The Factor-Portfolios Approach to Asset Management using Genetic Algorithms

We present an investment process that: (i) decomposes securities into risk factors; (ii) allows for the construction of portfolios of assets that would selectively expose the manager to desired risk factors; (iii) perform a risk allocation between these portfolios, allowing for tracking error restrictions in the optimization process and (iv) give the flexibility to manage dinamically the transfer coeffficient (TC). The contribution of this article is to present an investment process that allows the asset manager to limit risk exposure to macro-factors - including expectations on correlation dynamics - whilst allowing for selective exposure to risk factors using mimicking portfolios that emulate the behaviour of given specific. An Artificial Intelligence (AI) optimisation technique is used for risk-budget allocation to factor-portfolios.Active Management, Portfolio Optimization, Genetic Algorithms, Propensities. Classification JEL: G11; G14; G32.

Artificial Markets under a Complexity Perspective

The focus of this study is to build, from the ‘bottom-up’, a market with artificially intelligent adaptive agents based on the institutional arrangement of the Colombian Foreign Exchange Market (1994-1999) in order to determine simple agents’ design, rules and interactions that are sufficient to create interesting behaviours at the macroscopic level - emerging patterns that replicate the properties of the time series from the case study. Tools from artificial intelligence research, such as genetic algorithms and fuzzy logic, are the basis of the agents’ mental models, which in turn are used for forecasting, quoting and learning purposes in a double auction market. Sets of fuzzy logic rules yield adequate, approximately continuous risk and utility preferences without the need to fix their mathematical form ex-ante. Statistical properties of financial time series are generated by the artificial market, as well as some additional non-linearity linked to the existence of a crawling band. Moreover, the behaviour of the simulated exchange rate is consistent with currency band theory. Agent’s learning favours forecasting rules based on regulatory signals against rules based on fundamental information. Also, intra-day volatility is strongly linked to the rate of arrival and size of real sector trades. Intra-day volatility is also a function of the frequency of learning and search specialisation. It is found that when a moderately low frequency of learning is used, volatility increases.Adaptive agents, artificial markets, constrained generating procedures, fuzzy logic and genetic algorithms. Classification JEL: G1; G12; G39.

Investment horizon dependent CAPM : adjusting beta for long-term dependence

Financial basics and intuition stresses the importance of investment horizon for risk management and asset allocation. However, the beta parameter of the Capital Asset Pricing Model (CAPM) is invariant to the holding period. Such contradiction is due to

Artificial markets under a complexity perspective

The focus of this study is to build, from the "bottom-up", a market with artificially intelligent adaptive agents based on the institutional arrangement of the Colombian Foreign Exchange Market (1994-1999) in order to determine simple agents' design, rul

The factor-portfolios approach to asset management using genetic algorithms

We present an investment process that: (i) decomposes securities into risk factors; (ii) allows for the construction of portfolios of assets that would selectively expose the manager to desired risk factors; (iii) perform a risk allocation between these

The case for macro risk budgeting and portfolio tranching in reserves management

The set of objectives in reserves management are normally predefined and include: protecting the economy against potential external shocks on the current account or on capital flows; invest the reserves minimizing the potential of a loss and ensuring the availability of international liquidity when necessary. Whereas the adoption of a floating exchange rate in theory reduces the need for reserves to protect against external shocks, in the context of free capital movements it will be a function of the efficiency of international markets. Recently, given the increase in the size of the foreign reserves in recent decades for some central banks, as a result and in response to globalization and more volatility on currency flows, portfolio foreign investment and other related factors as contagion effects, the pressure to generate long-term returns has increased. However, the goal of increased returns is subdued to the security and liquidity objectives in international reserves management. As a result, the process of asset allocation and the construction of an efficient set of investment guidelines, as well as a risk policy, must be framed by a liquidity policy and, generally, to an asymmetric exposure to risk where capital loses are to be avoided in specific time horizons; i.e. a fiscal year. Tomado de la introducción a este documento1.Introduction. Pág.2 2.Asset allocation. Pág.4 3.Active management. Pág.7 4.Conclusions. Pág.1

The case for active management from the perspective of complexity theory

This paper approaches active management of baskets of currencies from the perspective of Complexity theory, where the market is analysed as a Complex Adaptive system. A basket of currencies is constructed using objective probabilities (propensities) and