Quantitative Finance Quotes

Understanding what businesses actually do to create and deliver value is essential knowledge, but many business programs have de-emphasized value creation and operations in favor of finance and quantitative analysis.

Investors look at economic fundamentals; traders look at each other; ‘quants’ look at the data. Dealing on the basis of historic price series was once described as technical analysis, or chartism (and there are chartists still). These savants identify visual patterns in charts of price data, often favouring them with arresting names such as ‘head and shoulders’ or ‘double bottoms’. This is pseudo-scientific bunk, the financial equivalent of astrology. But more sophisticated quantitative methods have since proved profitable for some since the 1970s’ creation of derivative markets and the related mathematics. Profitable

Reflections on Careers in Quantitative Finance Carnegie Mellon’s Steve Shreve is out with an interesting post on careers in quantitative finance, with his commentary on the changing landscape in quantitative research and the implications for financial education.

Global finance made so much hay, not through efficient markets but by riding up and down three interlinked giant global asset bubbles using huge amounts of leverage. The first bubble began in US equities in 1987 and ran, with a dip in the dot-com era, until 2007. It was the longest equity bull market in history, and it spread out from the United States to boost stock markets all over the world. The smart cash that was being made in those equity markets looked around for a hedge and found real estate, which began its own global bubble phase in 1997 and ran until the crisis hit in 2006. The final bubble occurred in commodities, which rose sharply in 2005 and 2006, long before anyone had heard the words “quantitative easing,” and which burst quickly since these were comparatively tiny markets, too small to sustain such volumes of liquidity all hunting either safety or yield. The popping of these interlinked bubbles combined with losses in the subprime sector of the mortgage derivatives market to trigger the current crisis.

Our standard of progress was conceived for a different era with different problems. Our statistics no longer capture the shape of our economy. And this has consequences. Every era needs its own figures. In the eighteenth century, they concerned the size of the harvest. In the nineteenth century, the radius of the rail network, the number of factories, and the volume of coal mining. And in the twentieth century, industrial mass production within the boundaries of the nation-state. But today it's no longer possible to express our prosperity in simple dollars, pounds, or euros. From healthcare to education, from journalism to finance, we're all still fixated on 'efficiency' and 'gains,' as though society were nothing but one big production line. But it's precisely in a service-based economy that simple quantitative targets fail... It's time for a new set of figures.

adjust the historical prices by a multiplier instead of subtracting $d so that the historical daily returns will remain the same pre- and post-adjustment. This is the way Yahoo! Finance adjusts its historical data, and is the most common way.

adjusted close prices here do not match the adjusted close prices displayed in the Yahoo! Finance table. The reason for this is that there have been dividends distributed after 6/9/2005,

readable little book by Jonathan Regenstein (Regenstein, 2018) called Reproducible Finance with R.

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Marx’s central question was: how can a society that converts interpersonal material relations into impersonal relations among things, and reproduces economic life for the abstract purpose of value augmentation or profit making, simultaneously meet general norms of economic life as a byproduct? This is the question seeking the “logic” or “method” of capitalist madness in our earlier words. All other questions of the march of capitalism in human history, its process of becoming, and the conditions of its historical transitoriness, hinge on that. And answering it is systemically threatening because, firstly, it reveals what bourgeois economic thought from its inception in classical political economy has fought to conceal: that capitalism is not a natural order but a historically transient society. And secondly, it shows that capitalism is not just an asymmetrically wealth distributive, exploitative, alienating, crisis ridden society. Rather, it is an “upside-down”, “alien” order (as Marx put it), which reproduces human material existence as a byproduct of its “extra-human” goal of augmenting abstract, quantitative value – or profit making.

The best quantitative finance brings real insight into the relation between value and uncertainty, and it approaches the quality of real science; the worst is a pseudoscientific hodgepodge of complex mathematics used with obscure justification.

QUANTITATIVE RESEARCH AND TRADING - The latest theories, models and investment strategies in quantitative research and high frequency trading

But after Kapor took Merton's finance course, he decided that quantitative finance was less a science than a faith - a doctrine for ideologues "blinded by the power of the model." It appealed to intellectuals who craved a sense of order but could lead them disastrously astray if markets moved outside the model.

Every time the politicians we elect attempt to increase our standard of living or employment prospects by increasing government spending to stimulate economic activity (‘Keynesian economics’ as it is called); and every time a national bank tries to increase our standard of living or employment prospects by stimulating economic activity by increasing the money supply (‘quantitative easing’ as it is called), each of those actions has its ideological origins in the ideas contained in John Law’s Money and Trade Considered, and the actions of John Law’s Mississippi Scheme.