8/6/20: 30 years of Financial Markets Manipulation

Students in my course Applied Investment and Trading in TCD would be familiar with the market impact of the differential bid-ask spreads in intraday trading. For those who might have forgotten, and those who did not take my course, here is the reminder: early in the day (at and around market opening times), spreads are wide and depths of the market are thin (liquidity is low); late in the trading day (closer to market close), spreads are narrow and depths are thick (liquidity is higher). Hence, a trading order placed near market open times tends to have stronger impact by moving the securities prices more; in contrast, an equally-sized order placed near market close will have lower impact.

Now, you will also remember that, in general, investment returns arise from two sources: 

1. Round-trip trading gains that arise from buying a security at P(1) and selling it one period later at P(2), net of costs of buy and sell orders execution; and 
2. Mark-to-market capital gains that arise from changes in the market-quoted price for security between times P(1) and P(2+).

The long-running 'Strategy' used by some institutional investors is, therefore as follows: 

Here is the illustration of the 'Strategy' via Bruce Knuteson paper "Celebrating Three Decades of Worldwide Stock Market Manipulation", available here: https://arxiv.org/pdf/1912.01708.pdf.

• Step 1: Accumulate a large long portfolio of assets;
• Step 2: At the start of the day, buy some more assets dominating your portfolio at P(1) - generating larger impact of your buy orders, even if you are carrying a larger cost adverse to your trade;
• Step 3: At the end of the day, sell at P(2) - generating lower impact from your sell orders, again carrying the cost.

On a daily basis, you generate losses in trading account, as you are paying higher costs of buy and sell orders (due to buy-sell asymmetry and intraday bid-ask spreads differences), but you are also generating positive impact of buy trades, net of sell trades, so you are triggering positive mark-to-market gains on your original portfolio at the start of the day.

Knuteson shows that, over the last 30 years, overnight returns in the markets vastly outstrip intraday returns. 

Per author, "The obvious, mechanical explanation of the highly suspicious return patterns shown in Figures 2 and 3 is someone trading in a way that pushes prices up before or at market open, thus causing the blue curve, and then trading in a way that pushes prices down between market open (not including market open) and market close (including market close), thus causing the green curve. The consistency with which this is done points to the actions of a few quantitative trading firms rather than

the uncoordinated, manual trading of millions of people."

Sounds bad? It is. Again, per Knuteson: "The tens of trillions of dollars your use of the Strategy has created out of thin air have mostly gone to the already-wealthy: 

• Company executives and existing shareholders benefi tting directly from rising stock prices; 
• Owners of private companies and other assets, including real estate, whose values tend to rise and fall with the stock market; and 
• Those in the financial industry and elsewhere with opportunities to privatize the gains and socialize the losses."

These gains to capital over the last three decades have contributed directly and signi ficantly to the current level of wealth inequality in the United States and elsewhere. As a general matter, widespread mispricing leads to misallocation of capital and human effort, and widespread inequality negatively a effects our social structure and the perceived social contract."

16/5/17: Insiders Trading: Concentration and Liquidity Risk Alpha, Anyone?

Disclosed insiders trading has long been used by both passive and active managers as a common screen for value. With varying efficacy and time-unstable returns, the strategy is hardly a convincing factor in terms of identifying specific investment targets, but can be seen as a signal for validation or negation of a previously established and tested strategy.

Much of this corresponds to my personal experience over the years, and is hardly that controversial. However, despite sufficient evidence to the contrary, insiders’ disclosures are still being routinely used for simultaneous asset selection and strategy validation. Which, of course, sets an investor for absorbing the risks inherent in any and all biases present in the insiders’ activities.

In their March 2016 paper, titled “Trading Skill: Evidence from Trades of Corporate Insiders in Their Personal Portfolios”, Ben-David, Itzhak and Birru, Justin and Rossi, Andrea, (NBER Working Paper No. w22115: http://ssrn.com/abstract=2755387) looked at “trading patterns of corporate insiders in their own personal portfolios” across a large dataset from a retail discount broker. The authors “…show that insiders overweight firms from their own industry. Furthermore, insiders earn substantial abnormal returns only on stocks from their industry, especially obscure stocks (small, low analyst coverage, high volatility).” In other words, insiders returns are not distinguishable from liquidity risk premium, which makes insiders-strategy alpha potentially as dumb as blind ‘long lowest percentile returns’ strategy (which induces extreme bias toward bankruptcy-prone names).

The authors also “… find no evidence that corporate insiders use private information and conclude that insiders have an informational advantage in trading stocks from their own industry over outsiders to the industry.”

Which means that using insiders’ disclosures requires (1) correcting for proximity of insider’s own firm to the specific sub-sector and firm the insider is trading in; (2) using a diversified base of insiders to be tracked; and (3) systemically rebalance the portfolio to avoid concentration bias in the stocks with low liquidity and smaller cap (keep in mind that this applies to both portfolio strategy, and portfolio trading risks).

28/8/15: Gold & Silver: Does technical analysis beat the market?

An interesting piece of research co-authored by Brian Lucey on efficacy of technical analysis in gold & silver markets: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2652637.

"This paper studies whether intraday technical trading rules produce significant payoffs in the gold and silver market using three popular moving average rules."

And the conclusions are (emphasis is mine): "The initial results show that the SMA, WMA and EMA trading rules generate significant negative payoffs using the parameters common in the literature in the high-frequency gold and silver markets. This suggests that there is no significant profit to be gained from technical trading in the gold and silver markets. However, our parameter sweep results show that there are a number of parameter combinations that generate significant profit in the gold market, but none in the silver market. Further, the best performing rules have different parameters to those used the existing literature. We show that longer run averages should be used by investors on intraday data and that investors need to employ different parameters when utilising technical analysis on daily and intraday data. In order to examine whether investors could have actually utilised the best performing rules, we perform an in- and out-of-sample test and show that only the SMA rule for gold generates significant profits in the in-sample as well as the out-of-sample period. All of the other best rules in the in-sample period generate either insignificant or negative payoffs in the out-of-sample period."

12/11/2014: Traders 2.0: Emotionlessly Perfect and Perfectly Inhuman

My blogpost for Learn Signal blog on innovation in trading relating to neuro-finance is available here: http://blog.learnsignal.com/?p=117

14/2/2014: Buffett's Alpha Demystified... or not?

Warren Buffett is probably the most legendary of all investors and his Berkshire Hathaway, despite numerous statements by Buffett explaining his investment philosophy, is still shrouded in a veil of mystery and magic.

The more you wonder about Buffett's fantastic historical track record, the more you ask whether the returns he amassed are a matter of luck, skill, unique strategy or all of the above.

"Buffett’s Alpha" by Andrea Frazzini, David Kabiller, and Lasse H. Pedersen (NBER Working Paper 19681 http://www.nber.org/papers/w19681, November 2013) shows that "looking at all U.S. stocks from 1926 to 2011 that have been traded for more than 30 years, …Berkshire Hathaway has the highest Sharpe ratio among all. Similarly, Buffett has a higher Sharpe ratio than all U.S. mutual funds that have been around for more than 30 years." In fact, for the period 1976-2011, Berkshire Hathaway realized Sharpe ratio stands at impressive 0.76, and "Berkshire has a significant alpha to traditional risk factors." According to the authors, "adjusting for the market exposure, Buffett’s information ratio is even lower, 0.66. This Sharpe ratio reflects high average returns, but also significant risk and periods of losses and significant drawdowns."

According to authors, this begs a question: "If his Sharpe ratio is very good but not super-human, then how did Buffett become among the richest in the world?"

The study looks at Buffett's performance and finds that "The answer is that Buffett has boosted his returns by using leverage, and that he has stuck to a good strategy for a very long time period, surviving rough periods where others might have been forced into a fire sale or a career shift. We estimate that Buffett applies a leverage of about 1.6-to-1, boosting both his risk and excess return in that proportion."

The conclusion is that "his many accomplishments include having the conviction, wherewithal, and skill to operate with leverage and significant risk over a number of decades."


But the above still leaves open a key question: "How does Buffett pick stocks to achieve this attractive return stream that can be leveraged?"

The authors "…identify several general features of his portfolio: He buys stocks that are
-- “safe” (with low beta and low volatility),
-- “cheap” (i.e., value stocks with low price-to-book ratios), and
-- high-quality (meaning stocks that profitable, stable, growing, and with high payout ratios).
This statistical finding is certainly consistent with Graham and Dodd (1934) and Buffett’s writings, e.g.: "Whether we’re talking about socks or stocks, I like buying quality merchandise when it is marked down"  – Warren Buffett, Berkshire Hathaway Inc., Annual Report, 2008."


Of course, such a strategy is not novel and Ben Graham's original factors for selection are very much in line with it, let alone more sophisticated screening factors. Everyone knows (whether they act on this knowledge or not is a different matter altogether) that low risk, cheap, and high quality stocks "tend to perform well in general, not just the ones that Buffett buys. Hence, perhaps these characteristics can explain Buffett’s investment? Or, is his performance driven by an idiosyncratic Buffett skill that cannot be quantified?"

The authors look at these questions as well. "The standard academic factors that capture the market, size, value, and momentum premia cannot explain Buffett’s performance so his success has to date been a mystery (Martin and Puthenpurackal (2008)). Given Buffett’s tendency to buy stocks with low return risk and low fundamental risk, we further adjust his performance for the Betting-Against-Beta (BAB) factor of Frazzini and Pedersen (2013) and the Quality Minus Junk (QMJ) factor of Asness, Frazzini, and Pedersen (2013)."

And then 'Eureka!': "We find that accounting for these factors explains a large part of Buffett's performance. In other words, accounting for the general tendency of high-quality, safe, and cheap stocks to outperform can explain much of Buffett’s performance and controlling for these factors makes Buffett’s alpha statistically insignificant… Buffett’s genius thus appears to be at least partly in recognizing early on, implicitly or explicitly, that these factors work, applying leverage without ever having to fire sale, and sticking to his principles. Perhaps this is what he means by his modest comment: "Ben Graham taught me 45 years ago that in investing it is not necessary to do extraordinary things to get extraordinary results." – Warren Buffett, Berkshire Hathaway Inc., Annual Report, 1994."


There is more to be asked about Warren Buffett's investment style and strategy. "…we consider whether Buffett’s skill is due to his ability to buy the right stocks versus his ability as a CEO. Said differently, is Buffett mainly an investor or a manager?"

Authors oblige: "To address this, we decompose Berkshire’s returns into a part due to investments in publicly traded stocks and another part due to private companies run within Berkshire. The idea is that the return of the public stocks is mainly driven by Buffett’s stock selection skill, whereas the private companies could also have a larger element of management."

Another 'Eureka!' moment beckons: "We find that both public and private companies contribute to Buffett’s performance, but the portfolio of public stocks performs the best, suggesting that Buffett’s skill is mostly in stock selection. Why then does Buffett rely heavily on private companies as well, including insurance and reinsurance businesses? One reason might be that this structure provides a steady source of financing, allowing him to leverage his stock selection ability. Indeed, we find that 36% of Buffett’s liabilities consist of insurance float with an average cost below the T-Bill rate.


So core conclusions on Buffett's genius: "In summary, we find that Buffett has developed a unique access to leverage that he has invested in safe, high-quality, cheap stocks and that these key characteristics can largely explain his impressive performance. Buffett’s unique access to leverage is consistent with the idea that he can earn BAB returns driven by other investors’ leverage constraints. Further, both value and quality predict returns and both are needed to explain Buffett’s performance. Buffett’s performance appears not to be luck, but an expression that value and quality investing can be implemented in an actual portfolio (although, of course, not by all investors who must collectively hold the market)."

Awesome study!