Relative Extinction of Heterogeneous Agents

In all the existing literature on survival in heterogeneous economies, the rate at which an agent vanishes in the long run relative to another agent can be characterized by the difference of the so-called survival indices, where each survival index only depends on the preferences of the corresponding agent and the properties of the aggregate endowment. In particular, one agent experiences extinction relative to another (that is, the wealth ratio of the two agents goes to zero) if and only if she has a smaller survival index. We consider a simple complete market model and show that the survival index is more complex if there are more than two agents in the economy. In fact, the following phenomenon may take place: even if agent one experiences extinction relative to agent two, adding a third agent to the economy may reverse the situation and force the agent two to experience extinction relative to agent one. We also calculate the rates of convergence

Sector level cost of equity in African financial markets

This paper assesses the effectiveness of Liu (2006) metrics in measuring illiquidity within a multifactor CAPM pricing model. Costs of equity are estimated using this model for the major sectors within Africa’s larger equity markets: Morocco, Tunisia, Egypt, Kenya, Nigeria, Zambia, Botswana and South Africa. In all countries, the cost of equity is found to be highest in the financial sector and lowest in the blue chip stocks of Tunisia, Morocco, Namibia and South Africa. At an aggregate level, Nigeria and Zambia have the highest cost of capital

Assessing the impact of algorithmic trading on markets: a simulation approach

Innovative automated execution strategies like Algorithmic Trading gain significant market share on electronic market venues worldwide, although their impact on market outcome has not been investigated in depth yet. In order to assess the impact of such concepts, e.g. effects on the price formation or the volatility of prices, a simulation environment is presented that provides stylized implementations of algorithmic trading behavior and allows for modeling latency. As simulations allow for reproducing exactly the same basic situation, an assessment of the impact of algorithmic trading models can be conducted by comparing different simulation runs including and excluding a trader constituting an algorithmic trading model in its trading behavior. By this means the impact of Algorithmic Trading on different characteristics of market outcome can be assessed. The results indicate that large volumes to execute by the algorithmic trader have an increasing impact on market prices. On the other hand, lower latency appears to lower market volatility

The Use of Trademarks in Empirical Research: Towards an Integrated Framework

This paper represents an early attempt to develop an integrated framework linking empirical studies that make use of trademark statistics. Despite its youth, this field of scholarly activity has already accumulated a critical mass of papers that allow us to draw first general conclusions about the trademark lifecycle and its impact on organisational functioning. Based on a systematic review of 64 articles with some elements of empirical trademark analysis, five broad research areas have been identified, namely: the determinants of trademark deposits; the relationship between trademarks and innovation processes; the role of trademarks in differentiating product offerings; the strategic use of trademarks; and the impact of trademarks on firm performance. Within each category, a more detailed aggregation of articles has also been proposed. Overall, the analysis has shown that the performance-based perspective currently dominates the research landscape, with studies on trademark deposits and the trademark-innovation link to follow. At the same time, there is still little known about micro-foundations of a company's trademarking behaviour; the use of trademarks and other intellectual property rights in a complementary way and its effect on value transference; as well as the performance implications of differentiation strategy. This paper considers these and other findings to outline directions for future research

Trading activity and price impact in parallel markets: SETS vs. off-book market at the London Stock Exchange

We empirically study the trading activity in the electronic on-book segment and in the dealership off-book segment of the London Stock Exchange, investigating separately the trading of active market members and of other market participants which are non-members. We find that (i) the volume distribution of off-book transactions has a significantly fatter tail than the one of on-book transactions, (ii) groups of members and non-members can be classified in categories according to their trading profile (iii) there is a strong anticorrelation between the daily inventory variation of a market member due to the on-book market transactions and inventory variation due to the off-book market transactions with non-members, and (iv) the autocorrelation of the sign of the orders of non-members in the off-book market is slowly decaying. We also analyze the on-book price impact function over time, both for positive and negative lags, of the electronic trades and of the off-book trades. The unconditional impact curves are very different for the electronic trades and the off-book trades. Moreover there is a small dependence of impact on the volume for the on-book electronic trades, while the shape and magnitude of impact function of off-book transactions strongly depend on volume.Comment: 16 pages, 9 figure

News, liquidity dynamics and intraday jumps: evidence from the HUF/EUR market

We study intraday jumps on a pure limit order FX market by linking them to news announcements and liquidity shocks. First, we show that jumps are frequent and contribute greatly to the return volatility. Nearly half of the jumps can be linked with scheduled and unscheduled news announcements. Furthermore, we show that jumps are information based, whether they are linked with news announcements or not. Prior to jumps, liquidity does not deviate from its normal level, nor do liquidity shocks offer any predictive power for jump occurrence. Jumps emerge not as a result of unusually low liquidity but rather as a result of an unusually high demand for immediacy concentrated on one side of the book. During and after the jump, a dynamic order placement process emerges: some participants endogenously become liquidity providers and absorb the increased demand for immediacy. We detect an interesting asymmetry and find the liquidity providers to be more reluctant to add liquidity when confronted with a news announcement around the jump. Further evidence shows that participants submit more limit orders relative to market orders after a jump. Consequently, the informational role of order flow becomes less pronounced in the thick order book after the jump

Impersonal efficiency and the dangers of a fully automated securities exchange

This report identifies impersonal efficiency as a driver of market automation during the past four decades, and speculates about the future problems it might pose. The ideology of impersonal efficiency is rooted in a mistrust of financial intermediaries such as floor brokers and specialists. Impersonal efficiency has guided the development of market automation towards transparency and impersonality, at the expense of human trading floors. The result has been an erosion of the informal norms and human judgment that characterize less anonymous markets. We call impersonal efficiency an ideology because we do not think that impersonal markets are always superior to markets built on social ties. This report traces the historical origins of this ideology, considers the problems it has already created in the recent Flash Crash of 2010, and asks what potential risks it might pose in the future