%  -1.28  43%        -42.12%
Melange               -39.81%  41.16   -1.46   34.86%  -1.26  21%        -41.45%
PIH4                  -38.75%  43.86   -1.29   33.72%  -1.27  43%        -41.17%
RSWEPS                -35.04%  53.46   -0.87   30.70%  -1.24  50%        -40.82%
TTI                   -33.32%  39.02   -1.14   29.98%  -1.21  29%        -40.77%
RSEP                  -40.43%  34.15   -1.73   34.92%  -1.27  29%        -40.56%
PLOW_PE2              -37.90%  34.74   -1.6    33.00%  -1.25  50%        -40.46%
RS13WKT12             -41.48%  45.95   -1.3    35.63%  -1.27  36%        -40.44%
RS4WK                 -39.97%  41.21   -1.42   34.65%  -1.27  29%        -39.95%
Advanced              -39.34%  37.36   -1.57   33.26%  -1.3   29%        -39.84%
GAR4                  -39.66%  42.32   -1.35   34.02%  -1.29  29%        -39.57%
ERS26                 -39.09%  34.5    -1.63   34.11%  -1.27  21%        -39.49%
CANSLIM-26            -35.38%  41.75   -1.16   30.94%  -1.26  21%        -39.40%
OVER_RS               -40.16%  32.79   -1.78   34.31%  -1.28  29%        -39.30%
RS2020                -38.49%  39.95   -1.44   33.30%  -1.27  43%        -39.15%
SOS_A                 -37.91%  38.67   -1.48   32.39%  -1.27  36%        -38.99%
Turnarounds           -35.02%  37.5    -1.36   30.88%  -1.25  21%        -38.98%
ERS13                 -38.93%  31.19   -1.86   33.38%  -1.28  36%        -38.77%
SOSBM_E               -26.43%  52.02   -0.68   23.98%  -1.16  43%        -38.65%
POI                   -19.59%  50.5    -0.45   20.29%  -1.07  50%        -38.59%
Overlap_4/13          -38.41%  34.31   -1.61   33.06%  -1.28  14%        -38.52%
SPARK                 -32.54%  40.91   -1.16   28.60%  -1.25  50%        -38.38%
POG                   -20.02%  46.72   -0.54   20.24%  -1.08  50%        -38.37%
TPEG13                -33.37%  41.51   -1.11   29.82%  -1.22  29%        -38.34%
GAR4CFS               -38.93%  39.11   -1.46   33.34%  -1.29  29%        -37.90%
RS4WKT12              -35.72%  42.85   -1.21   31.06%  -1.27  43%        -37.69%
LPS1+2_RSW            -35.73%  29.79   -1.7    30.88%  -1.27  43%        -37.66%
CAPRS                 -29.68%  39.05   -1.04   27.00%  -1.2   36%        -36.85%
SPARKRSW              -30.61%  46.53   -0.88   27.43%  -1.23  36%        -36.69%
TK1_R52               -27.16%  43      -0.79   24.94%  -1.19  36%        -36.69%
PLOW_PE2MOD           -32.39%  40.57   -1.13   28.95%  -1.21  29%        -36.67%
SOS_D                 -34.54%  44.29   -1.11   30.12%  -1.24  43%        -36.30%
RSW                   -36.17%  34.58   -1.49   31.28%  -1.27  29%        -36.25%
PST_5/10              -29.15%  44.74   -0.88   26.18%  -1.21  43%        -36.15%
SOS_F                 -35.38%  37.47   -1.38   30.33%  -1.27  43%        -36.02%
SOS_Annual            -25.62%  38.5    -0.89   23.59%  -1.16  43%        -35.93%
Shrinkage             -33.59%  33.44   -1.43   29.12%  -1.26  43%        -35.74%
IN_RS26               -33.46%  33.14   -1.41   29.40%  -1.25  36%        -35.68%
LLTD                  -30.70%  37.78   -1.14   26.95%  -1.25  21%        -35.55%
Bob                   -28.43%  43.17   -0.81   25.29%  -1.23  36%        -35.43%
LOWPE_ZLTDA           -34.85%  42.09   -1.15   30.07%  -1.28  29%        -35.18%
FOG_BDF               -21.00%  46.27   -0.6    20.49%  -1.12  57%        -35.05%
KEY100                -26.24%  31.08   -1.16   24.14%  -1.19  36%        -35.01%
Value_EG              -28.62%  41      -0.97   25.90%  -1.21  50%        -34.95%
Screamers             -22.75%  37.78   -0.78   22.10%  -1.13  43%        -34.77%
REIT                  -32.85%  32.48   -1.42   28.66%  -1.24  36%        -34.61%
SOS_Plow_RS           -35.56%  32.74   -1.54   30.43%  -1.27  29%        -34.51%
PIH_Naked             -26.78%  50.2    -0.64   24.58%  -1.19  21%        -34.43%
PEG-NT                -18.32%  49.08   -0.42   18.78%  -1.06  43%        -34.33%
HIGH_CASH             -26.48%  36.66   -0.97   24.63%  -1.18  36%        -34.11%
TA_A                  -30.54%  34.32   -1.27   26.97%  -1.24  43%        -34.10%
RSPEG1                -32.31%  31.18   -1.4    28.57%  -1.24  29%        -34.01%
ROEPLOW               -33.49%  33.32   -1.55   29.32%  -1.24  43%        -33.91%
LPSAD                 -21.05%  30.06   -0.96   20.09%  -1.15  50%        -33.74%
BLITZ                 -31.35%  27.22   -1.59   27.33%  -1.25  21%        -33.73%
PL_LD_NRS             -32.06%  29.43   -1.51   28.11%  -1.26  14%        -33.43%
TREPPE_E              -28.71%  31.76   -1.24   25.54%  -1.22  36%        -33.18%
RSCAP                 -22.93%  39.45   -0.74   21.83%  -1.15  50%        -33.04%
ZLTD                  -31.94%  37.56   -1.16   27.78%  -1.27  21%        -32.78%
SOS_BMOD              -31.77%  41.14   -1.08   27.76%  -1.23  36%        -32.77%
PEG13                 -33.07%  43.03   -1.02   28.84%  -1.23  50%        -32.67%
GARPEG                -30.17%  41      -0.99   26.69%  -1.21  50%        -32.57%
SOS_Ancer             -27.92%  37.96   -1      25.04%  -1.21  50%        -32.49%
SOS_Elan_v2001        -26.53%  40.99   -0.9    24.06%  -1.19  36%        -32.33%
TREPPE                -25.24%  35.38   -0.93   23.01%  -1.19  43%        -32.19%
LPE_YLD               -28.06%  33.1    -1.16   25.49%  -1.22  29%        -32.15%
PEG-Minimalist        -11.28%  35.79   -0.36   13.81%  -0.88  43%        -32.09%
RS26WKT12             -20.14%  46.29   -0.54   19.77%  -1.07  43%        -31.92%
SOS_B                 -28.19%  42.24   -0.92   25.12%  -1.2   50%        -31.80%
AssRS13               -31.95%  32.73   -1.37   28.17%  -1.24  29%        -31.74%
P/SLove_You        -11.94%  33.49   -0.43   13.76%  -0.92  43%        -31.71%
Incoming_Cash         -24.50%  34.75   -1.09   22.81%  -1.19  29%        -31.66%
HIGHCASHFLOW          -28.54%  27.79   -1.44   25.23%  -1.25  36%        -31.42%
RS52WKT12             -17.25%  49.25   -0.44   17.48%  -1.05  50%        -31.41%
RSPS                  -28.50%  36.52   -1.06   25.42%  -1.22  50%        -31.20%
SOS_Elan_v2002        -23.99%  42.47   -0.76   22.22%  -1.14  50%        -30.99%
OVER_PEG              -24.80%  44.23   -0.76   22.76%  -1.17  57%        -30.96%
SOS_E                 -21.55%  37.36   -0.77   20.24%  -1.14  43%        -30.82%
RS26WK                -28.80%  38.61   -0.98   25.55%  -1.22  43%        -30.67%
CAPLOWEG              -22.09%  31.37   -0.94   20.93%  -1.16  43%        -30.46%
HI_INC_CSH            -25.79%  36.1    -1.04   23.50%  -1.21  43%        -30.15%
GAR_EG5               -26.35%  29.27   -1.21   23.67%  -1.21  29%        -30.10%
SOS_C                 -24.52%  43.05   -0.76   22.41%  -1.18  50%        -30.06%
ROC_RS26WK            -27.85%  25.13   -1.51   24.81%  -1.23  36%        -30.01%
S&P_Peg               63.09%   59.81   1.11    1.08%   28.53  64%        -29.88%
EG5PE                 -23.02%  36.12   -0.85   21.21%  -1.17  29%        -29.72%
LOWPE                 18.08%   59.61   0.41    1.70%   8.73   64%        -29.66%
RS52WK                -26.00%  37.66   -0.92   23.56%  -1.21  43%        -29.29%
OPTION_A              -19.79%  39.58   -0.65   18.79%  -1.13  50%        -29.28%
PEGRSW                -20.42%  44.72   -0.61   19.37%  -1.13  50%        -29.21%
FCF-26                -19.23%  33.66   -0.8    19.01%  -1.12  50%        -29.16%
PLOWRSW               -25.92%  27.5    -1.3    23.26%  -1.21  43%        -29.03%
GS_Mungo              -23.41%  24.67   -1.28   21.78%  -1.19  29%        -28.47%
GS_Mungo_Voom         -23.41%  24.67   -1.28   21.78%  -1.19  29%        -28.47%
EGPLOW_PE             -23.87%  29.74   -1.05   21.81%  -1.19  36%        -28.41%
LowPEsafe             0.75%    54.99   0.04    4.87%   0.16   71%        -28.29%
REV                   -21.85%  37.15   -0.77   20.26%  -1.15  21%        -28.28%
EGPLOW_PE_E           -25.41%  29.51   -1.14   22.90%  -1.2   36%        -28.23%
REP                   -22.79%  32.67   -0.89   21.05%  -1.17  36%        -28.22%
RSPEGOL               -26.31%  35.41   -0.97   23.48%  -1.21  43%        -28.11%
Small_Value           -16.33%  33.61   -0.58   16.60%  -1.06  43%        -27.69%
LPSB                  -17.56%  26.75   -0.87   17.28%  -1.11  36%        -27.68%
H52EgPSlta            -20.70%  23.33   -1.14   19.36%  -1.17  36%        -27.65%
ROIC                  -22.33%  25.45   -1.19   20.54%  -1.19  50%        -27.57%
SLS_RS13              -26.16%  28.26   -1.27   23.11%  -1.22  36%        -27.56%
LPS1+2_R26            -22.27%  28.23   -1.05   20.40%  -1.19  36%        -27.49%
Olap_RS52keyeps       -25.69%  32.62   -1.05   23.17%  -1.21  36%        -27.42%
R13_EG_E              -19.03%  28.04   -1.02   18.39%  -1.11  36%        -27.39%
PLOWEG5_RS631         -24.09%  30.15   -1.09   22.19%  -1.19  43%        -27.32%
LowPS+                1.69%    45.8    0.15    3.88%   0.38   50%        -27.26%
PEG                   -12.97%  44.7    -0.33   14.25%  -0.94  57%        -27.02%
KEYEPS                -25.28%  26.72   -1.27   22.76%  -1.21  29%        -26.98%
KEYSTONE              -25.28%  26.72   -1.27   22.76%  -1.21  29%        -26.98%
EG5_PEG               -19.09%  37.56   -0.65   18.22%  -1.12  29%        -26.94%
FOG_MI                -26.62%  32.36   -1.1    23.41%  -1.22  36%        -26.94%
PEBsize               -19.38%  37.76   -0.66   18.55%  -1.12  36%        -26.93%
PLOW26WK              -22.32%  25.66   -1.17   20.46%  -1.18  29%        -26.93%
LOWPB                 -14.84%  29.32   -0.76   15.26%  -1.06  50%        -26.82%
Negative_FCF_s        -26.70%  29.03   -1.21   23.47%  -1.22  36%        -26.59%
SOS_G                 -17.11%  43.66   -0.49   17.08%  -1.06  50%        -26.58%
DIVIDEND_GROWTH       -25.82%  29.28   -1.21   22.90%  -1.23  29%        -26.52%
HIPRICE               -10.44%  35.27   -0.36   12.38%  -0.89  50%        -26.49%
R13_EG                -15.63%  29.44   -0.81   15.90%  -1.05  43%        -26.43%
HBSP                  -12.55%  28.99   -0.58   13.85%  -0.98  57%        -26.32%
RSPEG2                -23.28%  34.65   -0.86   21.28%  -1.17  43%        -26.32%
RSEG-rgonsal          -19.25%  28.81   -1.01   18.44%  -1.12  36%        -26.17%
KEYCLQ                -22.52%  26.48   -1.12   20.69%  -1.18  29%        -26.01%
KEYRSW                -23.05%  27.06   -1.14   21.17%  -1.18  36%        -26.00%
PEGFF                 -2.70%   44.99   -0.05   6.68%   -0.4   50%        -25.87%
EGRSW                 -16.90%  45.75   -0.47   16.86%  -1.07  50%        -25.75%
SOS_GJ                -20.60%  36.5    -0.74   19.32%  -1.14  36%        -25.68%
H52EgPS               -18.33%  23.01   -1.02   17.53%  -1.14  36%        -25.44%
R13_EG2               -14.98%  29.57   -0.75   15.38%  -1.04  43%        -25.39%
EG                    -7.71%   44.28   -0.18   10.38%  -0.73  57%        -25.25%
TK2_R52               -15.23%  33.72   -0.52   15.76%  -1.05  36%        -25.21%
SOS_Elan_v2000        -15.42%  38.27   -0.54   15.90%  -1.03  64%        -25.19%
SAFETY_HICCUP         -21.67%  24.11   -1.23   20.26%  -1.18  29%        -25.06%
Fundamentals          -0.40%   38.57   0.03    5.38%   -0.08  57%        -24.58%
PLOWBVS               -15.89%  29.14   -0.76   15.88%  -1.1   36%        -24.54%
PLOWPBV               -19.97%  27.92   -1.12   18.88%  -1.17  43%        -24.54%
SomeMoJoeSafe         -9.18%   25.09   -0.51   11.08%  -0.88  57%        -24.44%
SOS_KJ                -21.75%  37.47   -0.73   20.32%  -1.15  36%        -24.35%
LOWPSR                -22.54%  24.21   -1.3    20.27%  -1.2   50%        -24.30%
PLOW_PE               -15.95%  31.59   -0.69   16.10%  -1.08  36%        -24.28%
EG_PELA               -14.84%  37.12   -0.51   15.29%  -1.04  43%        -24.27%
Olap_RS52keystone     -22.32%  31.4    -0.93   20.53%  -1.18  36%        -24.23%
High_Relative_Value   -10.82%  18.88   -0.9    12.34%  -0.94  50%        -24.18%
GSX                   -18.95%  24.21   -1.08   17.67%  -1.16  36%        -23.99%
Value_at_the_Top      -14.05%  28.55   -0.61   14.87%  -1.04  57%        -23.84%
EGPR_PE               -14.97%  37.32   -0.5    15.28%  -1.04  29%        -23.83%
YEYPayout             6.72%    30.98   0.19    1.46%   3.75   64%        -23.70%
DALY                  11.88%   44.71   0.33    0.94%   7.95   57%        -23.65%
SomeMoSafe            -2.16%   26.15   -0.19   6.27%   -0.36  57%        -23.65%
PIH_CSO_safe          -18.26%  25.22   -0.95   17.76%  -1.13  36%        -23.64%
YldDiv                -9.32%   26.44   -0.5    11.44%  -0.88  50%        -23.58%
PIH_CSO_simple        -18.05%  25.28   -0.93   17.59%  -1.13  36%        -23.46%
PLOWLD_NRS            -10.97%  37.16   -0.35   12.66%  -0.92  43%        -23.45%
YLDEARNYEAR2          32.32%   40.03   0.79    0.88%   24.56  64%        -23.31%
3PT_Value_SmallCap    -17.33%  29.71   -0.75   16.61%  -1.11  43%        -23.23%
SOS_K                 -17.08%  37.17   -0.57   16.89%  -1.08  43%        -23.13%
SLS_RS26              -18.66%  24.2    -1.05   17.76%  -1.13  29%        -22.91%
JLC_DIV               26.50%   27.54   0.94    1.48%   15.1   71%        -22.88%
ARS                   -10.90%  29.19   -0.49   12.56%  -0.95  57%        -22.82%
Tvalue                -10.97%  37.27   -0.35   12.29%  -0.95  50%        -22.17%
PIH_MCP               -16.84%  24.79   -0.9    16.58%  -1.1   36%        -21.84%
YLDYEAR               24.14%   33.21   0.74    0.97%   18.21  71%        -21.65%
LPCF                  -4.73%   34.97   -0.23   8.01%   -0.6   50%        -21.48%
GSX2                  -14.85%  26.77   -0.7    14.76%  -1.07  50%        -21.37%
Fried_500             2.95%    22.94   0.05    2.64%   1.08   43%        -21.17%
NoMo                  -0.10%   27.74   -0.08   4.67%   -0.02  57%        -20.77%
CDPD                  -10.31%  27.59   -0.48   11.72%  -0.95  50%        -20.75%
NoMoSafe              -15.56%  28.23   -0.76   15.59%  -1.09  50%        -20.61%
YIELD4                -1.77%   26.14   -0.16   5.82%   -0.31  50%        -20.55%
SomeMo                -0.54%   27.69   -0.1    4.90%   -0.11  57%        -20.26%
H52EarnPS             -7.04%   24.89   -0.38   9.37%   -0.79  43%        -20.17%
SomeMoC               -1.78%   28.42   -0.14   5.75%   -0.32  57%        -20.17%
HI_DIV                16.99%   26.98   0.63    1.35%   11.7   64%        -20.01%
COREVALU              -14.78%  22.94   -0.89   14.74%  -1.08  36%        -20.00%
Up5X3                 -17.36%  20.62   -1.2    16.49%  -1.16  43%        -19.88%
RS-100                3.08%    36.02   0.17    1.99%   1.22   50%        -19.27%
HIYIELD               6.09%    19.66   0.13    1.26%   4.3    57%        -18.79%
LOWDV                 -8.60%   28.04   -0.41   10.49%  -0.88  50%        -18.27%
ValueRatio            19.08%   29.54   0.61    0.91%   15.08  71%        -18.13%
3pt_Relative_Value    -8.84%   22.42   -0.61   10.44%  -0.91  43%        -17.87%
YLDEARNYEAR           28.08%   30.48   0.85    0.74%   30.19  71%        -17.29%
BI                    -13.47%  23.82   -0.8    13.48%  -1.06  43%        -17.05%
3PT_SCV_pst_slta      -5.06%   23.51   -0.31   7.45%   -0.69  36%        -17.01%
3PT_SCV_pst           -4.10%   23.26   -0.25   6.68%   -0.61  36%        -16.68%
Gentle_Screamers      -9.26%   30.6    -0.38   10.56%  -0.91  36%        -16.61%
SAFETY_BOUNCE         1.97%    19.24   0       3.13%   0.61   64%        -15.62%
Silver_Parachute      -6.49%   24.77   -0.29   8.81%   -0.79  57%        -15.48%
AssRS26               -10.68%  23.27   -0.58   11.69%  -0.96  36%        -15.01%
OptiMan               13.45%   25.02   0.42    0.60%   14.85  64%        -14.91%

I'm a firm believer in quotes that Warren Buffet loves to proclaim to individual and professional investors alike:

Be fearful when others are greedy and greedy when others are fearful -- all of my research of the past twenty-five years is built on a conviction that this statement is true and applicable!

Rule No. 1 is never lose money. Rule No. 2 is never forget Rule No. 1! -- again, to think that avoiding a bear market is a waste of time flies in the face of this famous quote from Warren.

Here are all the MI Valueline screens returns over this time period.

Sorry ... am I correct that those are the screen returns during the beginning and ending periods you defined starting with 6% CPI values?

I don't think the desire to avoid a bear is dead; I certainly have that desire, having started investing soon before the great recession.
There was that, other 30% downturns, and lastly the period of underperformance starting in 2018 and capped by the pandemic.
In hindsight, all times that one would rather avoid.

During those bears, I was struck a couple times by how the absolute values of NH-NL got to be an extreme negative number.
Like, -700 or -1000 or something, don't recall. So one strategy for improving your strategy's returns would be:
- exit the market near a top (various indicators are said to be able to give a reasonable signal)
- enter back in during days of extreme negative breadth (rather like mungofitch's major bottom detectors)

Something like this would not guarantee that you picked either the top or the bottom. There may be multiple bad breadth days before a bottom is set.
And you never know if the bottoming process takes months or years. However, if you could do this in real life, it should improve your performance.

Mark

Thanks. If I could indulge just a little bit more QC... I've calculated all rolling year returns as the product of all the most recent rolling 12 monthly returns (1.005*.98*1.02*.991, etc). Since I don't feel like I've been more successful than any hedge fund out there (cough), perhaps that's not the right formula.

So I took a shot at calculating the annual returns by Ending / (Starting -12mo + net additions). An even more outlying result / lower deviation. Which probably means I have a bad outlier value in there.

But - am I handling the "returns under 10%" correctly? Squaring -.025 (1.075 - 1.10) = .000625. Very small numbers to sum and sqrt. But multiplying -.025 by 100, then squaring, turns it into 6.457, and summing & sqrting THOSE turns the deviation into 109%.

Math aficionado I'm not,
FC

Since there is certainly not much interest in such things - like avoiding bear markets - as in the past

Who should be interested in that when - looking at a 20+ year chart - we are essentially now since 15 years in abull market, interrupted just by a super-short blip in 2020 plus a bit more than half of 2022? People adapt and memories fade => "Even if there is a crash as 'always' it will be quickly undone".

P.S.: I wouldn't be surprised for the reckoning to be accordingly bad.

TG- Breadth - especially extremes - are the key. Percent of stocks above moving averages of 3 or 4 different, key, lengths, are telltale sentiment indicators. Bottoms - extreme low breadth combined with indexes below intermediate to long term moving averages - are shorter and easier to spot than tops. The emotional problem is it requires nerves of steel (robotics?) to put cash to work at those times.

FC

After all, a smooth ride won't get you any higher standard of living the day you retire: only the portfolio balance matters. There is no point at all in seeking a low-volatility, low-drawdown, or low-stress portfolio *

I would have to respectfully disagree in some cases. Let's say you were lucky enough to accumulate a lot of money. What matters then is return of capital, and low stress, not return on capital.

TG- Breadth - especially extremes - are the key. Percent of stocks above moving averages of 3 or 4 different, key, lengths, are telltale sentiment indicators. Bottoms - extreme low breadth combined with indexes below intermediate to long term moving averages - are shorter and easier to spot than tops. The emotional problem is it requires nerves of steel (robotics?) to put cash to work at those times.

Very useful information. When you say low breadth, do you mean low volume?

Bottoms - extreme low breadth combined with indexes below intermediate to long term moving averages - are shorter and easier to spot than tops.

I have no idea how to spot an exact top, but being interested in markets for 27 years, I noticed a pattern. When people who normally would have no interest in stocks, are all of a sudden very interested, we are in a bubble. Twice I have heard of every college student investing in internet stocks or crypto, and not long after, there was a crash.

Everybody buying gamestop is a perfect example of this.

After all, a smooth ride won't get you any higher standard of living the day you retire: only the portfolio balance matters. There is no point at all in seeking a low-volatility, low-drawdown, or low-stress portfolio

I would have to respectfully disagree in some cases.

There is an assumption that the high volatility/stress/drawdown portfolio leads to higher returns.
Even if that is true, one does not know that until the end.
Most of us humans feel the stress along the way if things are not going well.
That stress has a physiological cost, and also makes it more difficult to stick to a strategy.
So, I don't completely agree that only the endpoints matter, as the ride along the way cannot be dismissed lightly.

I guess there are those with iron stomachs for whom stress slides right off.
It would be nice to learn how they do that :)
(I'm pretty sure one way is to have enough assets that losing 50% of it doesn't affect anything).


Mark

FC

TG- Breadth - especially extremes - are the key. Percent of stocks above moving averages of 3 or 4 different, key, lengths, are telltale sentiment indicators.

Just to narrow down the search, I am guessing that would be a high percentage that is falling to indicate a top?? And a second guess would be prices falling rather than averages rising to show a falling percentage?

Aussi

Regarding breadth, here is an old spreadsheet I had from 2010 - haven't opened it since then.
It has Nasdaq NH, NL, NH-NL, and the 9-day weighted moving average of NH-NL from 2005-2010.
I don't recall if these data came out of GTR1 or somewhere else.

This goes through the great recession period. I recall watching those terrible market days.
Many blood in the street days with NH-NL less than -1200 or so.
When the 9DWMA gets down to -750 or lower those could potentially be entry days.
Or individual days with an even lower threshold.

Note that the days with the lowest NH-NL were 5 months or so before the bottom in March 2009.
If you actually acted on these worst days, there would still be a bit more downside.
But the goal would not be to find the bottom; just to get back in when everyone else is getting out.

Of course one could easily pull this information from GTR1 and look at it over different time periods.
NHNLRatio in GTR1 gets painfully close to zero during these days.

  Date    NH    NL   NH-NL  NH-NL 9DWMA
20051027  30   110    -80
20051028  45    88    -43
20051031  86    37     49
20051101  86    59     27
20051102  129   52     77
20051103  158   49    109
20051104  80    46     34
20051107  116   42     74
20051108  65    47     18       47
20051109  92    57     35       48
20051110  119   56     63       52
20051111  155   46    109       63
20051114  108   44     64       64
20051115  57    67    -10       49
20051116  62    86    -24       33
20051117  114   64     50       35
20051118  159   59    100       47
20051121  189   45    144       67
20051122  175   38    137       82
20051123  154   30    124       93
20051124  166   34    132       104
20051125  77    13     64       101
20051128  79    37     42       93
20051129  75    45     30       82
20051130  107   42     65       77
20051201  187   39    148       88
20051202  182   38    144       97
20051205  132   28    104       98
20051206  170   34    136       106
20051207  101   40     61       99
20051208  79    32     47       91
20051209  102   19     83       90
20051212  128   25    103       93
20051213  92    35     57       84
20051214  94    31     63       77
20051215  75    42     33       66
20051216  84    49     35       58
20051219  61    56     5        45
20051220  51    76    -25       29
20051221  67    42     25       25
20051222  100   42     58       29
20051223  94    29     65       34
20051226  117   36     81       43
20051227  92    46     46       45
20051228  58    43     15       40
20051229  65    53     12       36
20051230  56    53     3        30
20060102  75    77     -2       24
20060103  104   38     66       30
20060104  144   22    122       47
20060105  164   28    136       65
20060106  190   17    173       89
20060109  238   21    217       120
20060110  157   19    138       131
20060111  198   20    178       147
20060112  178   19    159       156
20060113  99    16     83       146
20060116  128   23    105       139
20060117  120   24     96       129
20060118  116   36     80       117
20060119  213   25    188       127
20060120  172   35    137       127
20060123  123   39     84       118
20060124  189   34    155       124
20060125  200   34    166       133
20060126  246   29    217       152
20060127  306   24    282       181
20060130  235   23    212       192
20060131  213   27    186       196
20060201  233   27    206       201
20060202  184   35    149       194
20060203  120   37     83       174
20060206  142   30    112       159
20060207  100   37     63       136
20060208  120   32     88       120
20060209  159   30    129       115
20060210  66    35     31       94
20060213  73    31     42       79
20060214  89    20     69       73
20060215  132   27    105       77
20060216  189   20    169       95
20060217  186   16    170       111
20060220  186   16    170       126
20060221  144   25    119       128
20060222  151   26    125       131
20060223  150   18    132       135
20060224  142   25    117       134
20060227  236   22    214       150
20060228  131   41     90       139
20060301  180   37    143       139
20060302  166   35    131       136
20060303  175   33    142       137
20060306  120   41     79       126
20060307  85    58     27       105
20060308  77    63     14       84
20060309  62    35     27       68
20060310  86    46     40       57
20060313  106   33     73       56
20060314  137   32    105       62
20060315  192   46    146       77
20060316  234   53    181       99
20060317  152   36    116       107
20060320  175   33    142       119
20060321  178   45    133       127
20060322  111   38     73       120
20060323  118   25     93       116
20060324  256   36    220       137
20060327  181   15    166       143
20060328  205   32    173       149
20060329  340   45    295       179
20060330  226   27    199       188
20060331  377   47    330       221
20060403  216   26    190       221
20060404  143   32    111       205
20060405  190   32    158       197
20060406  185   31    154       187
20060407  160   42    118       171
20060410  94    37     57       144
20060411  53    53     0        108
20060412  56    56     0        79
20060413  73    38     35       61
20060414  72    38     34       50
20060417  96    42     54       46
20060418  177   38    139       60
20060419  288   33    255       98
20060420  199   28    171       117
20060421  199   34    165       133
20060424  147   45    102       134
20060425  135   43     92       132
20060426  155   37    118       132
20060427  123   40     83       123
20060428  149   42    107       119
20060501  133   43     90       109
20060502  152   57     95       102
20060503  179   52    127       105
20060504  207   27    180       119
20060505  251   27    224       142
20060508  189   28    161       149
20060509  169   34    135       150
20060510  146   54     92       141
20060511  116   87     29       120
20060512  66   118    -52       85
20060515  62   142    -80       47
20060516  72   114    -42       20
20060517  58   152    -94       -13
20060518  57   139    -82       -38
20060519  42   115    -73       -54
20060522  37   155   -118       -74
20060523  37    84    -47       -74
20060524  35   130    -95       -80
20060525  43    50     -7       -67
20060526  67    40     27       -47
20060529  86    43     43       -27
20060530  41    65    -24       -22
20060531  54    60     -6       -14
20060601  91    40     51        2
20060602  111   40     71       21
20060605  75    64     11       22
20060606  38   110    -72        7
20060607  53    73    -20        0
20060608  45   148   -103       -22
20060609  48    89    -41       -29
20060612  37   151   -114       -49
20060613  31   261   -230       -90
20060614  20   221   -201       -120
20060615  41    53    -12       -107
20060616  37    63    -26       -95
20060619  36   121    -85       -94
20060620  24   135   -111       -97
20060621  38   103    -65       -90
20060622  41    97    -56       -81
20060623  31    92    -61       -74
20060626  47    74    -27       -60
20060627  37   130    -93       -65
20060628  35   140   -105       -74
20060629  89    72     17       -56
20060630  118   48     70       -29
20060703  74    28     46       -10
20060704  91    38     53        6
20060705  47    46     1        10
20060706  59    51     8        14
20060707  38    86    -48        5
20060710  33    93    -60       -6
20060711  36    81    -45       -15
20060712  32    88    -56       -27
20060713  27   176   -149       -56
20060714  23   187   -164       -83
20060717  24   199   -175       -108
20060718  20   188   -168       -126
20060719  47    87    -40       -115
20060720  34   105    -71       -109
20060721  23   231   -208       -130
20060724  45    92    -47       -116
20060725  69   100    -31       -98
20060726  46    95    -49       -84
20060727  55   113    -58       -75
20060728  66    74     -8       -58
20060731  69    68     1        -42
20060801  58   120    -62       -43
20060802  66    66     0        -32
20060803  81    97    -16       -24
20060804  66    60     6        -17
20060807  38    89    -51       -23
20060808  44   131    -87       -35
20060809  29   144   -115       -52
20060810  32   171   -139       -72
20060811  24   113    -89       -80
20060814  48   137    -89       -85
20060815  56    78    -22       -77
20060816  70    53     17       -60
20060817  88    52     36       -40
20060818  65    48     17       -25
20060821  43    47     -4       -15
20060822  54    57     -3       -7
20060823  40    56    -16       -4
20060824  44    66    -22       -5
20060825  38    41     -3       -4
20060828  57    38     19        0
20060829  78    41     37        7
20060830  88    23     65       18
20060831  83    25     58       28
20060901  71    20     51       35
20060904  96    28     68       45
20060905  94    26     68       53
20060906  43    29     14       48
20060907  40    49     -9       38
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20081124   3   265   -262       -744
20081125   6   180   -174       -642
20081126   6   129   -123       -538
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20081128   8    53    -45       -346
20081201   5   147   -142       -271
20081202   4   133   -129       -204
20081203   6   108   -102       -146
20081204   3   134   -131       -121
20081205   2   183   -181       -130
20081208   8    90    -82       -121
20081209   6    94    -88       -115
20081210   2    91    -89       -110
20081211   4    87    -83       -104
20081212   2   118   -116       -105
20081215   2    71    -69       -96
20081216   3    99    -96       -95
20081217  12    74    -62       -86
20081218  10    78    -68       -81
20081219  10   114   -104       -85
20081222   5   127   -122       -92
20081223  13   119   -106       -95
20081224   5    84    -79       -93
20081225   5    84    -79       -90
20081226   4    86    -82       -89
20081229   5   134   -129       -97
20081230  14   165   -151       -109
20081231  23    88    -65       -101
20090101  23    88    -65       -94
20090102  16    30    -14       -77
20090105  16    20     -4       -61
20090106  13    16     -3       -47
20090107   7    27    -20       -38
20090108  15    25    -10       -28
20090109  16    32    -16       -21
20090112   4    43    -39       -21
20090113   3    52    -49       -25
20090114   2    80    -78       -36
20090115   6   119   -113       -54
20090116   7    76    -69       -60
20090119   7    76    -69       -65
20090120   9   171   -162       -87
20090121   4   167   -163       -106
20090122   7   133   -126       -115
20090123   5   169   -164       -128
20090126   9   112   -103       -127
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20090203  12   122   -110       -110
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20090330   6    43    -37       -19
20090331  11    23    -12       -18
20090401  11    31    -20       -18
20090402  27    21     6        -13
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20090406  15    16     -1       -10
20090407   6    26    -20       -12
20090408   6    21    -15       -12
20090409  24    16     8        -8
20090410  24    16     8        -4
20090413  23    20     3        -2
20090414  12    19     -7       -2
20090415  10    25    -15       -5
20090416  26    21     5        -3
20090417  25    13     12        0
20090420   3    23    -20       -3
20090421   9    24    -15       -6
20090422  21    23     -2       -6
20090423  14    16     -2       -5
20090424  13    19     -6       -6
20090427  21    18     3        -4
20090428  18    22     -4       -4
20090429  31    22     9        -1
20090430  30    21     9         1
20090501  14    20     -6        1
20090504  33    17     16        4
20090505  27    16     11        6
20090506  31    21     10        7
20090507  26    16     10        8
20090508  29    17     12        9
20090511  29    16     13       10
20090512  25    16     9        10
20090513  10    22    -12        6
20090514  11    18     -7        3
20090515  10    18     -8        0
20090518  31    16     15        3
20090519  35    13     22        6
20090520  35    13     22        9
20090521  19    18     1         8
20090522  25    13     12        9
20090525  25    13     12       10
20090526  37    18     19       13
20090527  39    17     22       15
20090528  31    16     15       16
20090529  46    19     27       18
20090601  63    15     48       24
20090602  55    11     44       29
20090603  26     7     19       28
20090604  38    10     28       29
20090605  52    16     36       31
20090608  41    12     29       31
20090609  45    15     30       31
20090610  51    17     34       32
20090611  50    13     37       33
20090612  32    11     21       30
20090615  13    19     -6       23
20090616  16    21     -5       17
20090617  23    20     3        13
20090618  24    11     13       11
20090619  32    13     19       12
20090622  15    25    -10        7
20090623  13    25    -12        2
20090624  33    21     12        3
20090625  36    13     23        7
20090626  94    18     76       21
20090629  58    13     45       27
20090630  31    14     17       27
20090701  40    16     24       28
20090702  13    18     -5       22
20090703  13    18     -5       18
20090706  18    33    -15       11
20090707  19    27     -8        5
20090708  11    48    -37       -5
20090709  14    35    -21       -12
20090710   6    38    -32       -18
20090713  20    30    -10       -18
20090714  25    20     5        -15
20090715  38    13     25       -7
20090716  51    20     31        2
20090717  60    20     40       11
20090720  82    16     66       24
20090721  64    22     42       31
20090722  64    20     44       37
20090723  131   15    116       55
20090724  79    17     62       60
20090727  90    14     76       65
20090728  72    12     60       66
20090729  57    13     44       63
20090730  119   15    104       72
20090731  71    15     56       69
20090803  95    10     85       73
20090804  88    12     76       74
20090805  66    13     53       69
20090806  38    13     25       60
20090807  67    10     57       59
20090810  56    16     40       54
20090811  38    11     27       48
20090812  55     9     46       45
20090813  65    11     54       46
20090814  15     1     14       38
20090817  11    14     -3       29
20090818  18     7     11       24
20090819  20    10     10       20
20090820  44     6     38       22
20090821  67     7     60       29
20090824  75     5     70       37
20090825  74     8     66       44
20090826  66     7     59       48
20090827  49     6     43       50
20090828  70     8     62       54
20090831  31    10     21       49
20090901  38     9     29       46
20090902  13    10     3        36
20090903  15     6     9        29
20090904  31     6     25       26
20090908  70     5     65       32
20090909  94     5     89       42
20090910  108    4    104       56
20090911  95     1     94       65
20090914  59     4     55       67
20090915  111    6    105       77
20090916  133    3    130       91
20090917  140    5    135       103
20090918  104    4    100       105
20090921  99     4     95       105
20090922  146    4    142       113
20090923  130    5    125       116
20090924  46     6     40       103
20090925  39    10     29       88
20090928  90     7     83       84
20090929  98     7     91       83
20090930  83    13     70       78
20091001  38    14     24       66
20091002  29    16     13       53
20091005  56     6     50       49
20091006  118    8    110       60
20091007  94     7     87       66
20091008  183    9    174       88
20091009  138   10    128       98
20091012  200   12    188       119
20091013  94    11     83       117
20091014  236    8    228       144
20091015  161    8    153       151
20091016  101    4     97       143
20091019  165   11    154       146
20091020  104   12     92       136
20091021  144   15    129       133
20091022  52    12     40       113
20091023  93    12     81       104
20091024  105   18     87       97
20091026  91    28     63       86
20091027  33    28     5        68
20091028  10    39    -29       45
20091029  17    29    -12       29
20091030  25    42    -17       15
20091102  19    51    -32        1
20091103  34    44    -10       -5
20091104  47    33     14       -5
20091105  51    21     30       -1
20091106  69    16     53       10
20091109  99    20     79       25
20091110  81    33     48       33
20091111  109   22     87       47
20091112  60    40     20       46
20091113  55    36     19       43
20091116  161   16    145       65
20091117  116   17     99       73
20091118  80    14     66       74
20091119  33    23     10       62
20091120  44    21     23       54
20091123  129   12    117       66
20091124  55    13     42       61
20091125  84    12     72       64
20091127  33    30     3        51
20091130  42    33     9        40
20091201  83    20     63       43
20091202  108   20     88       51
20091203  95    24     71       56
20091204  129   27    102       66
20091207  100    9     91       71
20091208  62    15     47       69
20091209  47    21     26       62
20091210  88    17     71       65
20091211  56    15     41       60
20091214  111   10    101       67
20091215  130   19    111       75
20091216  143   19    124       85
20091217  59    27     32       76
20091218  103   35     68       75
20091221  141   17    124       86
20091222  175   19    156       102
20091223  200    8    192       122
20091224  182   10    172       135
20091228  203   13    190       149
20091229  114   12    102       144
20091230  92     7     85       135
20091231  99    12     87       127
20100104  217    5    212       144
20100105  206    7    199       154
20100106  185    7    178       159
20100107  118    4    114       150
20100108  163    4    159       152
20100111  211    3    208       164
20100112  83     6     77       150
20100113  107    8     99       140
20100114  143    2    141       139
20100115  96     5     91       126
20100119  149    4    145       127
20100120  76     8     68       114
20100121  94    10     84       106
20100122  42    15     27       88
20100125  34    11     23       71
20100126  35    21     14       57
20100127  34    22     12       44
20100128  31    14     17       34
20100129  38    22     16       27
20100201  28    13     15       21
20100202  44    13     31       21
20100203  42    18     24       20
20100204  14    42    -28       11
20100205  14    44    -30        2
20100208  19    25     -6       -1
20100209  28    21     7        -1
20100210  25    18     7         0
20100211  52    16     36        6
20100212  54    17     37       12
20100215  53    15     38       18
20100216  98     9     89       34
20100217  113    9    104       52
20100218  93     7     86       63
20100219  131    9    122       78
20100222  134    9    125       91
20100223  52    14     38       85
20100224  88    12     76       85
20100225  74    11     63       82
20100226  93     7     86       82
20100301  189   16    173       99
20100302  211   11    200       120
20100303  182    7    175       133
20100304  124    5    119       134
20100305  245    9    236       158
20100308  241    5    236       179
20100309  201    5    196       188
20100310  230    6    224       200
20100311  178    2    176       198
20100312  194    7    187       197
20100315  147    5    142       187
20100316  197    8    189       187
20100317  280    9    271       203
20100318  162   13    149       192
20100319  160   19    141       180
20100322  169   14    155       174
20100323  251   11    240       186
20100324  124    8    116       172
20100325  188    8    180       173
20100326  70    14     56       149
20100329  94    15     79       132
20100330  109   11     98       120
20100331  109   16     93       112
20100401  146   11    135       113
20100405  218   11    207       129
20100406  217   10    207       144
20100407  174    6    168       151
20100408  126    7    119       148
20100409  181    3    178       158
20100412  245    7    238       177
20100413  177    4    173       179
20100414  357    5    352       216
20100415  367    9    358       248
20100416  197    7    190       242
20100419  117   21     96       217
20100420  195    8    187       213

So, I don't completely agree that only the endpoints matter, as the ride along the way cannot be dismissed lightly.

I guess there are those with iron stomachs for whom stress slides right off.
It would be nice to learn how they do that :)
(I'm pretty sure one way is to have enough assets that losing 50% of it doesn't affect anything).

Thanks for pointing this out. Not everybody have enough assets to wait a year or so to recover from losing 50% or more.

GD_

Howard Marks latest memo has some discussion on success.


Investors must accept that success is likely to stem from making a large number of investments, all of which you make because you expect them to succeed, but some portion of which you know won’t. You have to put it all out there. You have to take a shot. Not every effort will be rewarded with high returns, but hopefully enough will do so to produce success over the long term. That success will ultimately be a function of the ratio of winners to losers, and of the magnitude of the losses relative to the gains.<?b> But refusal to take risk in this process is unlikely to get you where you want to go.

Interestingly to me, he does not define success compared to a benchmark.

The article is on Seeking Alpha but can also be found at Oaktree.

https://seekingalpha.com/article/4684685-latest-me...

Aussi

The link is to an article by Mark Hulbert,"Are market-beating fund managers truly skilled or just lucky?" According to Hulbert, it will take at least another 50 years to determine if Fidelity Magellan FMAGX, the top fund since 1969, is superior based on skill or has just been lucky so far. Makes determining if a screen is successful pretty difficult!

https://www.marketwatch.com/story/are-market-beati...

Aussi

Makes determining if a screen is successful pretty difficult!

Indeed.

I think of it this way: it's a curve of rising probability of actual "value added". You are never 100% sure...but you can be pretty darned sure at some point--functionally certain. The Buffett example.

Different metrics of success will give different curves of rising probability. The interesting work is to find the metric(s) which give the highest certainty that something "works" (topmost curve) with any given amount of out-of-sample data.

And realizing that failure is much easier to prove than success. If a strategy noticeably underperforms its universe in every 6 month interval for (say) four years post discovery, the chances of it having long run value approach zero pretty quickly. Whereas I believe four years of pretty good results would not give nearly as much certainty in the other direction.

Jim

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