Several studies have shown that knowledge about past and future earnings can lead to investors earning superior returns despite ambiguity in measuring earnings. Earnings reports are always among the most significant events for traders and investors for the reason over the short and long term stock prices track changes in earnings. Other relevant events include…
Value at Risk measures the likelihood of losses to an asset or portfolio, over a defined period for a given confidence interval, due to market risk. Such a narrow definition of risk is further limited to the VaR focus on downside risk and potential losses in the short-term; indeed, VaR can be computed over a quarter or a year, but it is usually computed over a day, a week or a few weeks.
The International Currency Market, or FOREX, is an over-the-counter market where banks, central banks, sharks, investment management firms, hedge funds, and brokers buy and sell currencies. In general, the key drivers of FOREX are Central Bank Interest Rates, Central Bank Intervention, Options, Fear and Greed, and News. Forex Screener by TradingView Technical analysis in the…
Portfolio analysis is essentially a statistical technique. However, because the ‘‘true’’ population parameters for the input data (expected returns, variances, and covariances) are unobservable, sample statistics must be estimated. Thus, the efficient portfolios generated by portfolio analysis are no better than the statistical input data on which they are based.
Macroeconomic indicators are statistics that indicate the current status of the economy of a state depending on a particular area of the economy (industry, labor market, trade, etc.). They are published regularly at a certain time by governmental agencies and the private sector. The main point is to get a grasp into the relationship between…
Estimation of betas with regression is adequate for asset managers, but it is not appropriate in risk management of portfolios because monitoring is done on a frequent basis – daily and even intra-daily. Indeed, parameters estimated by OLS at these frequencies will not reflect the actual market conditions because they just represent an average value over time on the sample.
The two fundamental ingredients of Markowitz (1952) mean-variance optimization are the expected (excess) return for each asset (the portfolio manager’s ability to forecast), and the covariance matrix of asset returns (the risk control).
Estimating and forecasting beta of each stock that is a potential candidate for inclusion in a portfolio is a prerequisite to apply the single-index model. Analysts could be asked to provide subjective estimates of beta for a security or a portfolio. Conversely, estimates of future beta could be arrived at by estimating beta from past data and using this historical beta as an estimate of the future beta.
The single-index factor model assumes that the co-movement between stocks is due to a single common influence or index. Casual observation of stock prices reveals that when the market goes up (as measured by any of the widely available stock market indexes), most stocks tend to increase in price, and when the market goes down, most stocks tend to decrease in price.
Factor models are applied by portfolio managers to analyze the potential returns on a portfolio of risky assets, to choose the optimal allocation of their funds to different assets and to measure portfolio risk. The theory of linear regression-based factor models applies to most portfolios of risky assets, excluding options portfolios but including alternative investments such as real estate, hedge funds, and volatility, as well as traditional assets such as commodities, stocks, and bonds.
