In this upcoming series of articles, we will delve into the concept of volatility. We will begin by studying its theoretical framework in detail, then explore its causes, effects, and consequences. In this way, we hope to provide a comprehensive and rigorous view of this important financial phenomenon.
How Would We Define Volatility?
Volatility is defined as the measure of uncertainty that exists in financial markets.
Due to their stochastic nature, target prices are subjective and each participant has their own view of the market, influenced by personal biases, chart analysis, or even unorthodox practices such as astrology. For this reason, in the market there are as many views as there are participants.
Volatility originates as a result of the actions of each participant, who constantly change their perspective through buying and selling financial products. The aggregate of all these decisions generates a stochastic process with Brownian motion, impossible to predict with certainty.
$$r_t = \ln\left(\frac{P_t}{P_{t-1}}\right)$$
$$\sigma = \sqrt{\text{Var}(r_t)} = \sqrt{\mathbb{E}[(r_t - \mu)^2]}$$
Volatility refers to the degree of variation in the price of a financial asset. An asset is considered to have higher volatility when its movements are more abrupt, that is, when more significant changes occur in its value over a given period of time. In contrast, an asset is considered to have lower volatility when the variation in its price is smaller.
import numpy as np
import pandas as pd
import yfinance as yf
# Download SPY data
data = yf.download("SPY", start="2020-01-01")[["Adj Close"]]
# Calculate daily log returns
returns = np.log(data["Adj Close"] / data["Adj Close"].shift(1)).dropna()
# Annualized volatility (252 trading days)
vol_daily = returns.std()
vol_annual = vol_daily * np.sqrt(252)
print(f"Daily vol: {vol_daily:.4f}")
print(f"Annualized vol: {vol_annual:.4f}")Causes of Volatility
The retail investor, often known as dumb money, tends to adopt preconceived ideas about trading without being able to properly verify them. There are two ideas in particular that are critical to understand and should not be overlooked.
Liquidity and the auction process are two key concepts that every market participant must understand. In the case of the forex market, the EUR/USD pair is considered the most liquid in the world due to its high demand and the large number of participants trading it.
Despite this, in situations where market conditions are uncertain, it may happen that only prices from some liquidity providers are visible and not the aggregated price of all of them. This can make it difficult for participants to make decisions, as they do not have all the available information to execute their trades efficiently.
When we request a price to execute a trade, it is common for the market maker to assign us a differential or spread, as this allows them to profit from their role in the transaction. For example, in the case of Darwinex, which profits from our trades through this practice.
It is important to remember that when trading in the market, we cannot ignore the fundamental basis of mathematical expectation. If we do not take it into account, our trade will likely underperform from the very beginning. By paying the spread, we are assuming a cost that other participants do not have.
Precisely for this reason, quantitative researchers dedicate a significant amount of time and resources to understanding the stochastic processes of price formation and their formulation. By better understanding these processes, we can have a clearer idea of the costs associated with our trades and make more informed trading decisions.
This article aims to be an educational guide to help readers overcome the erroneous mindset with which they approach trading. Instead of relying on preconceived assumptions, the goal is to adopt a more empirical and adaptive view, where market inefficiency and its constant self-regulation are assumed.
It is important to remember that the market is inefficient over time due to the numerous stochastic variables that influence its valuation process. Moreover, the market is the sum of the subjective valuations of all its participants. When an institution executes a trade to achieve specific objectives, it is adding information to the market, which causes other participants to adjust their positions based on the decisions of others.
For example, when a well-known commentator like Mr. Bernardos makes a statement, "smart money" tends to do the opposite, which generates a change in price information. At the same time, the market self-regulates, which can be seen in the impact of news on quotes. For example, when the COVID-19 pandemic emerged, markets plunged due to the information asymmetry that caused an overreaction.
However, as market participants received more information, their valuations became more optimistic, leading to a correction of the wrong positions taken on the day of the event.
Information Asymmetry
In a world where valuations are subjective, having the ability to improve the accuracy of our initial decisions is very useful. The great liquidity we enjoy in the markets, along with very low costs, is largely thanks to large institutions that act as market makers and do everything possible to serve their retail clients.
As we well know, in markets there is no such thing as "free money", so when one of the major financial institutions facilitates even the smallest detail so that small investors have access to very low transaction fees and ample liquidity, we can be sure there is a profit motive behind it.
Although we cannot define it precisely, we are certain that in the financial world there is no altruism. Therefore, when a major broker offers its clients very low transaction fees and ample liquidity, it is understandable to ask what the motive behind this low-cost plan is.
If we superficially analyze modern society, we find two types of models in technology companies: those that charge a fee for the service and those that consider the user as the product. In the latter case, the goal may be to keep the public hooked as long as possible, as the information of the uninformed user is extremely valuable to advertisers. In financial markets, the ability of one party to gain an advantage over another is of utmost importance, so it is important to be aware that large institutions are in the market to make profits.
In financial markets, a party with greater power and better information can obtain two advantages: bargaining power and the possibility of having an informational advantage, which allows them to obtain alpha at the expense of their clients. This is known as front running. By having a complete orderbook of previously categorized clients, it is possible to have a clear view of where markets are heading, giving an advantage over other participants and allowing better decisions to be made.
Liquidity providers offer reduced spreads and abundant liquidity in exchange for information that allows them to have a more accurate perspective of the current estimate of future volatility in the market. This prevents volatility from spiking due to increased uncertainty about liquidity itself.
Although some banks have been accused of practices such as front running and price manipulation, the SEC has established regulations to prevent these practices. Liquidity providers also help in the price discovery process, synthetically reducing spreads so that traders can execute their trades and obtain more information.
Liquidity Analysis
In a market with normal conditions, liquidity is omnipresent across all social strata. The monetary policy expansion carried out by the Federal Reserve of the United States of America, which could be considered the largest organized crime syndicate in history (ironically legal), has contributed to a lower appreciation of risk by market participants.
This translates into cheaper loans, which has made previously unprofitable projects and investments now attractive to investors. If interest rates are at 5%, investors will tend to move away from long-term investments and high-risk projects, opting to invest in assets needed to pay the lowest possible amount for financing.
Investing in products close to consumption is avoided. Liquidity is one of the main regulators in an economy. When liquidity is not a problem, competition between market makers is minimized.
If we analyze the variation of the bid-ask spread in any asset during all market phases, we can determine the real risk and flexibility of participants. Based on the idea that the market is a system formed by different agents with different objectives, each participant contributes in some way to the microstructure, affecting price and liquidity.
Market makers are algorithms that allow determining the price of different products, calculating the fair price based on the buy and sell volumes of the assets.
Conclusion
In summary, volatility is an essential phenomenon in financial markets that can be affected by numerous factors. Understanding these concepts and the importance of liquidity and information asymmetry can help investors make more informed decisions and minimize unnecessary risks.
This article is just the beginning of a series that will delve into the more technical and practical aspects of volatility in financial markets. Stay tuned for more!
