J. Doyne Farmer

From Wikipedia, the free encyclopedia
Jump to: navigation, search
J. Doyne Farmer
J. Doyne Farmer.jpg
Born 22 June 1952
Houston, Texas
Residence United States
Nationality United States
Fields Physics
Finance
Institutions Oxford University
Santa Fe Institute
Los Alamos National Laboratory
Alma mater Stanford University
University of California, Santa Cruz
Doctoral students Arnaud Trébaol

J. Doyne Farmer (born 1952) is an American physicist and entrepreneur, with interests in chaos theory, complexity and econophysics. He is a former professor at the Santa Fe Institute and member of Eudaemonic Enterprises. He is currently a Professor of Mathematics at Oxford University, where he is the Director of Complexity Economics at the Institute for New Economic Thinking (INET) at the Oxford Martin School in Oxford and remains affiliated with the Santa Fe Institute as an External Professor.

Biography[edit]

Born in Houston, Texas, Farmer spent most of his early life in Silver City, New Mexico, where he met Tom Ingerson, a young physicist and boy scout leader who helped inspire Farmer's attraction to physics.[1] Farmer initially followed Ingerson to the University of Idaho where he spent one year as an undergraduate before breaking out on his own and transferring to Stanford University, graduating in 1973 with BS in Physics.[1] Farmer stayed in California for graduate school at the University of California, Santa Cruz (UCSC). Here he studied astrophysics with George Blumenthal before switching his dissertation topic to chaotic dynamics, a field that evolved from Farmer's intense study of the physics of roulette and fascination with the problem of prediction.[2] While at UCSC, Farmer was a founding member of the Dynamical Systems Collective (also known as the Chaos Cabal) alongside Norman Packard, Robert Shaw, and James Crutchfield.[3] The collective was best known for its work in probing chaotic systems for signs of order. Farmer received his PhD in Physics from Santa Cruz in 1981.

After finishing his doctorate in 1981, Farmer took a post-doctoral appointment in the Centre for Nonlinear Studies at the Los Alamos National Laboratory and received a prestigious Oppenheimer Fellowship in 1983.[4] In 1988 Farmer founded the Complex Systems Group in the Theoretical Division and recruited a group of postdoctoral fellows who subsequently became global leaders in the new field of complex systems. During this time Farmer wrote several papers modelling the immune system and the origin of life, introducing the concept of metadynamics, i.e. dynamical systems that define a network that evolves conditionally based on dynamical outcomes.[5][6] He also continued his research on nonlinear dynamics and chaos, where his work included developing new algorithms for nonlinear time series forecasting and noise reduction.

In 1991 Farmer gave up his position at Los Alamos, reunited with Norman Packard and James McGill, and returned to his prediction roots by co-founding the Prediction Company.[7] A co-President of the company, Farmer was also Chief Scientist and led the research group and developed one of the earliest fully quantitative trading systems. Their underlying strategy was based on (what is now called) statistical arbitrage, but it included a variety of different signals, including a high frequency forecasting model as an overlay to reduce transaction costs. The intent of the company was to create automated trading systems for a variety of commodity and securities markets, making predictions of trends using principles of physics, particularly Chaos Theory (e.g., exploiting Takens's state space reconstruction[8]) and what is known today statistical learning theory.[9]

Farmer left Prediction Company in 1999 to return to academic research at the Santa Fe Institute (SFI), a non-profit organisation that specialised in complex systems. His time at Prediction Company led Farmer to believe that key concepts and approaches were missing from financial economics, so he took his academic research in this direction, building on his earlier background in complex systems and the domain knowledge acquired at Prediction Company. Having made statistical/machine learning models that produced results without providing a causal description, Farmer pursued the understanding how financial markets work and searched for possible laws governing their behaviour.[10]

While at SFI Farmer became one of several founders of the field of “econophysics”.[11] This is distinguished by a more empirically-driven approach to building fundamental models, breaking away from the standard theoretical template used in economics of utility maximization and equilibrium. Together with Michael Dempster of Cambridge, Farmer started a new journal called Quantitative Finance, and served as the co-editor-in-chief for several years.

His own research accomplishments during this time included developing a theory of market ecology and making many contributions to market microstructure.[12][13] On the empirical side, with his collaborators , Farmer identified several striking empirical regularities in financial markets, such as the extraordinary persistence of order flow, which says that imbalances in buying or selling are extremely persistent.[14][15] His most important contributions were in relation to the law of market impact, which states that the average change in price due to new supply or demand entering the is proportional to the square root of the order size.[16] Farmer has worked on both documenting this empirically, providing the foundational work that led to its explanation, and developing the explanation itself. This law is remarkable as it is universal, in the sense that the functional form of market impact remains the same as long as markets are operating under “normal” conditions.

In 2012, Farmer left the Santa Fe Institute for Oxford University, where he now co-directs the Oxford Martin Programme on Complexity.[17]

Work[edit]

Eudaemonic Enterprises[edit]

The Eudaemons were a small group headed by graduate physics students Doyne Farmer and Norman Packard at the University of California, Santa Cruz in the late 1970s.[18] The group's immediate objective was to find a way to beat roulette, but a loftier objective was to use the money made from roulette to fund a scientific community. The name of the group was inspired by eudaimonia, a philosophical ability which suffices for living well.

While a graduate student Doyne Farmer and other students from the University of California, Santa Cruz, spent several years researching a physics-based system that could predict outcomes of roulette games. During this time the group built a series of computers that were capable of calculating the motion of a moving ball, and trials in Las Vegas showed success. However, because of technical faults with computer equipment, the success was only partial and the technology was not feasible to use to make large profits. There is a book written about this project called The Eudaemonic Pie / Newton's Casino.[1]

Prediction Company[edit]

Farmer left Los Alamos in 1991 and co-founded The Prediction Company with Norman Packard and Jim McGill to apply principles of physics and mathematics to the financial sector. From 1991 to 1999 Doyne held the position of Chief Scientist and from 1995 to 1999 the position of co-president.

Other interests[edit]

Farmer is a co-founder of the Atalaya Institute, a new and independent public policy institute in Santa Fe and is currently part of the steering committee.[17]

In popular culture[edit]

Farmer and Packard's work toward predicting outcomes of roulette games, along with their actual attempt at a Las Vegas casino, has been featured in the 2004 Breaking Vegas series documentary, "Beat the Wheel".

See also[edit]

References[edit]

  1. ^ a b c Bass, Thomas (1991). The Newtonian Casino. Penguin. ISBN 978-0-14-014593-9. 
  2. ^ "Doyne Farmer's Santa Fe Institute CV" (PDF). 
  3. ^ Gleick, James (1987). Chaos: Making a New Science. Viking Books. ISBN 9780749386061. 
  4. ^ "Edge member biography". 
  5. ^ Farmer, Doyne (1982). "Chaotic attractors of an infinite-dimensional dynamical system". Physica D: Nonlinear Phenomena 4 (3): 366–393. 
  6. ^ Farmer, Doyne; Packard, Norman; Perelson, Alan (1986). "The immune system, adaptation, and machine learning". Physica D: Nonlinear Phenomena 22 (1-3): 187–204. 
  7. ^ "Santa Fe Institute short biography". 
  8. ^ Farmer J.D. & Sidorowich J.J. 1987. Phys. Rev. Lett. 59, 845
  9. ^ Pardo, Robert (2008). Evaluation and Optimization of Trading Strategies. John Wiley & Sons. ISBN 9780470262856. 
  10. ^ Farmer, Doyne (1999). "Physicists attempt to scale the ivory towers of finance". Computing in Science & Engineering 1 (6): 26–39. 
  11. ^ Lillo, F.; Farmer, J. D.; Mantegna, R. (2003). "Econophysics: Master curve for price-impact function.". Nature 421 (6919): 129–130. 
  12. ^ Farmer, J. D. (2002). "Market Force, Ecology, and Evolution". Industrial and Corporate Change 11 (5): 895–953. 
  13. ^ Farmer, J. D. (2003). "Looking Forward to the Future". Quantitative Finance 3 (3): C30. 
  14. ^ Farmer, J.D.; Joshi, S. (2002). "The Price Dynamics of Common Trading Strategies". Journal of Economic Behavior and Organization 49 (2): 149–171. 
  15. ^ Zorko, I.; Farmer, J. D. (2002). "The Power of Patience: A Behavioral Regularity in Limit Order Placement". Quantitative Finance 2 (5): 387–392. 
  16. ^ "Market Impact and Trading Profile of Hidden Orders in Stock Markets". Physical Review 80 (6). 2009. 
  17. ^ a b "INET Oxford biography". 
  18. ^ "People, Department of Physics, University of California Santa Cruz". 

External links[edit]