Do prediction markets produce well-calibrated probability forecasts?

This article presents new theoretical and empirical evidence on the forecasting ability of prediction markets. We develop a model that predicts that the time until expiration of a prediction market should negatively affect the accuracy of prices as a forecasting tool in the direction of a ‘favourite/longshot bias’. That is, high-likelihood events are underpriced, and low-likelihood events are over-priced. We confirm this result using a large data set of prediction market transaction prices. Prediction markets are reasonably well calibrated when time to expiration is relatively short, but prices are significantly biased for events farther in the future. When time value of money is considered, the miscalibration can be exploited to earn excess returns only when the trader has a relatively low discount rate.

The impact of litigation risk on the strategic timing of management earnings forecasts

This paper examines whether managers strategically time their earnings forecasts (MEFs) as litigation risk increases. We find as litigation risk increases, the propensity to release a delayed forecast until after the market is closed (AMC) or a Friday decreases but not proportionally more for bad news than for good news. Host costly this behaviour is to investors is questionable as share price returns do not reveal any under-reaction to strategically timed bad news MEF released AMC. We also find evidence consistent with managers timing their MEFs during a natural no-trading period to better disseminate information.

Evolution of New Zealand insects : summary and prospectus for future research

Knowledge on the evolution of the New Zealand insect fauna is reviewed and outstanding questions are highlighted. The New Zealand insect fauna is a composite of old and recent lineages and many spectacular examples of evolutionary processes are evident, including species radiations, hybridisation and unusual adaptations. We discuss the origins and evolution of four prominent communities within the insect fauna: terrestrial lowland insects, alpine insects, aquatic insects and insect communities from offshore islands. Within each of these communities, significant lineages are discussed, and in particular the crucial adaptations that enable these lineages to thrive and diversify. Glacial history has had a dramatic impact on the New Zealand insects, and the effects on different lineages are discussed. The New Zealand insects are unique, yet many are threatened with extinction, and efforts to preserve the fauna are reviewed. Despite the accumulating knowledge, major gaps still exist and these are outlined, as are opportunities to address key questions. The review concludes with a synthesis and a discussion of how systematics, new technologies and integrative approaches have the promise to improve dramatically our understanding of New Zealand insect evolution.

Probabilistic forecasts of the onset of the north Australian wet season

The amount and timing of early wet-season rainfall are important for the management of many agricultural industries in north Australia. With this in mind, a wet-season onset date is defined based on the accumulation of rainfall to a predefined threshold, starting from 1 September, for each square of a 1° gridded analysis of daily rainfall across the region. Consistent with earlier studies, the interannual variability of the onset dates is shown to be well related to the immediately preceding July-August Southern Oscillation index (SOI). Based on this relationship, a forecast method using logistic regression is developed to predict the probability that onset will occur later than the climatological mean date. This method is expanded to also predict the probabilities that onset will be later than any of a range of threshold dates around the climatological mean. When assessed using cross-validated hindcasts, the skill of the predictions exceeds that of climatological forecasts in the majority of locations in north Australia, especially in the Top End region, Cape York, and central Queensland. At times of strong anomalies in the July-August SOI, the forecasts are reliably emphatic. Furthermore, predictions using tropical Pacific sea surface temperatures (SSTs) as the predictor are also tested. While short-lead (July-August predictor) forecasts are more skillful using the SOI, long-lead (May-June predictor) forecasts are more skillful using Pacific SSTs, indicative of the longer-term memory present in the ocean.

How CBO Forecasts Income

[Excerpt] Because federal receipts are determined to a great extent by taxes collected on individual and business income, this background paper focuses on how CBO projects income earned by individuals and businesses. It concentrates primarily on CBO's methodology as it pertains to those categories of individual and business income that are encompassed within the framework of the national income and product accounts, or NIPAs (see Appendix A for explanations). Using that framework for projecting income helps to ensure consistency with CBO's projections of the overall economy.

Essays on Financial Analyst Forecasts and Recommendations

The trade of the financial analyst is currently a much-debated issue in today’s media. As a large part of the investment analysis is conducted under the broker firms’ regime, the incentives of the financial analyst and the investor do not always align. The broker firm’s commercial incentives may be to maximise its commission from securities trading and underwriting fees. The purpose of this thesis is to extend our understanding of the work of a financial analyst, the incentives he faces and how these affect his actions. The first essay investigates how the economic significance of the coverage of a particular firm impacts the analysts’ accuracy of estimation. The hypothesis is that analysts put more effort in analysing firms with a relatively higher trading volume, as these firms usually yield higher commissions. The second essay investigates how analysts interpret new financial statement information. The essay shows that analysts underreact or overreact to prior reported earnings, depending on the short-term pattern in reported earnings. The third essay investigates the possible investment value in Finnish stock recommendations, issued by sell side analysts. It is established that consensus recommendations issued on Finnish stocks contain investment value. Further, the investment value in consensus recommendations improves significantly through the exclusion of recommendations issued by banks. The fourth essay investigates investors’ behaviour prior to financial analysts’ earnings forecast revisions. Lately, the financial press have reported cases were financial analysts warn their preferred clients of possible earnings forecast revisions. However, in the light of the empirical results, it appears that the problem of analysts leaking information to some selected customers does not appear systematically on the Finnish stock market.

Flow forecasts in general planning of municipal water and sewage works

Vuorokausivirtaaman ennustaminen yhdyskuntien vesi- ja viemärilaitosten yleissuunnittelussa.

The Skill of ECMWF Medium-Range Forecasts during the Year of Tropical Convection 2008

This study uses the European Centre for Medium-Range Weather Forecasts (ECMWF) model-generated high-resolution 10-day-long predictions for the Year of Tropical Convection (YOTC) 2008. Precipitation forecast skills of the model over the tropics are evaluated against the Tropical Rainfall Measuring Mission (TRMM) estimates. It has been shown that the model was able to capture the monthly to seasonal mean features of tropical convection reasonably. Northward propagation of convective bands over the Bay of Bengal was also forecasted realistically up to 5 days in advance, including the onset phase of the monsoon during the first half of June 2008. However, large errors exist in the daily datasets especially for longer lead times over smaller domains. For shorter lead times (less than 4-5 days), forecast errors are much smaller over the oceans than over land. Moreover, the rate of increase of errors with lead time is rapid over the oceans and is confined to the regions where observed precipitation shows large day-to-day variability. It has been shown that this rapid growth of errors over the oceans is related to the spatial pattern of near-surface air temperature. This is probably due to the one-way air-sea interaction in the atmosphere-only model used for forecasting. While the prescribed surface temperature over the oceans remain realistic at shorter lead times, the pattern and hence the gradient of the surface temperature is not altered with change in atmospheric parameters at longer lead times. It has also been shown that the ECMWF model had considerable difficulties in forecasting very low and very heavy intensity of precipitation over South Asia. The model has too few grids with ``zero'' precipitation and heavy (>40 mm day(-1)) precipitation. On the other hand, drizzle-like precipitation is too frequent in the model compared to that in the TRMM datasets. Further analysis shows that a major source of error in the ECMWF precipitation forecasts is the diurnal cycle over the South Asian monsoon region. The peak intensity of precipitation in the model forecasts over land (ocean) appear about 6 (9) h earlier than that in the observations. Moreover, the amplitude of the diurnal cycle is much higher in the model forecasts compared to that in the TRMM estimates. It has been seen that the phase error of the diurnal cycle increases with forecast lead time. The error in monthly mean 3-hourly precipitation forecasts is about 2-4 times of the error in the daily mean datasets. Thus, effort should be given to improve the phase and amplitude forecast of the diurnal cycle of precipitation from the model.

Fuzzy State Real-Time Reservoir Operation Model for Irrigation with Gridded Rainfall Forecasts

A short-term real-time operation model with fuzzy state variables is developed for irrigation of multiple crops based on earlier work on long-term steady-state policy. The features of the model that distinguish it from the earlier work are (1) apart from inclusion of fuzziness in reservoir storage and in soil moisture of crops, spatial variations in rainfall and soil moisture of crops are included in the real-time operation model by considering gridded command area with a grid size of 0.5 degrees latitude by 0.5 degrees longitude; (2) the water allocation model and soil moisture balance equations are integrated with the real-time operation model with consideration of ponding water depth for Paddy crop; the model solution specifies reservoir releases for irrigation in a 10-day time period and allocations among the crops on a daily basis at each grid by maintaining soil moisture balance at the end of the day; and (3) the release policy is developed using forecasted daily rainfall data of each grid and is implemented for the current time period using actual 10-day inflow and actual daily rainfall of each grid. The real-time operation model is applied to Bhadra Reservoir in Karnataka, India. The results obtained using the real-time operation model are compared with those of the standard operating policy model. Inclusion of fuzziness in reservoir storage and soil moisture of crops captures hydrologic uncertainties in real time. Considerations of irrigation decisions on a daily basis and the gridded command area result in variations in allocating water to the crops, variations in actual crop evapotranspiration, and variations in soil moisture of the crops on a daily basis for each grid of the command area. (C) 2015 American Society of Civil Engineers.

Option-Implied Preferences Adjustments and Risk-Neutral Density Forecasts

The main objective of this paper is to analyse the value of information contained in prices of options on the IBEX 35 index at the Spanish Stock Exchange Market. The forward looking information is extracted using implied risk-neutral density functions estimated by a mixture of two-lognormals and three alternative risk-adjustments: the classic power and exponential utility functions and a habit-based specification that allows for a counter-cyclical variation of risk aversion. Our results show that at four-week horizon we can reject the hypothesis that between October 1996 and March 2000 the risk-neutral densities provide accurate predictions of the distributions of future realisations of the IBEX 35 index at a four-week horizon. When forecasting through risk-adjusted densities the performance of this period is statistically improved and we no longer reject that hypothesis. All risk-adjusted densities generate similar forecasting statistics. Then, at least for a horizon of four-weeks, the actual risk adjustment does not seem to be the issue. By contrast, at the one-week horizon risk-adjusted densities do not improve the forecasting ability of the risk-neutral counterparts.

Using forecasts to protect Federal facilities in the path of Hurricane Isabel

Hurricane Isabel made landfall as a Category 2 Hurricane on 18 September 2003, on the North Carolina Outer Banks between Cape Lookout and Cape Hatteras, then coursed northwestward through Pamlico Sound and west of Chesapeake Bay where it downgraded to a tropical storm. Wind damage on the west and southwest shores of Pamlico Sound and the western shore of Chesapeake Bay was moderate, but major damage resulted from the storm tide. The NOAA, National Ocean Service, National Centers for Coastal Ocean Sciences, Center for Coastal Fisheries and Habitat Research at Beaufort, North Carolina and the Center for Coastal Environmental Health and Biomedical Research Branch at Oxford, Maryland have hurricane preparedness plans in place. These plans call for tropical storms and hurricanes to be tracked carefully through NOAA National Weather Service (NWS) watches, warnings, and advisories. When a hurricane watch changes to a hurricane warning for the areas of Beaufort or Oxford, documented hurricane preparation plans are activated. Isabel exacted some wind damage at both Beaufort and Oxford. Storm tide caused damage at Oxford, where area-wide flooding isolated the laboratory for many hours. Storm tide also caused damage at Beaufort. Because of their geographic locations on or near the open ocean (Beaufort) or on or near large estuaries (Beaufort and Oxford), storm tide poses a major threat to these NOAA facilities and the safety of federal employees. Damage from storm surge and windblown water depends on the track and intensity of a storm. One tool used to predict storm surge is the Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model of the NWS, which provides valuable surge forecasts that aid in hurricane preparation.

Exploring the use of neural networks for biomass forecasts in the Peruvian upwelling ecosystem

A pilot study was conducted to study the ability of an artificial neural network to predict the biomass of Peruvian anchoveta Engraulis ringens, given time series of earlier biomasses, and of environmental parameters (ocenographic data and predator abundances). Acceptable predictions of three months or more appear feasible after thorough scrutiny of the input data set.

Wave forecasts associated with hurricane landfalls in the vicinity of Cape Lookout, North Carolina

Hurricanes can cause extensive damage to the coastline and coastal communities due to wind-generated waves and storm surge. While extensive modeling efforts have been conducted regarding storm surge, there is far less information about the effects of waves on these communities and ecosystems as storms make landfall. This report describes a preliminary use of NCCOS’ WEMo (Wave Exposure Model; Fonseca and Malhotra 2010) to compute the wind wave exposure within an area of approximately 25 miles radius from Beaufort, North Carolina for estuarine waters encompassing Bogue Sound, Back Sound and Core Sound during three hurricane landfall scenarios. The wind wave heights and energy of a site was a computation based on wind speed, direction, fetch and local bathymetry. We used our local area (Beaufort, North Carolina) as a test bed for this product because it is frequently impacted by hurricanes and we had confidence in the bathymetry data. Our test bed conditions were based on two recent Hurricanes that strongly affected this area. First, we used hurricane Isabel which made landfall near Beaufort in September 2003. Two hurricane simulations were run first by passing hurricane Isabel along its actual path (east of Beaufort) and second by passing the same storm to the west of Beaufort to show the potential effect of the reversed wind field. We then simulated impacts by a hurricane (Ophelia) with a different landfall track, which occurred in September of 2005. The simulations produced a geographic description of wave heights revealing the changing wind and wave exposure of the region as a consequence of landfall location and storm intensity. This highly conservative simulation (water levels were that of low tide) revealed that many inhabited and developed shorelines would receive wind waves for prolonged periods of time at heights far above that found during even the top few percent of non-hurricane events. The simulations also provided a sense for how rapidly conditions could transition from moderate to highly threatening; wave heights were shown to far exceed normal conditions often long before the main body of the storm arrived and importantly, at many locations that could impede and endanger late-fleeing vessels seeking safe harbor. When joined with other factors, such as storm surge and event duration, we anticipate that the WEMo forecasting tool will have significant use by local emergency agencies and the public to anticipate the relative exposure of their property arising as a function of storm location and may also be used by resource managers to examine the effects of storms in a quantitative fashion on local living marine resources.

Skill of monthly forecasts during the Northern Hemisphere summer

We have performed GCM experiments using the National Meteorological Center's Medium Range Forecasting (MRF) model to study the skill of monthly forecasts during the Northern Hemisphere summer and to test the impact of sea surface temperature anomalies (SSTAs) on such forecasts. The daily skill varies a great deal. The skillful daily forecasts last from 5 to 8 days for the Southern Hemisphere and from 6 to 8 days for the Northern Hemisphere. SSTAs have positive impact on the forecasts in the tropics and surface variables, but the impact of tropical SSTAs on the extra-tropical circulation is, in general, positive but small. Overall, the initial conditions play a more important role than SSTAs in determining the forecast skill.