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John Hull and Alan White, "One factor interest rate models and the valuation of interest rate derivative securities," Journal of Financial and Quantitative Analysis, Vol 28, No 2, (June 1993) pp. 235–254. John Hull and Alan White, "Pricing interest-rate derivative securities", The Review of Financial Studies, Vol 3, No. 4 (1990) pp. 573–592.
The idea is do a regular exponential moving average (EMA) calculation but on a de-lagged data instead of doing it on the regular data. Data is de-lagged by removing the data from "lag" days ago thus removing (or attempting to) the cumulative effect of the moving average.
In statistics, a moving average (rolling average or running average or moving mean [1] or rolling mean) is a calculation to analyze data points by creating a series of averages of different selections of the full data set. Variations include: simple, cumulative, or weighted forms. Mathematically, a moving average is a type of convolution.
For both of these reasons, models such as Black–Derman–Toy (lognormal and mean reverting) and Hull–White (mean reverting with lognormal variant available) are often preferred. [ 1 ] : 385 The Kalotay–Williams–Fabozzi model is a lognormal analogue to the Ho–Lee model, although is less widely used than the latter two.
The DPO is calculated by subtracting the simple moving average over an n day period and shifted (n / 2 + 1) days back from the price. To calculate the detrended price oscillator: [5] Decide on the time frame that you wish to analyze. Set n as half of that cycle period. Calculate a simple moving average for n periods. Calculate (n / 2 + 1).
The simple moving average, or SMA, is one of the most common pieces of technical data that investors rely on. In the case of the 200-day SMA, it shows you the stock's average price over the past ...
Ichimoku kinko hyo – a moving average-based system that factors in time and the average point between a candle's high and low; Moving average – an average over a window of time before and after a given time point that is repeated at each time point in the given chart. A moving average can be thought of as a kind of dynamic trend-line.
In time series analysis, the moving-average model (MA model), also known as moving-average process, is a common approach for modeling univariate time series. [ 1 ] [ 2 ] The moving-average model specifies that the output variable is cross-correlated with a non-identical to itself random-variable.