I want to short Apple so bad right now. But if I did, it would be a completely emotional play since I hate Apple. I am a hater. I’m going to release some of my feelings here so I don’t do anything silly. Apple is a superstar right now just like Sarah Palin and you can’t short something that is so blatantly brilliant. Here’s why I hate Apple.

• Their ridiculous marketing that can easily fool and brainwash poor saps
• The CIA/FBI/Nuclear code level secrecy and protection they have for their products
• The fact that when you buy their products they own you
• The fact that when you develop applications for their products they literally own you
• The insane 12 year old girls screaming for boy-bands level fan base that they’ve somehow accumulated
• The bubbly, happy, bright, colorful GUI interface they always seem to develop
• The bubbly, happy, bright, colorful apple users I see in coffee shops pretending to be working
• The fact that they call their tech support “geniuses”
• They called their latest product the “iPad”
• Market cap is equal to Microsoft…Ha!
• All I can envision are these lame, young, hip, nerdy douchebags sitting in a Starbucks with their MacBooks ignorantly bidding up the price of Apple’s stock with each fanatical purchase of a new Apple product not really knowing what they are getting into. 70% of the run up in Apple’s price has got to be due to these ignorant fanatics thinking Apple is going to take over the world.

And now on to the iPhone. Actually, I give it mad props; it is a pretty amazing, pushed cell phones to a whole new era piece of technology. The only problem is, Apple loves to control everything, hardware and software. Right now they are on top of the world, dominating the cell phone market. But, it is their lack of willingness to compromise that is going to knock them straight back down to the novelty items with a few measly percentage points of market share level. I really think Android is going to emerge victorious here just like Microsoft and IBM did back in the good old days. The Android is a phone OS that functions and performs just like the iPhone but is not limited in terms of hardware. Sure there isn’t anything wrong with how the iPhone looks, feels or performs, but you’ve got two choices, XGB or 2XGB. Gee, thanks Apple.  When there is a large line up of Android devices with multiple flavors and mixtures of features, I can find the exact phone I’m looking for. Small; durable; minimal with no camera; flip phone; an actual keyboard; cheap; whatever I want, assuming there is enough demand out there, will eventually come to fruition. And, as an added bonus, I won’t be a slave to the evil Apple empire. The key here is the customer base, and it grows larger and larger when you offer pretty much the same OS but with a wider range of hardware devices. You see, the war isn’t Apple versus Google…it’s Apple versus Google and a ton of it’s homies.

Out on the beaches of some remote island sippin’ on some sizzurp brought to you by a lackey that barely talks English. The sun warms your half naked body as your look to your left and smile at your lovely husband/wife. And at that moment that you realize that it isn’t the sun that’s keeping you warm but the fuzzy happiness radiating from deep down inside you. The nice calm ocean waves sounds sooth you into a half meditative, half asleep state and you feel confident that you will blissfully enjoy the rest of your days on this earth.

You think that is retirement? Ha. Get real. The picture painted above misses one key fundamental element…you’re old. You can’t relax on the beach because your back hurts. As soon as you find a position that relives the pain, you urgently need to take a piss. You return only to find your significant other has fallen and can’t get up. You cry for help since you are too weak to do much of anything after your arthritis. You have to piss again. Finally you return home from your vacation to find out that one of your good friends has died. You forget about 15 minutes later due the early stages of Alzheimer’s that you are soon to be diagnosed with.  Usually your significant other has helped you remember things but he/she is falling prey to dementia and continues to constantly fall and can’t figure out how to get up.

This is what I don’t get about retirement. People trying to save up too much cash (in other words, not enjoying it now) for what has to be the worst period of life. You just sit around, get weaker and have the ability to do less and less. Remember what it was like to be a kid and you couldn’t do grown up stuff? Remember how horrible that was not being able to do whatever you wanted? In retirement, you end up being a grown up that can’t do grown up stuff. You can’t eat whatever you want. You can’t work. You can’t have sex properly. You can’t play sports. You can’t get around easily and quickly like you used to. You can’t keep up with the times as technology zooms past you. In layman’s terms; you can’t do shit bro. You can’t even take a shit properly for heaven’s sakes. So why save up so much for it? I’m not against saving money in general here. I’m just against saving so much into your retirement accounts that make it incredibly difficult for you to withdrawal before the precipice of death. I’m against having so much blindly invested in stocks and bonds in retirement accounts when in fact there are better opportunities around you.

I also don’t like the typical retirement advice because it ignores one glaring probability; the fact that you might literally die tomorrow. It’s tough to face, but imagine the extreme case where an individual lives uncomfortably his whole life and saves a ton money but takes a death right before retiring. Retirement accounts should be used to save up for the essential costs during your retirement years. I’ll take myself as an example. I’m assuming that I have a house fully paid off at this point. I figure that at a bare minimum during retirement I’ll need about:

• $300 for food
• $300 for medical
• $300 for other miscellaneous expenses (insurance, repairs, speeding tickets, etc)
• $100 for miscellaneous entertainment expenses (entertainment isn’t an essential but I may need it to keep my sanity).

This brings my monthly expenses to $1000/mo (which is $3240 after adjusting for inflation for 30 years). I’m assuming that I will:

• Consistently save for retirement for 30 years
• Achieve a 8% return the first year of saving for retirement and 0.1% less each subsequent year as I move money into safer investments. 8% the first year, 7.9% the second, 7.8% the third, etc…
• Live for 30 years in retirement
• Achieve a rate of return equivalent to inflation during retirement

After some basic calculations it looks like I’ll need $1.3M to have all my essential expenses (adjusted for inflation) covered during retirement which using the assumptions above means I should save $1250 a month. What I’m suggesting here is that after you figure this out for yourself, is commit to saving this much and no more. Max out your Roth and put the rest in a 401k. Take the money immediately out of your paycheck and throw it into these retirement accounts so that you never even see it. I’m not even considering or relying on social security or any other savings as this is simply my ultimate backup money for retirement.

Since that’s been taken care of I can comfortably focus on other things now. No need to be spendthrift, but I definitely don’t need to be stingy either. No need to waste time clipping coupons and instead can work on looking for opportunities and major deals. Since a large chunk of my money isn’t tied up in retirement accounts and I have a backup plan setup, I have liquidity to go after opportunities that may arise. Cash is king in times of distress. Opportunities like investing in a friend’s business idea, buying stocks at depressed prices after the financial crisis of 2008, starting my own company with my bold ideas, making an offer on the neighbors’ foreclosed house, upgrading my furniture with going out of business sales, etc… These opportunities are far better and offer much greater returns that outweigh the one dimensional simplistic tax benefits of retirement accounts that aren’t liquid at all whatsoever.

Look, I know I’m oversimplifying things here, but lock up a significant portion of your assets in retirement accounts and you’ll miss out on a lot of great opportunities around you.

How much would someone have to pay you to play Russian roulette? It’s a game where a revolver is loaded with one bullet, the cylinder is spun, the gun is pointed at your head and the trigger is pulled. In essence, gambling with your own life. Is there any amount of money I can offer you to play this game? Almost everyone I’ve asked answers no. But what if God or a genie came down and could offer you things besides money, and you could have anything your heart desired; then would you play? Of course, you could always ask to guarantee a spot in heaven (or whatever you believe in), but let’s assume your wishes were restricted to the “real world”. I love this question, and I ask it a lot but I’ve never really figured out if there was any kind of fair value that could be computed for playing the game. I’d assume fair value goes beyond money as most people can’t really put a price on their own lives, but I’ve decided to try.

First and foremost, what are the factors that should influence the pricing of gambling with your own life?

• Current Wealth: The more money you have, the higher the price you would demand to play the game
• Current Happiness: I’d have to assume that if you already have a decent life you aren’t really willing to risk it for any amount. If your life pretty much sucks and you were contemplating committing suicide anyways, well then you’re probably more inclined to play.
• Number of chambers: What if the number of chambers (holes where the bullets reside) was increased from 6 to 12? Or to ten thousand?
• Life expectancy: If doctors told you that you were going to die within the next week anyways you might as well try to have one hell of a week

Hmmm… OK, now where do I go? The factors I’ve listed here sound reasonable and I’ve been thinking about this for weeks but I can’t figure out how to make use of them. There are too many non-quantifiable parameters here. Current happiness? How in the world do you figure that out and more importantly how does it fit into an equation? Life expectancy? For most normal people an estimate of how long they have to live is all but a wild guess. I don’t think this is going to work.

There is another way to look at things. It is a somewhat grim, dark way of looking at life but this game of Russian roulette is already something that we  play every day. No one goes to the extreme by living in a bubble and using every thought to figure out how to stay alive and escape death. What we do do is go ahead and eat heart clogging cheeseburgers, not put on our seat belts because the destination is only 5 miles away, figure that a condom is enough protection, amongst a long list of other minuscule, almost insignificant risks we incessantly take daily. And I say almost insignificant because when one of those microscopic, higgs boson sized risks do pull through, you’re dead, which is by no means insignificant… The only difference is that in this daily game of Russian roulette there are more chambers; instead of an 1-out-6 chance there is a 1 out of a million chance of death. So, an easier way to look at this problem is to figure out the prices people already play this game for and see what that implies they’ll play the original version of the game with only six chambers for. I got the data for the table below from the NSC (www.nsc.org) . It shows the number of deaths in 1999 due to various causes and the odds that the average person will die of those causes. Noteworthy are the risks that people take which could be avoided but are chosen to be taken because the rewards outweigh the risks for that particular individual. Things like alcohol, operations of war, automobile accidents and contact with machinery.

TYPE OF ACCIDENT OR MANNER OF INJURY	DEATHS, 1999	ONE YEAR ODDS	LIFETIME ODDS
All External Causes of Mortality, V01-Y98	151,109	1,805	24
Deaths Due to Unintentional (Accidental) Injuries, V01-X59, Y85-Y86	97,860	2,788	36
Transport Accidents, V01-V99, Y85	46,423	5,877	77
Pedestrian, V01-V09	6,047	45,117	588
Pedalcyclist, V10-V19	800	341,025	4,446
Motorcycle rider, V20-V29	2,316	117,798	1,536
Occupant of three-wheeled motor vehicle, V30-V39	33	8,267,273	107,787
Car occupant, V40-V49	14,549	18,752	244
Occupant of pick-up truck or van, V50-V59	3,133	87,079	1,135
Occupant of heavy transport vehicle, V60-V69	422	646,493	8,429
Bus occupant, V70-V79	62	4,400,323	57,371
Animal rider or occupant of animal-drawn vehicle, V80	110	2,480,182	32,336
Occupant of railway train or railway vehicle, V81	54	5,052,222	65,870
Occupant of streetcar, V82	1	272,820,000	3,556,975
Other and unspecified land transport accidents, V83-V89	16,992	16,056	209
Occupant of special industrial vehicle, V83	18	15,156,667	197,610
Occupant of special agricultural vehicle, V84	348	783,966	10,221
Occupant of special construction vehicle, V85	38	7,179,474	93,605
Occupant of all-terrain or other off-road motor vehicle, V86	603	452,438	5,899
Other and unspecified person, V87-V89	15,985	17,067	223
Water transport accidents, V90-V94	679	401,797	5,239
Drowning, V90, V92	501	544,551	7,100
Other and unspecified injuries, V91, V93-V94	178	1,532,697	19,983
Air and space transport accidents, V95-V97	715	381,566	4,975
Other and unspecified transport accidents and sequelae, V98-V99, Y85	510	534,941	6,974
Other specified transport accidents, V98	8	34,102,500	444,622
Unspecified transport accident, V99	6	45,470,000	592,829
Nontransport Unintentional (Accidental) Injuries, W00-X59, Y86	51,437	5,304	69
Falls, W00-W19	13,162	20,728	270
Fall on same level from slipping, tripping, and stumbling, W01	611	446,514	5,822
Other fall on same level, W00, W02-W03, W18	820	332,707	4,338
Fall involving bed, chair, other furniture, W06-W08	624	437,212	5,700
Fall on and from stairs and steps, W10	1,421	191,992	2,503
Fall on and from ladder or scaffolding, W11-W12	375	727,520	9,485
Fall from out of or through building or structure, W13	550	496,036	6,467
Other fall from one level to another, W09, W14-W17	772	353,394	4,607
Other and unspecified fall, W04-W05, W19	7,989	34,149	445
Exposure to inanimate mechanical forces, W20-W49	2,739	99,606	1,299
Struck by or striking against object, W20-W22	842	324,014	4,224
Caught between objects, W23	93	2,933,548	38,247
Contact with machinery, W24, W30-W31	622	438,617	5,719
Contact with sharp objects, W25-W29	68	4,012,059	52,308
Firearms discharge, W32-W34	824	331,092	4,317
Explosion and rupture of pressurized devices, W35-W38	33	8,267,273	107,787
Fireworks discharge, W39	7	38,974,286	508,139
Explosion of other materials, W40	166	1,643,494	21,428
Foreign body entering through skin or natural orifice, W44-W45	38	7,179,474	93,605
Other and unspecified inanimate mechanical forces, W41-W43, W49	46	5,930,870	77,326
Exposure to animate mechanical forces, W50-W64	214	1,274,860	16,621
Struck by or against another person, W50-W52	52	5,246,538	68,403
Bitten or struck by dog, W54	25	10,912,800	142,279
Bitten or struck by other mammals, W53, W55	69	3,953,913	51,550
Bitten or stung by nonvenomous insect and other arthropods, W57	10	27,282,000	355,698
Bitten or crushed by other reptiles, W59	45	6,062,667	79,044
Other and unspecified animate mechanical forces, W56, W58, W60, W64	13	20,986,154	273,613
Accidental drowning and submersion, W65-W74	3,529	77,308	1,008
Drowning and submersion while in or falling into a bath tub, W65-W66	320	852,563	11,116
Drowning and submersion while in or falling into swimming pool, W67-W68	530	514,755	6,711
Drowning and submersion while in or falling into natural water, W69-W70	1,212	225,099	2,935
Other and unspecified drowning and submersion, W73-W74	1,467	185,971	2,425
Other accidental threats to breathing, W75-W84	5,503	49,577	646
Accidental suffocation and strangulation in bed, W75	330	826,727	10,779
Other accidental hanging and strangulation, W76	307	888,664	11,586
Threat to breathing due to cave-in, falling earth and other substances, W77	47	5,804,681	75,680
Inhalation of gastric contents, W78	417	654,245	8,530
Inhalation and ingestion of food causing obstruction of respiratory tract, W79	640	426,281	5,558
Inhalation and ingestion of other objects causing obstruction of respiratory tract, W80	2,828	96,471	1,258
Confined to or trapped in a low-oxygen environment, W81	16	17,051,250	222,311
Other and unspecified threats to breathing, W83-W84	918	297,190	3,875
Exposure to electric current, radiation, temperature, and pressure, W85-W99	479	569,562	7,426
Electric transmission lines, W85	127	2,148,189	28,008
Other unspecified electric current, W86-W87	310	880,065	11,474
Radiation, W88-W91	0	---	---
Excessive heat or cold of man-made origin, W92-W93	18	15,156,667	197,610
High and low air pressure and changes in air pressure, W94	22	12,400,909	161,681
Other and unspecified man-made environmental factors, W99	2	136,410,000	1,778,488
Exposure to smoke, fire and flames, X00-X09	3,348	81,487	1,062
Uncontrolled fire in building or structure, X00	2,676	101,951	1,329
Uncontrolled fire not in building or structure, X01	78	3,497,692	45,602
Controlled fire in building or structure, X02	56	4,871,786	63,517
Controlled fire not in building or structure, X03	32	8,525,625	111,155
Ignition of highly flammable material, X04	73	3,737,260	48,726
Ignition or melting of nightwear, X05	6	45,470,000	592,829
Ignition or melting of other clothing and apparel, X06	112	2,435,893	31,759
Other and unspecified smoke fire and flames, X08-X09	315	866,095	11,292
Contact with heat and hot substances, X10-X19	123	2,218,049	28,918
Contact with hot tap-water, X11	51	5,349,412	69,745
Other and unspecified heat and hot substances, X10, X12-X19	72	3,789,167	49,402
Contact with venomous animals and plants, X20-X29	61	4,472,459	58,311
Contact with venomous snakes and lizards, X20	7	38,974,286	508,139
Contact with venomous spiders, X21	6	45,470,000	592,829
Contact with hornets, wasps and bees, X23	43	6,344,651	82,720
Contact with other and unspecified venomous animal or plant, X22, X24-X29	5	54,564,000	711,395
Exposure to forces of nature, X30-X39	1,488	183,347	2,390
Exposure to excessive natural heat, X30	594	459,293	5,988
Exposure to excessive natural cold, X31	598	459,293	5,948
Lightning, X33	64	4,262,813	55,578
Earthquake and other earth movements, X34-X36	46	5,930,870	77,326
Cataclysmic storm, X37	129	2,114,884	27,573
Flood, X38	15	18,188,000	237,132
Exposure to other and unspecified forces of nature, X32, X39	42	6,495,714	84,690
Accidental poisoning by and exposure to noxious substances, X40-X49	12,186	22,388	292
Nonopioid analgesics, antipyretics, and antirheumatics, X40	168	1,623,929	21,172
Antiepileptic, sedative-hypnotic, antiparkinsonism, and psychotropic drugs n.e.c., X41	671	406,587	5,301
Narcotics and psychodysleptics [hallucinogens] n.e.c., X42	6,009	45,502	592
Other and unspecified drugs, medicaments, and biologicals, X43-X44	4,307	63,343	826
Alcohol, X45	320	852,563	11,116
Gases and vapours, X46-X47	597	456,985	5,958
Other and unspecified chemicals and noxious substances, X48-X49	114	2,393,158	31,202
Overexertion, travel and privation, X50-X57	191	1,428,377	18,623
Accidental exposure to other and unspecified factors and sequelae, X58-X59, Y86	8,414	32,425	423
Deaths Due to Intentional Self-Harm (Suicide), X60-X84	29,199	9,343	122
Intentional self-poisoning, X60-X69	4,893	55,757	727
Intentional self-harm by hanging, strangulation, and suffocation, X70	5,427	50,271	655
Intentional self-harm by firearm, X72-X74	16,599	16,436	214
Other and unspecified means and sequelae, X71, X75-X84, Y87.0	2,280	119,658	1,560
Deaths Due to Assault (Homicide), X85-Y09	16,889	16,154	211
Assault by firearm, X93-X95	10,828	25,196	328
Assault by sharp object, X99	1,879	145,194	1,893
Other and unspecified means and sequelae, X85-X92, X96-X98, Y00-Y09, Y87.1	4,182	65,237	851
Deaths Due to Events of Undetermined Intent, Y10-Y34	3,917	69,650	908
Poisoning, Y10-Y19	2,595	105,133	1,371
Hanging, strangulation, and suffocation, Y20	110	2,480,182	32,336
Drowning and submersion, Y21	243	1,122,716	14,638
Firearm discharge, Y22-Y24	324	842,037	10,978
Exposure to smoke, fire, and flames, Y26	70	3,897,429	50,814
Falling, jumping, or pushed from a high place, Y30	59	4,624,068	60,288
Other and unspecified means and sequelae, Y25, Y27-Y29, Y31-Y34, Y87.2, Y89.9	516	528,721	6,893
Legal Intervention, Y35, Y89.0	398	685,477	8,937
Legal intervention involving firearm discharge, Y35.0	299	912,441	11,896
Legal execution, Y35.5	88	3,100,227	40,420
Other and unspecified means and sequelae, Y35.1-Y35.4, Y35.6-Y35.7, Y89.0	11	24,801,818	323,361
Operations of War and Sequelae, Y36, Y89.1	23	11,861,739	154,651
Complications of Medical and Surgical Care and Sequelae, Y40-Y84, Y88.0-Y88.3	2,823	96,642	1,260



If you would like to play along, find an item on this list that definitely fits your own profile. Or, better yet, think of an activity you do that has even the slightest chances of death. Do a little Google searching and find out what the number of deaths for that activity within a given year are. Next, download the following spreadsheet.

OddsOfDeath.xls

I’m going to use two examples to walk you through the spreadsheet. A really good example is an activity like sky diving. It is a total unnecessary risk for someone to take, but it brings satisfaction that is well worth the risk of admission. According to howstuffworks.com (http://adventure.howstuffworks.com/skydiving8.htm) there are 30 deaths per year from skydiving and around 3 million jumps per year.

Inputs into spreadsheet for skydiving example:

Total deaths per year – Input the total death statistic here. As mentioned earlier, for skydiving, this would be a grand total of 30

Estimate the number of times this was done in total per year – Estimate or find a statistic for the number of times this particular activity in was done in a given year. Thankfully, for skydiving, the howstuffworks.com links states that it was around 3 million

Estimated monetary equivalent benefit for doing this – Estimate how much benefit you specifically receive from participating in such an activity. For skydiving I would have to assume that the sheer thrill, the adrenaline rush, the natural high must be so amazing that it could command quite a high price. The rush must feel better than the craziest drugs on the planet but with no side effects (well, except if something goes awry and you die, but other than that…). Is it better than sex? For some people, maybe? I don’t know, I’m going to set the price equivalent to sex with a high class hooker which probably sets one back a cool $5000.  Sex with a high class hooker versus skydiving, they seem roughly equivalent.

Power growth factor for additional risk – There are two models I’ve come up with. The first simply linearly compensates you taking on additional risk which is completely unrealistic. For example, if you are willing to play a 1 in 10 shot of death game for $100, then with this simple model you would be willing to play a 1 in 5 shot of death game for twice as much, $200. Since a person is literally risking it all here, as the probability of death in the game approaches 100% the player will demand more and more as they are having to risk so much. So, the second model corrects this by taking things to a power as we step closer to that 100% certainty of death factor. The input here defines that power and it completely depends on the person. This number is what takes input from some of the factors I first described earlier, current wealth, happiness and life expectancy. The higher the number here indicates the better off you currently are. I’ve set it to 3 which means that we are rewarded by a power of 3 for each additional unit of probability of death we take on.

The results are to follow soon. I’m going to discuss the inputs for another example, namely driving. From the same howstuffworks.com skydiving article, they mention a few key statistics about driving. They state that 40,000 people die each year from driving and estimate that if you drive 10,000 miles per year your odds of death are 1 in 6000.

Inputs into spreadsheet for driving example:

Total deaths per year - 40,000

Estimate the number of times this was done in total per year – According to the Department of Transportation there are just under 200 million drivers in the US. Estimating that they all drive an average of twice per day (mostly to and from work) for 360 days a year, I’m estimating that the activity of driving is done around 144 billion times per year.

Estimated monetary equivalent benefit for doing this – Not much really. Most of the time we’re driving to and from work, to grab groceries, run errands, visit friends or go to the movies. We get some convenience out of it since we don’t have to walk or take public transportation to the destination. I’d say it’s worth $50, but could be more or less depending on the destination. Less if it’s just to get to work, more if it’s to go pick up that hooker from the last example…

Power growth factor for additional risk - I’ve left it at 3 to stay consistent with the previous example.

Results

	Skydiving (Linear Model)	Skydiving (Growth Model)	Driving (Linear Model)	Driving (Growth Model)
1M-Chamber Equivalent Reward	$500	$500	$180	$2,333
1000-Chamber Equivalent Reward	$500,000	$5,000,000,000	$180,000	$2,332,800,000,000
100-Chamber Equivalent Reward	$5,000,000	$5,000,000,000,000	$1,800,000	$2,332,800,000,000,000
10-Chamber Equivalent Reward	$50,000,000	$5,000,000,000,000,000	$18,000,000	$2,332,800,000,000,000,000
6-Chamber Equivalent Reward	$83,333,333	$23,148,148,148,148,100	$30,000,000	$10,800,000,000,000,000,000



Well, there you go folks. We all drive and therefore the price someone should pay you to play Russian roulette is just under 11 quintillion dollars. Quintillion being 10^18. And if you are a crazy skydiver then you should be willing to accept only 23 quadrillion dollars. Quadrillion being 10^15.

He dominates. If there is one man that has stood the brutal test of time, it is WB. I wanted to compare Warren Buffett to mutual funds and hedge funds using a few performance metrics. So, I put Berkshire Hathaway’s stock up against the top three Dow Jones hedge fund indexes (event driven, merger arb and equity long short) and the best mutual fund I could find by using the WSJ mutual fund scanner, which turned out to be EKWYX. The typical performance measure is the Sharpe ratio, which is simply average return divided by standard deviation. Using this measure Mr. Buffett is in third place and by no means dominating.

But, this measure is in fact way too simplistic. The Sharpe ratio is really good at being a quick and dirty measure, but the fact of the matter is that it is, well, dirty. And this is most definitely true if the distributions we are measuring are not actually normally distributed. The Sharpe ratio also does not take into account that there is good (positive returns) and bad (negative returns) variance. A better performance measure is the Omega ratio which is more complex but much more truthful. I’d rather not explain all the gory details of it, but in essence its power over the Sharpe ratio, and most other performance measurements, is derived from the fact that it makes no assumptions about the distribution it is evaluating. The output is not a scalar but rather a line which can be evaluated at various “reference rates”. When evaluating two strategies at a particular reference rate, the higher value indicates the superior strategy or fund. Obviously if a fund is always greater than another at all reference rates then it is dominating and should always be selected for investment.

The X-axis here is the annualized reference rate. An investor should refer to a rate that he is targeting and select the fund that has the highest value at that level for it is the one that probabilistically has the greatest chance of achieving that return. And what do we find here? It’s pretty simple, if you are targeting a 2% return or less, go with a good merger arb hedge fund. Otherwise, invest in Berkshire Hathaway. To give the competing funds a fighting chance I’ve eliminated the great recession by not looking at performance after 2008 for all funds except for Berkshire Hathaway. All funds took quite a beating during that time and let’s just pretend it never happened except to unlucky Warren Buffett in this quirky alternate universe…

Event driven and equity long short are superior for a target of 6% or less, but for anything beyond that Berkshire simply dominates. End of story.

Actually, not end of story. If any of you out there believe you’ve found a fund that has superior performance (there has got to be) let me know either by email, LivingInVol@gmail.com, or by commenting to this post. I plan on having a follow up where I pit WB against the funds others have suggested using the exact same analysis. I only have one restriction; the fund must have been around for at least 10 years. The winner gets the satisfaction of winning.

Fixed loans are for the conservative, polite, quiet, keep to themselves chumps with those steady jobs whose fixed payments sound as soothing as calm ocean waves rushing upon shore on a cool summer day. Variable rate loans are for the bold, aggressive, “brass balls” types that are comfortable with the fact that their future payment amounts are unknown, willing to look uncertainty straight in the eye.  Well, actually, this is essentially the non-helpful  conclusion that I came to after searching “variable versus fixed loans” on google. Although it is valid advice that the better of the two loans depends on the type of individual, there is a more quantitative way to contemplate things. And, as always, I have created an excel spreadsheet to help calculate things out.

Methodology

For a fair comparison I want to keep payments on both loans the same and see which one is paid off quicker, essentially finding the one that you end up paying less interest on. Usually the payments are dictated by the type of loan and interest rates, but here I am taking the approach that the consumer of the loan is dedicated to making a fixed payment amount monthly regardless of the type of loan. For the fixed rate, it is simple, just do the calculations and sum up the total interest paid each month…done. But for the ARM, how do we know what the future path of interest rates is going to be? Well, in short, we don’t, but we can use Eurodollar futures that are very actively traded in the market for the consensus on the anticipated path of interest rates 10 years out. It’s far from being a crystal ball that glimpses into the future, but many large banks and institutions have put up large sums of money betting that is where the rates will be to the best of their knowledge. What I’m trying to say is, these aren’t just petty $5 bets between you and you’re coworker, these are some serious calls here. In any case, these eurodollar futures provide an estimate of future libor, which is a common index used for variable loans. Even if your loan’s index isn’t libor, it is most likely highly correlated to it. So now, having a set of predictions for interest rates the process of calculating total interest paid on a variable loan is just a matter of plugging in this predicted rate path into the spreadsheet.

Download the Spreadsheet
ARM versus Fixed

Inputs

• Eurodollar Data – A tab where the latest eurodollar information goes. For the latest data simply copy and paste the table from here http://www.cmegroup.com/trading/interest-rates/stir/eurodollar.html
• Loan Amount – The total amount of your loan
• Fixed Rate – The fixed rate that you have been quoted
• Fixed Rate Length in Years -
• Fixed Rate Monthly Payment – The amount you plan on paying each month. The minimum required payment is conveniently calculated a few rows below and is called “Minimum fixed rate payment”, which is the amount the bank is going to charge you each month. I would keep this payment and the variable payment the same for comparisons sake.
• Variable Spread or Margin – The amount above the libor rate that you will be charged for a variable rate loan. If the variable loan index isn’t libor then you will need to do a few simple calculations and figure out your spread against libor
• Variable Rate in Months – The number of months between the reset of your rate
• Variable Rate Monthly Payment – The amount you plan on paying each month. For comparison purposes I would highly recommend keeping it the same as the fixed rate monthly payment as the goal here is to see which loan comes out to be cheaper

Sample Results

The sample results here are from using data from March 13, 2010. The graphs below are simply the amount of principal remaining on the loan after an amount of time.

Example #1

Let’s compare today’s 30 year fixed versus a variable rate that resets yearly. We will set the fixed interest rate at 5.00% and the variable rate spread to a very reasonable 2.50%. The minimum 30 year fixed payment is $536.82, but let’s round that up to $600. The chart below graphs what your remaining balance would look like for the next 30 years if you made $600 payments in the fixed and variable loan.

What in the world is going on here? Well, interest rates are predicted to rise at a fast enough rate to where making constant $600 payment each month isn’t enough for the variable rate. The fixed rate clearly wins here, unless you plan to get out of the loan before 72 months .

Example #2

What if we increased the payment in example #1 to $800 a month? Then variable leads up until 75 months and starts losing after that.

Example #3

What if the variable spread was only 1.50% instead of 2.50% and we were making $800 payments? Then variable wins, but just barely. Between 30 and 90 months is where the savings for the variable loan are the greatest.

Example #4

What if the variable reset was only 1 month instead of 12 and we use the same assumptions as in example 3 above? Then fixed wins again, but variable leads up until 120 months in.

Example #5

OK, so for the most part, it looks like the fixed rate loan is the superior choice if your goal is to pay it off in it’s entirety. You can’t justify picking the variable rate loan, gambling on the hope that interest rates play out like expected for such a minor advantages like in example #3. If interest rates actually rose faster than anticipated by the market then the choice of selecting the fixed rate is a no-brainer. But, what if the consumer thought that interest rates would remain low longer than what the market thought? Below we use an extended period of low interest rates and see how the loans end out. Everything else is the same with a 5% fixed rate and $800 monthly payment for both the variable and fixed.

Wait, what? That’s it dude? I guess, even when you hope for the absolute best scenario for a variable loan, you don’t end up saving that much. And note that the scenario considered is quite an unrealistic one.

Example #6

And here are the results using a future rate path of quickly rising interest rates (yellow line from example above). As expected, the variable ends up costing the consumer a lot more in the long run and the savings are drastically reduced in the short run.

Conclusion

If you are planning to fully pay off the loan, then in this low interest rate environment, it looks like the fix rate is definitely the way to go. If you are planning to exit within 7 years or less, then the variable starts making more sense. But, all this depends on the terms of the loan that you can get and current market conditions. Everything calculated here is based off of a snapshot on March 13, 2010. Utilize your own judgement and numbers when selecting the best type of loan for you. Evaluate the trade-offs between how much you can save and what happens if interest rates don’t play out the way you or the market expects them to. And just remember, if there was anything to be sure of, it is that you and the market are both going to be wrong as no one can accurately predict these things. So be safe and leave room for error. That’s all folks. Peace out.