Returns to Contrarian Investment Strategies: Tests of Naive Expectations Hypotheses

CFA Digest ◽  
1997 ◽  
Vol 27 (4) ◽  
pp. 47-48
Author(s):  
H. Kent Baker
Keyword(s):  
Investment Strategies

Pricing models of shares of Russian companies and their practical application

2019 ◽  
pp. 48-76 ◽  
Author(s):  
Alexander E. Abramov ◽  
Alexander D. Radygin ◽  
Maria I. Chernova
Keyword(s):  
Stock Market ◽  
Institutional Investors ◽  
Factor Model ◽  
Investment Strategies ◽  
Pricing Models ◽  
Foreign Portfolio Investment ◽  
Market Portfolio ◽  
Stock Market Performance ◽  
Long Time ◽  
Russian Stock Market

The article analyzes the problems of applying stock pricing models in the Russian stock market. The novelty of the study lies in the peculiarities of the methodology used and the substantive conclusions on the specifics of the influence of fundamental factors on the pricing of shares of Russian companies. The study was conducted using its own 5-factor basic pricing model based on a sample of the most complete number of issues of shares of Russian issuers and a long time horizon, from 1997 to 2017. The market portfolio was the widest for a set of issuers. We consider the factor model as a kind of universal indicator of the efficiency of the stock market performance of its functions. The article confirms the significance of factors of a broad market portfolio, size, liquidity and, in part, momentum (inertia). However, starting from 2011, the significance of factors began to decrease as the qualitative characteristics of the stock market deteriorated due to the outflow of foreign portfolio investment, combined with the low level of development of domestic institutional investors. Also identified is the cyclical nature of the actions of company size and liquidity factors. Their ability to generate additional income on shares rises mainly at the stage of the fall of the stock market. The results of the study suggest that as domestic institutional investors develop on the Russian stock market, factor investment strategies can be used as a tool to increase the return on investor portfolios.

The relation between R&D accounting treatment and the risk of the firm: Evidence from the Italian market

2014 ◽  
pp. 33-54 ◽  
Author(s):  
Riccardo Cimini ◽  
Alessandro Gaetano ◽  
Alessandra Pagani
Keyword(s):  
Earnings Management ◽  
Fiscal Year ◽  
Investment Strategies ◽  
Capital Assets ◽  
Italian Market ◽  
D Investment ◽  
Firm Evidence

In this paper, we investigate the relation between the different accounting treatments of R&D expenditures and the risk of the entity in order to identify under which treatment insiders are more likely to carry out earnings management. By analysing the R&D investment strategies of a sample of 137 listed Italian entities that complied with the requirements of IAS 38 during fiscal year 2009, following Lantz and Sahut (2005), we calculate several indexes that show the preferences of insiders to account R&D expenditures as costs or capital assets, and we study the relation of such preferences with the risk of the entity, which we measure with the unlevered beta. We hypothesize that the entities, which considered the R&D investments as costs, are the riskiest ones due to the higher probability that insiders carried out earnings management. Our results confirm such hypothesis. This paper could have implications for academics and standard setters that could learn that behind accounting discretion, insiders could opportunistically behave against outsiders.

On Back-Testing “Zero-Investment” Strategies

CFA Digest ◽  
2000 ◽  
Vol 30 (4) ◽  
pp. 54-55
Author(s):  
Johann U. de Villiers
Keyword(s):  
Investment Strategies ◽  
Back Testing

The profitability of algorithmic trading systems based on football sentiment

2020 ◽  
Vol 42 (1) ◽  
pp. 33-46
Author(s):  
Raúl Gómez-Martínez ◽  
Camila Marqués-Bogliani ◽  
Jessica Paule-Vianez
Keyword(s):  
Financial Markets ◽  
Investment Decisions ◽  
Futures Market ◽  
Algorithmic Trading ◽  
Investment Strategies ◽  
Measurable Effect ◽  
Behavioural Finance ◽  
Trading Systems ◽  
European Football

Behavioural finance has shown that investment decisions are the result of not just rational but also emotional brain processes. On the assumption that emotions affect financial markets, it would seem likely that football results might have a measurable effect on financial markets. To test this, this study describes three algorithmic trading systems based exclusively on the results of three top European football teams (Juventus, Bayern München and Paris St Germain) opening long or short positions in the next market season of the futures market of the index of each country (MIB (Milano Italia Borsa), DAX (Deutscher Aktien Index) and CAC (Cotation Assistée en Continu). Depending on the outcome of the last game played a long position was taken after a victory and a short position after a draw or defeat. The results showed that the algorithmic systems were profitable in the case of Juventus and Bayern whereas in the case of PSG, the system was profitable, but in an inverse way. This study shows that investment strategies that take account of sports sentiment could have a profitable outcome.

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