Forecasting high-frequency futures returns using online langevin dynamics

Forecasting the returns of assets at high frequency is the key challenge for high-frequency algorithmic trading strategies. In this paper, we propose a jump-diffusion model for asset price movements that models price and its trend and allows a momentum strategy to be developed. Conditional on jump times, we derive closed-form transition densities for this model. We show how this allows us to extract a trend from high-frequency finance data by using a Rao-Blackwellized variable rate particle filter to filter incoming price data. Our results show that even in the presence of transaction costs our algorithm can achieve a Sharpe ratio above 1 when applied across a portfolio of 75 futures contracts at high frequency. © 2011 IEEE.

Community-led resettlement: From a flood-affected slum to a new society in Pune, India

This paper describes the resettlement process of a community devastated by annual floods, to newly constructed housing in Pune, India. The relocation from Kamgar Putala slum to a housing society at Hadapsar was organized by a community-led NGO partnership in 2004. The housing development was coordinated by the local NGO Shelter Associates with significant community participation. The housing has been revisited in 2010 to evaluate the sustainability of the resettlement project's delivery model via stakeholder perception. The process of organizing for resettlement after natural disaster is described along with the implementation and evaluation of the new housing nearly six years after initial occupation. The strong partnership approach overcame a series of political and financial hurdles at various stages of the relocation project. The story of resettling Kamgar Putala is detailed alongside an outline of the current political climate for an alternative slum-upgrading policy in India and Pune. The advantages of an empowered community supported by an influential local NGO demonstrate a commendable team effort which has tackled the threat of floods. The paper highlights the merits of a community-led partnership approach to housing development for achieving sustainable urban development as well as the alleviation of poverty in a developing context. © 2011 Taylor & Francis.

Forecasting Daily Chlorophyll a Concentration during the Spring Phytoplankton Bloom Period in Xiangxi Bay of the Three-Gorges Reservoir by Means of a Recurrent Artificial Neural Network

A recurrent artificial neural network was used for 0-and 7-days-ahead forecasting of daily spring phytoplankton bloom dynamics in Xiangxi Bay of Three-Gorges Reservoir with meteorological, hydrological, and limnological parameters as input variables. Daily data from the depth of 0.5 m was used to train the model, and data from the depth of 2.0 m was used to validate the calibrated model. The trained model achieved reasonable accuracy in predicting the daily dynamics of chlorophyll a both in 0-and 7-days-ahead forecasting. In 0-day-ahead forecasting, the R-2 values of observed and predicted data were 0.85 for training and 0.89 for validating. In 7-days-ahead forecasting, the R-2 values of training and validating were 0.68 and 0.66, respectively. Sensitivity analysis indicated that most ecological relationships between chlorophyll a and input environmental variables in 0-and 7-days-ahead models were reasonable. In the 0-day model, Secchi depth, water temperature, and dissolved silicate were the most important factors influencing the daily dynamics of chlorophyll a. And in 7-days-ahead predicting model, chlorophyll a was sensitive to most environmental variables except water level, DO, and NH3N.

Application of forecasting structural cracks technique of 3D move in Chengdao buried hill

3DMove software, based on the three-dimension structural model of geologic interpretation, can forecast reservoir cracks from the point of view of formation of the structural geology, and analyze the characteristics of the cracks. 3DMove software dominates in forecasting cracks. We forecast the developments and directions of the cracks in Chengbei buried hill with the application of forecasting technique in 3DMove software, and obtain the chart about strain distributing on top in buried hill and the chart about relative density and orientation and the chart about the analysis of crack unsealing. In Chengbei 30 buried hill zone, north-west and north-east and approximately east-west cracks in Cenozoic are very rich and the main directions in every fault block are different. Forecasting results that are also verified by those of drilling approximately accord with the data from well logging, the case of which shows that the technique has the better ability in forecasting cracks, and takes more effects on exploration and exploitation of crack reservoir beds in ancient buried hill reservoirs.

开发早期油藏动态地质模型与油藏工程优化研究——以埕岛油田馆上段油藏为例

In order to developing reservoir of Upper of Ng at high-speed and high-efficient in Chengdao oilfield which is located in the bally shallow sea, the paper builds up a series of theory and means predicting and descripting reservoir in earlier period of oilfield development. There are some conclusions as follows. 1. It is the first time to form a series of technique of fine geological modeling of the channel-sandy reservoir by means of mainly seismic methods. These technique include the logging restriction seismic inversion, the whole three dimension seismic interpretation, seismic properties analysis and so on which are used to the 3-dimension distributing prediction of sandy body, structure and properties of the channel reservoir by a lot of the seismic information and a small quantity of the drilling and the logging information in the earlier stage of the oil-field development. It is the first time that these methods applied to production and the high-speed development of the shallow sea oilfield. The prediction sandy body was modified by the data of new drilling, the new reservoir prediction thinking of traced inversion is built. The applied effect of the technique was very well, according to approximately 200 wells belonging to 30 well groups in Chengdao oilfield, the drilling succeeded rate of the predicting sandy body reached 100%, the error total thickness only was 8%. 2. The author advanced the thinking and methods of the forecasting residual-oil prediction at the earlier stage of production. Based on well data and seismic data, correlation of sediment units was correlated by cycle-correlation and classification control methods, and the normalization and finely interpretation of the well logging and sedimentation micro-facies were acquired. On the region of poor well, using the logging restriction inversion technique and regarding finished drilling production well as the new restriction condition, the sand body distributing and its property were predicted again and derived 3-dimension pool geologic model including structure, reservoir, fluid, reservoir engineering parameter and producing dynamic etc. According to the reservoir geologic model, the reservoir engineering design was optimized, the tracking simulation of the reservoir numerical simulation was done by means of the dynamic data (pressure, yield and water content) of development well, the production rule and oil-water distributing rule was traced, the distributing of the remaining oil was predicted and controlled. The dynamic reservoir modeling method in metaphase of development was taken out. Based on the new drilling data, the static reservoir geologic model was momentarily modified, the research of the flow units was brought up including identifying flow units, evaluating flow units capability and establishing the fine flow units model; according to the dynamic data of production and well testing data, the dynamic tracing reservoir description was realized through the constant modification of the reservoir geologic model restricted these dynamic data by the theory of well testing and the reservoir numerical simulation. It was built the dynamic tracing reservoir model, which was used to track survey of the remaining oil on earlier period. The reservoir engineering tracking analysis technique on shallow sea oilfield was founded. After renewing the structure history since tertiary in Chengdao area by the balance section technique and estimating the activity character of the Chengbei fault by the sealing fault analysis technique, the meandering stream sediment pattern of the Upper of Ng was founded in which the meandering border was the uppermost reservoir unit. Based on the specialty of the lower rock component maturity and the structure maturity, the author founded 3 kinds of pore structure pattern in the Guanshang member of Chengdao oil-field in which the storing space mainly was primary (genetic) inter-granular pore, little was secondary solution pore and the inter-crystal pore tiny pore, and the type of throat mainly distributed as the slice shape and the contract neck shape. The positive rhythmic was briefly type included the simple positive rhythm, the complex positive rhythm and the compound rhythm. Interbed mainly is mudstone widely, the physical properties and the calcite interbed distribute localized. 5. The author synthetically analyzed the influence action of the micro-heterogeneity, the macro-heterogeneity and the structure heterogeneity to the oilfield water flood development. The efficiency of water flood is well in tiny structure of convex type or even type at top and bottom in which the water breakthrough of oil well is soon at the high part of structure when inject at the low part of structure, and the efficiency of water flood is poor in tiny structure of concave type at top and bottom. The remaining oil was controlled by sedimentary facies; the water flooding efficiency is well in the border or channel bar and is bad in the floodplain or the levee. The separation and inter layer have a little influence to the non-obvious positive rhythm reservoir, in which the remaining oil commonly locate within the 1-3 meter of the lower part of the separation and inter layer with lower water flooding efficiency.

Is China's fifth-largest inland lake to dry-up? Incorporated hydrological and satellite-based methods for forecasting Hulun Lake water levels

Hulun Lake, China’s fifth-largest inland lake, experienced severe declines in water level in the period of 2000-2010. This has prompted concerns whether the lake is drying up gradually. A multi-million US dollar engineering project to construct a water channel to transfer part of the river flow from a nearby river to maintain the water level was completed in August 2010. This study aimed to advance the understanding of the key processes controlling the lake water level variation over the last five decades, as well as investigate the impact of the river transfer engineering project on the water level. A water balance model was developed to investigate the lake water level variations over the last five decades, using hydrological and climatic data as well as satellite-based measurements and results from land surface modelling. The investigation reveals that the severe reduction of river discharge (- 364±64 mm/yr, ~70% of the five-decade average) into the lake was the key factor behind the decline of the lake water level between 2000 and 2010. The decline of river discharge was due to the reduction of total runoff from the lake watershed. This was a result of the reduction of soil moisture due to the decrease of precipitation (-49±45 mm/yr) over this period. The water budget calculation suggests that the groundwater component from the surrounding lake area as well as surface run off from the un-gauged area surrounding the lake contributed ~ net 210 Mm3/yr (equivalent to ~ 100 mm/yr) water inflows into the lake. The results also show that the water diversion project did prevent a further water level decline of over 0.5 m by the end of 2012. Overall, the monthly water balance model gave an excellent prediction of the lake water level fluctuation over the last five decades and can be a useful tool to manage lake water resources in the future.

Uncertainty in wind energy forecasting

Wind energy is the energy source that contributes most to the renewable energy mix of European countries. While there are good wind resources throughout Europe, the intermittency of the wind represents a major problem for the deployment of wind energy into the electricity networks. To ensure grid security a Transmission System Operator needs today for each kilowatt of wind energy either an equal amount of spinning reserve or a forecasting system that can predict the amount of energy that will be produced from wind over a period of 1 to 48 hours. In the range from 5m/s to 15m/s a wind turbine’s production increases with a power of three. For this reason, a Transmission System Operator requires an accuracy for wind speed forecasts of 1m/s in this wind speed range. Forecasting wind energy with a numerical weather prediction model in this context builds the background of this work. The author’s goal was to present a pragmatic solution to this specific problem in the ”real world”. This work therefore has to be seen in a technical context and hence does not provide nor intends to provide a general overview of the benefits and drawbacks of wind energy as a renewable energy source. In the first part of this work the accuracy requirements of the energy sector for wind speed predictions from numerical weather prediction models are described and analysed. A unique set of numerical experiments has been carried out in collaboration with the Danish Meteorological Institute to investigate the forecast quality of an operational numerical weather prediction model for this purpose. The results of this investigation revealed that the accuracy requirements for wind speed and wind power forecasts from today’s numerical weather prediction models can only be met at certain times. This means that the uncertainty of the forecast quality becomes a parameter that is as important as the wind speed and wind power itself. To quantify the uncertainty of a forecast valid for tomorrow requires an ensemble of forecasts. In the second part of this work such an ensemble of forecasts was designed and verified for its ability to quantify the forecast error. This was accomplished by correlating the measured error and the forecasted uncertainty on area integrated wind speed and wind power in Denmark and Ireland. A correlation of 93% was achieved in these areas. This method cannot solve the accuracy requirements of the energy sector. By knowing the uncertainty of the forecasts, the focus can however be put on the accuracy requirements at times when it is possible to accurately predict the weather. Thus, this result presents a major step forward in making wind energy a compatible energy source in the future.

Contribution of the North Atlantic subtropical high to regional climate model (RCM) skill in simulating southeastern United States summer precipitation

© 2014, Springer-Verlag Berlin Heidelberg.This study assesses the skill of advanced regional climate models (RCMs) in simulating southeastern United States (SE US) summer precipitation and explores the physical mechanisms responsible for the simulation skill at a process level. Analysis of the RCM output for the North American Regional Climate Change Assessment Program indicates that the RCM simulations of summer precipitation show the largest biases and a remarkable spread over the SE US compared to other regions in the contiguous US. The causes of such a spread are investigated by performing simulations using the Weather Research and Forecasting (WRF) model, a next-generation RCM developed by the US National Center for Atmospheric Research. The results show that the simulated biases in SE US summer precipitation are due mainly to the misrepresentation of the modeled North Atlantic subtropical high (NASH) western ridge. In the WRF simulations, the NASH western ridge shifts 7° northwestward when compared to that in the reanalysis ensemble, leading to a dry bias in the simulated summer precipitation according to the relationship between the NASH western ridge and summer precipitation over the southeast. Experiments utilizing the four dimensional data assimilation technique further suggest that the improved representation of the circulation patterns (i.e., wind fields) associated with the NASH western ridge substantially reduces the bias in the simulated SE US summer precipitation. Our analysis of circulation dynamics indicates that the NASH western ridge in the WRF simulations is significantly influenced by the simulated planetary boundary layer (PBL) processes over the Gulf of Mexico. Specifically, a decrease (increase) in the simulated PBL height tends to stabilize (destabilize) the lower troposphere over the Gulf of Mexico, and thus inhibits (favors) the onset and/or development of convection. Such changes in tropical convection induce a tropical–extratropical teleconnection pattern, which modulates the circulation along the NASH western ridge in the WRF simulations and contributes to the modeled precipitation biases over the SE US. In conclusion, our study demonstrates that the NASH western ridge is an important factor responsible for the RCM skill in simulating SE US summer precipitation. Furthermore, the improvements in the PBL parameterizations for the Gulf of Mexico might help advance RCM skill in representing the NASH western ridge circulation and summer precipitation over the SE US.

Towards an integrated forecasting system for pelagic fisheries

First results of a coupled modeling and forecasting system for the pelagic fisheries are being presented. The system consists currently of three mathematically fundamentally different model subsystems: POLCOMS-ERSEM providing the physical-biogeochemical environment implemented in the domain of the North-West European shelf and the SPAM model which describes sandeel stocks in the North Sea. The third component, the SLAM model, connects POLCOMS-ERSEM and SPAM by computing the physical-biological interaction. Our major experience by the coupling model subsystems is that well-defined and generic model interfaces are very important for a successful and extendable coupled model framework. The integrated approach, simulating ecosystem dynamics from physics to fish, allows for analysis of the pathways in the ecosystem to investigate the propagation of changes in the ocean climate and lower trophic levels to quantify the impacts on the higher trophic level, in this case the sandeel population, demonstrated here on the base of hindcast data. The coupled forecasting system is tested for some typical scientific questions appearing in spatial fish stock management and marine spatial planning, including determination of local and basin scale maximum sustainable yield, stock connectivity and source/sink structure. Our presented simulations indicate that sandeels stocks are currently exploited close to the maximum sustainable yield, but large uncertainty is associated with determining stock maximum sustainable yield due to stock eigen dynamics and climatic variability. Our statistical ensemble simulations indicates that the predictive horizon set by climate interannual variability is 2–6 yr, after which only an asymptotic probability distribution of stock properties, like biomass, are predictable.

Order Flow and the Monetary Model of Exchange Rates: Evidence from a Novel Data Set

We propose an exchange rate model that is a hybrid of the conventional specification with monetary fundamentals and the Evans–Lyons microstructure approach. We estimate a model augmented with order flow variables, using a unique data set: almost 100 monthly observations on interdealer order flow on dollar/euro and dollar/yen. The augmented macroeconomic, or “hybrid,” model exhibits greater in-sample stability and out of sample forecasting improvement vis-à-vis the basic macroeconomic and random walk specifications.

Habitat Isolation Reduces the Temporal Stability of Island Ecosystems in the Face of Flood Disturbance

Natural ecosystems are increasingly exposed to multiple anthropogenic stressors, including land-use change, deforestation, agricultural intensification, and urbanisation, all of which have led to widespread habitat fragmentation, which is also likely to be amplified further by predicted climate change. The potential interactive effects of these different stressors cannot be determined by studying each in isolation, although such synergies have been largely ignored in ecological field studies to date. Here, we use a model system of naturally fragmented islands in a braided river network, which is exposed to periodic inundation, to investigate the interactive effects of habitat isolation and flood disturbance. Food web structure was similar across the islands during periods of hydrological stability, but several key properties were altered in the aftermath of flood disturbance, based on distance of the islands from the regional source pool of species: taxon richness and mean food chain length declined with habitat isolation after flooding, while the proportion of basal species increased. Greater species turnover through time reflected the slower process of re-colonisation on the more distant islands following disturbance. Increased variability of several food web properties over a 1-year period highlighted the reduced temporal stability of isolated habitat fragments. Many of these effects reflected the differential successes of predator and prey species at re-colonising the islands: even though larger, more mobile consumers may reach the more distant islands first, they cannot establish populations until the lower trophic levels have successfully reassembled. These results highlight the susceptibility of fragmented ecosystems to environmental perturbations. © 2013 Elsevier Ltd.

Forecasting Death Rates Using Exogenous Determinants

Mortality models used for forecasting are predominantly based on the statistical properties of time series and do not generally incorporate an understanding of the forces driving secular trends. This paper addresses three research questions: Can the factors found in stochastic mortality-forecasting models be associated with real-world trends in health-related variables? Does inclusion of health-related factors in models improve forecasts? Do resulting models give better forecasts than existing stochastic mortality models? We consider whether the space spanned by the latent factor structure in mortality data can be adequately described by developments in gross domestic product, health expenditure and lifestyle-related risk factors using statistical techniques developed in macroeconomics and finance. These covariates are then shown to improve forecasts when incorporated into a Bayesian hierarchical model. Results are comparable or better than benchmark stochastic mortality models.

Bandwidth selection by cross-validation for forecasting long memory financial time series

The paper addresses the issue of choice of bandwidth in the application of semiparametric estimation of the long memory parameter in a univariate time series process. The focus is on the properties of forecasts from the long memory model. A variety of cross-validation methods based on out of sample forecasting properties are proposed. These procedures are used for the choice of bandwidth and subsequent model selection. Simulation evidence is presented that demonstrates the advantage of the proposed new methodology.

Is China's fifth-largest inland lake to dry-up? Incorporated hydrological and satellite-based methods for forecasting Hulun Lake water levels

Hulun Lake, China's fifth-largest inland lake, experienced severe declines in water level in the period of 2000-2010. This has prompted concerns whether the lake is drying up gradually. A multi-million US dollar engineering project to construct a water channel to transfer part of the river flow from a nearby river to maintain the water level was completed in August 2010. This study aimed to advance the understanding of the key processes controlling the lake water level variation over the last five decades, as well as investigate the impact of the river transfer engineering project on the water level. A water balance model was developed to investigate the lake water level variations over the last five decades, using hydrological and climatic data as well as satellite-based measurements and results from land surface modelling. The investigation reveals that the severe reduction of river discharge (-364±64 mm/yr, ∼70% of the five-decade average) into the lake was the key factor behind the decline of the lake water level between 2000 and 2010. The decline of river discharge was due to the reduction of total runoff from the lake watershed. This was a result of the reduction of soil moisture due to the decrease of precipitation (-49±45 mm/yr) over this period. The water budget calculation suggests that the groundwater component from the surrounding lake area as well as surface run off from the un-gauged area surrounding the lake contributed ∼ net 210 Mm3/yr (equivalent to ∼ 100 mm/yr) water inflows into the lake. The results also show that the water diversion project did prevent a further water level decline of over 0.5 m by the end of 2012. Overall, the monthly water balance model gave an excellent prediction of the lake water level fluctuation over the last five decades and can be a useful tool to manage lake water resources in the future.