Contrary to popular belief, money is no material good. It is created out of nothing by banks lending it. Therefore, for each newly created lot of money there’s the same amount of debt. You’re destroying the money by repaying your credits. Since this requires a higher sum due to interest and compound interest, and since money is also permanently withdrawn from circulation by hoarding, the entire money supply must constantly grow. It must never shrink. If it still does, as in the 1930 economic crisis, loan defaults, bank crashes and bankruptcies are the result. The monetary system is therefore a classic Ponzi scheme.
Because the money amount always corresponds to the same amount of private and public debt, this debt amount also must inevitably grow, in spite of all the political lamentoes. Reducing public debt would either destroy money or increase private debt proportionately. This happened in fact in the United States around the turn of the millennium, when then-President Bill Clinton managed to get by without borrowing, and even achieved a budget surplus. Which caused interests to drop and banks to look elsewhere for distributing their money. The indirect result of Clinton’s good deed was a massive increase in private debt that eventually led to the mortgage crash of 2007.
How to acquire it in large amounts
Money is considered a good thing in almost all cultures. After all, it allows you to do the things you want, and – even more important – not to do things you don’t want to do. It thus represents freedom. You can get to it with different methods. The most obvious is taking away other people’s money. Here’s the Top Ten fortunes by known villains, according to Forbes (in US $):
- Hugo Drax – 7.6 billion
- Auric Goldfinger – 6.5 billion
- Max Zorin – 5.3 billion
- Lex Luthor – 4.7 billion
- Franz Sanchez – 1 billion
- Ernst Stavro Blofeld – 640 million
- Karl Stromberg – 640 million
- Elektra King – 420 million
- Francisco Scaramanga – 115 million
- Dr. Julius No – 110 million
But the most successful in money taking are not, as you might think, drug cartel bosses or leaders of criminal underground organizations, but presidents and other heads of state. They can take their share of money with no risk, since they need not fear the law. Here’s the Top Ten of the acquired fortunes by this way (in US $):
- Muammar Gaddafi, Libya – 55 billion
- Hosni Mubarak, Egypt – 50 billion
- Mohamed Suharto, Indonesia – 25 billion
- Alexander Lukashenko, Belarus – 12 billion
- Mobutu Sese Seko, Congo – 7 billion
- Ben Ali, Tunisia – 4 billion
- Gnassingbé Eyadéma, Togo – 4 billion
- Obiang Nguema, Equatorial Guinea – 3 billion
- Slobodan Milosevic, Serbia – 1 billion
- ‘Baby Doc’ Duvalier, Haiti – 600 million
This list does naturally not include assets of monarchs such as the Sultan of Brunei, who have no need of pilfering because the country belongs to them by law anyway. Or of dictators like Wladimir Putin, whose estimated 125 billion booty (plus a 17,000 sqft palace) officially does not belong to them, but is kept for them by friendly oligarchs. The listed sums must also be considered in relation to the economy of the country. To bag 600 million in grinding poor Haiti is a much more impressive performance than the lousy one billion that Milosevic could siphon off in industrialized Serbia. But as long as you’re neither a supervillain, nor a head of state, nor both at the same time, you have no choice but to use other means to acquire money. There’s also the method of buying something cheap and selling it dear. Not as profitable as being a head of state, but it still can produce some handsome gains (annual income in US $):
- Jim Simons, Renaissance – 1.7 billion
- Ken Griffin, Citadel – 1.7 billion
- Raymond Dalio, Bridgewater – 1.4 billion
- David Tepper, Apaloosa – 1.4 billion
- Izzy Englander, Millenium – 1.1 billion
- David Shaw, Shaw Group – 750 million
- John Overdeck, Two Sigma – 500 million
- David Siegel, Two Sigma – 500 million
- Andreas Halvorsen, Viking – 370 million
- Joseph Edelman, Perceptive – 300 million
All in this list acquired their wealth with algorithmic trading. Which is the topic of most of the rest of this blog. It does not produce any goods. But on the other hand, it does not steal from anyone. On the contrary, private, small-scale financial trading can boost demand and soften economic inequality. It can redistribute money from the rich to the poor. So it should be rewarded by the government, for instance by a tax exemption. Well, one can dream, at least…
Why financial hacking?
Part of my job is developing financial tools and trading systems for clients. So far we coded hundreds of trading strategies with all sorts of algorithms for all sorts of financial instruments. Some worked and fulfilled the client’s expectations. Some failed miserably. And some worked in the backtest, but not in live trading. Coming from a background of theoretical physics and computer game programming, I wondered why trading seems not to be an exact science at all. What is the difference between a successful and a doomed strategy? And how can you determine that before actually trading it?
On this blog I’ll attempt a hacking approach to algorithmic trading. Hacking is nothing illegal, it’s just a pragmatic way to solve problems. Hackers prefer experiment over theory. They don’t give a damn about the wisdom of gurus or authorities. So I’ll start with considering all praised trade systems worthless and all “trader’s wisdom” irrational and nonsense until proven otherwise. I will try to evaluate by systematic experimenting whether, why, when, and how algorithmic trading does work. My goal is to find out how it can be a reliable income source for a private trader. This might require complex statistical or machine learning algorithms – but that’s no big deal with today’s software tools. All scripts and software to the articles will be put up for download, so anyone interested can reproduce all the results and use the strategies. After all, successful private trading is for the common good.
As this blog is about algorithmic trading, I’m going to post here a lot of algorithms and source code. Naturally not any trader is able to read code. On the other hand, some basic code and math understanding is required for making sense of the articles. To go from zero to a full understanding of the articles on this blog, here’s a list of Useful Books.