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Summary: Quantiative Finance And Algorithmic Trading
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Read the summary and the most important questions on Quantiative Finance and Algorithmic Trading
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Efficiently inefficient markets: trading strategies vs. Finance Theory
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Financial theory tells us what the price of stocks and bonds should be, What if the market price is different. The price could be wrong
Model is wrong or market is wrong what to do? -
Abreu & brunnermeier(2002) tells us that an arbritageur trades if
Expected benefits ( hazard rate =prob thatmispricing will be away soon) * gains (correcting misspricing ) MUST BE HIGHER > Expected costs = (1 - hazard rate ) * Holding cost ( lending fees, margin calls, time ) -
But sometimes it is even better to trade in the direction of the mispricing?
It can be more profitable to ride bubble than to gain from misspricing -
What is a Hedge fund?
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What is a hedge fund give a difinitions?
A hedge is an investment to reduce the risk of adverse price movements in asset -
How do you beat the market
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What are the profit sources of a hedge fund?
COMPENSATION FOR LIQUIDITY RISK
- market liquidity risk
-funding liquidity risk
- providing liquidity to demand pressure
COMPENSATION FOR INFORMATION
- production of information
- access to information
- news that travel slowly -
How do you beat the market in practice? What are the three strategies
- Equity strategies, A) discretionary long short equity, short bias, quant equity
- Macro strategies, B) Global Macro, managed Futures
- Arbitrage Strategies C) Fixed income, convertible bond, event driven -
Equity strategies --> equity Long/Short
-Discretionary trading
-Fundamental analysis
-It's easy to be contrarian except whn it's profitable
- buy on rumors, sell on news -
Understading market efficiency
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What is the weak form of market efficiency.
- Prices reflect information about past prices.
-information set = all historical security prices -
What is the consequence of weak?
That technical analysis is of no value! Not even momentum. -
objectives, fees and performance
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What are the props and cons of quant trading against discretionary trading
Props are that it's: disciplinary, way more data can be analyzed, but computers are not good in breaking a rule. You can easily backtest our ideas.
- But there are dangers, for example fat fingers that there is a lot of price pressure and at and algoritmes are gowing to sell.
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