Building a Financial Research Library has been a long time ambition of mine so it was great to finally get it off the ground earlier this year. The library currently consists of approximately 400 papers and is growing all the time.

Here are the most viewed papers since we relaunched in July.

Studies of interactions between human traders and Algorithmic Trading Systems
This review was commissioned as part of the UK Government’s Foresight Project, The Future of Computer Trading in Financial Markets.
This document reviews the very small amount of published literature that describes scientific studies of interactions between human and robot traders under experimental conditions. The author'scontend that the relative lack of such studies is a serious omission from the literature.

Noise
Fischer Black
This classic paper from 1985 discusses the effects of noise on the world, and on our view of the world, concluding that noise makes it very difficult to test either practical or academic theories about the way that financial or economic markets work.

High-Frequency Trading: Methodologies and Market Impact
Frank J. Fabozzi, Sergio M. Focardi, and Caroline Jonas
This paper discusses the state of the art of high-frequency trading and its requisite input, high-frequency data, the econometrics of which mark a significant departure from the econometrics used when dealing with lower frequencies.

Backbone of complex networks of corporations: The flow of control
J.B. Glattfelder and  S. Battiston
It turns out that the insight gained from a simple network analysis - that ownership and control of companies is distributed over large numbers of people - is entirely misleading. When new factors, such as the way ownership changes as shares are bought and sold, are included, it turns out that stock markets are controlled by a very small number of  companies.

High-frequency trading in the foreign exchange market
Bank for International Settlements
A timely input to the ongoing discussion about the impact of technological changes, including the rise of algorithmic trading in general and HFT in particular, on the functioning and integrity of financial markets. The FX market focus of this report complements a discussion that has so far been based mostly on developments in equity markets.

Locking in the Profits or Putting It All on Black? An Empirical Investigation into the Risk-Taking Behavior of Hedge Fund Managers
Andrew Clare, Nick Motson
In this paper, using a large database of hedge fund returns, the authors examine the risk taking behaviour of hedge fund managers in response to both their past returns relative to their high-water mark and their past returns relative to their peer group.

Psychology and Economics: Evidence from the Field (pdf)
Stefano DellaVigna
Research in Behavioral Economics suggests that individuals deviate from the standard model in three respects: (i) non-standard preferences; (ii) non-standard beliefs; and (iii) non-standard decision-making. This paper surveys the empirical evidence from the field on these three classes of deviations.

Twitter mood predicts the stock market
Johan Bollen, Huina Mao, Xiao-Jun Zeng
Behavioral economics tells us that emotions can profoundly affect individual behavior and decision-making. Does this also apply to societies at large? This paper investigates whether measurements of collective mood states derived from large-scale Twitter feeds are correlated to the value of the Dow Jones Industrial Average over time.

Machine Learning Markets
Amos Storkey
Prediction markets show considerable promise for developing flexible mechanisms for machine learning and in this paper, machine learning markets for multivariate systems are defined, and a utility-based framework is established for their analysis.

Credit Ratings Across Asset Classes: A ≡ A?
Jess Cornaggia, Kimberly Rodgers Cornaggia, John Hund
Contrary to assertions by the Big 3 credit raters, credit ratings are not comparable across asset classes.

Markets are Efficient if and Only if P = NP
Philip Maymin
This paper claims to prove that if markets are efficient, meaning current prices fully reflect all information available in past prices, then P = NP, meaning every computational problem whose solution can be verified in polynomial time can also be solved in polynomial time.

Featured Topics in the Research Library