Saturday Links: 6-10 February 2017

Saturday Links: Sunday edition! Yeah, that's right. I didn't get around to writing this yesterday.

How the Flash Crash Trader’s $50 Million Fortune Vanished -- Bloomberg Markets -- Investigative piece on Navinder Singh Sarao's fortune, which is tied up in a complicated web of offshore investments. Sarao, dubbed the "Flash Crash Trader" and "The Hound of Hounslow", was convicted for fraudulent trading in the financial markets. Interestingly, aged almost 40, he lived in and traded from his bedroom in his parents' house. He went on to make roughly $50 million from futures trading. US regulators claim he helped cause the Flash Crash of May 2010. After having been extradited by his home country England and subsequently sent to Chicago, Sarao was ordered to pay $38.4 million to the CFTC and US Justice Department. I'm working on a post about the accusations myself; watch this space for more. I'm not going to defend Sarao's trading strategies, which may have involved an HFT practice called "spoofing", but I think it's ridiculous this matter had to be settled in the US and I must say it's nothing short of embarrassing if one individual trader can break the international financial markets from his bedroom. I mean, if that's really true, how stable and trustworthy can today's automated markets be?!

A Litany of Problems With p-values -- Statistical Thinking -- Informative post about the shortcomings of null hypothesis testing and p-values. Practitioners will find this extremely useful. From personal experience, I can say that null hypothesis testing only looks easy from the outside. It's extremely easy to calculate p-values, after all. Press a button in the statistical software of your choice. But to make educated inferences you should look beyond the numbers and ask yourself whether you would fully trust your statistical tests: If you're testing a potential trading idea, would you put your own money into it?

Imperial College MSc Finance Spring Term

I know, it took way too long for me to publish this post, but good things come to those who wait! I've been super-busy over the past months, so please forgive the long wait. If you just arrived here for the first time via a search engine or a link and you haven't read my earlier posts about the Imperial College MSc Finance programme yet, please browse the IC section of my blog for the posts on the previous terms.

The spring term lasted from January through March and it was the first term where we were allowed to choose electives in addition to the term's two compulsory core courses, Asset Pricing and Derivatives and Advanced Financial Econometrics. Personally, I chose to do International Finance and Hedge Funds, but then dropped the Hedge Funds elective a few weeks later because it was different from what I had expected. Other electives, which students could choose from, included Banking, Advanced Investments and Advanced Corporate Finance. In addition, the business school offered an optional course in the C++ programming language. In this post, I will only comment on the courses I took. Let's start with the two core courses:

The course Asset Pricing and Derivatives (APD) was supposed to give students a more in-depth introduction into the pricing of assets in discrete time and by way of binomial trees than Mathematics for Finance had done in the first term. The course was also important, because it paved the way for the more advanced courses on options and fixed income securities that were to follow in the subsequent and final term. Unfortunately, I quickly got the impression that the lecturer had stepped in for someone else at the very last minute, because he was badly prepared. Apparently, there must have been a misunderstanding with the business school, considering that the lecturer initially assumed the course to be exclusively about models of the yield curve and the pricing of fixed income securities. He therefore had to change the syllabus while the course was already under way and I think the quality of the lectures suffered from this initial lack of structure. While the lectures on the fixed income world were actually quite good albeit highly theoretical, the lectures on equity derivatives often seemed improvised. Following negative feedback from the students, the business school promised that this would not happen again in the future and I can report that they organized an additional series of asset pricing lectures for us in the summer term, which were really excellent. This has been very professional, in my opinion, because it shows that while mistakes can happen, the business school is prepared to correct them quickly. But now on to the topics we covered: APD was not based on any book but on elaborate notes prepared by the lecturer. Of course, Options... by John Hull is usually a handy book when it comes to this subject matter. The courses started with a lecture on foundational issues in interest rate modelling and the use of binomial trees and then went on to no-arbitrage models, such as the Ho and Lee (1986) model, which takes the current yield curve as given and aims at matching model prices to observed market prices. In this part of the Asset Pricing course, we also learned about the calibration through Arrow-Debreu securities, which we applied to the Ho and Lee model and the Black, Derman and Toy (1990) model. In the second half of the course, the lecturer covered forwards and futures and possible explanations for backwardation and contango, the Black-Scholes model as well as the practice of hedging and volatility models (i.e. assuming volatility to be stochastic).

Advanced Financial Econometrics (AFE) was quite demanding, but it was very useful and one of the best lectures we have had. The lecturer was very well-prepared and I liked particularly that all theoretical concepts were followed up by a practical application in a statistical software package, such as OxMetrics or Matlab. The course started with non-parametric estimation and non-parametric regressions, followed by techniques to make inferences more robust. After that, we covered multivariate time-series models, including  vector auto-regressive (VAR) models, autoregressive distributed-lag (ADL) models and the concept of co-integration and the error-correction mechanism. I found this lecture particularly interesting and applicable to the analysis of financial time series. The course further covered time-series models of the variance, such as different versions of auto-regressive conditional heteroskedasticity (ARCH) models, and we looked at parametric models for qualitative variables, Monte Carlo methods and finally model specification issues. As said, the course was demanding. For those afraid of mathematics, it might seem a bit overwhelming at first, but the lectures and tutorials were really good and useful in preparing for the exam. The lecturer did not require students to purchase a textbook, because the lecture notes were already quite self-contained. Personally, I found The Econometrics of Financial Markets by Campbell, Lo and MacKinlay to be useful for some of the topics. Econometric Methods with Applications in Business and Economics by Heji et al. was also recommended to us, but it is more "wordy" than the book by Campbell et al.

In addition to the two core courses, students could choose up to two electives in the spring term. I took International Finance, because I am very interested in foreign exchange. I also wanted to do Hedge Funds at first, but the course seemed more like an introduction, which gave only a quick overview of the different strategies employed by hedge funds, so I dropped it after having been to a few of the lectures.

International Finance (IF) was another excellent course of the MSc Finance programme. I liked most about the course that we covered not just purely theoretical content but also looked at empirical evidence. In the first lecture, the professor talked mostly about foreign exchange market conventions. Having worked in FX before, I already knew about certain conventions, but it was a good refresher and certainly useful for students who have not yet had any contact with FX trading or research. Besides quoting conventions and specific terms used by currency traders, we were also introduced to certain types of arbitrage, such as spatial and triangular arbitrage. The lecture closed with some key statistics from the 2010 triennual central bank survey on the foreign exchange market. The second lecture covered foreign exchange market efficiency, including covered and uncovered interest rate parity and the carry trade. In the following weeks, we were taught about real exchange rates, purchasing power parity, the balance of payments and exchange rate determination and forecasts, which I found particularly interesting. The final two lectures covered current currency investment strategies and volatility strategies in FX. In the last two weeks, we also had talks by guest speakers from Goldman Sachs and Credit Suisse, both of which were very insightful. The recommended textbook for the International Finance course was International Financial Management by Bekaert and Hodrick, but the both the lectures and the final exam relied more heavily on the lecture notes and academic papers than on the textbook. All in all, International Finance has easily been one of my favourite courses so far.