Quantitative trading - page 28
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Rajib Ranjan Borah at POC2015 - Trade Options and be ahead of the markets
Rajib Ranjan Borah at POC2015 - Trade Options and be ahead of the markets
Contents:
Momentum Based Strategies for Low and High Frequency Trading | Webinar
Momentum Based Strategies for Low and High Frequency Trading | Webinar
This webinar focused on the various aspects of Momentum Trading Strategies for both Conventional/Low Frequency as well as High Frequency (HFT). Some popular strategies in momentum based trading were also dug deeper into to select niche momentum trading strategies. The webinar aimed to evaluate how HFT momentum strategies differ from conventional momentum strategies both from logic and deployment perspective.
Points discussed in detail:
[WEBINAR] Changing Notions of Risk Management in Current Markets
[WEBINAR] Changing Notions of Risk Management in Current Markets
In this video Mr. Rajib Borah, Director and Faculty at QuantInsti, talks about a few major risk oversight issues in algorithmic trading, like:
Nitesh Khandelwal at POC2015 - Trade Futures and be ahead of the markets
Nitesh Khandelwal at POC2015 - Trade Futures and be ahead of the markets
Nitesh Khandelwal delivers an overview of futures and options trading, emphasizing that futures are financial instruments whose value depends on the price of an underlying financial instrument. He differentiates between futures, which are standardized contracts traded on exchanges, and forwards, which are traded on the over-the-counter market. Khandelwal highlights the various participants in futures trading, including hedgers, speculators, and arbitrageurs, and explains how each group can benefit from engaging in futures trading. The pricing of futures contracts and the modeling of trading strategies using futures are also discussed.
Moving on, Khandelwal delves into the types of market participants in the futures market, namely hedgers, arbitrageurs, and speculators. Hedgers utilize futures contracts to safeguard themselves against potential price increases in the physical market, effectively minimizing their risk. Arbitrageurs seek profit opportunities by exploiting price discrepancies between different exchanges, while speculators participate in futures trading solely to capitalize on price fluctuations. Khandelwal proceeds to define two essential characteristics of futures markets: the spot price, which represents the underlying asset's current price, and the contract or lot size, which specifies the predetermined size of the futures contract.
The concept of futures trading is then explained, with Khandelwal highlighting that futures contracts come in various sizes and have expiration dates. Settlements can be made in cash or through cross settlements, with cash settlements being the most common. Margins are used to initiate and maintain positions, and each asset has specific margin requirements based on price expectations. Futures trading allows for substantial leverage, as only a small percentage of the underlying asset's value is required to take a position. However, this also increases the risk for traders and clearinghouses, especially during periods of extreme market volatility.
Delivery aspects in futures trading are discussed, as certain contracts can be deliverable while others cannot. Commodities and stock futures can be delivered, but index futures cannot, as indices are merely numerical representations without a physical counterpart. During delivery, the exchange provides a list of accepted parameters for the underlying asset to ensure quality standards. Khandelwal underscores the advantages of trading futures, such as the ability to leverage positions by paying a margin instead of the full asset price and the wider range of trading strategies available compared to the cash market.
Khandelwal then explores the benefits of trading futures over cash markets, including enhanced liquidity for larger quantities and a fair and transparent price discovery process at different points in time. He explains that futures prices are determined by various factors, including spot prices, the date of expiry, risk-free rates of return, storage and delivery costs, and the convenience yield. The convenience yield represents the price businesses are willing to pay to possess an asset physically, thereby avoiding supply and demand issues and potential delivery defaults upon expiry.
The speaker provides insights into the concept of convenience yield, particularly in relation to investable assets like gold, where physical ownership is often preferred due to its symbolic value. A formula for calculating the expected price of equity futures or index futures is presented, taking into account the current spot price and the potential return from investing the money elsewhere. Storage costs and convenience yield, reflecting the premium investors are willing to pay to hold the physical asset, are also factored into the equation. Khandelwal notes that rational investors consider convenience yield when formulating their market views.
The concept of cash-future strategy is introduced, which involves trading in both cash and futures in opposite directions to generate profits. This strategy requires sufficient liquidity in the cash market for the stocks being held and access to mechanisms for delivery if shorting is allowed. However, Khandelwal advises caution regarding the high returns observed in short cash and long futures positions, as the feasibility of such options depends on the available delivery mechanisms.
Factors affecting the volatility of spreads as the expiration date approaches are explained by Khandelwal. These include the lack of returns during the zero period, potential erratic spreads due to delivery mechanisms during futures delivery, the impact of prevailing interest rates, and market sentiment during periods of high volatility or news announcements that can cause swift price movements. Two spread trading strategies are discussed: calendar spreads, which are highly effective and offer risk-free opportunities on the spot market, and intermarket spreads, which involve arbitrage or statistical arbitrage across different but related asset classes.
Khandelwal delves into the analysis of correlations between different asset classes, such as commodities, equities, and currencies. He highlights that movements in one instrument can indicate potential movements in others, although the direct or inverse correlation depends on thorough analysis. Correlations can also exist within the same asset class, as exemplified by the inverse relationship between food prices and gold prices. Market sentiment and fundamental analysis play crucial roles for investors in taking positions based on these correlations. Khandelwal introduces interexchange spreads, which can be pure arbitrage or statistical arbitrage, depending on their connection to each other, even if they do not belong to precisely the same asset class.
Nitesh Khandelwal further discusses the importance of understanding correlations between different asset classes in trading. By recognizing the relationships between commodities, equities, or currencies, traders can gain valuable insights into potential market movements. When one instrument experiences a shift, there is a likelihood of similar movement in related assets. However, the nature of the correlation, whether direct or inverse, depends on in-depth analysis and market conditions. Khandelwal emphasizes that correlations can also exist within the same asset class, as demonstrated by the inverse relationship between food prices and gold prices. This type of correlation indicates the market sentiment and provides opportunities for fundamental analysis-based positions.
Additionally, Khandelwal introduces the concept of interexchange spreads, which involve trading strategies that exploit price discrepancies between different exchanges. These spreads can be categorized as pure arbitrage or statistical arbitrage, depending on the nature of the connection between the involved assets. Despite not belonging to the same asset class, interexchange spreads offer opportunities for profit if traders can identify and capitalize on the pricing disparities.
Nitesh Khandelwal's comprehensive overview of futures and options trading covers essential aspects such as the participants in the futures market, characteristics of futures contracts, trading strategies, pricing factors, convenience yield, spread volatility, correlations between asset classes, and interexchange spreads. By understanding these concepts and their interplay, traders can make informed decisions and potentially optimize their trading strategies in the dynamic and ever-changing financial markets.
Webinar Topic: A sneak peek into Artificial Intelligence based HFT Trading Strategies
Webinar Topic: A sneak peek into Artificial Intelligence based HFT Trading Strategies
This video is a recording of our Webinar on "A sneak peek into Artificial Intelligence based HFT Trading Strategies" conducted by QuantInsti on 27th February, 2015.
In this video Mr. Sameer Kumar, Director and Faculty at QuantInsti, How machine learning techniques can help us design better trading strategies. He will cover alpha in trading and how we can extract it by applying the knowledge about the market structure and order flow. He will also explain how to use machine learning for predicting asset paths. Watch the video to understand the high frequency trading and using Artificial Intelligence for trading.
Sameer graduated from BITS Pilani with Masters in Economics and Information Systems. He started his career with Yahoo! where he gained expertise in technical architecture, design and development of highly scalable systems. A C++ evangelist and Perl poet with broad understanding of economics and market dynamics, he now designs and builds financial strategies with built-in intelligence. He leads the infrastructure development team along with the low latency programming division at iRageCapital Advisory Private Ltd.
At QuantInsti, he shares his experience on low latency systems as well as strategies involving artificial intelligence.
Algorithmic Trading in Different Geographies
Algorithmic Trading in Different Geographies
In this video, Mr. Rajib Ranjan Borah, co-Founder QuantInsti & iRageCapital Advisory, compares algorithmic trading in different geographic across the globe. He shares his insights and experience of algorithmic trading across the major exchanges in Asia Pacific (APAC), Europe & Middle East (EMEA) and the Americas. The presentation has data of volumes of equity and options traded in more than 30 exchanges monthly and annually.
Order book dynamics in High Frequency Trading
Order book dynamics in High Frequency Trading
This Webinar on "Order book dynamics in High Frequency Trading" conducted by QuantInsti. In this video Mr. Gaurav Raizada, Director and Faculty at QuantInsti explains - How execution algorithms provide a price which is between Limit Order Execution and Market Order Execution.
An important task of high-frequency trading is to successfully capture the dynamics in the Data. Empirical Data on Indian Exchanges show that 95% of all NEW orders are placed within 5 ticks of best-bid and best-ask.
The Quantinsti® Replacement Matrix shows that most of the orders that are being replaced are among the top 3 levels and these replacements allow us to visualize and generalize about market behaviour. This matrix gives a visual representation of the cost metrics and replacement behaviour.
Financial Markets Microstructure course (Masters in Economics, UCPH, Spring 2020) - Lecture 1: Concepts and Institutions (Financial Markets Microstructure)
Lecture 1: Concepts and Institutions (Financial Markets Microstructure)
The instructor begins by setting the stage for the financial markets microstructure course, explaining that the lectures were primarily conducted as live streams and uploaded to YouTube due to the COVID-19 pandemic. The recordings, along with the slides, problem sets, and reading list, can be accessed on the instructor's personal website. The course heavily relies on a textbook authored by Terry Foucault, Marco Pagano, and Ilse Hoyle. Viewers are advised to start at lecture 11 if they prefer to skip material that can be easily read in the textbook. The introductory video establishes the course as a study of financial markets and aims to provide a comprehensive understanding of their functioning.
The concept of markets is introduced as institutions where property rights are exchanged, and people engage in trading activities. The main objective of studying markets is to ensure the efficient allocation of property rights and that market transactions contribute to the overall increase in social welfare. Financial markets, specifically, are highlighted as a distinct type of market that facilitates the trading of financial assets such as stocks, bonds, and derivatives. The purpose of investing in these assets is either to reallocate wealth over time or to navigate various contingencies or outcomes.
The instructor explains the concept of financial assets and how they serve as a means to transfer wealth across different time periods and contingencies. An example is given, illustrating how investing in renewable energy companies can help mitigate potential job losses in the coal industry if renewable energy becomes more prevalent. The video emphasizes that financial markets involve asymmetric information, where different market participants possess varying degrees of knowledge about different prospects of the world. The instructor also discusses the institutional details specific to financial markets and highlights their purpose of facilitating profitable trades between agents with opposing desires.
The multiple values of financial markets are then explored, focusing on their role as platforms for traders to compare their private evaluations and aggregate dispersed information. Financial markets also provide a degree of security. The distinction between primary and secondary markets is explained. Primary markets enable the allocation of savings to investments, with the final user of the money ensuring that it works to fulfill financial promises. In contrast, secondary markets serve the purpose of reallocating investments among savers, allowing trades between different owners and potential holders of assets on fixed platforms like exchanges.
The video specifically emphasizes secondary markets, such as stock markets, bond markets, derivatives markets, currency or foreign exchange markets, and commodity markets that function as derivative markets. It states that understanding market efficiency and the process of price formation are crucial aspects addressed in the course. The role of traders' behavior and the environment they operate in, as well as how they act on their information in comparison to the broader market, will be examined to understand the microstructure of financial markets.
The course is presented as utilizing different methods and approaches to answer questions related to market organization, design, and policy issues. Real-world markets will be discussed, and the knowledge gained will be used to build theories for analyzing policies within the framework of these institutions. Additionally, the course will touch upon empirical issues related to applying these theories and concepts to real-life data.
Prerequisites for the course are outlined, including a basic understanding of finance, microeconomics, game theory, and mathematics. While the course primarily focuses on rational models in finance, students are encouraged to explore the complementary field of behavioral finance. The section then delves into the fundamental concept of prices and how it differs from the idealized model of market prices without arbitrage.
The video explains the concept of bid-ask spreads and how they violate the law of one price in financial markets. It clarifies that in nearly all financial markets, there exist two prices: the bid price and the ask price. The difference between these prices is known as the bid-ask spread, which typically ensures the absence of arbitrage. However, bid-ask spreads can create inefficiencies in the market, resulting in less efficient market outcomes. The investigation of market efficiency is closely linked to the study of bid-ask spreads. The lecturer draws a parallel between bid-ask spreads and the difference in prices when buying or selling foreign currency, providing real-world examples to enhance understanding.
The video further explains that actual trading prices differ from the idealized market prices, as the former are forward-looking while the latter are backward-looking, often representing the price of the last trade. The fundamental value of a stock is described as arising from the future income streams it can generate, such as dividends or price appreciation. This value is influenced by managerial decisions within the company. The course aims to analyze how this fundamental value translates into market prices and whether prices accurately reflect it. The concept of price discovery is introduced, focusing on how quickly new information about the fundamental value is incorporated into market prices.
The lecturer proceeds to discuss how prices and asset allocations are established within the microstructure of financial markets. It is emphasized that not all agents seeking to trade a particular asset are present in the market simultaneously, leading to limited supply and demand at any given time. These limitations can result in temporary imbalances, which can impact the market price in the short term. However, the price eventually returns to its long-run level once the imbalance is resolved. Analyzing these market imbalances is crucial for determining the degree to which prices reflect the fundamental value and the speed at which they incorporate relevant information.
The concept of liquidity and its relationship to market depth is then explored. Liquidity refers to the market's ability to facilitate the sale of an asset quickly without significantly impacting its price. A more liquid market is characterized by a greater number of buyers and sellers, reducing the impact of individual orders on the price. Market depth, on the other hand, measures the amount of order volume required to cause a fixed price change. The lecturer highlights the importance of understanding liquidity and market depth for traders, as they affect the prices they receive for their trades. Liquidity can also influence the fundamental value of an asset. In the subsequent lecture, the measurement of liquidity will be discussed.
The concept of market depth is further examined, referring to the potential volume of buy and sell orders beyond the best quote visible in the market. Understanding market depth enables traders to gauge the extent to which their trades can impact market movement without causing significant price fluctuations. The video provides a broad overview of two types of financial markets: order-driven markets, where orders are submitted to a common limit order book, and dealer markets, where trades are facilitated through a centralized intermediary. The lecture delves into the sub-categories of each market type, including continuous markets and call auctions.
The lecturer elaborates on the dimensions that differentiate order-driven markets from one another. One such dimension is order precedence, wherein the highest bidder receives priority in buying. In case of two buyers offering the same amount, time priority is followed, giving priority to the order that was submitted first. Another dimension is price interval, where discriminatory pricing allows different trades to occur at different prices, rather than enforcing a single market price. Furthermore, markets differ in their trading day's beginning and end, with pre-trade call auctions potentially taking place before continuous trading commences. These concepts and institutions are essential for understanding the microstructure of financial markets.
The lecturer goes on to discuss how markets have opening and closing hours, along with specific trading rules that can vary across different exchanges. Limit orders, which are submitted to a limit order book, remain there until suitable trading opportunities arise. In contrast, market orders are executed immediately at the best available price. Patient traders tend to use limit orders, while impatient traders opt for market orders, depleting the limit order book. The pricing mechanism in markets is often discriminatory and depends on the timing of trades.
Two types of financial markets are then introduced: continuous limit or book exchanges and call auctions. Continuous limit or book exchanges, such as the New York Stock Exchange and the London Stock Exchange, are popular market structures where trading occurs through a limit order book. On the other hand, call auctions involve trades happening at specific intervals, and the price for the trade is determined to maximize the number of executed orders. However, call auctions have their drawbacks, including slower trading times and the absence of impatient traders, which can have long-lasting effects. Examples of call auction exchanges include Nasdaq, LSE, and Euronext, which may operate in parallel with continuous trading for certain assets.
Moving on, the lecturer explains the distinction between order-driven markets and dealer markets. In dealer markets, a central intermediary known as a market maker or dealer buys assets from sellers and sells them to buyers, setting prices that balance supply and demand. Dealers profit by quoting positive bid-ask spreads, but they must also compete with other dealers by narrowing their bid-ask spreads enough to attract business while generating sufficient trading profits. Exchanges are the most regulated and formalized markets, while alternative trading systems and multilateral trading facilities are less regulated and formal.
The video then delves into the comparison between exchanges and over-the-counter (OTC) trading, which represent two distinct types of financial markets. Exchanges provide a range of services, including security, clearing and settlement services, liquidity, stability, and transparency. On the other hand, OTC trading refers to transactions that are not conducted through exchanges but are still highly formalized platforms. However, OTC platforms may require less financial disclosure compared to major exchanges. While reduced transparency is a trade-off, it comes with corresponding benefits. Additionally, the existence of dark pools of liquidity is mentioned. These are internal platforms that enable large investment banks to match orders from their clients internally. The video notes that markets can differ in various dimensions and examines the factors that should be considered when comparing these markets.
The speaker addresses different perspectives on financial market microstructure. From a regulator's standpoint, ensuring competition on all sides of the market is crucial for achieving efficient allocation. Traders, on the other hand, prioritize liquidity, transparency, and information availability in the market to determine the optimal value for their assets. The speaker identifies three groups of agents in the market: retail investors, institutional investors, and for-profit traders. Retail investors are often amateurs, while institutional investors are professionals who are compensated for devising optimal trading strategies.
The video proceeds by discussing the various types of investors in financial markets, distinguishing between informed and uninformed traders. Informed traders possess private information that is not accessible to the rest of the market, while uninformed traders have the same information about asset value as the overall market. Brokers are introduced as intermediaries who facilitate orders between traders and investors. The video briefly touches upon conflicts of interest between traders and brokers and explores the role of regulation in achieving efficient market outcomes.
The lecturer moves on to explore the different goals of financial markets, which include protecting uninformed traders against insider trading, ensuring price discovery and efficiency, and stabilizing the market during sudden shocks. Selecting the optimal trading structure for various types of assets is also essential. Methods to achieve these goals encompass requiring interaction between fragmented markets, imposing transaction taxes or subsidies, mandating collateral, regulating algorithmic and high-frequency trading, and overseeing competition between exchanges. The trade-off between liquidity and natural monopoly must be considered, as excessive fragmentation can hinder the goals of the markets.
The video delves into how platforms can enhance the terms of trade for traders and the potential benefits of increased competition among exchanges. Statistics on different stock exchanges worldwide are presented, highlighting the concentration of exchanges in the US compared to Asia and Europe. The lecturer poses open questions for regulators regarding market structure and emphasizes the significance of comprehensive analysis in addressing the trade-offs associated with market design.
In conclusion, this lecture provides an overview of financial market microstructure, discussing concepts such as bid-ask spreads, price discovery, liquidity, market depth, and different market types. The speaker also touches upon the roles of various market participants, the distinction between exchanges and OTC trading, and the goals of financial markets. Understanding these concepts and structures is crucial for comprehending the dynamics of financial markets and designing efficient market systems that balance the interests of traders, investors, and regulators.
Stochastic Market Microstructure Models of Limit Order Books
Stochastic Market Microstructure Models of Limit Order Books
During the lecture, the speaker explains the process of executing a large trade order through an algorithm designed to achieve optimal execution quality. When a trader submits an order, it is sent to a trading engine that breaks it down into smaller blocks. These smaller order chunks are then sent into the market, which includes various venues such as exchanges and dark pools. To execute the order successfully, traders must decide where to route it. The market participants involved in the trading process include institutional investors, market makers, retail flow, and opportunistic or active liquidity providers.
Executing large orders can be challenging due to the limited liquidity available in the market. To mitigate the impact on prices and minimize information leakage, large orders are chopped into smaller chunks and executed over time. Market makers, on the other hand, have a different role as intermediaries, providing liquidity and avoiding adverse selection.
To trade a large position effectively, traders need to make market variable forecasts, such as bid-ask spread, volatility, market depth, and available liquidity. They also solve an optimization problem that guides them in sequencing their trades. The execution of small order chunks is carried out by a micro trader, who aims to minimize the impact on the market during each five-minute slice.
The lecturer further discusses the behavior of volumes, volatility, spreads, and liquidity in the S&P 500 security universe throughout the trading day. They observe that volumes exhibit a small spike at the beginning of the day due to news and then flatten out until increased activity occurs towards the end of the day. Volatility, on the other hand, tends to be high at the start of the day due to overnight news but gradually decreases as the day progresses. Spreads, which represent the difference between bid and ask prices, are wider in the morning due to uncertainty but narrow as the day unfolds. Liquidity follows a similar pattern, increasing towards the end of the day and decreasing at the beginning due to concerns about large position exposure.
The lecture also delves into the concept of a limit order book, which represents the queue of orders at different price levels. Each price level in the order book operates on a first-come, first-served basis, allowing orders to trade against arriving market orders. The lecturer explains that the structure of a limit order book creates a queuing control problem, and they highlight some of the challenges that arise in this context.
The speaker emphasizes the significance of stochastic modeling and multi-class queues for understanding high-dimensional systems with strategic interactions between market participants. Visual representations of the limit order books in the S&P 500 are showcased to illustrate the difference between trading rates and the number of limit orders placed and cancelled at the top prices.
The lecture continues by discussing inter-arrival times between events in a limit order book, focusing on trade frequency and cancellations. The speaker notes that these events do not occur randomly but exhibit predictable behavior, such as spikes every half a second for certain algorithms. Confidence intervals are used to check the stationary parameters of the system, indicating that the parameters typically change within five to ten minutes.
Waiting times in the limit order book are typically in the range of 1 to 100 seconds, suggesting that modeling should consider short horizons due to the difficulty of predicting parameter changes in the book. The tick period is also mentioned as being comparable to the queuing delay, highlighting the importance of modeling cancellations, which occur at a higher rate than trading. The lecturer suggests incorporating trading strategies and mathematical devices to capture jumps or bursts of events in the limit order book.
The lecture further explores the behavior of trades in limit order books, particularly when large orders are executed, resulting in instantaneous and simultaneous trades. The speaker emphasizes the importance of decomposing orders and rolling up trades to understand the different types of trades and their dependence on the state of the book. The modeling of cancellations, including exponential or state-dependent approaches, is also discussed, highlighting the tradeoffs between tractability and realism.
The lecture dives into the heterogeneous behavior of market participants in the queuing context. Some market participants constantly monitor the market and exit quickly when something seems unsettling, while others rely on alarms to send orders. The speaker suggests modeling this heterogeneity to estimate the length of time it takes for an order to be executed. This control problem and its queuing implications are deemed essential in algorithmic execution systems.
Estimating the waiting time for an order to get a trade is a crucial aspect of order placement. The speaker presents two methods: a simple calculation that disregards cancellation rates and a more sophisticated method that models cancellation rates. The latter approach involves solving a logarithmic formula that estimates how long it takes for the queue length to be depleted. The two methods are tested on an actual dataset of orders placed by an algorithmic trading system.
The lecture also addresses the biases in stochastic market microstructure models, pointing out that certain assumptions can lead to incorrect estimates. The use of exponential alarm clock models, for example, can be overly optimistic as they assume everyone cancels ahead of the trader. Disregarding cancellations altogether is also problematic, as different cancellation methods exist in the market. The speaker suggests modeling cancellations as a stopping time to account for the impact of market makers and other traders on cancel rates.
To achieve more accurate results, the speaker presents a model that estimates the number of market participants with alarm clocks and those who cancel orders when the queue length becomes small. By incorporating heterogeneity in the behavior of orders within the queue, more precise estimations can be obtained. The lecture highlights the importance of modeling heterogeneity in trading systems, distinguishing it as a novel aspect compared to queuing models studied in other settings. Characterizing queuing behavior is deemed important and plays a crucial role in algorithmic trading systems. The next section of the lecture will focus on routing and diffusion approximations.
The speaker explores the application of heavy traffic approximations in modeling the dynamics of limit order books at high frequencies. This approach allows for analytical approximations that are more manageable compared to discrete models. By treating the limit order book as a queuing system, it becomes possible to estimate waiting time distributions and rates while maintaining analytical tractability. The speaker emphasizes the wide range of time scales involved in the problem, from ultra-high frequencies to daily time scales, and highlights the importance of developing models that can be applied to different applications, such as optimal trade execution.
Building upon the previous discussion, the speaker describes how familiar techniques from heavy traffic limits of queues can be used to derive effective quantities on larger time scales. The focus is placed on the best queues, which have the highest bids and the lowest asks, to understand price dynamics. The rest of the order book is treated as a stationary reservoir of liquidity. Whenever the liquidity in the best queue is depleted, a new value is drawn from the distribution of the size of the next best queue. The bid-ask spread is assumed to be tight and equal to one tick for liquid stocks. The dynamics of the price are entirely determined by the interaction between the two best queues and the hitting times.
In the lecture, the speaker discusses a queuing model that incorporates the arrival and cancellation of orders while also considering price changes. The model assumes a diffusion scaling limit and features a covariance matrix that incorporates the variance of order sizes per unit time and the correlation between the order flow at the bid and ask. The queues exhibit diffusive behavior as long as they are not depleted. However, when a queue gets depleted, the price either increases or decreases. The price dynamics are modeled as a discrete process that jumps by one unit at the hitting time of the ask or bid queue. This model is particularly useful for analyzing high-frequency trading and exhibits interesting properties, such as diffusive dynamics interrupted by discontinuous reflections.
The lecture highlights that the diffusion limit allows for the computation of practically anything, even when starting from a complex discrete model. The duration between price changes can be characterized by a closed-form distribution, enabling precise price forecasting based on the orders in the queue. Additionally, a second diffusion limit is discussed, which explains that while the price undergoes discrete jumps at hitting times, it exhibits diffusive dynamics at longer time scales, such as daily or hourly. The lecture concludes by presenting a formula that expresses volatility in terms of features extracted from order flow. This formula can be tested against the empirical standard deviation of stocks in the S&P 500, showing good agreement.
The lecture acknowledges that there are numerous extensions and more sophisticated models beyond the basic two-queue model. These extensions include state-dependent arrival rates, explicit modeling of the next best queues, and more complex approaches such as modeling the entire order book or utilizing stochastic partial differential equations to model the order book as a density. While these models may be intricate, they can yield explicit formulas for various quantities of interest and provide analytical insights into the relationship between liquidity and price behavior in financial markets.
Lecture 2: Measuring Liquidity (Financial Markets Microstructure)
Lecture 2: Measuring Liquidity (Financial Markets Microstructure)
In the lecture, the concept of liquidity is introduced and defined as the market's ability to facilitate the quick sale of an asset without significantly reducing its price. Liquidity is seen as a characteristic of the market that determines how easy it is to trade in a particular market, and it can vary depending on the type of asset or the specific market being examined. The lecturer also mentions two other types of liquidity: monetary liquidity and funding liquidity, which are interconnected with the broader concept of liquidity.
The lecturer explains the importance of liquidity in relation to market efficiency. Liquidity affects the efficient allocation of assets in the economy. When a market is illiquid, it results in an inefficient allocation where extra costs are incurred to buy or sell items without significantly impacting their prices. This inefficiency limits access to assets for willing buyers and hampers market efficiency. Regulators are concerned about market efficiency and stability, and liquidity serves as a measure to assess market efficiency and identify inefficiencies. Therefore, reducing market illiquidity becomes a crucial goal for regulators.
The concept of liquidity is further explored, distinguishing between the fair price and the efficient price in a perfectly liquid market. Illiquidity can indicate structural issues in the market that may require regulatory intervention to address the inefficiencies. Market depth, which measures the amount that must be traded to move a price by a certain amount, is discussed as an important indicator of liquidity. The lecturer notes that liquidity is not constant over time and often decreases during times of adversity. The ideal scenario would be for markets to be more efficient during crisis times when assets need to be quickly exchanged.
Different measures to quantify liquidity in financial markets are introduced. These measures include spread measures, price measures, and non-trading measures. The lecturer demonstrates their application using a dataset from Krispy Kreme stock. The importance of accurately estimating liquidity is emphasized, and the lecturer explains that prices can sometimes fall within the spread. This occurrence can be attributed to hidden limit orders and individual price improvements offered by dealers.
The lecture delves into specific measures of liquidity, such as the quoted spread, normalized quoted spread, effective spread, normalized effective half spread, and realized spread. The quoted spread, which is the difference between the ask and bid prices, can be misleading, leading to the use of the normalized quoted spread, which considers the average price of the asset in the market. The effective spread, which takes into account the actual execution prices of transactions, is regarded as a better measure of liquidity. It captures the price improvements that occur in the market during transactions, providing a more reliable indicator. The normalized effective half spread and the effective spread offer a more consistent representation of spread behavior in the market. The realized spread measures the cost of taking a given position in an asset, incorporating the mid-quote with a delay to allow prices to adjust to new information.
The relationship between liquidity, transaction prices, and the mid-quote is discussed. The lecture explains how transaction prices and the mid-quote interact when an investor places a buy order at the ask price. The subsequent trade can cause the transaction price to remain the same or increase, depending on the next order being a sell order or another buy order. The lecture highlights the negative covariance between changes in the direction of trade, indicating that trade directions are mean-reverting.
Other measures of liquidity, such as price impact coefficient, bid-ask bounce, and volume-weighted average price (VWAP), are introduced. These measures provide insights into market liquidity and microstructures. The lecture emphasizes the need for careful application of these measures based on the level of data aggregation.
The lecture concludes by summarizing the different measures of liquidity and their variations based on data requirements and specific goals. It emphasizes that liquidity is not a static concept and can change throughout the trading day, with significant impacts during major events. The lecturer provides exercises for viewers to practice, including recreating figures and examining the implementation shortfall in the textbook. A link to an article comparing corporate bond markets to equity markets is shared to illustrate the differences in liquidity due to market structures. The next lecture is announced to focus on analyzing the determinants of the spread and illiquidity in the market.