EXPLOITING INEFFICIENCIES IN FINANCIAL AND SPORTS GAMBLING MARKETS: EXPLORATORY DRIFT MODELING

2012 ◽  
Vol 2 (3) ◽  
pp. 15-32
Author(s):  
William Mallios
Keyword(s):  
Time Series ◽  
Financial Markets ◽  
Public Information ◽  
Arma Models ◽  
Financial Modeling ◽  
Insider Information ◽  
Sports Gambling ◽  
Time Varying Parameter ◽  
Market Inefficiency ◽  
Individual Series

Cointegrated time series associated with financial and sports gambling markets are analyzed in terms of time-varying parameter models. Parameter drift is modeled in terms of lagged disequilibria. Model forecasts are intended to capitalize on periods of market inefficiency. Modeling premises are that (1) present and past disequilibria—shocks both within and between time series—may affect subsequent changes and rates of these changes within individual series and (2) sufficiently large shocks may disrupt/alter model structure such that resulting forecasts may be temporarily unreliable. Reduced forecasting equations are in terms of higher order ARMA models that are not limited to bilinear processes. Sports forecasting models based on public information are usually more effective—in terms of profitable trading/wagering strategies—than those for the financial sector for two reasons: (1) Insider information is less prevalent. (2) Modeling is simplified since lagged shocks associated with the gambling lines/spreads are known—in contrast with financial modeling where there are no comparable gambling shocks, only unknown, lagged statistical shocks in terms of MA variables. Forecasting is illustrated for NFL and NBA playoff games. In financial markets, cointegration is discussed in terms of candlestick chart variants with modeling illustrations given in terms of recent Google price changes.

Opportunities for improving the insider laws: A comparative analysis of the practice in the USA and Russia

2020 ◽  
Vol 26 (4) ◽  
pp. 796-814
Author(s):  
E.K. Ovakimyan
Keyword(s):  
Financial Markets ◽  
Insider Trading ◽  
Negative Impact ◽  
Business Environment ◽  
Market Manipulation ◽  
Insider Information ◽  
Analysis And Synthesis ◽  
The Usa ◽  
Legislative Perfection ◽  
Definition Of

Subject. The article examines the laws regulating insider trading. Objectives. The study outlines recommendations for refining Law On Countering the Illegal Use of Insider Information and Market Manipulation and Amendments to Some Legislative Acts of the Russian Federation, № 224-ФЗ of July 27, 2010. Methods. The methodological framework includes a general dialectical method, analysis and synthesis, induction and deductions, and some specific methods, such as comparative and formal logic analysis to specify the definition of insider information, structural logic and functional analysis to improve the mechanism for countering insider trading and market manipulation. Results. We discovered key drawbacks to be addressed so as to improve the business environment in Russia. Although the Russia laws mainly mirror the U.S. laws, they present a more extended list of terms concerning the insider information. I believe the legislative perfection should be continued. Conclusions and Relevance. The study helps apply the findings to outline a new legislative regulation or amend the existing ones, add a new mention on the course of financial markets to students’ books, develop new methods for detecting and countering and improving the existing ones. If all parties to insider relationships use the findings, they will prevent insider trading crimes in financial markets and (or) reduce the negative impact of such crimes on the parties.

scholarly journals Overweighting of public information in financial markets: A lesson from the lab

2021 ◽  
pp. 106298
Author(s):  
Alba Ruiz-Buforn ◽  
Eva Camacho-Cuena ◽  
Andrea Morone ◽  
Simone Alfarano
Keyword(s):  
Financial Markets ◽  
Public Information

scholarly journals Minimum Message Length in Hybrid ARMA and LSTM Model Forecasting

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1601
Author(s):  
Zheng Fang ◽  
David L. Dowe ◽  
Shelton Peiris ◽  
Dedi Rosadi
Keyword(s):  
Time Series ◽  
Environmental Science ◽  
Short Term Memory ◽  
Arima Model ◽  
Theoretic Approach ◽  
Arma Models ◽  
Information Theoretic ◽  
Minimum Message Length ◽  
Message Length ◽  
Real World Datasets

Modeling and analysis of time series are important in applications including economics, engineering, environmental science and social science. Selecting the best time series model with accurate parameters in forecasting is a challenging objective for scientists and academic researchers. Hybrid models combining neural networks and traditional Autoregressive Moving Average (ARMA) models are being used to improve the accuracy of modeling and forecasting time series. Most of the existing time series models are selected by information-theoretic approaches, such as AIC, BIC, and HQ. This paper revisits a model selection technique based on Minimum Message Length (MML) and investigates its use in hybrid time series analysis. MML is a Bayesian information-theoretic approach and has been used in selecting the best ARMA model. We utilize the long short-term memory (LSTM) approach to construct a hybrid ARMA-LSTM model and show that MML performs better than AIC, BIC, and HQ in selecting the model—both in the traditional ARMA models (without LSTM) and with hybrid ARMA-LSTM models. These results held on simulated data and both real-world datasets that we considered. We also develop a simple MML ARIMA model.

scholarly journals ARMA Models for Zero Inflated Count Time Series

2021 ◽  
Author(s):  
Vurukonda Sathish ◽  
Siuli Mukhopadhyay ◽  
Rashmi Tiwari
Keyword(s):  
Time Series ◽  
Arma Models ◽  
Count Time Series

Analysis of Time Series Based on a New Entropy Plane by Using Weighted Dispersion Pattern

2021 ◽  
Vol 31 (09) ◽  
pp. 2150128
Author(s):  
Guyue Qin ◽  
Pengjian Shang
Keyword(s):  
Time Series ◽  
Financial Markets ◽  
Stock Markets ◽  
Simulated Data ◽  
Tsallis Entropy ◽  
Dispersion Pattern ◽  
Complex Time ◽  
Plane Method ◽  
Stock Indexes ◽  
Analysis Of Time Series

Complexity is an important feature of complex time series. In this paper, we construct a weighted dispersion pattern and propose a new entropy plane using past Tsallis entropy and past Rényi entropy by using weighted dispersion pattern (PTEWD and PREWD, respectively), to quantify the complexity of time series. Through analyzing simulated data and actual data, we have verified the reliability of the entropy plane method. This entropy plane successfully distinguishes American and Chinese stock indexes, as well as developed and emergent stock markets. We introduce PTEWD and PREWD into multiscale settings, which could also well distinguish different stock markets. The results show that the new entropy plane could be used as an effective tool to distinguish financial markets.

Ambiguity in Insider Trading Regulations: Saudi Arabia as a Case Study

2020 ◽  
Vol 34 (4) ◽  
pp. 408-427
Author(s):  
Yahya A. Alomari
Keyword(s):  
Saudi Arabia ◽  
Insider Trading ◽  
Public Information ◽  
Case Law ◽  
Insider Information ◽  
The Law ◽  
Definition Of ◽  
Criminal Conduct ◽  
Material Information

Abstract The Saudi legal system recognises insider trading as a crime and has established laws in order to prevent it. Yet, the complicated nature of insider trading makes it challenging to enact regulations that cover all of the aspects of the crime and clearly identify criminal conduct. This article analyses insider trading regulations in Saudi Arabia and addresses their ambiguities. This article specifies current Saudi regulations pertaining to the crimes of insider trading and disclosing material information, as well as analysing both crimes. It addresses ambiguities found in the language of the law as well as in case law. This article also criticises the definition of insider information under the law. The issue of ‘use’ versus ‘possession’ is discussed: namely, whether what is prohibited is trading on the basis of material non-public information or trading while in possession of material non-public information.

scholarly journals Volatility Similarity and Spillover Effects in G20 Stock Market Comovements: An ICA-Based ARMA-APARCH-M Approach

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Shanglei Chai ◽  
Zhen Zhang ◽  
Mo Du ◽  
Lei Jiang
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Financial Markets ◽  
Stock Markets ◽  
Time Series Data ◽  
Multivariate Time Series ◽  
Spillover Effects ◽  
Series Data ◽  
Dominant Source ◽  
Financial Internationalization

Financial internationalization leads to similar fluctuations and spillover effects in financial markets around the world, resulting in cross-border financial risks. This study examines comovements across G20 international stock markets while considering the volatility similarity and spillover effects. We provide a new approach using an ICA- (independent component analysis-) based ARMA-APARCH-M model to shed light on whether there are spillover effects among G20 stock markets with similar dynamics. Specifically, we first identify which G20 stock markets have similar volatility features using a fuzzy C-means time series clustering method and then investigate the dominant source of volatility spillovers using the ICA-based ARMA-APARCH-M model. The evidence has shown that the ICA method can more accurately capture market comovements with nonnormal distributions of the financial time series data by transforming the multivariate time series into statistically independent components (ICs). Our findings indicate that the G20 stock markets are clustered into three categories according to volatility similarity. There are spillover effects in stock market comovements of each group and the dominant source can be identified. This study has important implications for investors in international financial markets and for policymakers in G20 countries.

Herding behaviour and Islamic market efficiency assessment: case of Dow Jones and Sukuk market

2019 ◽  
Vol 13 (1) ◽  
pp. 24-41
Author(s):  
Emna Mnif ◽  
Bassem Salhi ◽  
Anis Jarboui
Keyword(s):  
Financial Markets ◽  
Market Efficiency ◽  
Hurst Exponent ◽  
Efficiency Index ◽  
Parameter Method ◽  
Content Type ◽  
Efficiency Assessment ◽  
Time Varying Parameter ◽  
Activity Types ◽  
The Impact

Purpose The purpose of this paper is to present the Islamic stock and Sukuk market efficiency and focus on the presence of investor herding behaviour (HB) captured by Hurst exponent estimation. Design/methodology/approach The Hurst exponent was estimated with various methods. The authors studied the evolving efficiency of the “Dow Jones” indices from 1 January 2010 to 30 December 2016 using a rolling sample of the Hurst exponent. In addition, they used a time-varying parameter method based on the Hurst of delayed returns. After that, the robust Hurst method was considered. In the next step, the efficiency of the different activity types of Islamic bonds was studied using an efficiency index. Finally, the Hurst exponent estimates were applied to assess the presence of HB. Findings The results show that, firstly, there’s a strong correlation between the “DJIM” and “DJSI” prices and returns. Secondly, by using robust Hurst estimate, it is observed that the “DJIM” is the most efficient market. The Hurst exponent estimation results show that HB is more intensive in the Islamic stock market. These results indicate also the inexistence of this behaviour in the studied Sukuk market. Research limitations/implications Sukuk as Islamic financial assets is recent. Their relative time series are not long enough to apply the long memory approach. Furthermore, this work can be extended to study other Islamic financial markets. Practical implications Herding affects risk-return characteristics of assets and has an impact on asset pricing models. Practitioners are interested in understanding herding and its timing as it might create profitable trading opportunities. Social implications This work analyses the impact of Islamic principles on the financial markets and their ability to understand some behavioural biases. Originality/value This study contributes to the literature by identifying the efficiency and the presence of HB with Hurst exponent estimation in Islamic markets.

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