scholarly journals ANALISIS IMBAL HASIL DENGAN AUTOMATIC TRADING DALAM PERSPEKTIF MONEY MANAGEMENT : Studi Eksperimental dengan Expert Advisor pada Pasar Futures

2020 ◽  
Vol 8 (4) ◽  
Author(s):  
Paulus Candra
Keyword(s):  
Experimental Study ◽  
Moving Average ◽  
Descriptive Analysis ◽  
Fixed Ratio ◽  
Futures Market ◽  
Money Management ◽  
Martingale Method ◽  
Management Method ◽  
Gold Futures ◽  
Passive Strategy

In this study an experimental study was using automatic trading by develop an expert advisors to works with backtesting simulation from January 2010 to December 2019 to research the performance returns of the double moving average cross strategy with 6 pairs from SMA (10.30), SMA (10.50) and SMA (10,100) and EMA (10,30), EMA (10.50), and EMA (10,100). EMA performance (10.30) that given treated 3 types of money management methods, namely fixed lot, fixed % lot, and martingale (1.5x) in the GOLD futures market (XAUUSD) at 1 hour timeframe which will be compared with descriptive analysis. This study shows that the EMA (10.30) without using money management (fixed lot) method shows the most optimal results with a total return 63.5% in the futures market which is higher than the passive strategy. The experimental results show that the fixed % lot method decreases performance with lower returns and increases risk when compared without using money management (fixed lot). While the most optimal money management method is martingale (1.5x) with the achievement of a total return 6,610.56% and a risk adjusted ratio (RAR) at 5.02%. Individually, the method that gives the highest yield is shown by EMA (10.30) on the fixed lot method with a total return of 63.5% and RAR at 2.41%, EMA (10.30) on the fixed sum lot method with a total return of 62.77% and RAR 1.52% and EMA (10.100) with a total return 6.610.56% and RAR 5.02% on the martingale method simulated using expert advisors in the futures market.Keywords: Moving Average, Money Management, Gold, Return, risk adjusted return, Martingale, Fixed Lot, Fixed Ratio, Expert Advisor, Automatic Trading

scholarly journals Improving MACD Technical Analysis by Optimizing Parameters and Modifying Trading Rules: Evidence from the Japanese Nikkei 225 Futures Market

2021 ◽  
Vol 14 (1) ◽  
pp. 37
Author(s):  
Byung-Kook Kang
Keyword(s):  
Moving Average ◽  
Public Information ◽  
Technical Analysis ◽  
Weak Form ◽  
Futures Market ◽  
Traditional Model ◽  
Analysis Tool ◽  
Futures Prices ◽  
Improved Performance ◽  
Parameter Values

Much research has examined performance or market efficiency by using the moving average convergence divergence (MACD) technical analysis tool. However, most tests fail to verify efficiency with the traditional parameter settings of 12, 26, and 9 days. This study confirms that applying the traditional model to Japan’s Nikkei 225 futures prices produces negative performance over the period of 2011–2019. Yet, it also finds that the MACD tool can earn significant positive returns when it uses optimized parameter values. This suggests that the Japanese market is not weak-form efficient in the sense that futures prices do not reflect all public information. Hence, the three parameters values of the MACD tool should be optimized for each market and this should take precedence over finding other strategies to reduce false trade signals. This study also tests which models are able to improve profitability by applying additional criteria to avoid false trade signals. From simulations using 19,456 different MACD models, we find that the number of models with improved performance resulting from these strategies is far greater for models with optimized parameter values than for models with non-optimized values. This approach has not been discussed in the existing literature.

scholarly journals INDIKATOR MAKROEKONOMI DAN PEMBANGUNAN KOTA BANDUNG

2019 ◽  
pp. 622
Author(s):  
Teguh Santoso ◽  
Bayu Kharisma
Keyword(s):  
Economic Growth ◽  
Poverty Reduction ◽  
Moving Average ◽  
Descriptive Analysis ◽  
High Rate ◽  
Purchasing Power ◽  
Autoregressive Moving Average Model ◽  
Food Commodities ◽  
The City ◽  
Poverty Levels

The high rate of inflation has the potential to increase poverty because it can reduce people's purchasing power, where if inflation rises significantly it can shift the people who are categorized as not poor, become vulnerable to poverty, almost poor and even poor. The aims of this study are to analyze the development of macroeconomic indicators, namely inflation and economic growth that are associated with poverty levels in the city of Bandung. The methodology used in this study is descriptive analysis and the ARMA (autoregressive moving average) model. The results showed that the high inflation in the city of Bandung compared to national and West Java inflation carries its own burden for the economy of the community, where purchasing power will decrease when inflation rises significantly and will have an impact on people's welfare. Inflation in the city of Bandung is often due to the price of food commodities (volatile food inflation). In addition, the high economic growth in the city of Bandung is not directly proportional to the decline in poverty levels. This shows that the quality of economic growth in the city of Bandung has problems that need attention. Therefore, local government in their efforts to encourage economic growth must prioritize poverty reduction and inequality.

scholarly journals Has COVID-19 Changed the Hedge Effectiveness of Bitcoin?

2021 ◽  
Vol 9 ◽  
Author(s):  
Yinpeng Zhang ◽  
Panpan Zhu ◽  
Yingying Xu
Keyword(s):  
Futures Markets ◽  
Vector Autoregression ◽  
Spot Market ◽  
Futures Market ◽  
Conditional Heteroskedasticity ◽  
Volatility Spillover ◽  
Empirical Results ◽  
Dynamic Correlation ◽  
Autoregressive Conditional Heteroskedasticity ◽  
Gold Futures

The Bitcoin market has become a research hotspot after the outbreak of Covid-19. In this paper, we focus on the relationships between the Bitcoin spot and futures. Specifically, we adopt the vector autoregression-dynamic correlation coefficient-generalized autoregressive conditional heteroskedasticity (VAR-DCC-GARCH) model and vector autoregression-Baba, Engle, Kraft, and Kroner-generalized autoregressive conditional heteroskedasticity (VAR-BEKK-GARCH) models and calculate the hedging effectiveness (HE) value to investigate the dynamic correlation and volatility spillover and assess the risk reduction of the Bitcoin futures to spot. The empirical results show that the Bitcoin spot and futures markets are highly connected; second, there exists a bi-directional volatility spillover between the spot and futures market; third, the HE value is equal to 0.6446, which indicates that Bitcoin futures can indeed hedge the risks in the Bitcoin spot market. Furthermore, we update the data to the post-Covid-19 period to do the robustness checks. The results do not change our conclusion that Bitcoin futures can hedge the risks in the Bitcoin spot market, and besides, the post-Covid-19 results indicate that the hedging ability of Bitcoin futures increased. Finally, we test whether the gold futures can be used as a Bitcoin spot market hedge, and we further control other cryptocurrencies to illustrate the hedging ability of the Bitcoin futures to the Bitcoin spot. Overall, the empirical results in this paper will surely benefit the related investors in the Bitcoin market.

FDI Inflows in India: An Analysis of the Trend During 2004–2018 and Future Projections for the Next Decade

2018 ◽  
Vol 14 (3-4) ◽  
pp. 120-131 ◽  
Author(s):  
Rachna Madaan ◽  
Jitender Bhandari ◽  
Shraddha Mishra
Keyword(s):  
Open Economy ◽  
Developing Economies ◽  
Moving Average ◽  
Descriptive Analysis ◽  
Secondary Data ◽  
Positive Trend ◽  
Fdi Inflows ◽  
Future Projections ◽  
Growth History ◽  
History Of

Developing economies have been seeing an exhaustive rise of foreign direct investment (FDI) inflows all through the past two decades. Traditionally, India has pursued an enormously cautious approach; however, in 1991, India initiated the process of economic reforms towards a more open economy and got the sequence of processes to draw more FDI. The present study depends on the secondary data, and the time of the study is from 2004 to 2018. The FDI inflows have increased from US$5,777.8 million in 2004 to US$61,963.1 million in 2018. This article aims to present the descriptive analysis of FDI inflows in India during the selected period and also describes the long-term trend as well as the growth history of FDI inflows. The motivation behind this article is to make an effort to forecast the FDI Inflows in India for the coming years with the help of growth analysis, trend analysis and ARIMA (Autoregressive integrated Moving Average) forecasting. The result of future projections shows a positive trend indicating manifold increase in FDI inflows in India in the coming years.

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