Narrow Results

The price multiplier effect provides precious insight into the behavior of investors during episodes of speculative trading. It tells us that the higher the price of an asset (within a set of similar assets), the more its price is likely to increase during the upgoing phase of a speculative price peak. In short, instead of being risk averse, as is often assumed, investors rather seem to be "risk prone". While this effect is known to hold for several sorts of assets, it has not yet been possible to test it for stocks because the price of one share has no intrinsic significance, which means that one cannot say that stock A is more expensive than stock B on the basis of its price. In this paper we show that the price-dividend ratio gives a good basis for assessing the price of stocks in an intrinsic way. When this alternative measure is used instead, it turns out that the price multiplier effect also holds for stocks, at least if one concentrates on samples of companies which are sufficiently homogeneous.

Simultaneous Multi-Threading (SMT) processors provide improvement over the traditional out-of-order superscalar architecture by allowing instructions from several independent threads to execute out-of-order concurrently. Maintaining the accuracy of values read from and written to memory is a great bottleneck for processor performance, as loads must stall execution until all prior store addresses are known or risk reading invalid data. Prior research in this area has mainly focused on superscalar architecture, as such, it is only natural to extend memory dependence speculation techniques to an SMT architecture. In this paper, we allow for loads among threads to execute as soon as their addresses are resolved without checking for prior memory address conflicts. Stores also perform a check on all later loads to see if any read was too early due to an address match, if so, the processor state is recovered, and the load re-issued. This aggressive technique allows for the greatest potential instructions per clock cycle gains over predictive techniques as the pipeline is never stalled for loads. Our simulations show that an overall IPC gain up to 12% and 10% is possible for both 4-threaded and 8-threaded workloads respectively. Conversely, a maximum overall IPC loss of at least 2.3% and 2% for 4-threaded and 8-threaded workloads respectively was also observed.

In contrast to their role in theory, options are in practice not only traded for hedging purposes. Many investors also use them for speculation purposes. For these investors the Black–Scholes price serves only as an orientation, their decisions to buy, hold or hedge an option are also based on subjective beliefs and on their personal utility functions (in the widest possible sense). The aim of this paper is to present a general framework to include different types of investors, especially hedgers, pure speculators and speculators following strategies with bounded risk. We derive their subjective values of an option endogenously from the solution of their decision problems.

We examine how information asymmetry affects a firm's incentive to hedge versus speculate by using foreign currency derivatives. We find a quadratic relation between asymmetric information and a firm's risk management activities. In particular, we find that the firms facing medium level of information asymmetry are more likely to hedge, while firms with very high and low levels of asymmetric information tend to speculate. Moreover, we find that our results hold primary for firms operating in highly competitive industries.

This paper concerns the internal structure of reasoning that, basically consisting in conjecturing and refuting, is too often identified with only deducing, abducing and refuting, that is, with just the deductive search of consequences, hypotheses and refutations. With such identification, it is forgotten that in addition to consequences and hypotheses, there is a third class of conjectures, speculations or proper guesses. Speculations are inferentially non-comparable, or orthogonal, with the premise, and generate creativity. It is presented a very simple formal view for the structure of Commonsense Reasoning, a mathematical model allowing to show the importance of speculations, and specially to start with its systematic computational search.

This paper examines the effect of global liquidity and financialization on commodity price inflation. The novelty of the paper lies in exploiting recent advances in our understanding of global liquidity by separating private liquidity from official liquidity and digging into disaggregated level non-commercial commodity traders data. Private liquidity is found to be inflationary, while official liquidity is not. Among the non-commercial traders, both, active money managers and passive swap dealers seem to have played an important role in commodity inflation dynamics during the period 2006–2012. The paper also discusses emerging policy issues in a rapidly changing global commodities market.

To align with the global goal of keeping temperature below $2^{\circ }$C, a market-based initiative, “Emissions Trading System” (ETS), has been developed to mitigate climate change. However, while the carbon allowances traded at the ETS are mostly held and traded by polluting companies, financial actors engage in “speculation”, activities that might be detrimental to the functioning of the ETS have also invested in the ETS. By drawing from the big data archive of Google Trends, we construct a news-based speculation index to proxy for the role of speculation in the dynamics of carbon pricing. Given our preliminary finding of inherent volatility and the mixed-frequency nature of the dataset, we employ the GARCH-MIDAS econometric technique to test the hypothesis that an all-inclusive framework that reflects the emission compliance and emissions non-compliance dynamics of the ETS is the most accurate approach to modeling carbon prices. We show that higher speculation in the ETS fosters higher long-term volatility in carbon prices, that speculation is a good predictor of carbon prices, and that its positive impact on carbon price returns makes the ETS an attractive investment opportunity. We provide a data-driven framework upon which the growing debate about whether the behavior of the non-compliance emission actors in the ETS endangers or benefits the functioning of the ETS can be evaluated empirically.

A recent study shows that index futures prices are influenced by the index’s liquidity. This research describes the state of the index futures market following the epidemic as seen by index futures mispricing affected by liquidity and volatility during the outbreak.

We analyze the theoretical foundations of the efficient market hypothesis by stressing the efficient use of information and its effect upon price volatility. The "random walk" hypothesis assumes that price volatility is exogenous and unexplained. Randomness means that a knowledge of the past cannot help to predict the future. We accept the view that randomness appears because information is incomplete. The larger the subset of information available and known, the less emphasis one must place upon the generic term randomness. We construct a general and well accepted intertemporal price determination model, and show that price volatility reflects the output of a higher order dynamic system with an underlying stochastic foundation. Our analysis is used to explain the learning process and the efficient use of information in our archetype model. We estimate a general unrestricted system for financial and agricultural markets to see which specifications we can reject. What emerges is that a system very close to our archetype model is consistent with the evidence. We obtain an equation for price volatility which looks a lot like the GARCH equation. The price variability is a serially correlated variable which is affected by the Bayesian error, and the Bayesian error is a serially correlated variable which is affected by the noisiness of the system. In this manner we have explained some of the determinants of what has been called the "randomness" of price changes.

This article sketches an ethics of (financial) speculation in futures markets. (1) It identifies an intentionalistic fallacy prevalent in moral criticisms of speculation in general and of financial speculation in particular. (2) It scrutinizes the degree to which the recent debate on financial speculation with agricultural commodities follows the general pattern of moral criticism and its intentionalistic fallacy. (3) It then provides a theoretical and empirical in-depth analysis of long-only index funds' engagement in futures markets and concludes that moral criticisms which put them in the pillory as “hungermakers” are unjust(ified). This proves that ethics, understood as a theory of morality, can criticize moral criticisms of financial speculation on moral grounds. (4) Finally, this article discusses the option of interdisciplinary cooperation between ethics and economics.