The basis of our paper is that dividends are not exogenous but increase with the wealth invested in an asset, as is the case in a production economy. We use an analogy between financial trading strategies and biological species and characterize an evolutionary stable strategy in an ecology with fix-mix strategies. showed that a simple EF model can explain the excess volatility of the S&P 500.

Excess volatility was first pointed out by Shiller who showed that the prices of the Standard and Poor's (S&P) 500 index are more volatile than the fundamental values computed with models of expected utility maximization given rational expectations. What has this new paradigm for finance achieved so far? On one hand, it has improved our understanding of the dynamics of asset prices since many stylized facts, such as, for instance, excess volatility, can be explained by the endogenous dynamics of wealth. In financial evolution, there are other methods of innovation including rational and behavioral aspects, e.g., backtesting and forward performance testing (often akin to adaptive heuristics in game theory ). In biological evolution this is mostly done by sexual reproduction along which genes are recombined. While the market selection force reduces the variety of species in the financial markets, Farmer also points out that there is a countervailing force that innovates new strategies. As Farmer notes, this evolution of wealth models the market selection process acting on the financial species, i.e., the investment strategies. Thus, in order to understand asset returns, which are the ratios of next period prices (plus eventual dividends) to current period prices, one needs to understand the evolution of wealth behind investment strategies. Equating aggregate demand with the supply of assets, asset prices are then the wealth-weighted average of a few investment strategies. Many empirical studies have shown that a few strate-gies are sufficient to understand the dynamics of thousands of assets. While this is a trivial operation mathematically, it shifts the focus away from the intentions behind the investment strategies (e.g., utility maximization subject to expectations) toward the actions taken in financial markets. Alternatively, one can group all investors' wealth following the same strategy into one entity and write market demand as the wealthweighted average of investment strategies. Indeed, in financial market models, one can write market demand for assets as the wealth-weighted average of investors' demand. This shift parallels biological models in which the interaction of species and not that of individual organisms are considered. In particular, it would be useful to make investment strategies and not investors the actors in the model. In the seminal Santa Fe Institute working paper 'Market Force, Ecology, and Evolution,' Farmer argues that financial market models can benefit from reasoning analogous to models of biological evolution. Research in EF was started by the Santa Fe Institute, and the first time the term 'evolutionary finance' appears is in one of its publications dating back to 1995.

Friedman, , Penrose, , and Nelson and Winter. A crucial role in the creation of this branch of economics was played by the works of Alchian, , Downie, D.

Schumpeter laid the groundwork for evolutionary economics in the 20th century.

Veblen (2) coined the term 'evolutionary economics' and started a systematic use of the evolutionary approach in the social sciences (3). However, as witnessed by the present special issue, the research on evolutionary finance (EF) is gaining traction.Įvolutionary ideas have a long history in the social sciences going back to Malthus, who played an inspirational role for Darwin. D espite bulls and bears adorning financial investors' desks and the financial press and traders' assurance that 'it's a jungle out there,' the emergence of evolutionary models in finance has been slow.

Andrew pecunia new york