Altreva Adaptive Modeler is a software application for creating agent-based financial market simulation models for the purpose of forecasting prices of real world market traded stocks or other securities. The technology it uses is based on the theory of

agent-based computational economics Agent-based computational economics (ACE) is the area of computational economics that studies economic processes, including whole economies, as dynamic systems of interacting agents. As such, it falls in the paradigm of complex adaptive systems. I ...

(ACE), the computational study of economic processes modeled as dynamic systems of interacting

heterogeneous agents In economic theory and econometrics, the term heterogeneity refers to differences across the units being studied. For example, a macroeconomic model in which consumers are assumed to differ from one another is said to have heterogeneous agents. U ...

. Altreva's Adaptive Modeler and other agent-based models are used to simulate financial markets to capture the complex dynamics of a large diversity of investors and traders with different strategies, different trading time frames, and different investment goals. Agent-based models based on heterogeneous and boundedly rational (learning) agents have shown to be able to explain the empirical features of financial markets better than traditional financial models that are based on

representative Representative may refer to: Politics * Representative democracy, type of democracy in which elected officials represent a group of people * House of Representatives, legislative body in various countries or sub-national entities * Legislator, som ...

rational Rationality is the quality of being guided by or based on reasons. In this regard, a person acts rationally if they have a good reason for what they do or a belief is rational if it is based on strong evidence. This quality can apply to an abili ...

agents.

Technology

The software creates an agent-based model for a particular stock, consisting of a population of trader agents and a virtual market. Each agent represents a virtual trader/investor and has its own

trading rule Trade involves the transfer of goods and services from one person or entity to another, often in exchange for money. Economists refer to a system or network that allows trade as a market (economics), market. An early form of trade, barter, s ...

and funds. The model is then evolved step by step in the following way: At every step a new (historical) real market price is imported. All agents evaluate their trading rule and place orders on the virtual market. The virtual market then determines the clearing price and executes all matching orders. The clearing price is taken as the forecast for the next step real market price. (So the virtual market serves as a one-step-ahead

prediction market Prediction markets (also known as betting markets, information markets, decision markets, idea futures or event derivatives) are open markets where specific outcomes can be predicted using financial incentives. Essentially, they are exchange-trad ...

for the real market). This process is repeated for every new received real market price. Meanwhile, the trading rules evolve through a special adaptive form of

genetic programming In artificial intelligence, genetic programming (GP) is a technique of evolving programs, starting from a population of unfit (usually random) programs, fit for a particular task by applying operations analogous to natural genetic processes to t ...

. The forecasts are thus based on the behavior of the entire market instead of only the best performing trading rule. This intends to increase the robustness of the model and its ability to adapt to changing market circumstances. To avoid

overfitting mathematical modeling, overfitting is "the production of an analysis that corresponds too closely or exactly to a particular set of data, and may therefore fail to fit to additional data or predict future observations reliably". An overfitt ...

(or

curve-fitting Curve fitting is the process of constructing a curve, or function (mathematics), mathematical function, that has the best fit to a series of data points, possibly subject to constraints. Curve fitting can involve either interpolation, where an e ...

) to historical data - and unlike many other techniques used in trading software such as optimizing of trading rules by repeated

backtesting Backtesting is a term used in modeling to refer to testing a predictive model on historical data. Backtesting is a type of retrodiction, and a special type of cross-validation applied to previous time period(s). Financial analysis In a tradin ...

genetic algorithms In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to gene ...

and

neural networks A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological ...

- Adaptive Modeler does not optimize trading rules on historical data. Instead its models evolve incrementally over the available price data so that agents experience every price change only once (as in the real world). Also there is no difference in the processing of historical and new price data. Therefore, there is no specific reason to expect that a model's back-tested historical performance is better than its future performance (unlike when trading rules have been optimized on historical data). The historical results can therefore be considered more meaningful than results demonstrated by techniques based on optimization.

Examples and use cases

In an example model for the

S&P 500 The Standard and Poor's 500, or simply the S&P 500, is a stock market index tracking the stock performance of 500 large companies listed on stock exchanges in the United States. It is one of the most commonly followed equity indices. As of D ...

index, Adaptive Modeler demonstrates significant risk-adjusted excess returns after transaction costs. On back-tested historical price data covering a period of 58 years (1950–2008) a compound average annual return of 20.6% was achieved, followed by a compound average annual return of 22.2% over the following 6 year out-of-sample period (2008-2014). Adaptive Modeler was used in a study to demonstrate increased complexity of trading rules in an evolutionary forecasting model during a critical period of a company's history. In a study of profitability of technical trading in the

foreign exchange market The foreign exchange market (Forex, FX, or currency market) is a global decentralized or over-the-counter (OTC) market for the trading of currencies. This market determines foreign exchange rates for every currency. It includes all aspec ...

s, researchers using Adaptive Modeler found economically and statistically significant out-of-sample excess returns (after transaction costs) for the six most traded currency pairs. The returns were superior to those achieved by traditional econometric forecasting models. Adaptive Modeler was also used to study the impact of different levels of trader rationality on market properties and

efficiency Efficiency is the often measurable ability to avoid wasting materials, energy, efforts, money, and time in doing something or in producing a desired result. In a more general sense, it is the ability to do things well, successfully, and without ...

. It was found that artificial markets with more intelligent traders (compared to markets with less intelligent or zero-intelligence traders) showed improved forecasting performance, though also experienced higher volatility and lower trading volume (consistent with earlier findings). The markets with more intelligent traders also replicated the

stylized fact In social sciences, especially economics, a stylized fact is a simplified presentation of an empirical finding. Stylized facts are broad tendencies that aim to summarize the data, offering essential truths while ignoring individual details. A prom ...

s of real financial markets the best. As an example of virtual intelligent life in a

complex system A complex system is a system composed of many components which may interact with each other. Examples of complex systems are Earth's global climate, organisms, the human brain, infrastructure such as power grid, transportation or communication ...

(such as a stock market), Adaptive Modeler was used as an illustration of simple agents interacting in a complex (

nonlinear In mathematics and science, a nonlinear system is a system in which the change of the output is not proportional to the change of the input. Nonlinear problems are of interest to engineers, biologists, physicists, mathematicians, and many other ...

) way to forecast stock prices.{{cite web, title=Applying Emergent Behaviour in the Financial Markets, url=http://louisecypher.com/purevil.com/emergenceinfinance.pdf, publisher=Evil Ltd., accessdate=29 October 2014

References

Financial markets software Agent-based software Technical analysis software Simulation software

Technology

Examples and use cases

See also

References