PurposeOnline investment platforms offer an environment that may lead some traders into excessive behaviors akin to gambling. Over the last decade, gambling behaviors associated with the stock market have attracted the attention of many researchers but the literature on the subject remains scarce. This study aims to present the results of live interviews with a sample (N = 100) of retail investors trading online, and contrasts trading habits with gambling behaviors.Design/methodology/approachParticipants are divided in three groups according to their score on an adapted version of the Problem Gambling Severity Index (referred to as the PGSI-Trading), and their trading habits and behaviors are compared.FindingsThe authors find that traders with higher PGSI-Trading scores are more likely to display gambling-related behaviors such as trading within a short timeframe, being motivated by making money quickly and experiencing high sensations when trading.Research limitations/implicationsThe sample is small but the authors proceeded this way in order to gather some qualitative data that would be helpful to clinicians in the Province of Quebec. The questionnaire used to classify traders at risk of being gamblers (PGSI-Trading) has not been validated.Practical implicationsThe findings of this study will be helpful to clinicians who hwork with patients suffering from excessive online stock trading habits.Social implicationsClinicians observe an increasing number of patients who consult with excessive stock trading habits. This study has brought new information allowing clinicians to better understand how gambling manifests itself on the stock market.Originality/valueTo the authors' knowledge, this study is the first to investigate the trading habits of individuals classified in terms of their score on an adapted PGSI questionnaire.

Cannabis (Cannabis sativa L.; Rosales: Cannabaceae) is a newly legalized crop and requires deeper insights on its pest communities. In this preliminary study, we identified a thrips species affecting indoor-grown cannabis in Canada and tested its impact on plant yield. We used three levels of initial infestation (zero, one, and five thrips) on individual plants grown in two growing mediums: conventional substrate or substrate containing the biostimulant Bacillus pumilus Meyer and Gottheil (Bacillales: Bacillaceae). We found that the onion thrips, Thrips tabaci (Lindeman) (Thysanoptera: Thripidae), is proliferating in indoor-grown cannabis. Furthermore, our results showed that fresh yields were higher for the plants that initially received zero thrips compared to those that initially received five thrips. Moreover, the biostimulant only marginally helped reduce the impact of thrips. We highlight the importance for growers to carefully monitor thrips infestations in indoor-grown cannabis. Finally, we emphasize the need for more research related to the impact of pests on cannabis yields and safe means of pest control for this strictly regulated crop.

The purpose of this study was to analyze the relationship between light intensity, cannabis (Cannabis sativa L.) yields, and profitability. We also look for evidence that spectrum differences across broad-spectrum horticulture lights and general-purpose LEDs affect the relationship between yield and light intensity. Finally, we discuss the financial return of increasing light intensity in order to increase yields. We found that yields increase linearly with light intensity up to at least 1500 mu mol m(-2) s(-1), which is at least twice the intensity that is most commonly used by cannabis growers. That relationship did not appear to be influenced by spectrum quality differences among the lamps included in the study. Finally, for all the intensity ranges that we considered, the value of the gain in yields from increasing light intensity far exceeded the cost of using more electricity.

The purpose of this study was to analyze the relationship between light intensity, cannabis yields, and profitability. We also look for evidence that spectrum differences across broad-spectrum, horticulture lights and general-purpose LEDs impact the relationship between yield and light intensity. Finally, we discuss the financial return of increasing light intensity in order to increase yields. We find that yields increase linearly with light intensity up to at least 1500 μmols/m2·s, which is at least twice the intensity that is most commonly used by cannabis growers. That relationship did not appear to be influenced by spectrum quality differences across the lamps included in the study. Finally, for all the intensity ranges that we considered, the value of the gain in yields from increasing light intensity far exceeded the cost of using more electricity.

Rapidly growing demand for year-round fresh food, regardless of the weather or climate, is driving demand for controlled environment agriculture systems. Sales from greenhouses (GHs) are growing at 8.8%, while sales from vertical farms (VFs) are growing at 30%. It is commonly believed in industry circles that a VF cannot economically compete with a GH, due to the high cost of powering artificial lighting. Nonetheless, researchers have yet to analyze the economics underlying a VF, let alone compare the profitability of a VF to that of a GH. This research gap is particularly relevant to Canada, as it is uniquely positioned to be a leader in the VF market. Below, we report the results of a detailed simulation of the profitability of growing lettuce in a VF and in a GH located near Quebec City. Surprisingly, we find that the costs to both equip and run the two facilities are very similar, while the gross profit is slightly higher for the VF.

Rapidly growing demand for year-round fresh food, regardless of the weather or climate, is driving demand for controlled environment agriculture systems. Sales from greenhouses (GHs) are growing at 8.8%, while sales from vertical farms (VFs) are growing at 30%. It is commonly believed in industry circles that a VF cannot economically compete with a GH, due to the high cost of powering artificial lighting. Nonetheless, researchers have yet to analyze the economics underlying a VF, let alone compare the profitability of a VF to that of a GH. This research gap is particularly relevant to Canada, as it is uniquely positioned to be a leader in the VF market. Below, we report the results of a detailed simulation of the profitability of growing lettuce in a VF and in a GH located near Quebec City. Surprisingly, we find that the costs to both equip and run the two facilities are very similar, while the gross profit is slightly higher for the VF.

One of the goals of the U.S. ethanol mandate is to reduce fossil fuel use in the transportation sector. But some critics of the mandate argue that a more efficient way of reducing fuel consumption would be to focus on improvements in fuel efficiency of motor vehicles. We consider the time span between 2005 and 2015 and ask how much the mandated increases in ethanol use reduced fossil fuel consumption relative to increases in light-duty vehicle fuel efficiency, and how cost-effective each trend was for consumers. We show that, over this time period, changes in vehicle fuel efficiency reduced fossil fuel energy consumption by 0.90%, while increases in ethanol consumption decreased it by 1.21%. Accordingly, fuel savings caused by increases in fuel efficiency saved drivers $40.9B, while the ethanol mandate penalized drivers with $91.5B in additional fuelling costs.

Modelling futures term structures (price forward curves) is essential for commodity-related investments, portfolios, risk management, and capital budgeting decisions. This paper uses a novel strategy, wavelet thresholding, to de-noise futures price data prior to estimation in a state-space framework in order to improve model fit and prediction. Rather than de-noise the raw data, this method de-noises only wavelet coefficients linked to specific timescales, minimizing the amount of information that is accidentally removed. Our findings are that, for the first five futures maturities in our sample data, in-sample (tracking) and 5-day-ahead out-of-sample (forecasting) Root Mean Squared Errors (RMSEs) are smaller both (i) when we increase the number of factors from one to four, and (ii) when we de-noise the data using wavelet thresholding. The improvement due to wavelet thresholding is often greater than the improvement from adding one more factor to the model, which is important because going beyond four factors does not improve model fit. Wavelet-based de-noising thus has the potential to improve considerably the estimation of various economic time series models, helping practitioners and policymakers with better forecasting and risk management.

Experimental research suggests the Walrasian tâtonnement auction encourages traders to under-reveal preferences, even encouraging initial pledges contrary to true desires, because pledges are not binding. We analyze the timing and characteristics of individual pledges and trades during 9604 auctions for redbeans conducted by the Tokyo Grain Exchange. We find no evidence of contrarian pledging and little evidence of under-revelation – as many traders over-reveal as under-reveal. Most traders pledge seriously from the beginning. Despite the considerable heterogeneity in pledging behavior across individual traders, these differences appear to have no relationship with traders’ profits, nor do they appear to affect the achievement of equilibrium.

We study the effect of the presence of brokers in an experimental exchange market using the Walrasian tâtonnement mechanism. We find that brokers tend to act as liquidity providers, submitting orders likely to equilibrate supply and demand given the orders they receive from other participants. As a result, average excess demand and prices are less volatile, and markets reach equilibrium more often, when brokers are present compared with the case without brokers. Brokers’ liquidity-providing behavior is more pronounced when their compensation includes, in addition to their trading profit, a component related to trading volume when equilibrium is reached. Under-revelation, a strategic behavior inherent to Walrasian auctions, is about the same with and without brokers when markets clear, yielding similar levels of market efficiency, measured as total surplus divided by potential surplus. TOPICS:Exchanges/markets/clearinghouses, volatility measures

No matter how pronounced intraday patterns may appear, it is difficult to account for cross-correlations among related assets when those assets trade continuously and simultaneously. Futures contracts are auctioned periodically and sequentially on the Tokyo Grain Exchange (TGE). Even though intraday TGE volume is U-shaped, intraday volatility is closer to L-shaped. After accounting for the public information in immediately preceding auctions for the same commodity, for earlier trading in other commodities, and for trading on overseas markets open overnight in Tokyo, the intraday patterns are effectively flat. Thus, the timing of privately informed traders cannot be the source of intraday patterns.

Purpose - The purpose of this paper is twofold. The first is to estimate the correlation between market activity and volatility on an exchange that does not use continuous auctions to find prices. The second is to estimate the sensitivity of that relationship to differences in opinions across traders regarding asset value.Design/methodology/approach - Both objectives are accomplished by using seven years of trader-level data from the Tokyo Grain Exchange, which uses rapid sequences of Walrasian tatonnement auctions to discover prices. On the TGE, only one futures contract trades at any given time and all of a commodity's futures contracts are auctioned in a rapid sequence, with only seconds between a sequence's auctions. The results are interpreted under the hypothesis that this design causes traders' beliefs to become more accurate and more uniform as a sequence progresses.Findings - Intraday volume is u-shaped while intraday volatility is downward sloping. The volumevolatility link is positive and stays constant or strengthens as traders' beliefs about value become more precise. The link is driven by trades originating from small futures commission merchants, especially those trades entered on behalf of customers.Research limitations/implications - Evidence that accounting for cross-correlations when estimating volatility can have an important effect on estimates is presented. Researchers are encouraged to further explore the implications of cross-correlations.Practical implications - The paper includes implications for existing theory, the measurement of volatility, and the design of central exchanges.Originality/value - This paper uses the TGE as a natural laboratory to test theory. It is the first such study to use data from an exchange that does not use continuous auctions, and the first to document the simultaneous existence of u-shape volume and downward-sloping volatility.

We compare the financial benefits of displacing oil using three alternative-vehicle technologies: natural gas (NGVs), battery-electric (BEVs), and plug-in hybrid electric vehicles (PHEVs). On a cost-per-barrel basis, NGVs would be the least expensive way to displace oil, while PHEVs would be the most expensive. BEVs would displace the most oil. Furthermore, though the BEV case has the highest upfront cost, its payback rate is almost two-times faster than the NGV case. At current energy prices and without considering environmental costs, none of these technologies make financial sense. However, given historical relationships between oil, natural gas and electricity prices, each alternative would make financial sense if oil prices increased to at least $150 per barrel, and BEVs would offer the fastest payback. Finally, though electricity prices are the most volatile, the financial cost of fuel-price uncertainty is lowest for the BEV case. Moreover, the cost of uncertainty is unimportant for all cases, including gasoline-powered vehicles, and should not be an important part of this debate.

We conduct a detailed analysis of the relationship between excess demand and the convergence of price to equilibrium during a real-world Walrasian auction, paying special attention to the size and speed of the price adjustment. Using data from the Tokyo Grain Exchange (TGE), we first show that because auctions for the various futures contracts occur sequentially, information becomes more evenly dispersed across traders as an auction sequence progresses. Then we show that excess demand is positively correlated with both the eventual price change and the speed with which price adjusts. As information becomes more evenly dispersed, the strength of these relationships weakens. Finally, though excess demand explains a large proportion of the variability of the change in price, it explains only a small proportion of the variability of the speed of adjustment.

One explanation for meat sharing within hunter–gatherer communities is that sharing reduces variance in consumption that results from unpredictable harvests. If this food-risk reduction is the primary reason for sharing, then a good alternative to sharing would be selling meat in a market and using the cash to buy storable foods. We analyze the effect of market access on sharing behavior in two Huaorani communities in the Ecuadorian Amazon in order to test the hypothesis that hunters share mainly to reduce food risk. If this hypothesis is correct we expect to find that hunters are selling meat that would have otherwise gone into sharing networks. The alternative hypothesis is that sharing has multiple benefits, in addition to risk reduction, making sharing and selling imperfect substitutes. We find evidence that households use the market to reduce food risk, but that the amount of meat a hunter sells has no relationship with sharing intensity. Rather, the likelihood of selling meat simply increases with hunting returns. The results suggest that selling meat has lower expected benefits than sharing and so hunters first satisfy their sharing requirements and then sell any excess meat.

Though corn-ethanol is promoted as renewable, models of the production process assume fossil fuel inputs. Moreover, ethanol is promoted as a means of increasing energy security, but there is little discussion of the dependability of its supply. This study investigates the sensibility of promoting corn-ethanol as an automobile fuel, assuming a fully renewable production process. We then use historical data to estimate the supply risk of ethanol relative to imported petroleum. We find that devoting 100% of US corn to ethanol would displace 3.5% of gasoline consumption and the annual supply of the ethanol would be inherently more risky than that of imported oil. Finally, because large temperature increases can simultaneously increase fuel demand and the cost of growing corn, the supply responses of ethanol producers to temperature-induced demand shocks would likely be weaker than those of gasoline producers.

If ethanol were to be produced in a truly sustainable manner, it would take all the corn in the United States to displace about 3.5 percent of our gasoline consumption. Furthermore, ethanol would not necessarily be a more reliable source of fuel. By displacing gasoline with ethanol, we are displacing geo-political risk with yield risk, and historical corn yields have been about twice as volatile as oil imports.

The Tokyo Grain Exchange (TGE)’s itayose mechanism provides the opportunity to analyze functioning Walrasian tâtonnement auctions (WTA). In 15,677 auctions conducted over 1997–1998 for corn and redbean futures contracts, price formation is unexpectedly similar to that observed in continuous double auctions. Provisional prices and pledges are informative. In contrast to behavior observed in experiments, few pledges are deceptive, because the traders participate repeatedly and because the auctioneer has flexibility when changing the provisional price and ending the auction. Both the risk of the auction ending and the more equitable dispersion of information increase depth and the speed at which information is embodied in price.

The Tokyo Grain Exchange (TGE) finds prices for futures contracts using sequences of electronic Walrasian tâtonnement auctions. The lengths of auctions are endogenous, thus, unlike data from other exchanges, data from the TGE offer an obvious measure of the time it takes price to converge to equilibrium. We find that the convergence rate is positively affected by informed trading by both exchange locals and off-exchange customers. Surprisingly, informed trades by customers are more important than those by exchange locals when public information is scarce. Nonetheless, as customer volume increases relative to exchange local volume, the equilibrium path becomes more unstable.