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Wednesday, December 18, 2019

News VIX Script, Jim Simons/Ed Thorp Financial Trading Background, and More

- due to the amount of news out there and market manipulation now it's difficult to know what to do and how things are genuinely going in the world of finance. I decided to build a prototype for examination my own News VIX script for this reason. You can download it here:
news_vix-1.02.zip
http://sites.google.com/site/dtbnguyen/
https://dtbnguyen.blogspot.com/2019/07/comparing-icos-random-stuff-and-more.html
https://dtbnguyen.blogspot.com/2019/02/cryptocurrency-market-manipulation.html
http://dtbnguyen.blogspot.com/2016/03/psychological-warfaremind-control-more.html
https://dtbnguyen.blogspot.com/2019/09/big-data-and-social-trading-investments.html
https://dtbnguyen.blogspot.com/2018/03/social-media-bot-coding-notes-random.html
https://dtbnguyen.blogspot.com/2019/07/comparing-icos-random-stuff-and-more.html
https://dtbnguyen.blogspot.com/2019/07/online-marketing-and-sales-notes-random.html
https://dtbnguyen.blogspot.com/2016/07/neuroscience-in-psyops-world-order.html
https://dtbnguyen.blogspot.com/2016/05/more-psyops-social-systems-and-more.html
https://dtbnguyen.blogspot.com/2016/04/more-psyops-random-thoughts-and-more.html
https://dtbnguyen.blogspot.com/2016/04/hybrid-warfare-more-psyops-and-more.html
https://dtbnguyen.blogspot.com/2016/03/psychological-warfaremind-control-more.html
https://dtbnguyen.blogspot.com/2015/12/understanding-propaganda-us-anti-war.html
https://dtbnguyen.blogspot.com/2018/03/whitepaper-examine-script-random-stuff.html
https://dtbnguyen.blogspot.com/2019/11/a-sea-of-fakery-random-stuff-and-more.html
https://dtbnguyen.blogspot.com/2017/04/news-feed-bias-checker-random-stuff-and.html
https://dtbnguyen.blogspot.com/2017/04/news-bias-checker-2-random-stuff-and.html
https://dtbnguyen.blogspot.com/2017/05/news-homepage-bias-check-random-stuff.html
- description is as follows:
# This script is an iteration of my news_page_bias.sh, news_homepage_bias.sh, 
# news_feed_bias.sh, and planet_check.sh scripts. It's designed to check
# for financial news sentiment regarding a particular sector by examining news
# feeds and homepages. I've built a custom solution primarily because I
# want to avoid the issue of fake news feeds, fake social media accounts, etc... 
# which can lead to improper representations of reality especially as many of them
# often create perception bubbles. By taking a look at many different factors I hope 
# to be able to better guage market sentiment.
#
# Obviously, it's pretty rudimentary and reads feeds included via the first
# parameter. Add feeds as you want. Comment out newsfeeds that are irrelevant 
# using the "#" symbol like in Python and BASH (some feeds aren't really 
# possible to check because of their structure or you can't get a decent 
# gauge of bias because the size of the feeds vary drastically).
#
# It's not supposed to be taken too seriously (though I may write 
# something more relevant later on?).
# 
# I've been very surprised/perplexed by some of the results (a good example
# of this is the following. A lot of websites that don't look biased seem 
# to be while others that seem more neutral?) That said, since it's doing 
# the check on a very small sample that often differs from site to site 
# which makes adequate quantification of bias very difficult.
#    
# As this is the very first version of the program it may be VERY buggy). 
# Please test prior to deployment in a production environment.
- have to wonder whether it's realistic to get this script working on a company by company basis? Suspect it would take access to more data and frequent updates of it? Can't genuinely backtest for a lot of data that you may want to look at? Have to look at side channel intelligence and investigation techniques?
- if you are interested in financial analysis you may be interested in the following as well:

- financial trading encompases a lot of different styles. Jim Simons, Edward Thorpe and Stanley Druckenmiller are amongst the more successful quantitative style financial traders out there. Double digit growth of ~20-30% seems to be the norm for these guys?
Quants - The Alchemists of Wall Street - VPRO documentary
Edward Thorp · Math genius who beat the dealer and the market
Edward Thorp - Beating The Market and Casinos With Mathematics
Chat With Traders
- most stories of high performance is often buttressed by periods of learning/failure. Most people Jim Simons made money off the bat. It wasn't like that? Basically time bounded value trading using amortised bets, probability based algorithms, with technology being used to trawl through large sets of data? Jim Simons and Ed Thorp somewhat similar. Ed Thorp basically turned gambling into a game of mathematics and probability. Thereafter, he transferred his work from casinos to investment. Believes that markets aren't genuinely fair? It's a network based on relationships rather then performance? Believes that gold is a hedge against market collapse rather then something that you can genuinely invest in. Made ~800M for people over 30 years. Gambling is investing simplified? You need to develop a system to trade to genuinely make money
This is How You Beat Wall St. Right Now - Best-selling Author
The fall and rise of a gambling addict _ Justyn Rees Larcombe _ TEDxRoyalTunbridgeWells
- not as easy as you think. May take years to build up experience to get things done. Need good infrastructure and backend to support the overall operation. Can't patent things or else others would figure out strategies. That's the reason for secrecy regarding his funds? 100% model driven. That means that he limits his trading options and may miss out on trades such as next potential Google? Computer is a tool to get things done. He's a good manager, is lucky, etc... Had to work with other people. Others came up with a lot of the models and formula that he ultimately worked with. He thinks that financial world algorithms are different from basic math and science algorithms? Has always partnered with others rather then going it alone. Says that science and mathematics education is bad in US that's why he funds it via philantropy. Says brain drain from teaching to tech sector due to money and societal status. Believes in carrot more then stick approach? He and his wife like science and they give back for that reason?
James Simons (full length interview) - Numberphile
- getting a job in quantitative finance is pretty difficult? Linux, Java, BSD, and C++ and Open Source generally important. Need to know low level stuff that is difficult to find out during a normal education? They want experts rather then to be used as a training ground. Most people in this field are pretty smart but you can get some oddballs people from time to time? Use publicly available information to find out the type of people who work there. Most have worked there for a long time. They're big on real time operations and data processing. Low latency environment. They use a whole bunch of different technologies if you look at various companies
Rentech ask very tough questions for HFT quant trading  job interview
Guru focus on Jim Simons RenTech HFT Quant Manager
- was a relatively late developer. Only spoke when about 3 years old. Developed quickly thereafter and was particularly interested in science and maths. Did well in school. Parents were in defense industry. Went to a poor school. Focus on science helped him learn stuff quickly. Tenacious character. Strangely, disjointed speaking style sometimes. Published books on beating blackjack as well as stock market. Used systems to bet in casinos. Was able to bear Blackjack, Baccarat, Roulette, etc... Was drugged, banned, may have even had his car tampered with? Studies since 1520 saying that gambling games couldn't be beaten. He investigated it as an intellectual exercise. Invested because he wanted to just no be insolvent/bankrupt all the time. Warrants issued by companies rather then exchanges. Often came up with theories on his own rather then reusing other people's theories. He wrote a book with another academic before investing his own money and other peoples. He came up with something similar to Black Scholes Merton formula before they did? Like Thorpe Black Scholes Merton formula took time before it was accepted for publication. Noticed that upward stocks went down and downward stocks went up based on time periods. Had a series of core formulas that he came up and worked with. Arbitraged lots of different financial instruments including new ones? Looked into heaps of different areas. Much more exploratary personality then Jim Simons. Citadel evolved from Princeton Newport and would have been something he would have built had it not been for an investigation by Rudi Guiliani? More balanced personality not driven purely by money and materialism. He invested in Berkshire Hathaway. Pretty much everything he does is backed up by statistical probability? Buffett driven by money and compounding effect?
Edward Thorp - Beating The Market and Casinos With Mathematics
The Black–Scholes /ˌblæk ˈʃoʊlz/[1] or Black–Scholes–Merton model is a mathematical model for the dynamics of a financial market containing derivative investment instruments. From the partial differential equation in the model, known as the Black–Scholes equation, one can deduce the Black–Scholes formula, which gives a theoretical estimate of the price of European-style options and shows that the option has a unique price regardless of the risk of the security and its expected return (instead replacing the security's expected return with the risk-neutral rate). The formula led to a boom in options trading and provided mathematical legitimacy to the activities of the Chicago Board Options Exchange and other options markets around the world.[2] It is widely used, although often with some adjustments, by options market participants.[3]:751
- Jim Simons worked in intelligence analysis a long time ago? He seems to be dodging tax? Doing better then Buffett and Dalio. The history of many traders seems to be that they branch out into higher yield and risker financial instruments as they mature? He was one of the pioneers of computer based trading. He started off using Hidden Markov Models? He wanted to make money as well as do something interesting? He was lucky as well as intelligent? Over time they became more data driven. He keeps his ego in check? He uses Big Data, basic value based trades that often involve pairs, and intuition/experience of markets as well. Has moved beyond linear based relationship checking. Uses computers to point out interesting patterns rathern then automatically trading based on patterns that may be found?
Hidden Markov Model is a statistical Markov model in which the system being modeled is assumed to be a Markov process with unobservable states. The hidden Markov model can be represented as the simplest dynamic Bayesian network. The mathematics behind the HMM were developed by L. E. Baum and coworkers
In electrical engineering, computer science, statistical computing and bioinformatics, the Baum–Welch algorithm is a special case of the EM algorithm used to find the unknown parameters of a hidden Markov model (HMM). It makes use of the forward-backward algorithm to compute the statistics for the expectation step.
The Story of Jim Simons - The World’s Most Successful Investor
https://www.youtube.com/watch?v=_RpPg4ew4E4
- constant theme of large political donations amongst some of the elite? Some of the Artificial Intelligence and Machine Learning algorithms that they work with are quite common in computer science in general. I've used them in automated music composition previously
https://www.youtube.com/results?search_query=robert+mercer
https://en.wikipedia.org/wiki/Robert_Mercer
https://en.wikipedia.org/wiki/Brown_clustering
https://sites.google.com/site/dtbnguyen/
http://dtbnguyen.blogspot.com
- he was a code breaker during the Cold War. Got fired due to his views on Vietnam war. Went to Stoney Brook. He sort of realised that he was lucky early on in financial trading. Then he hired mathematicians when he realised there were patterns in financial markets and then used this to figure out how to trade properly (namely, with some credence given to risk and reward)? Check for time based trends and trend following. Realised that he could distort markets if he managed too much money? He found pockets of opportunities by examining heaps of data. He didn't examine just financial data. He hoovered up heaps of stuff so that he could stop anomalies? Philantropy into math and science projects. Interested in the origins of life on Earth and whether humanity is a lucky abberation or whether there are other intelligent species in outer space?
The mathematician who cracked Wall Street _ Jim Simons
The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution by Gregory Zuckerman
- they've basically applied probability theory to this field? Divergence/convergence, bounded, trends, contrarian, etc... You need volume and volatility for contrarian trades. Anything is possible for trend trades? Pick out the contrarians and influencers and figure out their time frame?
Ed Thorpe Trading Strategy of of Hedge Fund Trader
How Science is Taking the Luck out of Gambling - with Adam Kucharski
- you can tell the type of trades that people engage in by information that sometimes leaks regarding their operations (small spread with massive leverage or big bets on small spreads. You can figure out which by the total number of transactions if any data is in the open)
jim simons performance
As this column previously explained, RenTec has found greatest success exploiting short-term, rather than long-term, anomalies. That makes perfect sense given it is much easier to predict what will happen over hours, days and weeks than months or years (volatility grows with the square root of time).
Having said that, its win ratio is only just north of 50 per cent, and its enormous returns are a function of gargantuan leverage combined with massive trading volume on a global scale. And the impressive monthly return series conceals large losses and variability on a trade-by-trade basis.
While one lesson from this tale might be that markets are inefficient, with the corollary that active managers can generate alpha, perhaps the superior insight is that it is bloody hard work identifying and capitalising on those anomalies.
Edward Thorp is the bestselling author of Beat the Dealer. He revolutionized gambling as he proved how to beat blackjack with card-counting and invented the first wearable computer. As Thorp transitioned out of gambling, he then achieved the unthinkable with 20% annual returns over 30 years trading options.
- interesting is how they spend their philantropic money? A lot of them seem to invest back into basic maths and science. A lot of elite interested in transhumanism?
Interview with James Simons and C.N. Yang for Investing
According to various sources, Epstein, beginning in the early 2000s, showed a strong interest in improving the human race through genetic engineering and artificial intelligence, including using his own sperm. He addressed the scientific community at various events and occasions and communicated his fascination with eugenics.[242] It was reported in August 2019 that Epstein had planned to "seed the human race with his DNA" by impregnating up to 20 women at a time using his New Mexico compound as a "baby ranch", where mothers would give birth to his offspring. He was an advocate of cryonics and his own idiosyncratic version of transhumanism, and had said that he intended to have his penis and head frozen.[243][244]
Kathleen Hall Jamieson, director of the Annenberg Public Policy Center at the University of Pennsylvania said: "Scientists need funding for important work ... if the funding is for legitimate scientific work, there is nothing wrong with accepting support from a billionaire. However it would have been wrong for scientists to accept his funding if they were aware that he was planning a eugenics experiment that might draw legitimacy from his association with them." Professor George Church also publicly apologized for meeting Epstein after his 13-month sentence, saying "There should have been more conversations about, should we be doing this, should we be helping this guy? There was just a lot of nerd tunnel vision."[241]
Kurzweil admits that he cared little for his health until age 35, when he was found to suffer from a glucose intolerance, an early form of type II diabetes (a major risk factor for heart disease). Kurzweil then found a doctor (Terry Grossman, M.D.) who shares his somewhat unconventional beliefs to develop an extreme regimen involving hundreds of pills, chemical intravenous treatments, red wine, and various other methods to attempt to live longer. Kurzweil was ingesting "250 supplements, eight to 10 glasses of alkaline water and 10 cups of green tea" every day and drinking several glasses of red wine a week in an effort to "reprogram" his biochemistry.[49] By 2008, he had reduced the number of supplement pills to 150.[30] By 2015 Kurzweil further reduced his daily pill regimen down to 100 pills.[50]
Kurzweil has made a number of bold claims for his health regimen. In his book The Singularity Is Near, he claimed that he brought his cholesterol level down from the high 200s to 130, raised his HDL (high-density lipoprotein) from below 30 to 55, and lowered his homocysteine from an unhealthy 11 to a much safer 6.2. He also claimed that his C-reactive protein "and all of my other indexes (for heart disease, diabetes, and other conditions) are at ideal levels." He further claimed that his health regimen, including dramatically reducing his fat intake, successfully "reversed" his type 2 diabetes. (The Singularity Is Near, p. 211)
He has written three books on the subjects of nutrition, health, and immortality: The 10% Solution for a Healthy Life, Fantastic Voyage: Live Long Enough to Live Forever and Transcend: Nine Steps to Living Well Forever. In all, he recommends that other people emulate his health practices to the best of their abilities. Kurzweil and his current "anti-aging" doctor, Terry Grossman, now have two websites promoting their first and second book.
Kurzweil asserts that in the future, everyone will live forever.[51] In a 2013 interview, he said that in 15 years, medical technology could add more than a year to one's remaining life expectancy for each year that passes, and we could then "outrun our own deaths". Among other things, he has supported the SENS Research Foundation's approach to finding a way to repair aging damage, and has encouraged the general public to hasten their research by donating.[27][52]
- a lot of the finance world is about taking money in spite of not earning it?
This is How You Beat Wall St. Right Now - Best-selling Author
- if you understand how his operation (and many other Quantitative based trading) works then you begin to understand why they need such high investment in technology and staff. I've built some very basic analytical tools and processing time is rediculous due to the amount of data that needs to be ingested and analysed. I looked at parallelisation and clustering (ironically, it doesn't really help unless you build your software up from the get go to support this), hardware changes (such as moving from mechanical hard drives to SSD and pure RAM based implementations of software), general optimisation, software type (there's a lot of good free stuff out there now), custom software (you're better off going the custom route if you're a good coder because it's cheaper and is better optimised), etc... At the end of the day you need to focus in on your bottlenecks that you face (HFT is obviously network latency, Quantitative finance is more to do with large scale mathematical calcaulations so you need more primary level memory as well as high CPU clock speed, depending on your strategies you may find gains in parellisation of acquisition and processing of data, etc...) and to do what you can with the rest of everything else which is why the management fee and entry fee for many similar type funds seems to be so high? As I've mentioned elsewhere in this post data processing can take hours even on small data sets so I've been looking at Big Data methods, basic high performance computing solutions, optimised algorithms, parallelism, compiled vs scripting languages, etc... as a means to get around this. There aren't too many options out of the box for what I want so it feels like I have to create many custom solutions? Scripting languages are nice to work with because they're high level but setting up and maintaining the environment can be a chore (even with the advent of technologies such as Docker), compiled languages run quick but are often painful to work and prototype with, Java sounds great until you realise how heavy and slow it can run, etc...
http://dtbnguyen.blogspot.com/2019/07/docker-container-notes-random-stuff-and.html
making ramdrive linux
multithread bash
find gradient for series of numbers linux
https://ourcodingclub.github.io/2018/04/18/pandas-python-intro.html
best computer setup for quant finance
https://www.quantstart.com/articles/best-operating-system-for-quant-trading/
https://www.anaconda.com/distribution/
https://www.quora.com/What-are-the-most-important-specs-to-consider-when-choosing-a-laptop-for-Quant-trading
https://stockstotrade.com/best-trading-computers-and-laptops/
https://www.wallstreetoasis.com/forums/laptoppc-advice-for-financial-modelling
https://www.reddit.com/r/buildapc/comments/2278ka/build_help_pc_build_for_algorithmic_trading/
https://www.reddit.com/r/buildapcforme/
https://awesomeopensource.com/projects/quantitative-finance
floating point operations benchmark
https://cloudspectator.com/benchmark-floating-point-computations-with-python/
http://www.keil.com/benchmarks/whetstone.asp
https://www.eembc.org/fpmark/
https://www.cpubenchmark.net/cpu_test_info.html
cpu benchmarks
https://www.cpubenchmark.net/
https://www.cpubenchmark.net/high_end_cpus.html
https://cpu.userbenchmark.com/
https://browser.geekbench.com/processor-benchmarks
simple linux cluster
https://computing.llnl.gov/tutorials/linux_clusters/
https://www-users.cs.york.ac.uk/~mjf/pi_cluster/src/Building_a_simple_Beowulf_cluster.html
ansible run script on another cpu across network
https://docs.ansible.com/ansible/latest/modules/script_module.html
parallel bash
https://www.gnu.org/software/bash/manual/html_node/GNU-Parallel.html
- it's not really Machine Learning and Artificial Intelligence that we're dealing with? It's more pattern spotting? The algorithms in this field are semi-useful for automated analysis. It's obvious that there are those who have worked in other industry sectors (such as government, defense, intelligence, healthcare, science, technology, medicine, etc...) who have seen similarities as well? I know that many people want a more socially considerate version of capitalism to be applied in the future. My guess is that a lot of this could be facilitated via high end supercomputer style technologies. As it currently stands, a lot of politicians sort of pick whatever topic they deem to be important to them? What if computers could pick out what issues were most pertinent, feasible, etc much like automated financial trading (I'll likely build something out if I have the time as it's seems to be an interesting problem to solve. Can you build a self governing, better, and more fair world that is driven mostly by technology?)?
We're living in a computer simulation - philosopher
blue ocean economics
The metaphor of red and blue oceans describes the market universe.
Red oceans represent all the industries in existence today – the known market space. In the red oceans, industry boundaries are defined and accepted, and the competitive rules of the game are known. Here companies try to outperform their rivals to grab a greater share of product or service demand. As the market space gets crowded, prospects for profits and growth are reduced. Products become commodities or niche, and cutthroat competition turns the ocean bloody; hence, the term "red oceans".[9]
Blue oceans, in contrast, denote all the industries not in existence today – the unknown market space, untainted by competition. In blue oceans, demand is created rather than fought over. There is ample opportunity for growth that is both profitable and rapid. In blue oceans, competition is irrelevant because the rules of the game are waiting to be set. Blue ocean is an analogy to describe the wider, deeper potential of market space that is not yet explored.[9]
evangelion supercomputer
The S.C. Magi System (マギ) are a trio of supercomputers designed by Dr. Naoko Akagi during her research into bio-computers while at Gehirn.[1] The Magi's 7th generation organic computers were implanted with three differing aspects of Dr. Naoko Akagi's personality using the Personality Transplant OS (Operating System). The same system is used to operate the Evangelions.[2] The Magi are used during episode #13 to connect the simulation bodies to the Evas in their cages and, presumably, the synch-tests when the pilots are not present in the actual Evas are also conducted through the Magi.
The three Magi run Nerv Headquarters and the municipal government of Japan by majority decision.
The three original Magi in Nerv Headquarters collectively form the set Magi 01:
Magi-1: Melchior: Dr. Naoko Akagi as a scientist;
Magi-2: Balthasar: Dr. Naoko Akagi as a mother;
Magi-3: Casper: Dr. Naoko Akagi as a woman.
http://www.nervarchives.com/glossary.magi.php
https://www.theatlantic.com/magazine/archive/2020/01/wheres-my-flying-car/603025/
https://www.theatlantic.com/magazine/archive/2017/11/x-google-moonshot-factory/540648/
https://www.zerohedge.com/economics/bad-capitalism-and-good-socialism
https://www.zerohedge.com/personal-finance/socal-millennials-are-piling-most-credit-card-debt
https://www.zerohedge.com/crypto/fed-presidents-shocking-admission-we-need-be-pretty-focused-asset-prices-not-just-inflation
Financial services as currently structured is the most pernicious, predatory and corrupt industry on earth. Moreover, it’s the deliberately complex and opaque nature of the industry which then limits public debate when some problem arises and governments and central banks are called upon to take emergency measures to “save the system,” which is just a euphemism for enormous sums of corporate welfare being funneled to people and institutions who couldn’t survive otherwise.
https://www.zerohedge.com/markets/krieger-its-systemic-looting-massive-scale
Confucius said, “by three methods we may learn wisdom: first, by reflection, which is noblest; second, by imitation, which is easiest; and third by experience, which is the bitterest.”
https://thediplomat.com/2019/09/chinas-non-state-universities-what-it-takes-to-succeed/
75% of financial-services firms invest significant money in Machine Learning.
https://www.openquants.com/
- some things to note. Doing what Buffett does isn't hard as long as you have enough capital, doing what Soros isn't difficult provided you have enough capital and enough contacts with the security services, doing what Ed Thorp, Stanley Druckenmiller, etc... takes nerves though. They're basically trying to play the odds when they are in their favour. Obviously, if you bet big even when the odds at slightly in your favour you're still risking money
Prop Trader Makes 7-Figures Trading Flash Crash
- you really rely on standard structured database or even NoSQL/Big Data type database technology because of limitations in querying  and data ingestion. What I've found is that the primary problem has always been data filtration. A problem that I (and others) was aware of years ago? You can not rely or use online data unless you have good or specialised link. That will be your bottleneck. Even in developed countries this may mean special or dedicated lines. This problem is made worse if you rely on automated trading which exacerbates potential trading losses in the event of link failure and a lack of a proper bailout mechanism?
- one thing I've realised is that if you want to analyse financial data you can't really rely on general software. You may need to create your own? Often a lot of the better known investment managers take large margins which is the reason why their returns aren't that great? A lot of microinvestment options are very limited in what you can invest in, have relatively poor returns, high fees, etc...
microinvestment
https://www.thepennyhoarder.com/investing/how-to-start-micro-investing/
- crime intersects with the finance sector from time to time. The following is an interesting perspective of crime, trading, and the "charity paradox" (namely, the more money you have the more generous and less desperate you can be)?
How I learned to read -- and trade stocks -- in prison _ Curtis 'Wall Street' Carroll
https://www.youtube.com/watch?v=F89eycANUrQ
https://projectfeel.org/
https://en.wikipedia.org/wiki/Curtis_Carroll
shoplifting vs economic growth
Recession Sparks Global Shoplifting Spree
http://content.time.com/time/world/article/0,8599,1937944,00.html
http://www.news.com.au/lifestyle/real-life/news-life/two-aussie-porn-stars-speak-about-pressures-in-the-industry-after-four-colleagues-die-in-three-months/news-story/41f9002a1303fb92f35b785757a2292d
reason for people doing porn
https://www.psychologytoday.com/blog/homo-consumericus/201405/why-do-women-become-porn-actresses
http://www.huffingtonpost.com.au/entry/porn-stereotypes_n_5129137
belle knox
https://www.salon.com/2014/09/24/the_3_biggest_myths_about_pornography_debunked_by_belle_knox_partner/
https://en.wikipedia.org/wiki/Belle_Knox
https://www.salon.com/2014/09/16/a_lot_of_my_life_has_been_ruined_because_of_sex_belle_knox_opens_up_in_a_gripping_new_documentary/
http://time.com/2873280/duke-porn-star-belle-knox-college-cost/
reason for people doing crime
reasons for crime
http://www.bbc.co.uk/bitesize/intermediate2/modern_studies/crime_and_law_in_society/causes_types_crime/revision/1/
http://www.encyclopedia.com/law/encyclopedias-almanacs-transcripts-and-maps/causes-crime
https://phys.org/news/2013-10-crime.html
http://www.independent.co.uk/news/uk/what-causes-crime-1584969.html
http://www.smh.com.au/money/investing/normal-is-great-what-to-do-when-the-sharemarket-turns-downwards-20180107-h0entk.html
http://www.executivestyle.com.au/15-gram-method-the-simple-sugar-rule-that-helped-me-drop-weight-h0928m
http://www.smh.com.au/business/world-business/amazon-chief-jeff-bezos-knows-he-can-no-longer-afford-to-stay-in-the-shadows-20180115-h0irwg.html
- there aren't genuinely a lot of details regarding their trading strategies out there? You have to read between the lines a lot and guess based on what is publicly available and genearl knowledge of finance to figure out what they may be doing? There aren't that many mispricings in the market and where there are they are small? A lot of companies operate on a very limited number of models which obviously limits their options? Simons was highly adaptive with regards to modelling? Simons much more evasive then Thorp. Aware that secrecy is important to maintaining edge. Thinks that luck plays a bigger role in life then many think? His intuition is better then most?
Billionaire Quant Fund Manager James Simons - Top Trading and Investing Quotes
https://www.youtube.com/watch?v=rgxVbXjb13M
Billionaire James Simons - Quantitative Investment Strategy, Career and Trading (2019)
https://www.youtube.com/watch?v=6c7ce0_utKA
https://www.youtube.com/results?search_query=ed+thorp+strategies
https://www.youtube.com/results?search_query=jim+simons+strategies
Chat With Traders
Investors Archive
https://www.youtube.com/channel/UCVJalJNQWimC2zWrIHR_bSQ/videos
- Thorp is an idealist Says there isn't much difference between good gamblers and good traders. Says lots of conflicts of interest and corruption in finance and politics which means that life and finance is semi-rigged.
A Man for All Markets by Edward O. Thorp - Best Free Audiobook Summary
https://www.youtube.com/watch?v=B5gNckObsW8
- unrealistic models are one of the the reasons for poor returns in quantitative finance? Warren Buffett sits on cash if he can't find value in markets? Bernie Madoff story didn't add up? SEC poorly run, under resourced, don't care, etc? Came up with Black Scholes before they did? Kept it quiet and used it to make money? Keeps healthy. Interested in social issues and learning about stuff in general
Inside OC with Rick Reiff - A Man for All Markets, Part One
https://www.youtube.com/watch?v=20DZ8eHKJtQ
Inside OC with Rick Reiff - A Man for all Markets, Part Two
https://www.youtube.com/watch?v=6xxu2mjMmlI
- Ed Throp probably more interested in problem solving then making money when compared with Jim Simons. Specialised in options and derivatives trading. Was able to be profitable in 227 out 230 months. Better then 20% over 29 year trading career. Was first to invent wearable computer. Did it to try and beat roulette. Believes that experts are over rated and that life isn't as predictable as many think? He started investigating investing after he had some bad investments
TIP128 - EDWARD THORP – A MAN FOR ALL MARKETS

Random Stuff:
- as usual thanks to all of the individuals and groups who purchase and use my goods and services
- latest in science and technology
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Random Quotes:
- Scandinavia is one of the world's most secular and irreligious regions, with only one in 10 Swedes believing that religion plays an important role in daily life. This tendency extends even to worshippers themselves. One poll surprisingly found that only 15 percent of the Church of Sweden members actually believe in Jesus.
- While eugenic principles have been practiced as far back in world history as ancient Greece, the modern history of eugenics began in the early 20th century when a popular eugenics movement emerged in the United Kingdom[8] and spread to many countries including the United States, Canada[9] and most European countries. In this period, eugenic ideas were espoused across the political spectrum. Consequently, many countries adopted eugenic policies with the intent to improve the quality of their populations' genetic stock. Such programs included both "positive" measures, such as encouraging individuals deemed particularly "fit" to reproduce, and "negative" measures such as marriage prohibitions and forced sterilization of people deemed unfit for reproduction. People deemed unfit to reproduce often included people with mental or physical disabilities, people who scored in the low ranges of different IQ tests, criminals and deviants, and members of disfavored minority groups. The eugenics movement became negatively associated with Nazi Germany and the Holocaust when many of the defendants at the Nuremberg trials attempted to justify their human rights abuses by claiming there was little difference between the Nazi eugenics programs and the U.S. eugenics programs.[10] In the decades following World War II, with the institution of human rights, many countries gradually began to abandon eugenics policies, although some Western countries, among them the United States and Sweden, continued to carry out forced sterilizations.
Since the 1980s and 1990s, when new assisted reproductive technology procedures became available such as gestational surrogacy (available since 1985), preimplantation genetic diagnosis (available since 1989), and cytoplasmic transfer (first performed in 1996), fear has emerged about a possible revival of eugenics.
A major criticism of eugenics policies is that, regardless of whether "negative" or "positive" policies are used, they are susceptible to abuse because the criteria of selection are determined by whichever group is in political power at the time. Furthermore, negative eugenics in particular is considered by many to be a violation of basic human rights, which include the right to reproduction. Another criticism is that eugenic policies eventually lead to a loss of genetic diversity, resulting in inbreeding depression due to lower genetic variation.
- Drones have already changed warfare, providing a more efficient – from the military’s point of view – alternative to conventional aerial missions. But analysts worry that they make it easier for countries to embark on wars and undeclared “shadow wars”, and put non-combatants at greater risk. “Simply put, they transfer risk from combatants to civilians,” says Chris Cole, director of Drone Wars.
The long term question is whether humans will be removed from the loop – the science fiction nightmare where AI-powered drones will select and lock on to targets with no human oversight. There is no shortage of speculation about the topic and concern about the idea, but as yet little evidence of the use of drones, particularly lethal drones, being governed solely by computer.
Nevertheless, the medium-term risk remains, and there is a campaign – Stop Killer Robots – hoping to halt their development with a global treaty, that is opposed by the US, Russia and China. Experts now hope to introduce rules for autonomous warfare, but as with drone technology itself, there is no serious attempt to halt development – or proliferation.
- The North Korea nuclear test in early September 2017 was so powerful that it resulted in an entire mountain being lifted off the ground and was the equivalent of "17 times the size of the bomb dropped on Hiroshima," according to a new study.
The research, published in the scientific journal Geophysical Journal International, also notes that the weapons test caused Mt. Mantap to be displaced by 1.7 feet, in addition to lifting it upward by several feet.
"The nuclear explosion produced large-scale surface deformation causing decorrelation of the InSAR data directly above the test site, Mt. Mantap, while the flanks of the Mountain experienced displacements up to 0.5 m along the Line-of-Sight of the Satellite," the authors wrote in the study's abstract.
- Bernie isn’t exactly a commoner. This is the man who told the New York Times: “I wrote a best-selling book. If you write a best-selling book, you can be a millionaire, too.” As Forbes pointed out this sounds downright Trumpian. In the end, it’s all a bit too reminiscent of Orwell’s satirical Animal Farm. All animals are equal but some animals are more equal than others. Ruffalo and Bernie share an equality denied to the rest of us.
- Appreciation post for the technology supporting my product business. (MR MIST.)
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Thanks!
- While assisted reproductive technology (ART), commonly referred to as IVF, revolutionized treatment of infertility from the late seventies, in Africa the services are limited to a few countries like Ghana, Nigeria, South Africa and Kenya. The continent lacks specialists like embryologists, who know how to extract eggs and fertilize them outside the womb.

It has been estimated that for a population to have adequate IVF services, there should be about 1,500 IVF cycles to one million people. An IVF cycle typically consists of four steps: ovarian stimulation, egg collection, insemination and finally embryo transfer. Africa needs about 1.5 million cycles to meet its current population demand for such services. It is nowhere near reaching that goal.
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Saving Money (without Sacrificing), Random Stuff, and More

- use price matching when you can to get an extra discount. Note, a lot of companies advertise low prices just to get you through the door. ...