Financial Tools
Warning: all others tools have been moved to Financial.
Objective
Create an economically self-sustaining (learning) system.
Solutions
API
Raw
- generate a new bank account
- set up a cloud service with this bank account
- select a statistical analysis framework
- install it on the cloud service
- start the framework to issue and log decisions
- set up a finance API with this bank account
- issue trades resulting from generated decisions*
Single simulation refinement
- set up the raw version
- replace the finance API by a virtual portfolio APIpt
Multi simulations refinement
- set up a single simulation version
- duplicate it changing the model used
- order the resulting models based α
- overall performance
- minimum risks
Mult-agent refinement
- run the raw version
- add external information APIs
- order by return on investment
- re-allocate resources accordingly K
- re-allocate resources accordingly K
All those, especially the Multi simulations refinement, can benefit from the FOSS community model and, for example, exchange simulations results (or even trade them but this, not gaining from others simulations).
"Finance or real"
Note that this last step is precisely what differentiate a "classical business" that does produce physical good or services by producing a margin. In this situation the core competency is strictly financial instead of being secondly financial (managing the margins).
Consequently the same overall system could be used to other businesses by changing this final step to the core competency of the corporation.
Warning
- The Fourth Quadrant: a map of the limits of statistics by Nassim Nicholas Taleb for Edge, 2008
- David Cameron in Conversation with Nassim Taleb, Royal Society for the encouragement of Arts, August 2009
References
- Quantitative Trading: How to Build Your Own Algorithmic Trading Business by Ernest Chan, Wiley 2008
- see also my reading notes QuantitativeTrading
- and the resulting FinancialTools.QuantitativeTradingBookAnswers
- see also my reading notes QuantitativeTrading
- Automated Trading and Cloud Computing, The Online Investing AI Blog April 2009
- R/Finance 2009: Applied Finance with R first annual R/Finance conference for applied finance using R
- MLOSS.org Machine Learning Open Source Software
- Finance group, Ecole Polytechnique, Paris
- Homepage of Nicole EL KAROUI, Professor of Applied Mathematics, Ecole Polytechnique, Paris
- Using Genetic and Evolutionary Algorithms to Build a Trading Model from Neural Market Trends
- TheTechnicalTrader.net : Live Technical Analysis
- Cybernetic Trading Strategies - Developing a Profitable Trading System with State-of-the-art Technologies by Murray Ruggiero Jnr, Wiley 1997
- Algorithmic Finance journal
CONTENT
CONTACT
UPDATES
LAST TWEET
RSS for this page only


