In Trading, It’s Quality, Not Quantity

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Quality vs Quantity – Which is Better for Trading?

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There seems to be a ton of confusion on both sides regarding the Quality vs Quantity Argument when it comes to trading. Being such an important subject for a trader, I have been wanting to write about this for some time so it’s time to put some of the myths, mis-information and confusion to bed here.

One of the big forex trading arguments going around has to do with ‘Quality vs Quantity‘, and it is often masked in the typical;

-Trading Higher Time Frames = More Accuracy

-Trading Smaller Time Frames Carry More Risk

-Anything Below The 1HR Charts is Just Noise

-Quality Trades Make More Money Than Quantity

In regards to the above statements, only one of them is true, but it is incomplete by itself and does not paint the whole picture.

Today’s article is here to dive into this subject, explore both sides of it, and talk about which of the two competing theories is correct.

Quality Is Better Than Quantity When It Comes To Trading
I know two groups of billion dollar business entities that would completely disagree with this argument. They would be Casino’s and HFT shops ( High Frequency Trading ).

Casinos often times ( in the various games you can play there ), only have a slight edge, often times 1-4%, meaning they are 51-56% likely to win at every play, with a 49-44% chance to lose. This small edge might not seem like a lot, but played out over 1000’s of times a day, and it all adds up.

HFT algos also take a similar approach. They are not trying to make huge winners and let trades run for days. They are in anywhere from hours to minutes, perhaps seconds, or even nan0-seconds. They make small trades for ultra small profit, but they do this hundreds of times a day, and make money year in year out.

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These two things alone debunk the whole quality is better than quantity argument , as they are highly successful at what they do. In 2020 alone, HFT firms made over $1.2B ( yes, billion ) in profits. Not bad for having such an inferior trading style!

HFT methods simply use the mathematics and repetition of the edge to make profit. It’s an edge – maybe not the easiest for a human trader, but an edge nonetheless, and it makes money.

The bottom line is, if you have an edge, the more times you can apply it with the same level of accuracy, the more the edge will play out in your favor . And that leads to more profits.

A Comparison Approach
To really see the numbers and a comparison approach, let’s take System A with 60% accuracy, trading 5x a month, risking 100 pips and targeting 200 pips. Below is how the math works out;

5 trades over 12 months = 60 trades per year
60 trades x 60% accuracy = 36 winners and 24 losers
36 winners at 200 pips gained = 7200 pips gained
24 losers at 100 pips lost = 2400 pips lost
Total Profit = +4800 pips

Now, lets take System B , which is the same as System A, but bring down the accuracy just 5%, assuming you will be less accurate trading the same system on a lower time frame. Let’s have you trading 20x a month (

5x per week ), risking 50 pips and targeting 100 pips (same ratio of risk to reward). Here is how the math plays out below;

20 trades a month = 240 trades per year
240 trades at 55% accuracy = 132 winners and 108 losers
132 winners at 100 pips gained per trade = 13200 pips gained
108 losers at 50 pips lost per trade = 5400 pips lost
Total Profit = +7800 pips

Assuming you risked the same equity % per trade using System B – trading quantity over quality made more pips and profit . Even if I make System A 15 % more accurate than System B, here is how the math plays out;

60 trades at 70% accuracy = 42 winners and 18 losers
42 winners at 200 pips gained per trade = 8400 pips gained
18 losers at 100 pips lost per trade = 1800 pips lost
Total Profit = +6600 pips

As you can see, even being 15% more accurate, System A still under-performs System B . Only until you get to 77% accuracy will System A outperform System B.

So this whole argument that Quality over Quantity is mathematically false .

One of the key questions you should be asking yourself then is;

Can I be 77% accurate trading my system on the higher time frames?

If not, you may want to reconsider how to maximize your edge, which is all you are really doing in trading. But the fact is that trading on higher time frames will take longer to make money as you will have less signals in the market.

Key Points
A few of the typical or vanilla counter-arguments to the quantity makes more than quality statements are;

1) Trading higher time frames is less stressful and is More Accurate

2) Anything below 1hr charts is just noise

3) Trading lower time frames causes you to over-trade and over-analyze

Of the above statements, only one is true to some degree (#1) , but again it is incomplete by itself and needs to be fully understood. Let me break down each one so you can fully understand the differences.

Trading Higher Time Frames is Less Stressful and More Accurate:
Of all the statements, this is really the only one with some truth, and it has to do with the second part ( being more accurate ).

I have quantitatively tested various 1, 2 and 3 bar price action signals (over 24 in total), such as pin bars, inside bars, engulfing bars, 2-bar reversals, outside bars, and more across every time frame from the 1m to weekly. Statistically, if you are just trading these patterns by themselves, they tend to be more accurate on time frames such as daily and 4hr strategies (along with the 1hr), then they do on say the 5m.

The reason for this is, a daily candle includes 24hrs of price action, therefore 24hrs of market sentiment and order flow, which is three sessions total. This can have a lot of info as to how players are positioning themselves both intraday and daily.

Thus, with a greater amount of market sentiment over a longer period of time, you can trade some of these patterns with greater accuracy.

However, as we have seen above, greater accuracy does not always = more profits. One thing should be noted though accuracy is not the same trading the often promoted NY Daily Close.

I have one system that on the NY Daily Close, on one pair, trades highly accurate, but another pair quite poorly. If you have an idea as to why, write in a comment below, but the statistics and profitability are night and day, so NY Daily Close is not ideal for all systems, pairs and time frames, and in many cases, under-performs massively.

Thus to sum it up, trading the higher time frame ‘can’ lead to more accuracy.

However, the notion of trading the higher time frame is less stressful is not true, and really a matter of having a successful trading mindset. Some people are more naturally wired to have a set and forget style of trading. Others are better at managing small details, so trading a higher time frame would actually work against their natural mindset.

There is no one-size fits all, thus the key is to find what is most natural to you.

I would like to state generally, if I was starting with a new student, I would start them on a higher time frame as accuracy in the beginning is critical to the learning process. This is exactly how it is in my archery training – in the beginning you start with a target close by, say 3-6 meters, and only after time do you move to targets farther away.

But the idea of lower time frames being more stressful is a matter of mindset, training and practice. Stress is based on how one perceives information and reacts to stimuli. To some people, being bored is more stressful, and there are tons of studies that boredom can hugely interfere with the trading and learning process. For an F1 driver, being stuck in traffic may feel like torture, but doing 150MPH may be joyful. Food for thought.

Anything below 1hr charts is just noise:

First off, this argument often comes from daily chart traders saying price action below the 1hr is just noise. Ironically, this same argument comes from 1hr chart traders who say the 1m time frame is just noise. Who is right, and is it just a matter of perspective?

The truth of the matter is, although there is a greater possibility to witness ‘ noise ‘ (price action that is the result of non-directional interest and order flow), on lower time frames, support and resistance levels work just the same. They simply require a little tweaking. But the bottom line is, order flow creates price action, and price action is simply information.

Using a recent example of a live intraday price action trade I did on Gold, take a look at the two charts below;

Exhibit A (4hr Time Frame Gold/USD)

Looking at the chart above, we can see three strong reactions to the $1685 level on Gold, all communicating strong buying interest at this level.

Now look at the chart below which is the third rejection on the 5m time frame.

Exhibit B (5m Time Frame Gold/USD)

Looking at the chart above, we can see the same strong reaction and buying interest off this level in the first wick. But we can also see there are two high quality price action signals off this level, with a pin bar false break, along with an inside bar + pin bar combo.

I actually got long on this trade, and made over +1415 pips of profit just using pure price action on the 5m chart.

Does the price action at the bottom of this chart look like ‘ noise ‘ to you?

I don’t think so, and it shouldn’t.

Learning to filter out useful information and helpful information is just a matter of training and time. But the idea anything below the 1hr chart is just ‘noise‘ is ridiculous and really a freshman understanding of price action.

Trading Lower Time Frames Causes You To Over-Trade and is Greater Risk:

Although there is some truth to this, it really is misleading. If you analyze each bar, sure, you will be over-analyzing the charts, but this applies to any time frame. In a choppy range, you are not watching every bar for clues, especially the bars in the middle of the range.

However, if you are marking your key levels on a higher time frame, and simply looking for signals at those levels, then the chances of you over-analyzing are slim. It is really a question of trading and preparation- not a fact that you will over-analyze.

The mind has neuro-plasticity to it and can learn almost any skill. You can learn to filter out unimportant bars and price action on the chart – all it takes is a little practice. Once you do, you wait for your key levels and signals, and get in without any extra analysis or stress.

The whole idea of doing less is better for you (or being lazy), I have already demonstrated, doesn’t make you more profitable. Try this same logic to exercising, playing piano or hitting a golf ball, and tell me how that works out!

As to trading the lower time frames or intraday trading equaling greater risk, is a confusion. Risk has nothing to do with the time frame. Risk has to do with three things;

1) Position Sizing
2) Size of Stop Loss in Relation to Target
3) Accuracy

I can have a 3 pip stop (via position sizing) = more risk than a 500 pip stop. I can also make more money with a 50 pip target and 20 pip stop (2.5:1 reward-risk ratio) than a 500 pip target and 250 pip stop (2:1 reward to risk ratio), with the same equity % at risk per trade. So this notion that risk is > on lower time frames is mis-informed.

Does This Mean Quantity Is Better Than Quality?
This is the real question, and it comes down to edge, personality and availability . If you are not available to trade more throughout the day, and have a full time job with only a few hours to view the charts, then I’d suggest trading the higher time frames. However, if your personality is more suited to being more active, then trading 4-5x a month could be harmful to your learning process. So remember trading rule # 1 – know thyself when it comes to trading, and find a system, time frame and style that best suits you.

And we always have to consider our edge. If we trade the daily time frame at 60% accuracy, and the 4hr or 1hr time frames more often with slightly less accurately, do the math and see how it works out. If it’s more profitable trading more often with slightly less accuracy, then do it, as long as it doesn’t throw off your life or health.

But the bottom line is, the whole argument quality is better than quantity doesn’t always hold up , and you need to do the research and the numbers to determine which has a greater edge. And without a doubt, it is a fact if you can take your same edge, and apply it more often than you are now, you will make more money and be more profitable.

Thus, in regards to the question as to which is forex trading method is better, the answer is neither one is better, but both!

Quality matters, but can under-perform. Quantity repeats the process faster of making profit, but has to be considered in the larger scheme and what is most natural for you. However neither forex trading method is better, and the best edge lies somewhere in between the two.

So don’t be fooled by any freshman arguments stating one is better than the other – because they are simply not true, highly inaccurate and misleading.

Hopefully this quality vs quantity forex trading article will put a lot of the mis-information to rest, and give you a new perspective on this critical subject. In a follow up article, I will talk about how I approach this subject in my personal trading, and what I think is the ‘ Ideal Trader ‘ in relationship to these two.

Kind Regards,
Chris Capre

In Workers’ Comp, It’s Quality Not Quantity That Matters

Is this claimant supposed to be off work? Did I get enough discount on the services? Were those services even necessary? I would argue that the question everyone should be asking instead is: Who is your doctor? After all, the physician is the person who sets all of the other wheels in motion — wheels that influence things from quality of care to how long an employee is out of work and the ultimate cost of an injury.

Throughout the past 15 years that I’ve spent managing networks and working with top companies developing custom solutions, one thing has consistently held true: physician quality matters … A LOT. In fact, provider quality is shown to make the single greatest impact on a claim. It’s something that shouldn’t be overlooked, and yet all too often it is.

Numerous studies have shown that good doctors make a difference. There is a huge discrepancy in claims associated with doctors who score well on an outcomes basis versus those who don’t. The average costs associated with a problematic D or E-rated physician, compared to a rock star A or B-rated doctor, are astounding when you really dig into the data.

It is even more profound when you factor in case mixing and adjust results based on severity or type of claim.

A wealth of information now exists on physician quality, and many different models, from simple to complex, can provide useful insights into which doctors can be associated with better outcomes. Carriers and employers should apply this data to think more aggressively about their networks.

The PPO Dilemma

Before we get there, however, let’s look at what’s going on with PPOs. PPOs are the most common strategy utilized to impact costs in our market. A PPO’s value comes from providing a negotiated discount on a medical encounter. Once you have entered into business with the PPO, its primary revenue source comes from matching your bills to a pre-negotiated discount — and they get more matches by contracting with more doctors. Therefore, if they only contract with the best outcomes doctors, they lose significant amounts of revenue any time bills come in from uncontracted doctors that don’t perform as well in outcomes.

As such, all discount networks must contract with as many doctors as possible to assure they don’t lose revenue by missing a hit on a bill. A perfect PPO would include 100 percent of doctors who pass the base qualifications of credentialing. As shown in the prior illustration, there is a huge difference in outcomes between the top half and bottom half of the PPO’s doctors. I don’t fault PPOs for this — PPOs do offer a clear value in reducing purchase costs per episode. They also must contend with multiple factors from jurisdiction to jurisdiction that will always limit how “choosy” they can be. There is a role to be played by discount networks, but that role is not the full picture of how to bend the curve on claim costs.

“Savings” Don’t Always Reduce Costs

Here is a simple concept: If a cheap pair of shoes costs 30 percent less than a high-quality pair, I might save money on the initial purchase, but if the cheaper pair of shoes needs to be replaced twice as often, my savings on each transaction doesn’t lower my total shoe cost.

Applying this logic to medical care, let’s look at two patients — one going to a discounted doctor and one going to a full-fee schedule doctor. Let’s assume a typical ratio of 7:5 visits between high scoring and mid-tier doctors (the real difference is typically higher). Patient A goes to an in-network doctor selected at random from an approved list of providers that generates a five percent savings off each bill. Patient B is sent to a doctor with a high outcome score but no discount. The average bill from each doctor is $100. After the first visit, Patient A has cost $95 and Patient B has cost $100. The payer for Patient A saved $5, and the payer for Patient B has saved $0. By the time Patient A has been to his/her seventh and final visit, medical care cost $665, with PPO savings of $35. Patient B’s care wrapped up after five visits, costing $500, with $0 in PPO savings. This showcases the problem of using percent of savings as a metric – longer duration and $165 more in total medical costs reflects $35 in savings over Patient B. The metric is flawed because the more you spend the more you save.

The point to consider is that network savings are the shiny object that distracts from the difference in total costs. I am not arguing against leveraging savings where available; rather, I want to underscore that quality at a higher price point can significantly outpace discounts when you look at the total cost of a patient in any market.

All health markets suffer from the cost of care that requires too many visits or the additional costs of a second necessary procedure to repair a bad surgery. In workers’ comp, this is exponentially compounded when you factor in the costs of temporary disability as a result of poor recovery and permanent disability stemming out of failed procedures.

The Path Forward

The best way to start down the path forward is to separate the decision about which doctors to work with from how to work with them. The who should be determined by some level of quality metric while the how is figuring out which PPO or contractual relationships get you the best access to doctors who will get you the best results. This means you should first find the doctors that perform well on your chosen metrics, and then look at the PPO or combination of PPOs that get you contractual access. It works in the opposite flow as well; you can look at the total population of doctors available through your network vendors, then pick who you want to work with from that list.

In part two of this series, I will go into the concept of right-sizing networks and the relationship between PPOs and Exclusive Provider Organizations (EPOs). Pick the doctor, and then figure out which network or combination of networks provides access. It may require a little more work and data science on the front end, but the outcome is well worth it.

Quality NOT Quantity

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Quality, a word I rarely seem to find myself thinking over these days. PMC is becoming an ever-so resourceful way to post minecraft ideas. These ideas are creative, extravagant, innoative, and sadly, a lot of the time, desperate attempts made be sadistic PMCers to gain “experience”, this is something I like to call, crap.
I think that to understand crap, we must journey into the question, what is “experience”. XP was never a tool that PMC made to be abused heavily. It was a way to encourage minecrafters to share ideas, gain feedback, and even see how their work shares with the many people that visit this website often. This is something made to create optimistic attempts, and to create a base on PMC, while continually running into update log abuse, reposting, stealing, and the ever so evident, CRAP!

And now we move onto crap, a subject which I do not want to flame about, but which must be said. As much as I respect everyone who uses this website appropriately, and do really inspire me to be honest, I can’t say the same for as many. I often find myself looking through the skins, trying to find that one skin, the one, the perfect, the almighty. There are quite in fact, many of those skins, and this is where I have a problem. I never find them, because I’m constantly bombarded with psychadelic works that make me want to smash my head against a wall and chuck my computer out the window. Here’s something that many skinners might have not found, a secret you may call it, giving people seizures and making skins shiiiiny, or RAINBOWWW, don’t really influence me or anyone for that matter to diamond you.

But if there’s something I hate the most, I think reposting would take it by a longshot. As I scroll down many projects, skins, even blogs, lets say I come across something called “House with automatic farm”(I really don’t have any clue if this is someone’s actual project, and do not intend this message to be for them in particular.). Now I think to myself, oh that’s kind of neat, lets see what else there is. I scroll to something posted a couple minutes before. “House with- hey wait a minute”. and I keep scrolling to find not 1, not 2, but 3 repostings of this. Now, I really don’t buy any of the “oh the website glitched my project” comments I see on many of these projects, and I know, if you have the intelligence to effeciently operate a computer, than I think you can learn how to press one button, just one button properly.

Now, I think there are many positive influences that are helping turn this tide around. And if I may name one, then I think Angel Blocks Society wins it for me. There persistence in excellence, their mindset of never posting anything that isn’t top quality, I just love to sweep my mind off the floor after seeing some of their works. I truly do respect people like this, and I don’t want you to think I hate all of you that do like to grab things with Quantity, but in the end, Quality will outweigh quantity. I know I would feel a lot better with something getting 10 000 views than 20 things getting 500 views each, with no real pride in my work. This blog wasn’t trying to spread my love of smashing my head, getting my mind blown, or having seizures( I really hope this doesn’t offend anyone, it’s not meant to), but plz, remember one thing, quality over quantity. Thank You for reading, and I wish the best for you PMCers to create top notch things that made me love this website because after all, I berievin YOU!

All feedback, and comments are well appreciated, and I’d love to keep more blogs on common problems coming, Thank You for the support!

XLRE: Quality, Not Quantity In Real Estate

Several other bigger, better-known ETFs cover the U.S. real estate space, such as the $34 billion Vanguard REIT ETF (VNQ) or the $4.5 billion iShares U.S. Real Estate ETF (IYR). These funds have more assets than XLRE. Higher daily volumes. Longer track records. At a glance, it’s hard to see how XLRE can compete.

But XLRE has one big point in its favor: an uber-concentrated portfolio. Whereas most real estate ETF portfolios cast a wide net over the sector, including 100 stocks in their portfolios (or more), XLRE holds just 31 names.

That smaller basket is XLRE’s biggest selling point, says Jason Ware, chief investment officer of the $1 billion Albion Financial Group, adding that, for him, XLRE hits “the sweet spot” between diversification and high-conviction picks.

“We don’t need a fund that has 100 or 150 holdings in it,” he says. “We’d rather have a fund of only 30 REITs, as long as they’re all REITs we actually want to own.”

A Sector Is Born

XLRE is one of 10 Select Sector SPDR ETFs that slice and dice the S&P 500 Index into chunks along certain investment themes, such as energy or financials. In XLRE’s case, that’s real estate: The Real Estate Select Sector Index tracks a market-cap-weighted basket of real estate investment trusts (REITs).

The Select Sector Indexes follow the Global Industry Classification Standard (GICS), a system jointly developed by S&P and MSCI in 1999 to standardize which companies fall into which thematic buckets.

For 15 years, the GICS lumped real estate with banks and brokerage firms into the financials sector. Back when the GICS first launched, that choice made sense: In 2001, for example, REITs represented just 0.6% of the financials sector, and 0.1% of the S&P 500 as a whole.

But throughout the 2000s, as investment into real estate grew, it began to evolve into its own unique asset class, distinct from financials. Real estate also came to increasingly drive sector performance: By 2020, REITs had swelled to 19% of financials.

“The operating structure of real estate firms is much different than that of the big financial firms,” said Matt Bartolini, VP at State Street Global Advisors and head of SPDR Americas Research. That impacts their risk/return profile, he added: “For example, real estate did really well during the interest rate decline, asynchronous to financials.”

XLRE, which tracked this new sector category, launched in October 2020. Yet the fund failed to gain much traction until the following year, when State Street shifted the real estate exposure in its existing financials fund, the Financial Select Sector SPDR Fund (XLF), into XLRE. This transition, timed to coincide with when the GICS change became official, transformed XLRE overnight into a $3 billion fund.

From there, however, XLRE has mostly stagnated. Today the fund has $2.27 billion in assets and $56 million in daily volume. That’s not bad, of course. But it’s nowhere near the level of, say, XLF, which has more than 20 times XLRE’s AUM ($21 billion) and more than 25 times its daily volume ($1.7 billion).

That said, XLRE is also more than a decade younger than the other Select Sector SPDR ETFs, with barely two years’ trading under its belt. The fund may just need time to catch up.

Quality, Not Quantity

XLRE’s 31-stock portfolio is much smaller than those of its competitors: The Schwab U.S. REIT ETF (SCHH) and the SPDR Dow Jones REIT ETF (RWR) both hold 105 companies; IYR holds 126, VNQ holds 156. (For context, only about 200 REITs currently trade on major stock exchanges.)

XLRE’s portfolio still hides a few surprises, however.

True, in XLRE, you’ll find many of the same residential and commercial REITs you’d find in VNQ or RWR: Its top 10 include Public Storage, a self-storage REIT; AvalonBay Communities, a high-end apartment developer; and Simon Property Group, the U.S.’ largest shopping mall operator.

Interestingly, though, two of XLRE’s top three names—American Tower Corporation and Crown Castle International—are cell tower companies. Cell tower companies own and lease the physical infrastructure carriers that Verizon, AT&T and Sprint use to provide mobile network coverage; together, American Tower and Crown Castle comprise over 15% of XLRE’s portfolio.

“American Tower and Crown Castle are fantastic. We like that they’re overweight in XLRE,” says Ware.

Also, XLRE invests 4.2% in Weyerhaeuser, one of the largest private owners of timberlands in the world. The company owns some 13 million acres of U.S. timberland and leases another 14 million acres in Canada.

Neither cell tower companies nor Weyerhaeuser appear in the portfolio of real estate behemoth VNQ. Nor are they included in smaller-but-still-popular ETFs SCHH and RWR, which share the same index.

American Tower, Crown Castle and Weyerhaeuser do appear in IYR’s lineup, however, but in much smaller proportions: Together, the cell tower companies comprise just 8.7% of IYR, while Weyerhaeuser makes up barely over 2.5%.

To some, this breakdown may sound like splitting hairs. But percentages matter, especially since IYR’s portfolio holds more than quadruple the stocks XLRE does. Investors get watered-down coverage, and also pay more for it: At 44 basis points, IYR is significantly more expensive than the 14 bps XLRE charges.

“You can over-diversify,” says Ware.

Long-Term Play

As part of the Select Sector SPDR ETF suite, XLRE’s intended use is as part of a sector rotation strategy, notes Bartolini. As such, he sees “a good amount of cross-pollination” between investors in other Select Sector SPDR funds, such as XLF and XLK.

“Being able to ensure there aren’t any gaps in your coverage is a big positive,” he says. “XLRE provides granularity, without fear of style drift.”

Active sector rotation, however, is not how Ware’s firm uses the ETF.

“For us, XLRE is a long-term play,” he explained. “We’re bullish on U.S. real estate, and XLRE gives our clients diversification while augmenting income.”

He points to XLRE’s yield, which, at 3.7%, is substantially higher than other investments now offer in today’s environment of ultra-low interest rates.

XLRE, like all REIT funds, does carry significant sensitivity to interest rates. That risk dictates whether Albion remains invested, says Ware.

“If rates rise without economic growth, REITs will be impacted negatively, and we’ll exit the fund,” he noted. “If the economy’s doing well, though, I think REITs can absorb rate rises, and so can XLRE.”

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