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Questions and Answers
What is a 'many-one function'?
What is a 'many-one function'?
- A function where multiple elements from set A map to the same element in set B. (correct)
- A function where each element from set A maps to multiple elements in set B.
- A function where each element in set A maps to a unique element in set B.
- A function where no two elements in set A map to the same element in set B.
What is the range of an Onto function?
What is the range of an Onto function?
- An empty set.
- Always smaller than codomain.
- Always larger than co-domain.
- Equal to its co-domain. (correct)
What defines an 'into' function?
What defines an 'into' function?
- The codomain is equal to its range.
- The codomain is a proper subset of its range.
- The domain and the codomain are equal
- The codomain is not equal to the range. (correct)
What is the graphical test to check if a function is one-one onto?
What is the graphical test to check if a function is one-one onto?
What does $f(f(x)) = x$ imply?
What does $f(f(x)) = x$ imply?
In a many-one function, what is the relationship between elements?
In a many-one function, what is the relationship between elements?
What is the condition for a function to be considered 'onto'?
What is the condition for a function to be considered 'onto'?
Graphically, how can you identify an 'into' function?
Graphically, how can you identify an 'into' function?
What happens if $R = {(x,y) : x, y \text{ divisible by } 2}$?
What happens if $R = {(x,y) : x, y \text{ divisible by } 2}$?
What is the number of remainders of $R = {(x,y) : x, y \text{ divisible by } 2}$?
What is the number of remainders of $R = {(x,y) : x, y \text{ divisible by } 2}$?
Flashcards
Many-one function
Many-one function
More than one element from set A maps to a single element in set B.
Onto function
Onto function
Every element 'y' in set B has a corresponding element 'x' in set A such that y = f(x). The range equals the co-domain.
Into function
Into function
A function which is not surjective (onto). The co-domain of 'f' is not equal to the range of 'f'.
Graphical test for One-One Onto
Graphical test for One-One Onto
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Number of Onto functions
Number of Onto functions
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Involution Property
Involution Property
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Study Notes
- Algorithmic trading uses computer programs to execute orders based on predefined rules.
- It exploits computer speed and automation for efficient, effective trading.
Why Algorithmic Trading?
- Computers react faster than humans.
- It reduces manual errors.
- Algorithms execute exactly as programmed.
- Strategies can be tested on historical data.
- It handles intricate strategies beyond human capability.
- Executes large orders without market impact.
Types of Algorithmic Trading Strategies
Execution Algorithms
- Minimizes market impact and transaction costs.
- VWAP (Volume Weighted Average Price) targets the average price weighted by volume.
- VWAP = (sum of (Price at transaction i * Volume at transaction i)) / (sum of Volume at transaction i).
- TWAP (Time Weighted Average Price) targets the average price over a period.
- TWAP = (sum of Price at time i) / (Number of prices)
- Percentage of Volume (POV) participates in a fixed percentage of market volume.
- Implementation Shortfall balances the cost of delay vs. the cost of immediacy.
Market Making
- Profits from bid-ask spreads while providing liquidity.
- Posts bid and ask orders, capturing the spread.
- Faces challenges in inventory management and adverse selection.
Statistical Arbitrage
- Exploits statistical mispricings.
- Pairs Trading identifies correlated assets and trades on temporary divergence.
- Index Arbitrage exploits price differences between an index and its constituent stocks.
Trend Following
- Identifies and capitalizes on price trends.
- Uses technical indicators to detect trends and place orders accordingly.
- Moving Averages involve buying when the price crosses above a moving average and selling when it crosses below.
High-Frequency Trading (HFT)
- Exploits very short-term market inefficiencies.
- It is characterized by high speed, high turnover, and co-location.
- Strategies includes; order anticipation, quote stuffing, and arbitrage.
- Is subject to market manipulation and unfair advantage controversies.
Order Execution
Order Types
- Market Order executes immediately at the best available price.
- Limit Order executes only at a specified price or better.
- Stop Order becomes a market order when the stop price is reached.
- Stop-Limit Order becomes a limit order when the stop price is reached.
- Hidden (Iceberg) Order displays only a portion of the order to reduce market impact.
- Fill or Kill (FOK) executes the entire order immediately or cancels it.
- Immediate or Cancel (IOC) executes any portion of the order immediately and cancels the rest.
- All or None (AON) executes the entire order at once, if possible.
Order Placement Considerations
- Higher market liquidity reduces the risk of large price movements.
- Larger orders require more careful execution strategies.
- Short-term vs. long-term goals influence strategy selection.
- Risk tolerance affects the aggressiveness of the execution.
- Volatility, news events, and economic indicators affect strategy.
Market Microstructure
- Market Microstructure is the fine-grained details of how a market operates.
- Key elements; Order Book, Quote Sizes, Tick Size and Market Participants.
- Order Book is defined as a list of outstanding buy and sell orders.
- Quote Sizes is defined as the number of shares available at each price level.
- Tick Size is defined as the minimum price increment.
- Market Participants are different types of traders .
Impact of Algorithmic Trading on Market Microstructure
- It provides liquidity and narrow spreads which increases liquidity.
- Efficient execution lowers costs, which reduces transaction costs.
- HFT can exacerbate price swings, which increases volatility.
- Rapid order execution can trigger sudden market drops, which leads to flash crashes.
- Order flow is spread across multiple exchanges and dark pools, which leads to market fragmentation.
Dark Pools
- Dark Pools are the private exchanges where orders are matched anonymously.
- Dark Pools allow institutions to trade large blocks of shares without revealing their intentions.
- Dark Pools reduce market impact and price discovery which is an advantage.
- Dark Pools lack transparency and have potential for abuse which is a disadvantage.
Regulatory Considerations
- Regulations prohibit strategies that artificially inflate or deflate prices, which is market manipulation.
- Illegal to trade on non-public information, which is insider trading.
- Regulators require exchanges to disseminate market data to increase order book transparency.
- Brokers must seek the most favorable terms for their clients to attain best execution.
- SEC Rule 611 and Market Access Rule are examples of regulatory considerations.
- SEC Rule 611 (Order Protection Rule) requires brokers to route orders to the exchange with the best price.
- Market Access Rule (Rule 15c3-5) requires brokers to have risk management controls in place for algorithmic trading.
Challenges and Risks
- The risk that the algorithm is based on flawed assumptions is Model Risk.
- Software bugs or hardware failures cause technical glitches.
- Inaccurate or incomplete data can lead to poor decisions, which are data errors.
- Strategies that perform well in backtesting may fail in live trading, which is Overfitting.
- Strategies must be adapted to evolving market conditions because of changing market dynamics.
- New rules can render strategies obsolete, which causes regulatory changes.
Best Practices
- Test strategies on a variety of historical data using Robust Backtesting.
- Implement controls to limit potential losses using Risk Management.
- Continuously monitor performance and adjust strategies as needed using Monitoring.
- Stay up-to-date with regulatory requirements to ensure compliance.
- Document the logic and assumptions behind the algorithm to ensure transparency.
- Have strategies reviewed by an independent party to ensure independent review.
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