A short story for quants

Dear Mr Derman,

You are always writing about the difficulty of being a good quant, but it’s not that hard. Read please my story and don’t be so serious!

I have come to New York with a PhD from ********. Quickly, I answered an internet ad by a chasseur de tête who sent me to a foreign bank. Two interviews and I aced them all. A week later, I’m on the desk. “Dude, you are getting a Dell!” I say to myself.

With my scientific PhD, I find option theory easy as π. I have studied heat conduction and quantum mechanics so I quickly comprehend the options: α is intercept, β slope, Γ curvature, ∆ tangent, σ temperature, θ sensitivity, µ drift. If I know derivatives, I know Derivatives. Soon I am an expert at Black-Scholes and Beyond. Yield curves are strings. Feynman to me? Kaç to you! Everything’s an option. I am one dynamic hedger, man.

On the prop desk my boss is Alden, an MBA, and I’m his quantitative guy. He calls me a geek;
he knows no math but he sure knows business; he can use the same word as noun, adjective, exclamation and gerund in single sentence when he’s angry. Alden’s risque assistant is Lidia, a truly exotic option, a total knock-out with a non-normal distribution which makes the option salesman whistle and mutter softly about barrier penetration.

I have rational expectations for Lidia but I feel she don’t respect me. She like old movies but has no taste for mathematics and its beauty. To her I am far out-of-the-money.

Now the bank wants to do structured products. I have Excel, I buy VBA, I get models from optionmodels.com and now I’m in business. We’re doing long-term puts and calls, down-and-outs, converts, one-touches, spread options, CDS, vol swaptions, whatever, and I’m getting all the prices. I find model for anything. Easy as Dell. Once a week we run my spreadsheet to mark the book. Big P&L fast. Then late dinner with Alden at Bouley or Jean-Georges.

But always Lidia’s on my mind. When I watch her wandering across the floor, I cannot but think of excess kurtosis. I try to cliquet with her for coffee but she DK my trade. I sense there is little chance of a transformation between her p-measure and my q-measure.

One day someone offer Alden a big position in spread option barrier reversal American no-touch interest rate euro swaptions, denominated in Turkish lira. According to my model, these Sobranies are pretty cheap. Lots of α, high κ, big Sharpe. Alden take $100 million face for the desk and his boss bought some for his own PA too.

Next day the broker offered us much more at the same price – great deal! Each day’s close I tell Alden how my model says to rehedge the Eurodollar futures and the lira, and then we execute. Except I am always thinking sadly about Lidia, dreaming of her capital assets. Will I ever know her efficient frontier?

Next week comes by the head of model risk, ENS graduate Dr Jean-Martin Geille, an expert in Malliavin calculus. And Vlad, chief risk modeller.

“You’re VAR is way up, mon ami,” said J-M to Alden, very loud. “What model ‘ave you used for the Sobranies?”

My model is one-factor Monte Carlo with control variate, $125 from the web. Vlad’s is three-factor Crank-Nicolson PDE with fat tails and LU decomposition, he tells me, written in Java on his Linux laptop. His say we have a lot less α than mine.

“You pay too much µ for too little κ!” say Vlad.

“What’s it all about, α?” Lidia sings in her deep voice. She cannot understand the situation is serious.

But J-M does. “I am arrestin’ you for ze future mis-markin’ of complex instruments,” he yells, waving his hands as he jumps in front of Alden. He joke, but Alden doesn’t laugh. He knows J-M would do anything to make risk department look good. We are ε away from big trouble.

That night the risk committee uses Vlad’s model. Their report shows big drop in our marks. “No-one knows what this is really worth,” moans Alden. “We’d better unwind and cut our losses. No Zermatt this Xmas …” Bonus day is only a month away.

So much volatility is difficult to concentrate… At the close I execute the end-of-day Eurodollar hedge and leave lira rebalancing for next morning.

When I get to work Alden is popping.

“Did you hedge last night?” he yell.

“Eurodollars yes, lira no!” I say.

“Great!” shout Alden. “Trouble in the Middle East – 7 percentage point drop in the Turkish lira overnight. The Sobranies knocked in. How’d you guess?”

“I been learning extreme value theory,” I tell Alden.

“Good call, guy!” he say as he squeeze my shoulder.

The Sobranies triple and we close out. I make 20 units for the desk. Lidia looks at me with new respect. On bonus day I invite her to dinner at Jean-Georges.

“How did you do it?” she smile at me over the Petrus ‘85.

I can see our implied correlation is approaching unity and I am ready to early exercise.

“Behavioural finance,” I tell Lidia as I take her hand. “The market is like a shy woman who suddenly
find she’s beautiful: slow to passion but fiery when aroused…”

Soon perhaps I start my own market-neutral hedge fund, offshore. Meanwhile, I hope my story encourage your readers.

Yours,
D***** B*****

Source: www.risk.net October 2003

A day in the life of a foreign exchange trader

By Mitesh of Goldman Sachs

Working as a trader in FX, I trade the Swiss franc. It is exciting — the foreign exchange markets operate 24 hours a day and any moment anything can happen. You have to be ready to react. The anticipation ahead of big numbers and the buzz you get from trading them is phenomenal.

6:30 a.m. – Getting Started

I usually get to my desk about 6:30 a.m. I start the morning by noting down the overnight ranges and calling our Asian desk to find out what’s happened overnight. Then I read the overnight recaps and news, and look at where things are trading at the moment. Usually, if one currency or another has made a notable move, we will discuss it and collate thoughts regarding what we think and what positions to put on/take off.

7:30 a.m. – Take the orders from Tokyo

The day speeds up once Europe and London are all in and liquidity improves. Clients can call in any time. Most tend to call in early to find out what’s been happening overnight. The majority of the business we handle tends to take place after 7:30-8:00 a.m. London time. European and UK data usually comes out from 9 a.m.-11a.m.

Mid-day – New York and London both open

Throughout the day, we take calls from clients. We take an active interest in what our clients are doing and their trading styles. We have a lot of contact with them and it is always interesting. Over time, I’ve developed relationships with several. This helps us improve the services we offer as well as build brand loyalty in the transparent currency markets. Lunch — which we have at our desk if the markets and phones are quiet — is usually just a quick sandwich.

Afternoon – London closes

The day goes by very quickly. The New York markets trade briskly at mid-day. The markets in London move towards the close in late afternoon. Each of the traders here covers separate books, i.e. different currencies, and on any given day, one may trade more actively then others. That’s why, while we’re each focused on a different currency, essentially we work as a team. We’ll often cover for each other taking calls and orders so someone else can handle a large position or talk with a client. We’re also constantly bouncing trading ideas off each other. There’s a good deal of give and take on the desk.

Winding Down – New York closes

There is a typically a lull in currencies as the NY markets wind down for the day. Tokyo won’t open again for several hours. So I usually go home around six. The workday, though, isn’t always over. Sometimes I’ll take positions overnight, monitor them from home and, if necessary, call into NY or Tokyo to trade. The currency markets trade around the clock — and there’s always something happening. That’s what makes this job so interesting.

Commodity Price Cycle – 200 year view

Commodity Price Cycle

“We will not bet this company,” said BHP Billiton CEO Chip Goodyear this week, while presenting record group results for the year to June 30, 2005. The world’s biggest diversified resources company posted a bottom line profit of $6.5-bn for the year, a growth of nearly 90% on the previous year’s figure.

On the question of betting, Goodyear was referring to a graph which shows that despite the monster profits delivered by BHP Billiton, commodity prices are barely out of the starting blocks from 200-year lows.

Goodyear’s amazing graph was compiled from a variety of sources, including the US All Commodities Producer Price Index, US Consumer Price Inflation, US Bureau of the Census, Historical Statistics of the United States, and the Colonial Times, to 1970.

Goodyear stressed that the graph needed to be looked at “quite carefully.” A small move on the graph, Goodyear explained, “is actually several decades.” According to the graph, “today we find ourselves at a period of time which is, or rather close to it anyway, 2001/2002 when real commodity prices were the lowest they’ve been in the last 200 years which essentially puts them at the lowest price they’ve been in known history.”

Commodity cycle vs Major wars

Most important market moving indicators

What Are the Most Market Moving Economic Indicators for the U.S. Dollar?
By John Kicklighter (DailyFX) – 8 August 2006

It is irrefutable that news or economic data can elicit a sharp reaction from currencies and other financial markets. However not all economic data is created equal. The monthly Non–farm payrolls for example has had a far bigger impact on the US dollar than other perennial top market movers like consumer prices. Indicators rarely keep their same level of influence over a currency though; so it common to see major shifts in the top ranking from year to year. Continue reading “Most important market moving indicators”

Interdependence in World Equity Markets

By Ricardo Coelho, Claire G. Gilmore, Brian Lucey, Peter Richmond, Stefan Hutzler ( source)

 Over the period studied, 1997-2006, the tree shows a tendency to become more compact. This implies that global equity markets are increasingly interrelated. The consequence for global investors is a potential reduction of the benefits of international portfolio diversification.

Developed European markets are at the global centre. Since 2000, France is central node of European markets (used to be Germany before 2000). US links a cluster of North American and South American countries (except Peru) to France, via Germany. Interestingly, US market dominates globally in market value, but has only a loose linkage to other markets. Japan only became linked to other Asian markets since 2001, before that it was more linked to Western markets. South Africa, Turkey and Russia cluster emerged in 2000 and stays reasonable stable since then.

Legend: Europe grey circles
North America white diamonds
South America grey squares
Asia-Pacific black triangles
Other white squares

Interdependence in Currencies

By A. Z. Gorski, S. Drozdz, J. Kwapien and P. Oswiecimka ( source)

Over the period studied, December 1998 – May 2005, the chart below shows the correlation grouping of around 60 currencies (including gold, silver and platinum) using the US dollar as the base currency. The distance between pairs represents correlation values where the smaller the distance the higher the correlation.

Gold intraday pattern

By Dimitri Speck (27 October 2006)

Since August 5, 1993, there has been a systematic attempt to administer downward impulse to the gold price through loans and sales of the metal. How do we know the date when the systematic interventions began? By observing their execution times. These actions are not divided evenly throughout the day, but instead tend to focus on important time points such as the PM-Fixing and the New York closing price. Additionally, COMEX trading hours are preferred. This creates an intra-day pattern that can be statistically identified and allows us to pinpoint the starting date of the interventions on August 5, 1993.

This intra-day anomaly existed for a very long time, but has weakened the last few years in the course of the continued upward trend in prices. The attached chart shows the average intra-day trend of all days for which there are high numbers of price fixings. The right axis shows the price, the bottom scale the time of day. The average is calculated by taking the minute by minute prices throughout the day from about 2000 days and consolidating them as a single day. Thus this so-called intra-day seasonal chart shows at a glance how intra-day prices behaved over the last eight years.

Clearly visible is the price decrease at the time of the London afternoon fixing. The minor lows near the morning fixing as well as the open and close in New York are all worth noting. Also conspicuous is that during American market hours the price generally trends sideways, in contrast to the rest of the time when it is moving upwards.