SeminarDepartment of Systems Engineering and Engineering Management
Title : Program Trading and the Use of Volatility Term Structure and Dynamic Correlation in Predicting the Movement of Hang Seng Index (HSI).Speaker : Prof. Jerome Yen
In this talk, I will cover two parts. Part 1 will focus on the discussion on some issues that related to Program Trading or Algo trading. In Part 2, I will discuss our recent research in the development of model to forecast equity index movement based on the volatility term structure and dynamic correlation.
Program/Algorithm Trading has become more and more important in various financial markets that it covers over sixty percent of trades in Nasdaq. To have good P&L, the most important are good trading strategies and powerful platform/system to support the execution of these trading strategies, which include opportunities identification, trading strategies selection, trade scheduling, capital and liquidity management, and risk management.
The first step in the development of a trading strategy is to understand the behavior of asset, which includes trend, volatility, mean-reversion, and correlations with other assets or factors. The second step is to understand the behavior of market, for example, trading volume and pattern, liquidity level, spread or trading cost, market impact, etc. Then select appropriate models to calibrate for the parameters to describe such behaviors. In manual trading, traders tried to reach optimal performance by incorporating their experience or knowledge into trade selection and execution. However, in program trading, such knowledge or experience is captured by trading rules and optimization is always a key element. Such optimization is even more important to the high-frequency trading (HFT) that the scope of issues need to be considered are much broader, for example, size of trades, holding period, latency or micro-structural issues, selection of programming language, etc. "Is that possible to use HFT in China or Hong Kong equities, options, or futures markets?" was a question that always asked by practitioners.
In the second part of this talk, I will discuss how we modified the Heston model so that the estimation of asset movement can be based on the dynamic volatility term structure and the dynamic correlation between asset and volatility. We will discuss under what condition that a dynamic correlation is better in describing the behavior of an asset. I will also discuss how a trading strategy that based on such model been tested in the market and what technical issues we encountered, for example, computation speed.
Prof. Jerome Yen is currently a Professor at Tung Wah College and also chairs its Research Committee. He also holds an Adjunct Professor in the Department of Finance at Hong Kong University of Science and Technology (HKUST). He was the program coordinator of BSc in Quantitative Finance, where majority of the graduates went to respectful banks, for example, Goldman Sachs, Morgan Stanley, and CIC.
He received his PhD. in 1992 in Systems Engineering and Management Information Systems from the University of Arizona. He has taught or held research positions at leading universities, such as, Carnegie Mellon University (CMU), the University of Arizona, the University of Hong Kong (HKU), and Chinese University of Hong Kong (CUHK).
At HKUST, he supported the establishment of the Financial Trading Lab, with supports from Reuters and HP, to provide students an environment that similar to Wall Street, where students learned how to develop, price, and trade equities, foreign exchange, options, and structured products like Accumulator. His current research includes Algo Trading as well as strategies to support derivatives and exotic options trading. The models and systems that developed by the research team that led by Prof. Yen and his research partner, Prof. K. K. Lai at City University of Hong Kong, have been adopted by hedge funds to forecast the movement of underlying assets, for example, gold and equity indices like Hang Seng Index (HSI). The speed of such forecasting reached the order of second and was made possible by high-speed generation of Volatility Term Structure and Volatility Surface.
Prof. Yen has a successful career in both academia and industry. He was a senior vice president (SVP) and deputy chief risk officer at Cathay Financial Holdings (CFH), which was the largest financial holding company in Taiwan with assets greater than USD 150 Billion and also one of the Forbes 500 and Fortune 500 firms. He developed the ¡°Quant¡± team for the Cathay Union Bank, one of the subsidiaries of CFH, to develop credit scoring/rating models as well as pricing models and trading strategies for derivative and structured products.
Prof. Yen also provided advisory/consulting services to leading financial institutions, for example, Invesco-Greatwall, Essence Securities, Societe Generale, Hang Seng Bank, GoldenWay, Head and Shoulder, Bank of East Asia, and AIA. He has published more than fifty journal papers in respectable journals and three books, and also an active column writer for top newspapers like economic journal (ĐÅ±¨). He was the winner of the Best Paper Award at Hawaii International Conference on System Sciences (HICSS).
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