Study of BSE sectors' behavior and indicators of financial crashes.
problem Understanding financial crashes in the Bombay Stock Exchange.
method Analysis of daily returns, cross correlation coefficients, and PE ratios.
result PE ratio can predict impending financial market crashes.
We apply a recently developed wavelet based approach to characterize the correlation and scaling properties of non-stationary financial time series. This approach is local in nature and it makes use of wavelets from the Daubechies family for detrending purpose. The built-in variable windows in wavelet transform makes t…
Study finds Indian stock market inefficient, suggesting undervalued securities offer returns.
problem Determining market efficiency and identifying undervalued securities.
method Analyzed five BSE indices, tested random walk model, and identified biased random time series.
result Indian stock market is inefficient, with undervalued securities offering higher returns.
Study compares Indian derivatives markets and finds NSE outperforming BSE.
problem Lack of strong regulations and robust framework in Indian derivatives market.
method Comparison of performance of derivatives in BSE and NSE, analysis of derivatives with cash market and market volatility.
result NSE derivatives outperform BSE, need stronger regulations.
Study reveals complex, multi-scale relationships between NYSE and BSE indexes.
problem Understanding the causal and correlation dynamics between NYSE and BSE indexes.
method Multi-scale analysis of monthly closing price indexes over 300 months.
result NYSE Granger causes BSE with a 9-month lag, and BSE reflects NYSE fluctuations with a smaller lag.
BSE simulates a stock exchange for teaching and research.
problem Lack of realistic teaching and research environments for automated trading systems.
method Minimal simulation of a Limit Order Book (LOB) system.
result BSE successfully used for teaching and research since 2012.
In this paper we study BSE Index financial time series for fractal and multifractal behaviour. We show that Bombay stock Exchange (BSE)Index time series is mono-fractal and can be represented by a fractional Brownian motion.
Empirical study finds robust optimization can improve portfolio performance in Indian markets.
problem Comparing robust optimization to Markowitz model for portfolio performance.
method Three robust optimization models (box, ellipsoidal, separable uncertainty sets) tested on Indian market data.
result Robust optimization can be a viable alternative to Markowitz model in real market setups.
New simulation shows trading algorithms' performance varies with parallelism.
problem Validation of trading algorithms' performance in parallel markets.
method Used TBSE, a threaded market simulator, to compare algorithms' performance.
result Trading algorithms' performance differs in parallel vs. sequential markets.
Study examines downsizing impact on Indian construction firms' profitability.
problem Impact of downsizing layoffs on construction firms' profitability in India.
method Used Co-integration test, OLS, and VAR models on secondary data of 15 companies.
result Employee Expenses and Number of Employees have significant impact on profitability.
Study confirms Indian stock market is weak form inefficient.
problem Impact of stock market efficiency on investment returns.
method Runs test, Autocorrelation test, Autoregression test on daily stock indices.
result Indian stock market is weak form inefficient and can be outperformed.
One of the principal statistical features characterizing the activity in financial markets is the distribution of fluctuations in market indicators such as the index. While the developed stock markets, e.g., the New York Stock Exchange (NYSE) have been found to show heavy-tailed return distribution with a characteristi…
The nature of fluctuations in the Indian financial market is analyzed in this paper. We have looked at the price returns of individual stocks, with tick-by-tick data from the National Stock Exchange (NSE) and daily closing price data from both NSE and the Bombay Stock Exchange (BSE), the two largest exchanges in India.…
Study of stock market sectors' correlations over 8 years.
problem Understanding correlations in Indian stock market sectors.
method Direct model-free analysis of daily returns of sectors over 8 years.
result Significant auto-correlation and cross-correlation among sectors.
A fuzzy expert system selects stocks for BSE using AI techniques.
problem Selecting stocks for investment allocation is challenging due to many influencing factors.
method Dempster-Shafer (DS) evidence theory for rule base generation, portfolio optimization model with ACO algorithm.
result The model's performance is satisfactory for short-term investment.
The paper examines Indian market bubbles using financial ratios.
problem Detecting bubbles in emerging markets like India is challenging.
method Utilizes financial ratios and the Philips et al 2015 right-tailed unit test.
result Identifies various bubble episodes in the Indian market.
This paper examines how different data normalization techniques affect DNN performance in time series forecasting.
problem Improving DNN performance for time series forecasting with nonlinear, dynamic data.
method Different data normalization techniques were applied to time series data before feeding it into a DRNN model for forecasting.
result Data normalization significantly impacts the DNN's performance in time series forecasting.
We analyze the Bombay stock exchange (BSE) price index over the period of last 12 years. Keeping in mind the large fluctuations in last few years, we carefully find out the transient, non-statistical and locally structured variations. For that purpose, we make use of Daubechies wavelet and characterize the fractal beha…
Blind source separation (BSS) is one of the most important and established research topics in signal processing and many algorithms have been proposed based on different statistical properties of the source signals. For second-order statistics (SOS) based methods, canonical correlation analysis (CCA) has been proved to…
Paper predicts Indian stocks using news psycholinguistic features.
problem Predicting Indian stock market performance using financial news.
method Hybrid intelligent models using psycholinguistic variables (LIWC and TAALES) from news articles.
result GMDH and GRNN are statistically the best techniques for prediction.
We examine volatility of an Indian stock market in terms of aspects like participation, synchronization of stocks and quantification of volatility using the random matrix approach. Volatility pattern of the market is found using the BSE index for the three-year period 2000-2002. Random matrix analysis is carried out us…
The paper examines market efficiency in China and India post financial crises.
problem Testing market efficiency in emerging markets post crises.
method Examined daily returns using auto correlation tests, runs tests, and unit root tests.
result Both Chinese and Indian stock markets do not exhibit weak form of market efficiency.
New composite indicators reveal hidden relationships between indicators.
problem Subjective aggregation of indicators leads to missed information.
method Used dimensionality reduction techniques (PCA, filtering, clustering) to reveal hidden relationships.
result Cluster-driven composite indicators outperform traditional ones in data reconstruction.
The paper optimizes portfolios by selecting financial ratios via PCA for better value investment.
problem Embedding value investment in portfolio optimization models.
method Principal Component Analysis (PCA) to filter out dominant financial ratios, then applying portfolio optimization model with second-order stochastic dominance criteria.
result PCA-SPO(B) strategy outperforms other models in terms of downside deviation, CVaR, VaR, Sortino, Rachev, and STARR ratios.
Optimal text-based indices track VIX and inflation.
problem Maximizing contemporaneous relation or predictive performance with target variables.
method Optimizing text-based indices focusing on VIX and inflation expectations.
result Superior performance compared to existing indices.
Indices of vector fields and 1-forms studied for singular varieties and actions.
problem Understanding indices of vector fields and 1-forms in various contexts.
method Generalization to singular varieties and actions of finite groups.
result New insights into indices of vector fields and 1-forms.
We analyzed cross-correlations between price fluctuations of global financial indices (20 daily stock indices over the world) and local indices (daily indices of 200 companies in the Korean stock market) by using random matrix theory (RMT). We compared eigenvalues and components of the largest and the second largest ei…
This study examined how the correlation and network structure of 30 global indices and 145 local Korean indices belonging to the KOSPI 200 have changed during the 13-year period, 2000-2012. The correlations among the indices were calculated. The results showed that although the average correlations of the global indice…
Financial market created for wellbeing indices to mitigate socioeconomic risks.
problem Risk mitigation in financial indices of socioeconomic wellbeing.
method Developed new quantitative measure, created financial market, and implemented insurance instruments.
result Optimal portfolio weights and efficient frontiers for wellbeing indices.
We study the dynamic interactions and structural changes in global financial indices in the years 1998-2012. We apply a principal component analysis (PCA) to cross-correlation coefficients of the stock indices. We calculate the correlations between principal components (PCs) and each asset, known as PC coefficients. A …
Financial markets worldwide do not have the same working hours. As a consequence, the study of correlation or causality between financial market indices becomes dependent on wether we should consider in computations of correlation matrices all indices in the same day or lagged indices. The answer this article proposes …
The paper analyzes indices based on counting object pairs for assessing partition agreement in unsupervised learning.
problem The difficulty in interpreting overall indices like Rand and adjusted Rand indices.
method Analysis of three families of indices based on counting object pairs, decomposing overall indices into cluster-level indices.
result Overall indices based on pair-counting approach are sensitive to cluster size imbalance and provide limited information on smaller clusters.
The paper shows how reducible complexes affect local indicability.
problem The local indicability of subcomplexes in reducible complexes.
method Characterization of diagrammatic reducibility and application to local indicability.
result Injective labeled oriented trees are locally indicable if reducible of degree 2.
New Monte Carlo method outperforms existing strategy for estimating Sobol' indices.
problem Estimating first-and total-orders Sobol' indices accurately.
method Comparing two Monte Carlo estimators for Sobol' indices.
result New method outperforms current approach in accuracy.
Invariants for virtual and twisted links using affine indices.
problem Computing invariants for virtual and twisted links.
method Using affine indices to define invariants for virtual and twisted links.
result Invariants for virtual and twisted links computed using affine indices.
Paper simplifies Gittins indices calculation for bandits.
problem Difficulty in calculating Gittins indices for multi-armed bandits.
method Accessible general methodology for calculating Gittins indices.
result Removes computation barrier for Gittins indices.
Ranking stock indices based on causal influence using directed information graphs.
problem Identifying which countries exert the most economic influence in a subset of the global economy.
method Representing indices as nodes in a directed graph, estimating causal influences using directed information functional, ranking indices based on net-flow.
result Indices representing smaller economies can exert significant influence on larger economies.
We apply RMT, Network and MF-DFA methods to investigate correlation, network and multifractal properties of 20 global financial indices. We compare results before and during the financial crisis of 2008 respectively. We find that the network method gives more useful information about the formation of clusters as compar…
Novel approach detects early warning indicators in complex systems.
problem Detecting abrupt transitions in complex systems.
method Directed anisotropic diffusion map and latent stochastic dynamical systems.
result Early warning indicators can detect tipping points in state transitions.
Investigates local indicability of groups with circle homology presentations.
problem Conditions for local indicability in groups with circle homology presentations.
method Generalizes results for two-relator presentations to circle homology presentations.
result Extends results on local indicability to LOT groups and non-cycle-free Adian presentations.
New algorithm forecasts health indicators for better equipment lifespan prediction.
problem Improving equipment lifespan prediction through health indicator forecasting.
method Generative + scenario matching approach using Gaussian Process.
result Superior performance compared to existing methods.
The paper studies topological indices of geometric operators on manifolds with fibered boundaries.
problem Investigating indices of geometric operators on manifolds with fibered boundaries.
method Defining K-groups relative to pushforward for boundary fibration, using groupoid deformation techniques to prove properties of indices.
result Indices of twisted geometric operators can be understood as index pairings over K-groups.
New indices for determining cluster compactness and separability.
problem Challenges in identifying true clusters in data sets.
method Developed absolute cluster indices to measure compactness and separability.
result Demonstrated improved performance compared to existing indices.
Study fragility in global financial indices using network analysis.
problem Monitor fragility in global financial indices.
method Network-based approach to analyze daily closing prices of global financial indices.
result Network-centric measures reveal fragility in global financial indices.
Research uses Sutte Indicator to predict stock market movements.
problem Predicting stock market movements accurately.
method Applied Sutte Indicator alongside SMA and MACD for comparison.
result Sutte Indicator shows better reliability in predicting stock movements.
The study identifies different global dependence regimes in equity and volatility indices.
problem Varying correlations and higher moments between equity and volatility indices across continents.
method Markov-switching R-vine models to investigate changing dependence structures. result Global regime switching identified in times of 'normal' and 'abnormal' states.
Study shows HFT improves market liquidity indicators.
problem Impact of high-frequency trading on market liquidity.
method Agent-based simulations comparing HFT and non-HFT markets.
result All liquidity indicators improved in markets with HFTs.
This research simplifies computation of feature attribution methods under certain conditions.
problem Computational complexity of feature attribution methods, especially power indices.
method Identifying conditions for polynomial computation and introducing new indices.
result Conditions for efficient computation of feature attribution methods are identified.