Lecture

Trading Strategies: Measuring Market Dynamics

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In course

FIN-525: Financial big data

The course introduces modern methods to acquire, clean, and analyze large quantities of financial data efficiently. The second part expands on how to apply these techniques and robust statistics to financial analysis, in particular to intraday data and inv ...

Description

This lecture delves into the definition of trading strategies in mathematical finance, emphasizing the transformation of raw returns into new assets. It explores the role of strategies in biasing price returns and provides examples of buy and hold strategies. The lecture discusses the scientific model behind trading strategies, the process of backtesting, and the challenges of testing strategies in non-stationary markets. It also covers the concepts of mean-reversion versus trend following in US equities and the importance of assessing and replicating fund performance. The lecture concludes with a critical analysis of fitting wrong models to financial data and the implications of overfitting strategies on the S&P 500.

Instructor

Damien Challet

Teaching & PhD Courses Financial big data FIN-525 The course introduces modern methods to acquire, clean, and analyze large quantities of financial data efficiently. The second part expands on how to apply these techniques and robust statistics to financial analysis, in particular to intraday data and investment strategies.

Official source

Related concepts (32)

Trading strategy

In finance, a trading strategy is a fixed plan that is designed to achieve a profitable return by going long or short in markets. The main reasons that a properly researched trading strategy helps are its verifiability, quantifiability, consistency, and objectivity. For every trading strategy one needs to define assets to trade, entry/exit points and money management rules. Bad money management can make a potentially profitable strategy unprofitable. Trading strategies are based on fundamental or technical analysis, or both.

Mathematical finance

Mathematical finance, also known as quantitative finance and financial mathematics, is a field of applied mathematics, concerned with mathematical modeling of financial markets. In general, there exist two separate branches of finance that require advanced quantitative techniques: derivatives pricing on the one hand, and risk and portfolio management on the other. Mathematical finance overlaps heavily with the fields of computational finance and financial engineering.

Hedge fund

A hedge fund is a pooled investment fund that trades in relatively liquid assets and is able to make extensive use of more complex trading, portfolio-construction, and risk management techniques in an attempt to improve performance, such as short selling, leverage, and derivatives. Financial regulators generally restrict hedge fund marketing to institutional investors, high net worth individuals, and accredited investors. Hedge funds are considered alternative investments.

Investment fund

An investment fund is a way of investing money alongside other investors in order to benefit from the inherent advantages of working as part of a group such as reducing the risks of the investment by a significant percentage. These advantages include an ability to: hire professional investment managers, who may offer better returns and more adequate risk management; benefit from economies of scale, i.e., lower transaction costs; increase the asset diversification to reduce some unsystematic risk.

Trend following

Trend following or trend trading is a trading strategy according to which one should buy an asset when its price trend goes up, and sell when its trend goes down, expecting price movements to continue. There are a number of different techniques, calculations and time-frames that may be used to determine the general direction of the market to generate a trade signal, including the current market price calculation, moving averages and channel breakouts.

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