IAS 19 valuations for DB Schemes – true or fair?

Purpose - This paper argues that the accounting standards’ requirement for pension scheme liabilities to be discounted by reference to market yields at the end of the reporting period on high quality corporate bonds, potentially produces an artificial result which is at odds with the “fair representation” objective of these standards. Design/methodology/approach –The approach is a theoretical analysis of the relevant reporting standards with the use of a theoretical example to demonstrate the impact where trustees adopt a hedged approach to portfolio investment. Findings - Where the fund has adopted a hedging strategy and has invested in “risk – free” assets, the term, quantity and duration/maturity of which, is intended to match the term quantity and maturity of the scheme liabilities, applying the requirements potentially results in the reporting in sponsoring company financial statements of fluctuating surpluses or deficits each year which are potentially ill-informed and misleading. Originality/value – Pension scheme surpluses or deficits reported in the financial statements of listed companies are potentially very significant numbers, however the dangers posed by theoretical nature of the calculation has largely gone unreported

IAS 19 valuations for DB Schemes – true or fair?

Purpose - This paper argues that the accounting standards’ requirement for pension scheme liabilities to be discounted by reference to market yields at the end of the reporting period on high quality corporate bonds, potentially produces an artificial result which is at odds with the “fair representation” objective of these standards. Design/methodology/approach –The approach is a theoretical analysis of the relevant reporting standards with the use of a theoretical example to demonstrate the impact where trustees adopt a hedged approach to portfolio investment. Findings - Where the fund has adopted a hedging strategy and has invested in “risk – free” assets, the term, quantity and duration/maturity of which, is intended to match the term quantity and maturity of the scheme liabilities, applying the requirements potentially results in the reporting in sponsoring company financial statements of fluctuating surpluses or deficits each year which are potentially ill-informed and misleading. Originality/value – Pension scheme surpluses or deficits reported in the financial statements of listed companies are potentially very significant numbers, however the dangers posed by theoretical nature of the calculation has largely gone unreported

M of a kind: A Multivariate Approach at Pairs Trading

Pairs trading is a popular trading strategy that tries to take advantage of market inefficiencies in order to obtain profit. Such approach, on its classical formulation, uses information of only two stocks (a stock and its pairs) in the formation of the trading signals. The objective of this paper is to suggest a multivariate version of pairs trading, which will try to create an artificial pair for a particular stock based on the information of m assets, instead of just one. The performance of three different versions of the multivariate approach was assessed for the Brazilian financial market using daily data from 2000 to 2006 for 57 assets. Considering realistic transaction costs, the analysis of performance was conducted with the calculation of raw and excessive returns, beta and alpha calculation, and the use of bootstrap methods for comparing performance indicators against portfolios build with random trading signals. The main conclusion of the paper is that the proposed version was able to beat the benchmark returns and random portfolios for the majority of the parameters. The performance is also found superior to the classic version of the strategy, Perlin (2006b). Another information derived from the research is that the proposed strategy picks up volatility from the data, that is, the annualized standard deviations of the returns are quite high. But, such event is “paid” by high positive returns at the long and short positions. This result is also supported by the positive annualized sharpe ratios presented by the strategy. Regarding systematic risk, the results showed that the proposed strategy does have a statistically significant beta, but it isn’t high in value, meaning that the relationship between return and risk for the trading rules is still attractive.pairs trading, asset allocation, quantitative strategy

Financial contagion: Evolutionary optimisation of a multinational agent-based model

Over the past two decades, financial market crises with similar features have occurred in different regions of the world. Unstable cross-market linkages during a crisis are referred to as financial contagion. We simulate crisis transmission in the context of a model of market participants adopting various strategies; this allows testing for financial contagion under alternative scenarios. Using a minority game approach, we develop an agent-based multinational model and investigate the reasons for contagion. Although the phenomenon has been extensively investigated in the financial literature, it has not been studied through computational intelligence techniques. Our simulations shed light on parameter values and characteristics which can be exploited to detect contagion at an earlier stage, hence recognising financial crises with the potential to destabilise cross-market linkages. In the real world, such information would be extremely valuable in developing appropriate risk management strategies

Applied Computational Intelligence for finance and economics

This article introduces some relevant research works on computational intelligence applied to finance and economics. The objective is to offer an appropriate context and a starting point for those who are new to computational intelligence in finance and economics and to give an overview of the most recent works. A classification with five different main areas is presented. Those areas are related with different applications of the most modern computational intelligence techniques showing a new perspective for approaching finance and economics problems. Each research area is described with several works and applications. Finally, a review of the research works selected for this special issue is given.Publicad

Price dynamics, informational efficiency and wealth distribution in continuous double auction markets

This paper studies the properties of the continuous double auction trading mechanishm using an artificial market populated by heterogeneous computational agents. In particular, we investigate how changes in the population of traders and in market microstructure characteristics affect price dynamics, information dissemination and distribution of wealth across agents. In our computer simulated market only a small fraction of the population observe the risky asset's fundamental value with noise, while the rest of agents try to forecast the asset's price from past transaction data. In contrast to other artificial markets, we assume that the risky asset pays no dividend, so agents cannot learn from past transaction prices and subsequent dividend payments. We find that private information can effectively disseminate in the market unless market regulation prevents informed investors from short selling or borrowing the asset, and these investors do not constitute a critical mass. In such case, not only are markets less efficient informationally, but may even experience crashes and bubbles. Finally, increased informational efficiency has a negative impact on informed agents' trading profits and a positive impact on artificial intelligent agents' profits

Soft computing techniques applied to finance

Soft computing is progressively gaining presence in the financial world. The number of real and potential applications is very large and, accordingly, so is the presence of applied research papers in the literature. The aim of this paper is both to present relevant application areas, and to serve as an introduction to the subject. This paper provides arguments that justify the growing interest in these techniques among the financial community and introduces domains of application such as stock and currency market prediction, trading, portfolio management, credit scoring or financial distress prediction areas.Publicad

An intelligent system for risk classification of stock investment projects

The proposed paper demonstrates that a hybrid fuzzy neural network can serve as a risk classifier of stock investment projects. The training algorithm for the regular part of the network is based on bidirectional incremental evolution proving more efficient than direct evolution. The approach is compared with other crisp and soft investment appraisal and trading techniques, while building a multimodel domain representation for an intelligent decision support system. Thus the advantages of each model are utilised while looking at the investment problem from different perspectives. The empirical results are based on UK companies traded on the London Stock Exchange