James Harris Simons is a well known Math PhD who created the very successful hedge fund Renaissance Technologies, where most of the trading algorithms are mathematically founded. Bloomberg's piece on Simons' history
With that, here's the man on camera
There was a time when you didn’t have to worry during your first few years of college; it was only the final year in which you had to start thinking of a job and how you were going to find one. But as the years went by, jobs started getting outsourced, the cost of college skyrocketed, and all of a sudden, college became a stressful affair. Not only did you have to choose a degree that would give you an edge in the job market, you also had to be able to afford it at a decent and reputable institution. Students were faced with tough economic decisions even before they were out of high school and debt-ridden before they set foot in college. The average college student of today grapples with the following challenges, which are a mix of financial and academic concerns:
They are unsure about getting into the college and course they want.
They are hesitant about taking out student loans because they know it takes a lifetime to pay them back and that they’re going to be saddled with debt for the better part of their lives.
They’re plagued by unscrupulous recruiters who work on behalf of private, for-profit colleges and tempt them to enroll in courses by making false promises about jobs with fat salaries when they graduate.
These recruiters also talk them into taking out loans even when they’re not really necessary and their savings will cover the cost of college.
They face poor teaching and academic standards if they settle for colleges that are new and relatively untested and inexperienced.
They are forced to work at part-time jobs in order to stay out of debt and have enough money for necessities and luxuries in college.
They struggle to balance academics, social life and work and keep them on an even keel, but it’s always a difficult task because they have to make many sacrifices to keep their grades up.
If you’re a student just about to finish high school and enter college, there are ways to tackle this academic conundrum if you can plan ahead and endeavor to make your plan work:
Start looking for scholarships in high school.
Work on your grades in high school.
Take college-level classes in high school – this allows you to spend less time in college and save on tuition and living costs.
Learn a trade at community college – the pay may not be extremely high, but if you think about it, it’s the hands-on jobs that cannot be done with computers and the Internet that cannot be outsourced, and which are soon going to be in great demand. Any blue collar job will earn you a steady salary and a steady stream of work. It may not be prestigious, but it will allow you to live in comfort and take care of your family without a debt hanging over your heads.
If you want a four-year degree, choose wisely and opt for a college that does not charge exorbitant tuition fees. There’s no point in incurring a large amount of debt which you’re going to struggle to pay back.
Choose to study online if your employer will accept the degree – it’s a great way to earn and learn simultaneously, and stay out of debt.
If you’re in college, plan your career and establish a network through which you can find suitable jobs – it’s the connections you have that help you find a good position.
Take up an internship during your breaks to see if you like working in the industry of your choice. This also helps with your experience when you’re searching for a job.
Use your last year in college to find a job; if you know where you’re going to work when you graduate, then you know that college has not been a wasted experience.
By-line:
This guest post is contributed by April Davis, she writes on the topic of Accredited Degree Online . She welcomes your questions and comments at her email id: april.davis83(@)gmail(.)com.
The Computer Group is like a hedge fund who specialized in exploiting ineffiencies within the sports betting scene. Again, they started with a few math and computer guys, and this story ends with both success and grief.
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...It was almost as if they had invented junk bonds. Every season the cash arrived by the millions, all because their computer told them which teams should be favored to win everything from the mammoth Ohio State-Michigan football game to the basket-ball game pitting Monmouth against Fairleigh Dickinson. The Computer Group did not fix games. It simply understood them.
The group began to assert its mastery of sports betting in 1980, when the computer as an everyday machine had no firm place in sports. Most of the big Las Vegas players of 1980 were still relying on their own good sense and whatever trends they could pick up. A computer seemed to them a gimmick from the future, a big blinking queen-bee serviced by men in white coats. There were relatively few of these "personal computers" that are everywhere today. As a matter of fact, the Computer Group didn't even own its own computer. Until 1983. the group settled for renting time on a computer 2,400 miles away in Rockville, Md. As for the group's invaluable program, it was maintained on thousands of clumsy old "batch" cards, kept in shoeboxes, then fed to the computer like hay into a thrasher.
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I've looked at NFL statistics in the past and have found some interesting numbers, still opportunity cost remains high as my specialty remains in quantitative finance. It is nice to see that with a good understanding of math and stats, money isn't so hard to make today.
Market Harmonics provides updated sentiment figures for free. It saves some of us number crunching time, especially things like the Rydex NOVA/URSA and Nasdaq ratios (see below).
We can see that sentiment numbers have high absolute correlation with the underlying indices, and mostly represent dumb money. They are then pretty important for trading.
OK nobody wants to just "lose weight", because losing lean body mass (muscle, organ tissue, etc.) is simply unhealthy and well... most of us don't want the anorexic look. Therefore, to become more fit, it is only logical to look at how natural bodybuilders achieve that 5%~ body fat level while maintaining all that muscle.
As I've already mentioned why intermittent fasting helps in this, let's move to the other parts.
Intense Muscle is a very good discussion forum for both amateur and pro bodybuilders and power lifters. While the details around fat loss optimization gets complex, I will summarize some basic ideas here,
Fasted workout: Having a workout before first meal of the day
Carb cut off: Cutting off carbohydrates somewhere between Afternoon~ 6PM (depends on metabolism)
C+P/F+P: Each meal must be either a mix of Carbs + Protein or Fats + Protein, never Carbs +Fats
Workout days: Mostly Carbs + Protein
Rest days: Mostly Fats + Protein
So that's it! There's no need for crazy expensive, low quality supplements.
Power Law distributions can explain data sets with extreme values, which includes a whole lot of things in nature, and pretty much everything in financial economics; Normal/Gaussian distributions can not. At the same time, Power Law models are just as, if not more flexible and mathematically elegant.
So here's the walk through,
Definition source: Forecasting Extreme Financial Risk
The Tail Exponent alpha "a" is the key to its tail fatness. A number of existing research papers suggest that actual financial returns resemble a Power Law distribution with the tail exponent between 2 and 3.
An example:
Given a probability P= .2, i.e. 20% for a security to return a minimum of .01/day, so P(.01)= .2
Let the Tail Exponent= 2, we can now work out the probability of it returning .05 (5 times .01/day) in a day. So we want to find P(.05)
P(.05)= P(.01)(5)^(-2)
P(.05)= .2(.04)
P(.05)= .008 = .8%
That was pretty easy right?
Obviously, better probability estimations is critical for anyone planning business models where it's all about "calculated risks".
Citadel is a successful hedge fund well known for proprietary quantitative strategies. I find this letter quite motivating.
Citadel Letter Dec 22
This book is pretty informative for anyone new to arbitrage. Stephane Reverre explains a fairly comprehensive field of existing means of arbitrage (up to the year of the book, 2001), covering a very wide range of instruments and explains both technical and economical grounds behind the mentioned market inefficiencies.
Prerequisite knowledge
A good understanding of statistics is necessary to fully understand some of the concepts from this book. The reader is also expected to have basic understanding of corporate finance and familiarity with intermediate financial mathematics.
Some interesting things from the book
Mathematical explanations for Index Arbitrage opportunities and expected mispricings (Index futures vs. Spot ETF, component portfolio, etc.)
Risk arbitrage exploiting scheduled corporate events (mergers and acquisitions)
Existing statistical arbitrage (e.g. pair trading) means
Examples of actual arbitrage opportunities and exploitations off empirical data
GM (General Motors), AKA "Government Motors" as the US government is a 61% shareholder, has relisted on NYSE late last year, and its financials still do not look all that great. While the Economist suggests that net income's in the green, its fiancial statments suggests otherwise.
Balance Sheet
While GM's Total Assets have increased from $131,899M to $137,238M, at +4%; Total Liabilities have increased from $101,886M to $107,493M, at +5.5%. This means net equity has actually suffered a -1.5% for the shareholders.
Cash Flow
"Cash from Financing Activities " has spiked significantly the past 2 quarters. This suggests that GM is in dire need for cash, a bulk of it to pension liabilities, "Issuance (Retirement) of Debt, Net ", of around $7.3B.
Back to the income statement. We see a net income of roughly $2.1B from last quarter, far short of the cash flow hemorrhage. So yeah, things aren't all that peachy!
