Singapore’s Monetary Authority to Begin Work on Payments Linkage with Malaysia

Posted on September 28, 2021 by Maurice Quinten

Last week, The Monetary Authority of Singapore announced of government plans of pursuing a phased linkage of its PayNow payment systems with Malaysia’s DuitNow.

Once the first phase of linkage achieves completion the linked payment systems between the two countries will enable participating financial institutions to offer customers, real-time fund transfer services between Singapore and Malaysia using their mobile number. Moreover, the linkage will also let customers make retail purchases and pay for them using the DuitNow or NRTS QR codes displayed by participating stores.

In July of this year, Singapore’s Bank for International Settlements and the Monetary Authority of Singapore revealed the plan as well issued a set of guidelines specifically pertaining to multilateral linking of domestic real-time payment systems beyond and across borders.

The Singapore-Malaysia Payment Systems Linkage is Actually Part of a Greater Plan

The greater significance of linking the two payment systems is the enhancement of seamless fund transfers of large amounts of remittances between the two countries, which even reached $1.3 billion last year. The linkage comes just after the successful completion of a similar project involving The Reserve Bank of India’s Unified Payment Interface. Fund transfers between customers in Singapore and India are now more affordable since the reciprocity eliminates the need to process transactions using a third party payment system.

The project has been named Project Nexus, as it envisions the creation of “Nexus Gateways.” The goal is to synchronize all compliance, message translations, sequencing of payments, and foreign exchange conversion of all participating financial institutions. The project also includes the tie-up between Thailand’s PromptPay and Singapore’s PayNow that was launched last April 2021.

High Returns Mean Profitable Investments?

Posted on September 12, 2021 by Ned Queen

Investment professionals know that the highest return is not always the best return. If you want to invest your saved money profitably, you have to carefully examine investments with high returns. It is important to have a certain amount of mistrust when investing your money. High-interest rates in the double-digit range usually go hand in hand with equally high risks for the loss of total capital.

Profitable investments are not based exclusively on a good return, but rather on the right balance between collateral and profit opportunities.

Therefore, not every investment with a high return is a successful investment

Where are the best interest rates for a high return? If investors deal with promised interest rates before investing their capital, they should not automatically invest their money in the first investment opportunity in the double-digit interest rate range. However, high returns of this kind may be included in the portfolio. A good return is of little use if there is no distribution before the loss of capital.

A good return starts at 4% pa

There is talk of financial investment with a high return starting at 4% pa. In the current low-interest market, you will not achieve this interest rate if you invest your money in classic investments such as savings books. Most savings accounts don’t even hit 2% these days. But it should be at least as much so that the invested capital does not experience devaluation due to inflation. If you want to invest money profitably, minimum interest rates of between 4 and 5% pa are required.

Where to get the most interest on money?

High returns are in the double-digit range. They can be the prospect for securities, funds and other stock market products, for example. As a saver with limited capital, you should invest little or no money in most of these investment opportunities. High-interest rates of this kind characterize high-risk investments and therefore encourage healthy mistrust. Investments of this kind shouldn’t gain the upper hand on your portfolio. According to studies, the best overall return is waiting for investors who distribute their capital across various types of investment and classes.

Trading Robot – Automated Stock And Futures Exchange

Posted on September 4, 2021 by Grace Alita

Robot Trading. Many day traders who trade a precisely defined strategy every day soon want to automate trading. There are many trading platforms on the market that allow the creation of trading robots. The most popular of these are available for free and allows you to trade CFDs and Forex.

However, many underestimate the complexity of programming and properly testing these automatic trading systems. In this article we look at the trading algorithm and testing of these trading robots as part of growing technology and its impact on trading.

This article is the beginning of a series of texts and videos on the implementation of automatic trading ideas in day trading. Articles on the topics of backtests, tips & tricks for programming, the definition of trading strategies, and others are planned.

The trading algorithm

An algorithm is a clear rule for solving a problem, in this case, a precise definition for buying, selling, and determining position sizing in stock exchange trading. It is the basis for every trading robot and assumes that a trading strategy can be precisely described and defined. Things like “the chart actually looks short” or “my gut feeling tells me to exit the trade now” are not enough. The algorithm defines how the trading idea on which the robot is based is implemented in detail. Trading ideas can relate to the evaluation of one or more indicators or take advantage of market behavior ( breakouts from consolidation zones, gap closings, etc.).

A well-defined set of instructions needs at least:

Rules for entering a position
Rules for exiting a position
Rules for choosing position size – an often underestimated part of the strategy

Defining these rules forces you as a day trader to think carefully about the elements of your strategy and write them down. You should have already done this in your trading plan if you have been trading this method manually up to now!

Testing trading systems

Almost all robots have a set of parameters that can be used to influence trading. These can be, for example, settings for the stop-loss limit, the period length of a moving average indicator, or the position size. Testing trading programs with historical data to optimize these parameters is called “backtesting”. The English term has also become common in German literature on the subject, and this applies to almost all terms in this context. Some programs, such as the Metatrader program presented below, offer the option of automatically optimizing the input parameters.

You will often find that a successfully tested robot with fresh current data (“forward test”) fails. The problem goes back to the over-optimization of the parameters on the old data, the so-called “curve fitting”. The parameters are then precisely adapted to the test data and only earn money in this previous period. Example: If you find that your system makes money with a moving average length of 11.15 and 17 but loses money with 12.13.14 etc., then the system is not robust enough for live trading.

When calculating performance, you should also exclude random hits, as these can distort the track record and create unrealistic expectations of the system. There is a separate article on this with a simple method.

Testing and evaluating trading systems is a complex activity. The subject is so extensive that books have already been written about it. That is why we can only give initial general information here in this article, but we are planning further articles on this.

At this point, a warning about a stumbling block brings down many system developers. Many developers try to stick to a losing system because they put a lot of effort into design and implementation. Be honest with yourself! It hurts to retire a system you’ve been writing on for weeks. However, it’s still better than losing money all the time.