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 31 of 2025.

Malaysia's main stock market index, the FKLCI, fell to 1519 points on July 31, 2025, losing 0.39% from the previous session. Over the past month, the index has declined 1.49% and is down 6.51% compared to the same time last year, 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.

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.

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.

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]

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.

Key information about Malaysia P/E ratio

• Malaysia FTSE Composite Index recorded a monthly P/E ratio of 17.270 on Mar 2025, compared with 19.480 from the previous month.
• Malaysia FTSE Composite Index P/E ratio is updated monthly, with historical data available from Jul 2009 to Feb 2025.
• The P/E ratio reached an all-time high of 29.800 in Apr 2023 and a record low of 12.150 in Sep 2022.
• Bursa Malaysia provides monthly P/E Ratio.

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。