Socially responsible investing and stock performance: New empirical evidence for the US and European stock markets

This paper empirically examines the theoretically ambivalent relationship between socially responsible investing (SRI) and stock performance. It contributes to the existing literature by considering both the US and the entire European stock markets and by using consistent world-wide corporate sustainability performance data. Our portfolio analysis from 1998 to 2009 is based on the common four-factor model according to Carhart (1997), which comprises market return, size, value, and momentum factors. We show for the US and the European stock markets that SRI is associated with large-sized firms. The insignificant abnormal stock returns for SRI in both regions are the main result of our paper. Therefore, our study supports the view that SRI stocks are correctly priced by market participants, although we cannot rule out that a corresponding mispricing has existed before the beginning of our observation period in 1998.     

Framing and the disposition effect: evidence from mutual fund investor redemption behaviour

Research on decision-making under uncertainty has highlighted that individuals often use simple heuristics and/or exhibit behavioural biases. Specifically, with respect to portfolio decisions, research has indicated that investors are subject to the disposition effect, i.e. they are reluctant to sell assets that have performed poorly (losers) and prone to sell assets that have performed well (winners). We find that the mutual fund investors in our sample are subject to the disposition effect when they withdraw the redemption proceeds from their account, but not when they reallocate the proceeds within the account. The evidence is consistent with Shefrin and Statman’s hypothesis that framing a transaction as a transfer as opposed to a sale mitigates the disposition effect.     

When do improved covariance matrix estimators enhance portfolio optimization? An empirical comparative study of nine estimators

The use of improved covariance matrix estimators as an alternative to the sample estimator is considered an important approach for enhancing portfolio optimization. Here we empirically compare the performance of nine improved covariance estimation procedures using daily returns of 90 highly capitalized US stocks for the period 1997–2007. We find that the usefulness of covariance matrix estimators strongly depends on the ratio between the estimation period T and the number of stocks N, on the presence or absence of short selling, and on the performance metric considered. When short selling is allowed, several estimation methods achieve a realized risk that is significantly smaller than that obtained with the sample covariance method. This is particularly true when T/N is close to one. Moreover, many estimators reduce the fraction of negative portfolio weights, while little improvement is achieved in the degree of diversification. On the contrary, when short selling is not allowed and T?>?N, the considered methods are unable to outperform the sample covariance in terms of realized risk, but can give much more diversified portfolios than that obtained with the sample covariance. When T?<?N, the use of the sample covariance matrix and of the pseudo-inverse gives portfolios with very poor performance.     

收入和流动性风险约束下家庭金融资产选择的实证研究

本文采用SCF数据,运用TOBIT模型从实证的角度研究收入风险和流动性约束对投资者资产选择的影响。研究结果表明：控制其他变量的影响之后，收入风险的增加会使得投资者降低对风险资产的需求．预期未来流动性的约束也减少投资者的风险资产投资比例。接着本文采用分类回归及将风险资产投资比例概念由狭义转变为广义，得到的结论都和前面的研究一致。最后．本文采用迭代LAD回归技术所得到的结果也证明了本模型的结论具有稳健性。     

Optimal high-frequency trading with limit and market orders

We propose a framework for studying optimal market-making policies in a limit order book (LOB). The bid–ask spread of the LOB is modeled by a tick-valued continuous-time Markov chain. We consider a small agent who continuously submits limit buy/sell orders at best bid/ask quotes, and may also set limit orders at best bid (resp. ask) plus (resp. minus) a tick for obtaining execution order priority, which is a crucial issue in high-frequency trading. The agent faces an execution risk since her limit orders are executed only when they meet counterpart market orders. She is also subject to inventory risk due to price volatility when holding the risky asset. The agent can then also choose to trade with market orders, and therefore obtain immediate execution, but at a less favorable price. The objective of the market maker is to maximize her expected utility from revenue over a short-term horizon by a trade-off between limit and market orders, while controlling her inventory position. This is formulated as a mixed regime switching regular/impulse control problem that we characterize in terms of a quasi-variational system by dynamic programming methods. Calibration procedures are derived for estimating the transition matrix and intensity parameters for the spread and for Cox processes modelling the execution of limit orders. We provide an explicit backward splitting scheme for solving the problem and show how it can be reduced to a system of simple equations involving only the inventory and spread variables. Several computational tests are performed both on simulated and real data, and illustrate the impact and profit when considering execution priority in limit orders and market orders.     

Portfolio efficiency of a dynamic capital asset pricing model

In the present study we show that, based on equally weighted portfolios of continuously listed Finnish and Swedish stocks, aDynamic Model of Capital Asset Pricing (DCAPM) outperforms the static Capital Asset Pricing Model (CAPM) in the Super Criterion Test. It is demonstrated that the portfolio efficiency of the dynamic model is improved, when using a properly defined transition matrix in the Kalman Filtering Algorithm.The advice and encouragement of Professor Leif Nordberg (Department of Statistics, Åbo Akademi University) is gratefully acknowledged. I thank Jaana Aaltonen for her assistance in monitoring the computer programs. I also thank an anonymous referee for his valuable comments and suggestions for improving the quality of the paper.     

Portfolio selection with two-stage preferences

We propose a model of portfolio selection under ambiguity, based on a two-stage valuation procedure which disentangles ambiguity and ambiguity aversion. The model does not imply “extreme pessimism” from the part of the investor, as multiple priors models do. Furthermore, its analytical tractability allows to study complex problems thus far not analyzed, such as joint uncertainty about means and variances of returns.     

A view of the European Union as an evolving country portfolio

We apply portfolio theory to assess the consequences in terms of risk sharing of the evolution of the industry mix of European Union countries between 1986 and 1997, and of the changes in the membership configurations of both economic and monetary unions. We compute a measure of risk-return performance for EU countries, by considering countries as collections of industries, and observe that risk-return performance improved in most countries. We find that the EU9 is marginally more efficient than the other historical EU groupings and that the Euro Zone might slightly benefit from the inclusion of the United Kingdom.     

Explaining asset pricing puzzles associated with the 1987 market crash

The 1987 market crash was associated with a dramatic and permanent steepening of the implied volatility curve for equity index options, despite minimal changes in aggregate consumption. We explain these events within a general equilibrium framework in which expected endowment growth and economic uncertainty are subject to rare jumps. The arrival of a jump triggers the updating of agents' beliefs about the likelihood of future jumps, which produces a market crash and a permanent shift in option prices. Consumption and dividends remain smooth, and the model is consistent with salient features of individual stock options, equity returns, and interest rates.     

Two-step multi-criteria model for selecting optimal portfolio

In spite of a large number of multi-criteria models applied to solve the problem of optimal portfolio selection and a large number of market criteria and accounting criteria proposed for these models, the problem of portfolio containing securities from different industries has not yet been adequately solved. Namely, neither can stocks of companies from different industries be compared using the same criteria nor can the weight of a particular criteria be equal for them all. Therefore this paper develops a new two-step model that will overcome the shortcomings of the previously used models. The model is divided into two different but related pillars: the choice of different industries to form the overall portfolio and the choice of portfolio for each industry. The multi-criteria model used in this paper is a modified multi-criteria programming model based on the PROMETHEE II approach. The selected model has been applied at the Zagreb Stock Exchange (ZSE) as a real case.