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Malaysia's main stock market index, the FKLCI, fell to 1536 points on July 11, 2025, losing 0.03% from the previous session. Over the past month, the index has climbed 0.62%, though it remains 5.13% lower than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Malaysia. Malaysia Stock Market (FBM KLCI) - values, historical data, forecasts and news - updated on July of 2025.
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Prices for FTSE Bursa Malaysia KLCI Index including live quotes, historical charts and news. FTSE Bursa Malaysia KLCI Index was last updated by Trading Economics this July 13 of 2025.
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Key information about Malaysia Composite
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Bursa Malaysia: Dividend Yield: FTSE Composite Index data was reported at 3.320 % pa in Apr 2025. This records an increase from the previous number of 2.100 % pa for Mar 2025. Bursa Malaysia: Dividend Yield: FTSE Composite Index data is updated monthly, averaging 3.080 % pa from Jul 2009 (Median) to Apr 2025, with 190 observations. The data reached an all-time high of 4.080 % pa in Aug 2009 and a record low of 1.890 % pa in Dec 2020. Bursa Malaysia: Dividend Yield: FTSE Composite Index data remains active status in CEIC and is reported by Bursa Malaysia. The data is categorized under Global Database’s Malaysia – Table MY.Z: Bursa Malaysia: Dividend Yield. [COVID-19-IMPACT]
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Stock market return (%, year-on-year) in Malaysia was reported at 3.2716 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Malaysia - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.
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Bursa Malaysia: PE Ratio: FTSE Composite Index data was reported at 15.430 NA in Apr 2025. This records a decrease from the previous number of 16.760 NA for Mar 2025. Bursa Malaysia: PE Ratio: FTSE Composite Index data is updated monthly, averaging 17.165 NA from Jul 2009 (Median) to Apr 2025, with 190 observations. The data reached an all-time high of 29.800 NA in Apr 2023 and a record low of 12.150 NA in Sep 2022. Bursa Malaysia: PE Ratio: FTSE Composite Index data remains active status in CEIC and is reported by Bursa Malaysia. The data is categorized under Global Database’s Malaysia – Table MY.Z: Bursa Malaysia: Price Earnings Ratio. [COVID-19-IMPACT]
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Heteroscedasticity effects are useful for forecasting future stock return volatility. Stock volatility forecasting provides business insight into the stock market, making it valuable information for investors and traders. Predicting stock volatility is a crucial task and challenging. This study proposes a hybrid model that predicts future stock volatility values by considering the heteroscedasticity element of the stock price. The proposed model is a combination of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) and a well-known Recurrent Neural Network (RNN) algorithm Long Short-Term Memory (LSTM). This proposed model is referred to as GARCH-LSTM model. The proposed model is expected to improve prediction accuracy by considering heteroscedasticity elements. First, the GARCH model is employed to estimate the model parameters. After that, the ARCH effect test is used to test the residuals obtained from the model. Any untrained heteroscedasticity element must be found using this step. The hypothesis of the ARCH test yielded a p-value less than 0.05 indicating there is valuable information remaining in the residual, known as heteroscedasticity element. Next, the dataset with heteroscedasticity is then modelled using an LSTM-based RNN algorithm. Experimental results revealed that hybrid GARCH-LSTM had the lowest MAE (7.961), RMSE (10.466), MAPE (0.516) and HMAE (0.005) values compared with a single LSTM. The accuracy of forecasting was also significantly improved by 15% and 13% with hybrid GARCH-LSTM in comparison to single LSTMs. Furthermore, the results reveal that hybrid GARCH-LSTM fully exploits the heteroscedasticity element, which is not captured by the GARCH model estimation, outperforming GARCH models on their own. This finding from this study confirmed that hybrid GARCH-LSTM models are effective forecasting tools for predicting stock price movements. In addition, the proposed model can assist investors in making informed decisions regarding stock prices since it is capable of closely predicting and imitating the observed pattern and trend of KLSE stock prices.
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Malaysia Leading Index: % Change: KLSE Share Price Index, Industrial data was reported at -0.100 % in Jan 2006. This records a decrease from the previous number of 0.000 % for Dec 2005. Malaysia Leading Index: % Change: KLSE Share Price Index, Industrial data is updated monthly, averaging 0.000 % from Sep 2000 (Median) to Jan 2006, with 65 observations. The data reached an all-time high of 0.700 % in Aug 2001 and a record low of -0.400 % in Apr 2004. Malaysia Leading Index: % Change: KLSE Share Price Index, Industrial data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Malaysia – Table MY.S003: Composite Index: 1990=100.
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Malaysia Leading Index: % Change: KLSE Industrial Index data was reported at 0.100 % in Sep 2018. This records an increase from the previous number of -0.100 % for Aug 2018. Malaysia Leading Index: % Change: KLSE Industrial Index data is updated monthly, averaging 0.000 % from Nov 2010 (Median) to Sep 2018, with 95 observations. The data reached an all-time high of 0.400 % in Jan 2017 and a record low of -0.400 % in Jun 2013. Malaysia Leading Index: % Change: KLSE Industrial Index data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Malaysia – Table MY.S001: Composite Index: 2005=100.
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Key information about Malaysia P/E ratio
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Key information about Malaysia Market Capitalization: % of GDP
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Key information about Malaysia Market Capitalization
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领先指数:百分比变化:吉隆坡证券交易所股价指数,工业在01-01-2006达-0.100%,相较于12-01-2005的0.000%有所下降。领先指数:百分比变化:吉隆坡证券交易所股价指数,工业数据按月更新,09-01-2000至01-01-2006期间平均值为0.000%,共65份观测结果。该数据的历史最高值出现于08-01-2001,达0.700%,而历史最低值则出现于04-01-2004,为-0.400%。CEIC提供的领先指数:百分比变化:吉隆坡证券交易所股价指数,工业数据处于定期更新的状态,数据来源于Jabatan Perangkaan Malaysia,数据归类于Global Database的马来西亚 – 表 MY.S003:综合指数:1990=100。
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领先指数:百分比变化:马来西亚吉隆坡综合股价工业指数在09-01-2018达0.100%,相较于08-01-2018的-0.100%有所增长。领先指数:百分比变化:马来西亚吉隆坡综合股价工业指数数据按月更新,11-01-2010至09-01-2018期间平均值为0.000%,共95份观测结果。该数据的历史最高值出现于01-01-2017,达0.400%,而历史最低值则出现于06-01-2013,为-0.400%。CEIC提供的领先指数:百分比变化:马来西亚吉隆坡综合股价工业指数数据处于定期更新的状态,数据来源于Jabatan Perangkaan Malaysia,数据归类于Global Database的马来西亚 – 表 MY.S001:综合指数:2005年=100。
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(停止更新)领先指数:百分比变化:马来西亚吉隆坡综合股价工业指数在12-01-2010达0.100%,相较于11-01-2010的-0.300%有所增长。(停止更新)领先指数:百分比变化:马来西亚吉隆坡综合股价工业指数数据按月更新,12-01-2005至12-01-2010期间平均值为0.100%,共61份观测结果。该数据的历史最高值出现于07-01-2009,达0.600%,而历史最低值则出现于03-01-2008,为-0.400%。CEIC提供的(停止更新)领先指数:百分比变化:马来西亚吉隆坡综合股价工业指数数据处于定期更新的状态,数据来源于Jabatan Perangkaan Malaysia,数据归类于Global Database的马来西亚 – 表 MY.S002:综合指数:2000年=100。
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Malaysia's main stock market index, the FKLCI, fell to 1536 points on July 11, 2025, losing 0.03% from the previous session. Over the past month, the index has climbed 0.62%, though it remains 5.13% lower than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Malaysia. Malaysia Stock Market (FBM KLCI) - values, historical data, forecasts and news - updated on July of 2025.