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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

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48 results for Taiwan Stock Exchange

A new method for efficient option pricing using AR and MCS.

problem Infeasibility of pricing financial derivatives due to computational limitations.
method Multi-path option pricing approach via autoregression and Monte Carlo Simulations.
result Our approach is comparable to prior models in pricing weekly TAIEX options.

Volatility, fitting with first order Landau expansion, stationarity, and causality of the Taiwan stock market (TAIEX) are investigated based on daily records. Instead of consensuses that consider stock market index change as a random time series we propose the market change as a dual time series consists of the index a…

2003-04-06abs ↗pdf ↗

Quantum model outperforms classical in training but underperforms in real-world metrics.

problem Mismatch between proxy reward signals and true investment objectives in financial domains.
method Hybrid quantum-classical reinforcement learning framework with automated feature engineering.
result Quantum models achieve higher training rewards but underperform in real-world metrics.

Study finds GBM model accurately predicts stock prices on Ghana Stock Exchange.

problem Investigating the suitability of GBM for modeling stock price dynamics.
method Geometric Brownian Motion model applied to weekly and monthly returns of equities listed on the Ghana Stock Exchange.
result GBM model accurately forecasts stock prices with minimal deviations, as evidenced by MSE evaluations.

We use insight from a model of earth tectonic plate movement to obtain a new understanding of the build up and release of stress in the price dynamics of the worlds stock exchanges. Nonlinearity enters the model due to a behavioral attribute of humans reacting disproportionately to big changes. This nonlinear response …

2009-12-18abs ↗pdf ↗

This paper analyzes ETFs with Taiwan exposure, finding heavy tails and asymmetric volatility.

problem Heavy tails and asymmetric volatility in Taiwan-related ETFs.
method Tail-risk diagnostics, asymmetric volatility modeling, and portfolio optimization under mean--variance and CVaR criteria.
result CVaR optimization produces more concentrated allocations, favoring SMH during the post-COVID AI-driven expansion.

Study shows negative stock returns after Moroccan companies issue profit warnings.

problem Impact of profit warnings on stock returns in Moroccan market.
method Event study methodology, analyzing Casablanca Stock Exchange, 2009-2016.
result Negative average abnormal return after profit warning announcements, greater for qualitative than quantitative warnings.

Study the Mexican stock market's interdependency structure from 2000-2019.

problem Characterize the interdependency structure of the Mexican Stock Exchange.
method Estimate correlation/concentration matrices from different models and compute network theory metrics.
result Visualizations provide a comprehensive overview of the stock market's interdependency structure.

Study shows demonetization strengthened Indian currency and stock market.

problem Impact of demonetization on Indian stock market and foreign exchange rate.
method Daily rate of return analysis of foreign exchange rate and Nifty 50 index, use of dummy variable for demonetization period.
result Demonetization led to an upward trend in Indian stock market and strengthened the Indian currency (decreased foreign exchange rate).

We analyze the constituents stocks of the Dow Jones Industrial Average (DJIA30) and the Standard & Poor's 100 index (S&P100) of the NYSE stock exchange market. Surprisingly, we discover the data collapse of the histograms of the DJIA30 price fluctuations and of the S&P100 price fluctuations to the universal non-paramet…

2008-10-14abs ↗pdf ↗

Stock exchanges are considered major players in financial sectors of many countries. Most Stockbrokers, who execute stock trade, use technical, fundamental or time series analysis in trying to predict stock prices, so as to advise clients. However, these strategies do not usually guarantee good returns because they gui…

2014-12-17abs ↗pdf ↗

We use the correlation matrix of stocks returns in order to create maps of the São Paulo Stock Exchange (BM&F-Bovespa), Brazil's main stock exchange. The data reffer to the year 2010, and the correlations between stock returns lead to the construction of a minimum spanning tree and of asset graphs with a variety of thr…

2011-07-21abs ↗pdf ↗

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.

2001-08-28abs ↗pdf ↗

Article proposes a profitable intraday trading strategy for Chinese stocks.

problem Intraday trading opportunities in Chinese stock market.
method Markowitz optimization and Multilayer Perceptron (MLP) for stock price prediction.
result Validation of Markowitz portfolio optimization and MLP for intraday stock price prediction.

We investigate the average frequency of positive slope να+ν_α^{+}, crossing for the returns of market prices. The method is based on stochastic processes which no scaling feature is explicitly required. Using this method we define new quantity to quantify stage of development and activity of stocks exchange. We compare …

2006-01-26abs ↗pdf ↗

LSTM model predicts stock prices with high accuracy in stable sectors but struggles with volatile ones.

problem Predicting stock prices in emerging markets with limited data.
method Developed and evaluated an LSTM network on historical OHLCV data and technical indicators.
result Strong predictive performance (R2>0.87R^2 > 0.87) for stable sectors, but challenges for volatile ones.

Study examines how BRICS nations' economies respond to COVID-19.

problem Impact of COVID-19 on BRICS nations' economic indicators.
method Structural variable autoregression (SVAR) to analyze growth, exchange rate, and stock market data.
result COVID-19 shock to exchange rate growth persists for 10+ days, stock market growth for 15 days.

The study aims to explore the strength of causal relationship between stock price search interest and real stock market outcomes on worldwide equity market indices. Such a phenomenon could also be mediated by investor behavior and extent of news coverage. The stock-specific internet search trends data and corresponding…

2018-04-05abs ↗pdf ↗

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.

We confirm universal behaviors such as eigenvalue distribution and spacings predicted by Random Matrix Theory (RMT) for the cross correlation matrix of the daily stock prices of Tokyo Stock Exchange from 1993 to 2001, which have been reported for New York Stock Exchange in previous studies. It is shown that the random …

2003-12-25abs ↗pdf ↗

We respond to the issues discussed by Farmer and Lillo (FL) related to our proposed approach to understanding the origin of power-law distributions in stock price fluctuations. First, we extend our previous analysis to 1000 US stocks and perform a new estimation of market impact that accounts for splitting of large ord…

2004-03-02abs ↗pdf ↗

The article presents a new entropy model for assessing stock market interest.

problem Assessing investor interest and market sentiment in exchange-traded securities.
method Intrinsic entropy model using actual trading data, without exogenous factors.
result Empirical evidence supports the model's ability to predict trading activity.

We study the inter-stock correlations for the largest companies listed on Warsaw Stock Exchange and included in the WIG20 index. Our results from the correlation matrix analysis indicate that the Polish stock market can be well described by a one factor model. We also show that the stock-stock correlations tend to incr…

2008-03-01abs ↗pdf ↗

An original method, assuming potential and kinetic energy for prices and conservation of their sum is developed for forecasting exchanges. Connections with power law are shown. Semiempirical applications on S&P500, DJIA, and NASDAQ predict a coming recession in them. An emerging market, Istanbul Stock Exchange index IS…

2005-06-10abs ↗pdf ↗

Investment strategy for NYSE stocks minimizes market correlation.

problem Minimizing market correlation for steady returns.
method Combining momentum, fundamentals, and analyst recommendations; feature selection; backtesting various portfolio construction methods.
result Risk parity outperformed other methods, offering higher Sharpe ratio and lower beta.