Unlocking the Power of Financial Econometrics
Much has been said about the power of data: Businesses can leverage analytics to drive performance, healthcare institutions can tap on data to inform better pandemic responses, and marketers can utilise metrics to finetune their campaigns.
In the world of finance, the ability to harness and employ data is nothing short of a superpower: It helps manage risks and forecasts financial trends to optimise investment opportunities and strategies.
And that superpower lies in the practice of econometrics, whereby real-world data is put to statistical tests to develop or test economics theories, which are then used to make more accurate forecasts. For example, when applied to the pandemic, econometrists have provided density forecasts for daily Covid-19 infections, uncovered a "consumer index for panic" and related it to government policies, and forecasted the peak of infections in various countries.
The SMU Master of Science in Financial Econometrics (MSFE) combines two central strengths of the University – econometrics and finance – in a programme that helps graduates meet the industry demand for professionals with the skills for deep analysis of increasingly complex financial problems.
One of the courses taught in the MSFE programme is Continuous-Time Financial Economics, where students use continuous-time stochastic models to study stock prices, interest rates, exchange rates, and more complicated derivative contracts. These tools are useful for trading and investment, not only for professionals but also for individuals who can benefit from the vast investment opportunities offered by the modern financial world.
Specifically, investors have been studying "candlestick charts" — charts showing high, low, opening, and closing prices of a security for a specific period — to guide their trades and manage risk. By using econometric tools, investors can extract useful information from these charts, particularly for gauging the level of financial risk in real-time. Based on the theory of Brownian motion, it shows, mathematically, why the different shapes of candlesticks are highly informative about the level of prevailing risk.
The paper "Reading the Candlesticks: An OK Estimator for Volatility" co-authored by SMU School of Economics professor Li Jia — with "OK" standing for "optimal candlestick" — closely studied a recent event during which the Chairman of the Federal Reserve Jerome Powell testified before the US Congress. By using their estimation method, the authors can identify how the risk level of the long-term Treasury bond fluctuates as the market gleans information from the testimony in real-time.
Top: Candlestick chart of 10-year Treasury yield during the day when Jerome Powell gave his congressional testimony on February 23, 2021. Bottom: Estimated volatility and confidence intervals (CI) using the "OK" method.
Most notably, the method can be easily implemented based on data available to retail investors in real-time. Hence, it may help an ordinary investor better manage risk and make more informed investment decisions. The study provides an easy-to-implement econometric procedure based on readily accessible candlestick data, with a user-friendly proposed inference method, as it can be carried out manually on a basic calculator. The study's findings may thus offer the average investor an accessible way to conduct volatility inference.
Fifty years after continuous-time methods in finance were pioneered by Robert C Merton, recent applications of econometrics are also designed to capture the imperfections and uncertainties of financial markets — features of investment increasingly apparent during the 2008 global financial crisis and the current pandemic. Besides pursuing a career in academic research, being an econometrics specialist helps build on existing knowledge to advance technical skills as a much sought-after financial analyst who could help navigate volatile activity in a rocky economy. Programmes such as the MSFE are therefore essential in taking graduates from theories mastered in the classroom to real-world applications in the boardrooms of tomorrow.
The disruptions faced by the modern-day financial industry and a globalised economy have driven new challenges and triggered exciting opportunities for the business world. Financial managers today are grappling with the uncertainties of global events and their effects on capital markets. Alongside the introduction of new economic policies and regulations, breakthroughs in technology have also elevated novel modelling, forecasting and surveillance methods in financial theory and econometrics to address these challenges.
Finance and economics professionals need to update their toolkits of economic theory, financial econometrics and computational methods to take advantage of the potential upsides provided by the evolving financial industry. Through a rigorous curriculum linking economics and econometrics to finance, the MSFE programme imparts the foundational knowledge in economics and econometrics and the domain knowledge of the workings of the financial markets.
Market-oriented professionals, armed with the breadth of capabilities powered by econometrics, are poised for various career tracks, such as the roles of a financial risk analyst, risk analyst, actuarial analyst, compliance specialist, external auditor or fund manager. Furthermore, the multidisciplinary nature of every SMU programme translates into a unique "transformational" learning experience involving faculty with expertise in economics, econometrics and finance, thereby preparing graduates with the soft and hard skills required to make headway in the highly competitive realm of global finance.
Last updated on 15 Oct 2021 .
