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In finance, technical analysis is an analysis methodology for analysing and forecasting the direction of prices through the study of past market data, primarily price and volume. As a type of active management, it stands in contradiction to much of modern portfolio theory. The efficacy of technical analysis is disputed by the efficient-market hypothesis, which states that stock market prices are essentially unpredictable, and research on whether technical analysis offers any benefit has produced mixed results. It is distinguished from fundamental analysis, which considers a company's financial statements, health, and the overall state of the market and economy.
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In finance, a portfolio is a collection of investments.
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Robert (Bob) Arthur Haugen was a financial economist and a pioneer in the field of quantitative investing and low-volatility investing. He was President of Haugen Custom Financial Systems and also consulted and spoke globally.
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Sheridan Dean Titman is a professor of finance at the University of Texas at Austin, where he holds the McAllister Centennial Chair in Financial Services at the McCombs School of Business. He received a B.S. degree (1975) from the University of Colorado and an M.S. (1978) and Ph.D. (1981) from Carnegie Mellon University.
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Quantitative analysis is the use of mathematical and statistical methods in finance and investment management. Those working in the field are quantitative analysts (quants). Quants tend to specialize in specific areas which may include derivative structuring or pricing, risk management, investment management and other related finance occupations. The occupation is similar to those in industrial mathematics in other industries. The process usually consists of searching vast databases for patterns, such as correlations among liquid assets or price-movement patterns.
In investing and finance, the low-volatility anomaly is the observation that low-volatility stocks have higher returns than high-volatility stocks in most markets studied. This is an example of a stock market anomaly since it contradicts the central prediction of many financial theories that taking higher risk must be compensated with higher returns.
Factor investing is an investment approach that involves targeting quantifiable firm characteristics or “factors” that can explain differences in stock returns. Security characteristics that may be included in a factor-based approach include size, low-volatility, value, momentum, asset growth, profitability, leverage, term and carry.
References
- ↑ Jegadeesh, N; Titman S (1999). "Profitability of Momentum Strategies: An Evaluation of Alternative Explanations". NBER Working Paper (7159).
- ↑ Jegadeesh, N; Titman S (1993). "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency". Journal of Finance. 48 (48): 65–91. doi:10.1111/j.1540-6261.1993.tb04702.x. S2CID 13713547.
- ↑ Low, R.K.Y.; Tan, E. (2016). "The Role of Analysts' Forecasts in the Momentum Effect" (PDF). International Review of Financial Analysis. 48: 67–84. doi:10.1016/j.irfa.2016.09.007.
- ↑ Daniel, K; Hirschleifer D; Subrahmanyam A (1998). "A Theory of Overconfidence, Self-Attribution, and Security Market Under and Over-reactions". Journal of Finance (53). doi:10.2139/ssrn.2017. hdl: 2027.42/35542 . S2CID 155014440.
- ↑ Barberis, N; Shleifer A; Vishny R (1998). "A Model of Investor Sentiment". Journal of Financial Economics. 49 (49): 307–343. doi:10.1016/S0304-405X(98)00027-0. S2CID 17623242.
- ↑ Crombez, J (2001). "Momentum, Rational Agents and Efficient Markets". The Journal of Psychology and Financial Markets. 2 (2): 190–200. doi:10.1207/S15327760JPFM0204_3. S2CID 155049349.