Market risk is commonly modelled as a normal distribution of the expected returns for a financial instrument: The most likely outcome is at the peak, located in the middle of the distribution. The width of the curve on either side of the peak indicates the uncertainty or volatility of the market. Large volatility brings the possibility of making a lot of money, but also the risk of losing a lot of money.
Your Guide to the World of Quantum
Market Sentiment Meter (MSM)
With social media gaining popularity in the world of financial trading, there is interest in using the sentiment, or opinion, of many people automatically in algorithmic trading.
The idea of making money by exchanging one type of currency with another is well-known. Many Canadians remember a time or two when the Canadian dollar was on par with, or even worth more than, the US dollar, such as in 2007. Canadians revelled at the lower cost of goods south of the border. At the same time, people expected the US dollar to rise in value again, so many held onto their US currency in order to sell it later. Events like these are rare between established countries, and returns are typically low for foreign exchange (FX).
The price of bitcoin has almost doubled since the beginning of the year, while gold has fallen by almost 15%. Cryptocurrency has emerged as a competitor to gold as a hedge against inflation, that is, a protection against depreciation. Gold is often used as such a hedge: when the US dollar loses value due to inflation, the price of gold tends to increase.
Options contracts are more popular than ever, with more options contracts traded last year than any other year in history.1 With people spending more time at home due to the COVID-19 pandemic, many are turning to trading and investing their new surplus of time and money. Brokers have eliminated previous barriers in options trading with smaller fees, increased usability, and the elimination of required minimum account balances to trade options.
The study of finance relies on making the best possible decisions despite future uncertainty. There is always risk when making financial decisions, and it goes hand in hand with return. A core problem in computational finance is risk minimization, and classical computers (that is, non-quantum computers) are often used to solve this problem using a variety of algorithms. But such methods are not always the solution. It will be explained below why there are limitations to using classical computers to solve challenging real-world financial problems, and what is being done to overcome these limitations by means of quantum computing.
The world is in the wake of the Information Age and computer technology is increasingly improving almost all industries. In finance, for example, algorithmic trading can be more profitable than human trading because of the speed and data processing advantages that computers have over human traders. But not all algorithms are equal. Some perform better than others. In certain cases, there are missed opportunities in which trading decisions could have been navigated from good to better, resulting in greater profit.
The US elections are held on the first Tuesday of November, and campaign-related events are widely covered in the news. These events generally have an impact on various US markets as the winning candidate’s policies and viewpoints are very likely to tangibly affect many aspects of US operations going forward into the candidate’s term.
Events that occur in October can greatly influence the results of the election simply because they happen at a time leading up to an election. The term “October surprise” refers to these types of events.
It is widely believed that gold prices reveal the overall health of the economy, and will continue to be an integral part of foreign exchange markets. Aside from the usual suspects (i.e., market activity, wealth reserves, or supply and demand), major events involving economic policy tend to affect gold prices.
The COVID-19 pandemic has changed the world forever, and its effect will continue to send shockwaves through many parts of society, notably among the world’s financial markets. These include the eight commodity futures and options products tracked by the CME Market Sentiment Meter (MSM): S&P index futures, US Treasury note futures, crude oil, natural gas, corn, soybeans, the Euro/USD exchange rate, and gold. The MSM is a computational tool that calculates market sentiment with respect to the above futures and options products based on the assumption that their prices and volumes reflect the aggregate sentiments of traders. Asset managers need information that helps them to avoid risks and earn higher returns, even though day-to-day fluctuations are usually small relative to the total value of the instruments being traded.