Relating Trade Value and Volume to Market Volatility and Forecast Limits

Summary

This document proposes that randomness in market trades contributes to the stochastic behavior of prices and returns. It examines trade values and volumes over an averaging interval, treating them as random variables, and relates price and return volatility to their volatilities and correlations. It also extends this perspective to the accuracy limits of macroeconomic variables, using macroeconomic investment accuracy as an example.

The argument is that common macroeconomic models focus on first-order quantities such as summed trade values or volumes, while predicting volatility requires theories that also represent dependencies involving second-order variables. The document contends that the absence of such theories limits the economic basis for volatility forecasts and constrains forecast accuracy, at best, by Gaussian distributions. This is a conceptual claim in the excerpt: it offers no empirical analysis, estimation procedure, or evidence comparing alternative models. The proposed relationships therefore remain a motivation for further data collection and econometric work rather than a demonstrated forecasting method.

Key ideas

• The document treats randomness in trade values and volumes as a source of price and return volatility.
• It relates market volatility to the variation and correlation of trade activity over an averaging interval.
• It argues that macroeconomic models need to account for dependencies among second-order variables to forecast volatility.
• The excerpt calls for econometric methods, data, and theory but provides no empirical test or practical forecasting procedure.
• It asserts a Gaussian limit on forecast accuracy under the stated absence of second-order macroeconomic theories.

Tags

# Volatility Depends on Market Trades and Macro Theory


# Volatility Depends on Market Trades and Macro Theory









We consider the randomness of market trade as the origin of price and return stochasticity. We look at time series of trade values and volumes as random variables during the averaging interval Δ and describe the dependences of market-based volatilities of price and return on the volatilities and correlations of market trade values and volumes. We describe the market-based origin of the lower boundaries of the accuracy of macroeconomic variables and consider, as an example, the accuracy of macroeconomic investments. We highlight that current macroeconomic models describe relations between the 1st order variables determined by sums of trade values or volumes. To predict market-based volatilities of price, return, and volatilities of macroeconomic variables, one should develop econometric methodologies, collect data, and elaborate macroeconomic theories of the 2nd order that model the mutual dependence of the 1st and 2nd order economic variables. The absence of macroeconomic theories of the 2nd order means no economic basis for predictions of market-based volatilities of price and return, as well as volatilities of any macroeconomic variables. In turn, that limits the accuracy of forecasting probabilities of price, return, and the accuracy of macroeconomic variables in the best case by Gaussian distributions.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.