Tuesday, February 28, 2012

Market Manipulation, Part 1

If the investment advice and forums are any indication, a lot of people consider the markets rigged and manipulated. But what is a good working definition of manipulation? There is price manipulation. That entails the defining what an "artificial" price is. Price manipulation is probably one of those things with a long, long history. One of the most famous cases is that of the Hunt brothers' attempted cornering of the silver market in the late 1970s and early 1980s. Market bubbles may also contribute to "artificial" prices, but bubbles are more of a natural psychological reaction of market participants, not some insidious conspiracy. This difficulty works both ways. Government and industry regulatory organizations cannot be too specific about what signals of fraudulent market activity they are scanning for lest the perpetrators simply work around those signals to escape detection. Besides straight price manipulation, regulatory agencies also consider order flow and spread manipulation.

Johan and Cumming did a study on Market Surveillance regimes around the world in a 2008 paper Global Market Surveillance.

Rosa Abrantes-Metz has written a number of papers on the subject including a 2007 paper Is the Market Being Fooled? An Error-Based Screen for Manipulation.

Wednesday, February 15, 2012

Flash Crash Research, Part 1

Unsurprisingly, given the interest of regulators and trading firms, there is a growing literature on the May 6, 2010 Flash Crash and "mini-flash crashes" throughout recent history. Unofficial high-speed liquidity providers, free from any contractual obligations, can become high-speed liquidity takers. Filimonov and Sornette investigate prediction of endogenous-feedback loops in the research paper Quantifying reflexivity in financial markets: towards a prediction of flash crashes.

Tuesday, February 14, 2012

Behavioral Finance and Sentiment/Tone Mining

There are two prominent claims about the stock market: one is that machines are driving the entire market these days. The other is that behavioral finance works and even sentiment-based trading can produce excess profits.

Friday, February 10, 2012

Dividends and Capital Gains Taxes

It probably won't garner much fanfare this time through, but the Bush-era (Jobs and Growth Tax Relief Reconciliation Act of 2003) qualified dividend and long-term capital gains tax cuts are set to expire by the end of 2012. This would potentially more than double the tax on qualified dividends. For non-tax sheltered accounts, this could dramatically affect the net returns of dividend income-oriented portfolios especially if there ends up to be a discrepancy between qualified dividend and capital gains taxes. It will be interesting to see how this affects investment strategies. Tax-free muni-bonds have appreciated considerably during last year. The relative tax efficiency of different investment instruments may change in the decline of special treatment of qualified dividends and long-term capital gains.

Richard Shaw studied this issue a few years ago before Obama and Congress extended the tax cuts.

Thursday, February 9, 2012

Functional Languages and Call-By-Value, Part 1

A whole lot of work goes into avoiding unnecessary copies in C++. Much of this responsibility lies in the programmer with manual optimizations such as passing large objects by pointer or by reference rather than by value. This concern is pervasive in the language, from the choice of increment/decrement operators to the implementation of constructors. Many compiler optimizations are also target copying such as the return value optimization (RVO) and, more recently, the move semantics in C++11. The reasoning behind the emphasis on copying seems intuitive enough: pass-by-value of any data larger than a primitive type (i.e., larger than a pointer) gets too expensive especially if the data in question is in a temporary which must be destroyed anyway. C++'s machinery to work-around this inefficiency isn't representative of imperative and object-oriented languages. For example, Java makes references the default way for manipulating objects even though the primitive calling semantics is pass-by-value. However, in functional programming, copying is seldom the overriding emphasis. Why isn't copy as big of a deal in functional languages? For the sake of argument, I will take ML as the canonical functional language. Lazy evaluation in languages such as Haskell adds another layer of complexity which I won't address here.

Wednesday, February 8, 2012

Indicators and Timeframes

MarketSci has a short post on what they consider long, intermediate, and short term indicators and strategies. Most indicators can vary sampling periods in order to smooth them out to avoid false alarms. As indicated by MarketSci, the relevancy of different indicators does depend on the amount of data as well as the timeframe. However, with the advent of practical high-frequency data, it is no longer the case that smaller time frames necessarily implies sparser data. One could certainly be sampling weekly for a multi-year indicator and end up with less data than sampling ticks for a few minutes in high-frequency data. The guidelines seem to be that long-term is ruled by trend-following (e.g., moving averages), intermediate-term by mean reversion, and short-term by "noise" (their example is RSI).

Monday, February 6, 2012

Quantitative Behavioral Finance

Though Fama's Efficient Market Hypothesis (EMH) and variants thereof reigned unchallenged for several decades, during the 1980s and 1990s, behavioral finance gained significant credibility. Behavioral finance has since evolved and given rise to subfields such as Quantitative Behavioral Finance. The hypothesis remains the same: markets are not completely efficient because the human participants are not completely rational. Cognitive biases are the main culprit. Quantitative Behavioral Finance takes this idea a little further by rigorously modeling market prices given such biases (which manifest themselves in terms of underreaction and overreaction) exist by combining differential equations and statistical time series analysis.

Richard Thaler's article, "The End of Behavioral Finance", is an excellent survey of the first decade.

Friday, February 3, 2012

Saving Up for College Tuition and Hedging, Part 4

Are prepaid tuition programs a great investment? One is right to be skeptical. The programs vary considerably from state to state. Bankrate.com has an article about some of the programs. It turns out that one can be paying anything from 41% to a slight discount to current tuition. Two states, Pennsylvania and Texas offer programs which do not ask for a premium as long as you use the tuition vouchers for state schools. In the Texas case, you receive fund performance if you elect to go to a non-state school. Virginia's program appears to be offering tomorrow's tuition at a slight discount even compared to today's tuition rates if one goes to the most expensive state school. Otherwise, you would be paying a premium. For most of the state programs, tuition inflation will have to accelerate considerably for the programs to be worthwhile. Still, though purchasers of prepaid tuition vouchers pay a premium, the states are still on the hook if tuition inflation does get out of hand.

Thursday, February 2, 2012

Saving Up for College Tuition and Hedging, Part 3

Ever since the government permitted it, many private colleges have been hopping onto the tuition prepayment plan bandwagon. Unlike the College Board's IC 500 index, tuition prepayment often does not include room and board increases. Colleges including some of the Ivies (e.g., Dartmouth, Penn, Princeton), MIT, Stanford, UChicago, and USC tout the private college prepaid plan. For a complete list of the 270+ private schools using this plan, see the consortium's website (managed by OppenheimerFunds, which also happens to manage many of the state 529 plans). States sponsor their own, but some are portable and can be used to fund tuition at out-of-state private schools or even select foreign ones.

Wednesday, February 1, 2012

Saving Up for College Tuition and Hedging, Part 2

To answer the question of college tuition hedging, we need to determine the amount of tuition increases and the variability in that change. Generally, higher education revenues come from federal and state aid, alumni giving, endowment returns, and tuition. For research universities, a big chunk comes from research grants. Thus, changes in funding levels for each of these components must be compensated by the others. How have these factors evolved in the past few decades? Can we explain tuition inflation in terms of these other factors?

This is second in my on-going series of posts on college tuition and investment. See the first post.