The role of the media in a bubble

We examine the role of the news media during the British Railway Mania, arguably one of the largest financial bubbles in history. Our analysis suggests that the press responded to changes in the stock market, and its reporting of recent events may have influenced asset prices. However, we find no evidence that the sentiment of the media, or the attention which it gave to particular stocks, had any influence on exacerbating or ending the Mania. The main contribution of the media was to provide factual information which investors could use to inform their decisions. © 2012 Elsevier Inc.

The Multiple Facets of ETF Investing: A World-Wide Analysis

The global ETF industry provides more complicated investment vehicles than low-cost index trackers. Instead, we find that the real investments of ETFs that do not fully replicate their benchmarks may deviate from their benchmarks to leverage informational advantages (which leads to a surprising stock-selection ability), to benefit from the securities lending market, to support ETF-affiliated banks’ stock prices, and to help affiliated OEFs through cross-trading. These effects are more prevalent in ETFs domiciled in Europe. Market awareness of such additional risk is reflected in ETF outflows. These results have important normative implications for consumer protection and financial stability.

Outperformance in exchange-traded fund pricing deviations: Generalized control of data snooping bias

An investigation into exchange-traded fund (ETF) outperforrnance during the period 2008-2012 is undertaken utilizing a data set of 288 U.S. traded securities. ETFs are tested for net asset value (NAV) premium, underlying index and market benchmark outperformance, with Sharpe, Treynor, and Sortino ratios employed as risk-adjusted performance measures. A key contribution is the application of an innovative generalized stepdown procedure in controlling for data snooping bias. We find that a large proportion of optimized replication and debt asset class ETFs display risk-adjusted premiums with energy and precious metals focused funds outperforming the S&P 500 market benchmark. 

Stock structure of Atlantic herring Clupea harengus in the Norwegian Sea and adjacent waters

The genetic structure of Atlantic herring Clupea harengus L. was investigated in its north-easterly distribution in the Norwegian Sea and adjacent waters, using 23 neutral and one non-neutral (Cpa111) microsatellite loci. Fish from the suspected 2 main populations - the Norwegian spring-spawning herring (NSSH) and the Icelandic summer-spawning herring (ISSH) - were collected at spawning locations in their respective spawning seasons from 2009 to 2012. Samples were also collected from Norwegian autumn spawning locations, from different local Norwegian fjords such as the inner part of Trondheimsfjorden, Lindås pollene, Landvikvannet and Lusterfjorden, as well as from suspected Faroese spawning components. The observed level of genetic differentiation was significant but low (F_ST = 0.007) and mostly attributable to the differentiation of the local Norwegian fjord populations. The locus Cpa111, which was detected to putatively be under positive selection, exhibited the highest FST value (0.044). The observed genetic patterns were robust to exclusion of this locus. Landvikvannet herring was also genetically distinguishable from the 3 other fjord populations. In addition, the present study does not support genetic structuring among the ISSH and the NSSH.

Avoiding Negligence and Profusion: The failure of the Joint-Stock form in the Anglo-Indian Tea Trade, 1840-1870

In the 19th century, firms operating in the Anglo-Indian tea trade were organised using a variety ownership forms including the partnership, joint-stock and a combination of the two known as the Managing agency. Faced with both an increasing need for fixed capital and high agency costs caused by the distance between owners and managers, the firms adapted and increasingly adopted the hybrid managing agency model to overcome these problems. Using new data from Calcutta and Bengal Commercial Registers and detailed case studies of the Assam Company and Gillanders, Arbuthnot and Co, this paper demonstrates that British entrepreneurs did not see the choice of ownership as a dichotomy or firm boundaries as fixed, but instead innovatively drew on the strengths of different forms of ownership to compete and grow successfully.

Identifying the relative importance of stock characteristics

There is no consensus in the literature as to which stock characteristic best explains returns. In this study, we employ a novel econometric approach better suited than the traditional characteristic sorting method to answer this question for the UK market. We evaluate the relative explanatory power of market, size, momentum, volatility, liquidity and book-to-market factors in a semiparametric characteristic-based factor model which does not require constructing characteristic portfolios. We find that momentum is the most important factor and liquidity is the least important based on their relative contribution to the fit of the model and the proportion of sample months for which factor returns are significant. Overall, this study provides strong evidence to support that the momentum characteristic can best explain stock returns in the UK market. The econometric approach employed in this study is a novel way to assess relevant investment risk in international financial markets outside U.S. Moreover, multinational institutions and investors can use this approach to identify regional factors in order to diversify their portfolios.

The direction of media influence: Real-estate news and the stock market

This paper uses a novel identification strategy to test the influence of news media on the stock market. Because the stock market does not impact the media coverage of the housing market, a relationship between real-estate news and shares of companies engaged in the housing market is attributable media influence. I find that the content of reporting exhibits a significant relationship with stock returns, and the amount of news with the number of trades. These relationships exist even after controlling for known risk factors, housing market performance and intra-week correlation. This finding is consistent with the function of the media as a source of information and sentiment in financial markets.

Integer-valued APARCH processes in the analysis of time series of counts

The Asymmetric Power Arch representation for the volatility was introduced by Ding et al.(1993) in order to account for asymmetric responses in the volatility in the analysis of continuous-valued financial time series like, for instance, the log-return series of foreign exchange rates, stock indices or share prices. As reported by Brannas and Quoreshi (2010), asymmetric responses in volatility are also observed in time series of counts such as the number of intra-day transactions in stocks. In this work, an asymmetric power autoregressive conditional Poisson model is introduced for the analysis of time series of counts exhibiting asymmetric overdispersion. Basic probabilistic and statistical properties are summarized and parameter estimation is discussed. A simulation study is presented to illustrate the proposed model. Finally, an empirical application to a set of data concerning the daily number of stock transactions is also presented to attest for its practical applicability in data analysis.

Analysis of stock market indices through multidimensional scaling

We propose a graphical method to visualize possible time-varying correlations between fifteen stock market values. The method is useful for observing stable or emerging clusters of stock markets with similar behaviour. The graphs, originated from applying multidimensional scaling techniques (MDS), may also guide the construction of multivariate econometric models.

Dynamics of the Dow Jones and the NASDAQ stock indexes

The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indices. We analyze the Dow Jones Industrial Average ( ∧ DJI) and the NASDAQ Composite ( ∧ IXIC) indexes at a daily time horizon. The methods and algorithms that have been explored for description of physical phenomena become an effective background, and even inspiration, for very productive methods used in the analysis of economical data. We start by applying the classical concepts of signal analysis, Fourier transform, and methods of fractional calculus. In a second phase we adopt a pseudo phase plane approach.

Analysis of Electricity Market Prices Using Multidimensional Scaling

This paper studies the impact of the energy upon electricity markets using Multidimensional Scaling (MDS). Data from major energy and electricity markets is considered. Several maps produced by MDS are presented and discussed revealing that this method is useful for understanding the correlation between them. Furthermore, the results help electricity markets agents hedging against Market Clearing Price (MCP) volatility.

Three essays on economics of predictability of stock returns

A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics