Modeling and forecasting the outcomes of NBA basketball games

2016 ◽  
Vol 12 (1) ◽  
Author(s):  
Hans Manner
Keyword(s):  
Time Variation ◽  
State Space Model ◽  
Dynamic State ◽  
Common Finding ◽  
Forecast Combination ◽  
Weak Evidence ◽  
Betting Market ◽  
Modeling And Forecasting ◽  
The Common ◽  
Betting Odds

AbstractThis paper treats the problem of modeling and forecasting the outcomes of NBA basketball games. First, it is shown how the benchmark model in the literature can be extended to allow for heteroscedasticity and estimation and testing in this framework is treated. Second, time-variation is introduced into the model by introducing a dynamic state space model for team strengths. The in-sample results based on eight seasons of NBA data provide weak evidence for heteroscedasticity, which can lead to notable differences in estimated win probabilities. However, persistent time variation is only found when combining the data of several seasons, but not when looking at individual seasons. The models are used for forecasting a large number of regular season and playoff games and the common finding in the literature that it is difficult to outperform the betting market is confirmed. Nevertheless, a forecast combination of model based forecasts with betting odds can lead to some slight improvements.

scholarly journals Linearity extensions of the market model: a case of the top 10 cryptocurrency prices during the pre-COVID-19 and COVID-19 periods

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Serdar Neslihanoglu
Keyword(s):  
State Space Model ◽  
Additive Model ◽  
Market Model ◽  
Time Varying ◽  
Daily Data ◽  
Forecasting Performance ◽  
Modeling And Forecasting ◽  
Crypto Currency ◽  
Beta Risk ◽  
The Relationship

AbstractThis research investigates the appropriateness of the linear specification of the market model for modeling and forecasting the cryptocurrency prices during the pre-COVID-19 and COVID-19 periods. Two extensions are offered to compare the performance of the linear specification of the market model (LMM), which allows for the measurement of the cryptocurrency price beta risk. The first is the generalized additive model, which permits flexibility in the rigid shape of the linearity of the LMM. The second is the time-varying linearity specification of the LMM (Tv-LMM), which is based on the state space model form via the Kalman filter, allowing for the measurement of the time-varying beta risk of the cryptocurrency price. The analysis is performed using daily data from both time periods on the top 10 cryptocurrencies by adjusted market capitalization, using the Crypto Currency Index 30 (CCI30) as a market proxy and 1-day and 7-day forward predictions. Such a comparison of cryptocurrency prices has yet to be undertaken in the literature. The empirical findings favor the Tv-LMM, which outperforms the others in terms of modeling and forecasting performance. This result suggests that the relationship between each cryptocurrency price and the CCI30 index should be locally instead of globally linear, especially during the COVID-19 period.

scholarly journals Multi-attribute Decision-making is Best Characterized by an Attribute-Wise Reinforcement Learning Model

2017 ◽  
Author(s):  
Shaoming Wang ◽  
Bob Rehder
Keyword(s):  
Computational Models ◽  
Theoretical Models ◽  
Decision Makers ◽  
Common Finding ◽  
Cue Competition ◽  
Recency Effects ◽  
Multiple Attribute ◽  
Multi Attribute Decision Making ◽  
The Common ◽  
Alternative Choice

AbstractChoice alternatives often consist of multiple attributes that vary in how successfully they predict reward. Some standard theoretical models assert that decision makers evaluate choices either by weighting those attribute optimally in light of previous experience (so-called rational models), or adopting heuristics that use attributes suboptimally but in a manner that yields reasonable performance at minimal cost (e.g., the take-the-best heuristic). However, these models ignore both the possibility that decision makers might learn to associate reward with whole stimuli (a particular combination of attributes) rather than individual attributes and the common finding that decisions can be overly influenced by recent experiences and exhibit cue competition effects. Participants completed a two-alternative choice task where each stimulus consisted of three binary attributes that were predictive of reward, albeit with different degrees of reliability. Their choices revealed that, rather than using only the “best” attribute, they made use of all attributes but in manner that reflected the classic cue competition effect known as overshadowing. The time needed to make decisions increased as the number of relevant attributes increased, suggesting that reward was associated with attributes rather than whole stimuli. Fitting a family of computational models formed by crossing attribute use (optimal vs. only the best), representation (attribute vs. whole stimuli), and recency (biased or not), revealed that models that performed better when they made use of all information, represented attributes, and incorporated recency effects and cue competition. We also discuss the need to incorporate selective attention and hypothesis-testing like processes to account for results with multiple-attribute stimuli.

Diagnostic Evaluation of Patients Presenting with Rectal Bleeding by Colonoscopy

2020 ◽  
Vol 42 (1) ◽  
pp. 36-39
Author(s):  
Bala R Malla ◽  
Suyog Simkhada
Keyword(s):  
Rectal Bleeding ◽  
Diagnostic Yield ◽  
Adult Population ◽  
Common Finding ◽  
Common Causes ◽  
Optic Colonoscopy ◽  
The Common ◽  
Gastro Intestinal Tract ◽  
Histopathologic Findings ◽  
Malignant Mass

Introduction Rectal bleeding indicates the bleeding from lower gastro-intestinal tract occurring distal to ligaments of Treitz. Annual incidence of per rectal bleeding has been estimated to be 20% . Colonoscopy is the examination of choice for investigation. The objective of this study is to know the diagnostic yield of colonoscopy in cases with per rectal bleeding and to know the common causes of per rectal bleeding in adults MethodsOne hundred and twenty-nine adult patients, age more than 18years, who presented to Surgical OPD and ward of Dhulikhel Hospital during the year 2018 and 2019 were taken for the study irrespective of their sex. All the patients were subjected to fibre-optic colonoscopy after necessary preparation and the findings were recorded. Diagnosis was based on colonoscopic and histopathologic findings. ResultsA total of 129 (77 male and 52 female )patients with per rectal bleeding were evaluated with colonoscopy. The age ranged from 18 years to 79 years with the mean age 42.25 (SD+/- 15.29). Colonoscopy showed abnormalities in 102 patients (79.06%). The most common finding was hemorrhoids in 36 patients (27.90%) followed by colorectal malignant mass in 20 patients (15.50%). Polyps were diagnosed as the cause of rectal bleeding in 14 patients (10.84%). ConclusionColonoscopy has good diagnostic yield at evaluating cases with per rectal bleeding. Hemorrhoids, colorectal malignant mass and polyps are the common causes producing PR bleeding in Nepalese adult population.

Meteorological Tidal Predictions in the Mekong Estuary Using an Evolved ANN Time Series

2019 ◽  
Vol 53 (6) ◽  
pp. 27-34
Author(s):  
Tim Chen ◽  
C.Y.J. Chen
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Time Variation ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Neural Systems ◽  
Modeling And Forecasting ◽  
Physically Based ◽  
Artificial Neural Network Ann ◽  
Meteorological Tsunamis

AbstractThe reproduction of meteorological waves utilizing physically based hydrodynamic models is very difficult in light of the fact that it requires enormous amounts of information, for example, hydrological and water-driven time arrangement limits, stream geometry, and balance coefficients. Accordingly, an artificial neural network (ANN) strategy utilizing a back-propagation neural network (BPNN) and a radial basis function neural network (RBFNN) is perceived as a viable option for modeling and forecasting the maximum and time variation of meteorological tsunamis in the Mekong Estuary in Vietnam. The parameters, including both the nearby climatic and breeze field factors, for finding the most extreme meteorological waves are first examined, depending on the preparation of the evolved neural systems. The time series for meteorological tsunamis are used for training and testing the models, and data for three cyclones are used for model prediction. This study finds that the proposed advanced ANN time series model is easy to utilize with display and prediction tools for simulating the time variation of meteorological tsunamis.

The common finding of covert hypothyroidism at initial clinical evaluation for hyperlipoproteinemia

1991 ◽  
Vol 201 (1-2) ◽  
pp. 113-122 ◽  
Author(s):  
Charles J. Glueck ◽  
James Lang ◽  
Trent Tracy ◽  
James Speirs
Keyword(s):  
Clinical Evaluation ◽  
Common Finding ◽  
The Common ◽  
Initial Clinical Evaluation

AN EXAMINATION OF IN-PLAY SPORTS BETTING USING ONE-DAY CRICKET MATCHES

2012 ◽  
Vol 1 (2) ◽  
pp. 93-109
Author(s):  
Steve Easton ◽  
Katherine Uylangco
Keyword(s):  
Financial Markets ◽  
Psychological Factors ◽  
Predictive Ability ◽  
Sports Betting ◽  
Bad News ◽  
Good News ◽  
Informational Efficiency ◽  
Betting Market ◽  
Betting Markets ◽  
Betting Odds

There is a wide literature on sports betting markets, a literature that examines the informational efficiency of these markets and uses them as laboratories to test for possible impacts of psychological factors on financial markets. The innovation of this study is the examination of price behaviour in an in-play betting market – namely that for one-day cricket. Cricket provides an ideal construct in which to examine in-play market behaviour, as it is a sport where outcomes can be calibrated as good news or bad news on a play-by-play basis. The results from an examination of over 8000 balls corresponding to over 8000 “news events” shows that the in-play betting market is one in which news is impounded rapidly into betting odds. There is also evidence that odds have a level of predictive ability with respect to outcomes from balls before they are bowled. Further, there is evidence of a drift in odds subsequent to the outcome of balls being known.

Poisson flats in Euclidean spaces Part I: A finite number of random uniform flats

1969 ◽  
Vol 1 (2) ◽  
pp. 211-237 ◽  
Author(s):  
R. E. Miles
Keyword(s):  
Euclidean Space ◽  
Finite Number ◽  
Time Variation ◽  
Stochastic Independence ◽  
Geometrical Probability ◽  
Wide Range ◽  
Dimensional Distribution ◽  
The Common ◽  
High Degree ◽  
Physical Phenomena

This is the first part of a three part work, the common setting being Ed, Euclidean space of d dimensions. Many random physical phenomena, often in the form of structures, admit models which are assemblages of random s-flats in Ed. Indeed, taking s = 0, any n-sample from a d-dimensional distribution may of course be so regarded! For static phenomena generally 0 ≦ s < d ≦ 3, while 4 is to be substituted for 3 if time variation is allowed. By postulating a high degree of stochastic independence and uniformity, a variety of “simple” models is defined. However, their investigation poses problems in geometrical probability of a wide range of difficulty; the solutions of many of which are still far from complete.

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