{"id":61690,"date":"2026-06-29T21:41:45","date_gmt":"2026-06-29T13:41:45","guid":{"rendered":"https:\/\/nightfame.com\/style\/?p=61690"},"modified":"2026-07-01T21:36:39","modified_gmt":"2026-07-01T13:36:39","slug":"chapter-3-the-twap-solution-the-time-weighted-average-price-trap","status":"publish","type":"post","link":"https:\/\/nightfame.com\/style\/chapter-3-the-twap-solution-the-time-weighted-average-price-trap\/","title":{"rendered":"Chapter 3: The TWAP Solution – The Time-Weighted Average Price Trap"},"content":{"rendered":"
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The break room on the eighteenth floor was an oasis of calm in the midst of the trading floor’s relentless chaos. Soft ambient lighting replaced the harsh glare of workstation monitors. Plush blue couches were arranged in conversational clusters around low glass tables. A state-of-the-art coffee machine hummed quietly in the corner, its surface gleaming under the warm light.<\/p>\n\n\n\n

At 12:27 PM, the room was mostly empty. Most traders ate at their desks, too consumed by the market’s movements to take a proper break. But today, two figures sat hunched over a small table near the windows, their attention focused on the glowing screen of a laptop.<\/p>\n\n\n\n

Kiran Patel had arrived first, as he always did. At sixteen, he was the youngest person in the research division, but his age was rarely mentioned\u2014his work spoke for itself. He had a slender build and dark hair that fell across his forehead in a perpetual state of dishevelment, as if he’d been running his fingers through it while thinking. His eyes, however, were sharp and focused, scanning the data on his screen with an intensity that belied his youth.<\/p>\n\n\n\n

He wore a simple button-down shirt, untucked, the sleeves rolled up to his elbows. A lanyard with his company badge hung around his neck, the photo showing a younger, more awkward version of himself. His laptop was covered in stickers\u2014a testament to his various interests in cryptography, market analysis, and competitive programming.<\/p>\n\n\n\n

Jaya arrived at 12:31, slightly out of breath from rushing through the trading floor. She carried her own laptop under one arm and a folder stuffed with printouts in the other. Her face was flushed, and there was a sheen of perspiration on her forehead.<\/p>\n\n\n\n

“Sorry I’m late,” she said, sliding into the chair across from Kiran. “I had to document a few more trades before I could step away.”<\/p>\n\n\n\n

Kiran waved off her apology. “Don’t worry about it. I’ve been tracking your order flow all morning. I have more than enough data to work with.”<\/p>\n\n\n\n

Jaya set down her laptop and opened it, the screen flickering to life. “I’ve been gathering my own data too. I want to make sure we’re seeing the same thing.”<\/p>\n\n\n\n

Kiran nodded approvingly. “Good. The more data we have, the clearer the picture becomes.”<\/p>\n\n\n\n

He turned his laptop to face her, and Jaya leaned forward to study the screen. The display showed a detailed analysis of the AETH order book, overlaid with Jaya’s trade history. Green and red lines crisscrossed the chart, marking the moments when her orders had executed and the price movements that surrounded them.<\/p>\n\n\n\n

“Okay,” Kiran began, his voice taking on a teaching cadence. “Let me show you what I’ve found.”<\/p>\n\n\n\n

He pointed to the first section of the chart. “Here’s your first hour of trading\u20148:00 AM to 9:00 AM. Your TWAP executed sixty orders, each one 13,333 units, at one-minute intervals. The price impact during this period was minimal, and your average fill price was 42.52 units.”<\/p>\n\n\n\n

Jaya nodded. “That was the best hour. Everything seemed to be working perfectly.”<\/p>\n\n\n\n

“Exactly,” Kiran said. “And that’s when the bot noticed you.”<\/p>\n\n\n\n

He scrolled to the next section, the period from 9:00 AM to 10:00 AM. “Here’s where things start to change. At 9:00 AM, I started seeing the first signs of a pattern. Small sell orders\u20141,000 to 2,000 units\u2014beginning to appear in the order book approximately two seconds before each of your TWAP executions.”<\/p>\n\n\n\n

Jaya leaned closer to the screen. “I saw that too. I thought it was just market noise at first, but when I looked at the tick-by-tick data, the pattern was unmistakable.”<\/p>\n\n\n\n

Kiran nodded. “It’s not noise. It’s the bot’s signature. Here’s how it works.”<\/p>\n\n\n\n

He pulled up another window, this one showing a schematic diagram. “The bot is an automated trading algorithm that’s been designed specifically to exploit predictable order flow. It monitors the market in real-time, analyzing every trade, every order book update, every price movement. When it detects a pattern\u2014like a TWAP executing at regular intervals\u2014it springs into action.”<\/p>\n\n\n\n

Jaya watched the diagram animate, showing the bot’s thought process. “It identifies my pattern, then sells ahead of me to push the price down. Then it buys back at the bottom after my order fills.”<\/p>\n\n\n\n

“Exactly,” Kiran confirmed. “The bot uses small orders to create a temporary price dip. The dip is small enough that it doesn’t trigger any alarms, but large enough to shift your execution price. You sell at the bottom of the dip, the bot buys at the bottom, and then the price recovers. The bot captures the spread\u2014the difference between the price it bought at and the price it sold at.”<\/p>\n\n\n\n

Jaya’s mind raced as the mechanics became clear. “So the bot doesn’t need to hold a position for long. It just needs to be there for a few seconds around my execution.”<\/p>\n\n\n\n

“Precisely,” Kiran said. “That’s what makes it so effective. It’s not trying to predict the market’s overall direction. It’s just exploiting a temporary price dislocation that it creates itself.”<\/p>\n\n\n\n

Jaya sat back, absorbing the full scope of the exploitation. “How much is it making from me?”<\/p>\n\n\n\n

Kiran pulled up another spreadsheet. “I’ve calculated the total cost. From 9:00 AM to 11:00 AM, the bot executed approximately 150 front-running trades, each one generating a profit of about 0.06 units per token. That’s a total of 1,200,000 units in profits.”<\/p>\n\n\n\n

Jaya felt the blood drain from her face. “One point two million units? In two hours?”<\/p>\n\n\n\n

Kiran nodded grimly. “And that’s just the front-running profits. The bot also profits from the market impact it creates\u2014the broader price effects that ripple through the market. When you add those in, the total cost is even higher.”<\/p>\n\n\n\n

Jaya stared at the screen, her mind reeling. She had known the bot was costing her money, but she hadn’t realized the scale of the damage. Over a million units in just two hours. And she still had six hours of trading left.<\/p>\n\n\n\n

“I had no idea it was this bad,” she whispered. “I thought the slippage was just normal market fluctuation.”<\/p>\n\n\n\n

Kiran shook his head. “Normal market fluctuation doesn’t have this kind of pattern. Look at the timing\u2014every single trade, exactly the same pattern. That’s not coincidence. That’s exploitation.”<\/p>\n\n\n\n

He paused, allowing the information to sink in. Then he continued, his voice softer. “The bot is designed to be invisible. It uses tiny orders, timed perfectly, that blend into the market’s natural noise. Most traders never notice it’s happening. But once you know what to look for, the pattern becomes obvious.”<\/p>\n\n\n\n

Jaya looked at him, a mixture of frustration and admiration in her eyes. “How do you know so much about this?”<\/p>\n\n\n\n

Kiran shrugged modestly. “It’s my job. I study market microstructure\u2014how algorithms interact with the market and with each other. The Predator Bot is one of the most sophisticated algorithms I’ve seen. It’s been active for months, targeting predictable order flow across multiple tokens and exchanges.”<\/p>\n\n\n\n

“The Predator Bot?” Jaya asked. “That’s what you call it?”<\/p>\n\n\n\n

Kiran nodded. “It’s not an official name. It’s just what I call it in my research. It’s a perfect description, though\u2014it’s a predator, and it’s hunting.”<\/p>\n\n\n\n

Jaya felt a chill run down her spine. The image of an invisible predator, stalking her through the market, was unsettling. But it was also motivating. She refused to be prey.<\/p>\n\n\n\n

“Okay,” she said, her voice firming. “Now that I know what’s happening, how do I stop it?”<\/p>\n\n\n\n

Kiran leaned forward, his eyes gleaming with enthusiasm. “That’s the question I’ve been waiting for. The answer is simple, but implementing it is complex.”<\/p>\n\n\n\n

He turned his laptop back toward himself and pulled up a new screen. “The bot is designed to exploit predictability. It looks for patterns, and when it finds them, it exploits them. So the solution is to become unpredictable.”<\/p>\n\n\n\n

Jaya frowned. “But how? The TWAP is inherently predictable. That’s the whole point\u2014it executes at regular intervals to minimize market impact.”<\/p>\n\n\n\n

“Exactly,” Kiran said. “The TWAP’s strength is also its weakness. The consistency that makes it effective also makes it exploitable. So we need to break that consistency.”<\/p>\n\n\n\n

He pulled up a diagram showing different types of execution strategies. “There are several ways to do this. We can randomize the timing of your orders, so the bot can’t predict when you’ll trade. We can randomize the size of your orders, so the bot can’t predict how much you’ll trade. Or we can use a completely different strategy\u2014like VWAP, which bases your trades on market volume rather than time.”<\/p>\n\n\n\n

Jaya studied the diagram, her mind working through the possibilities. “Randomization sounds promising. But won’t the bot just adapt? If I randomize my orders, it might find a new pattern to exploit.”<\/p>\n\n\n\n

Kiran nodded approvingly. “That’s the right question to ask. The answer is yes\u2014the bot will adapt. But we can stay one step ahead by using a truly random system. Something that even the bot can’t predict.”<\/p>\n\n\n\n

Jaya raised an eyebrow. “What do you mean by ‘truly random’?”<\/p>\n\n\n\n

Kiran’s smile widened. “A verifiable random function. VRF for short. It’s a cryptographic system that generates random numbers in a way that’s both unpredictable and verifiable. No one\u2014not you, not me, not the bot\u2014can predict what the next number will be. But once it’s generated, we can prove that it was generated fairly.”<\/p>\n\n\n\n

Jaya’s eyes lit up with understanding. “So I could use a VRF to generate random times and sizes for my orders. The bot wouldn’t be able to predict the pattern, but I could prove to the firm that I wasn’t just trading randomly.”<\/p>\n\n\n\n

“Exactly,” Kiran said. “It’s the best of both worlds\u2014unpredictability for the market, but accountability for the firm.”<\/p>\n\n\n\n

Jaya felt a surge of excitement. This was the solution she had been looking for. But even as she imagined the possibilities, a practical concern surfaced.<\/p>\n\n\n\n

“How long would it take to implement?” she asked. “I have to finish my liquidation by the end of the day. I don’t have time for a complex setup.”<\/p>\n\n\n\n

Kiran waved her concern away. “I’ve already built the system. I’ve been working on a VRF-based execution engine for months, testing it in simulations. It’s ready to go.”<\/p>\n\n\n\n

Jaya stared at him, stunned. “You built it already? Why?”<\/p>\n\n\n\n

Kiran shrugged, a hint of self-consciousness in his expression. “I knew the Predator Bot existed. I knew it was a threat. I wanted to be ready when someone needed to fight back. I just didn’t know that someone would be you.”<\/p>\n\n\n\n

Jaya felt a wave of gratitude wash over her. This was more than just research for Kiran\u2014it was preparation. He had been anticipating this moment, building the tools to counter the bot’s exploitation. And now, those tools were available to her.<\/p>\n\n\n\n

“Show me how it works,” she said.<\/p>\n\n\n\n

Kiran nodded and turned his laptop toward her. On the screen was a clean, well-designed interface. At the top, a field labeled “Seed” displayed a long string of random characters. Below that were controls for “Order Frequency,” “Order Size Range,” and “Execution Venue.”<\/p>\n\n\n\n

“The VRF generates random numbers based on a secret key,” Kiran explained. “You’re the only one who knows the key, so no one else can predict the sequence. The system uses those numbers to determine when to place your orders and how large they should be.”<\/p>\n\n\n\n

He demonstrated by clicking a button labeled “Generate Next Order.” A new window appeared, displaying a random time\u20142 minutes and 17 seconds from now\u2014and a random size\u201414,821 units.<\/p>\n\n\n\n

“The bot has no way to predict this,” Kiran said. “It can watch the market for hours, but it won’t see a pattern. It won’t know when the next order is coming, or how large it will be. And by the time the order appears, it’s too late for the bot to react.”<\/p>\n\n\n\n

Jaya studied the interface, her mind racing. The system was elegant in its simplicity. It took the core idea of the TWAP\u2014splitting a large order into smaller pieces\u2014but added an element of unpredictability that made exploitation impossible.<\/p>\n\n\n\n

“This is brilliant,” she said. “How quickly can we set it up for my position?”<\/p>\n\n\n\n

Kiran smiled. “Give me five minutes to configure it. I just need your remaining position size and your target execution time.”<\/p>\n\n\n\n

Jaya pulled up her execution summary on her own laptop. “I’ve sold 2.4 million units so far. That leaves 5.6 million units. I need to finish by 6:00 PM, which gives us about six hours.”<\/p>\n\n\n\n

Kiran nodded, typing furiously. “I’ll set the system to execute between 80,000 and 120,000 units per hour, broken into random chunks. That should keep the market impact low while making the bot’s job impossible.”<\/p>\n\n\n\n

Jaya felt a weight lifting from her shoulders. For the first time since the morning, she felt like she had a fighting chance.<\/p>\n\n\n\n

“One more question,” she said. “Why are you helping me? You could have just sent me your research and let me figure it out myself.”<\/p>\n\n\n\n

Kiran paused, his fingers hovering over the keyboard. He looked at her with an expression that was both serious and warm.<\/p>\n\n\n\n

“Because this isn’t just about you,” he said. “The Predator Bot is a threat to the whole market. Every time it exploits a trader, it erodes trust in the system. The more traders who know how to fight back, the less effective the bot becomes.”<\/p>\n\n\n\n

He resumed typing, but continued speaking. “I’ve been studying this bot for months. I’ve seen it exploit dozens of traders, and I’ve seen what it does to them. Some of them quit trading altogether. Some of them lost their jobs. Some of them just gave up.”<\/p>\n\n\n\n

He looked up at her, his eyes fierce. “You didn’t give up. You saw the pattern, you asked for help, and you’re ready to fight back. That’s exactly the kind of trader I want to help.”<\/p>\n\n\n\n

Jaya felt a lump form in her throat. She had come to Kiran looking for a technical solution, but she was leaving with something more\u2014a sense of purpose, a feeling that she was part of something bigger than her own position.<\/p>\n\n\n\n

“Thank you,” she said, her voice quiet but sincere.<\/p>\n\n\n\n

Kiran smiled and turned his laptop back toward her. “The system is configured. I’ll transfer the control interface to your terminal. Once you activate it, your TWAP will be replaced by the VRF-based randomization.”<\/p>\n\n\n\n

Jaya reached for her laptop, but Kiran held up a hand.<\/p>\n\n\n\n

“Wait,” he said. “Before you go, there’s one more thing you should know.”<\/p>\n\n\n\n

Jaya froze, her heart sinking. “What is it?”<\/p>\n\n\n\n

Kiran’s expression grew serious. “The randomization will stop the bot from front-running your individual trades. But the bot is smart\u2014it will adapt. It might try to exploit you in other ways. It might try to predict your overall execution rate, or use macro-level data to anticipate your trades.”<\/p>\n\n\n\n

Jaya nodded slowly. “I understand. This isn’t a perfect solution. It’s just the first step.”<\/p>\n\n\n\n

Kiran smiled approvingly. “Exactly. We’re going to have to stay ahead of the bot. But this will buy us time\u2014and it will make the bot work harder to exploit you.”<\/p>\n\n\n\n

He handed her a small card with a QR code on it. “This is the configuration file for the VRF system. Scan it on your terminal, and it’ll install automatically.”<\/p>\n\n\n\n

Jaya took the card, examining it carefully. “How do I know when to use it?”<\/p>\n\n\n\n

“Anytime,” Kiran said. “The bot will adapt eventually, but the VRF system can generate new random sequences on demand. You can change the seed whenever you want, making it impossible for the bot to learn the pattern.”<\/p>\n\n\n\n

Jaya stood up, her laptop tucked under her arm. “I’ll activate it right away. Thank you, Kiran. I owe you.”<\/p>\n\n\n\n

Kiran waved her gratitude away. “You don’t owe me anything. Just beat the bot. That’s all the thanks I need.”<\/p>\n\n\n\n

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Jaya walked back to her workstation with a new sense of purpose. The break room conversation had been a revelation\u2014not just about the bot, but about the nature of the market itself. She had learned that predictability was vulnerability, and that the only way to survive was to adapt.<\/p>\n\n\n\n

She settled into her chair and scanned the QR code on her laptop. A window appeared, asking for confirmation. She clicked “Install,” and within seconds, the VRF-based execution system was integrated into her terminal.<\/p>\n\n\n\n

The interface was clean and intuitive. A large button labeled “Activate Randomization” dominated the center of the screen, flanked by fields showing her remaining position and the current random seed.<\/p>\n\n\n\n

Jaya took a deep breath. This was it. The moment she would abandon the TWAP that had seemed so perfect, so elegant, just hours ago.<\/p>\n\n\n\n

She clicked “Activate Randomization.”<\/p>\n\n\n\n

The screen flashed, and a new set of parameters appeared. The system had generated a random sequence of orders for the next hour, each one with a unique time and size. The first order was scheduled for 1:47 PM, just over a minute away, with a size of 14,200 units.<\/p>\n\n\n\n

Jaya watched the countdown timer tick down. 10 seconds… 5 seconds… 3… 2… 1…<\/p>\n\n\n\n

The order executed at exactly 1:47:00, filling at 42.48 units. Jaya watched the order book for any sign of the bot’s manipulation. Nothing. The price was stable, the order filled cleanly, and the bot’s small sell orders were nowhere to be seen.<\/p>\n\n\n\n

Jaya let out a breath she hadn’t realized she’d been holding. “It worked,” she whispered. “It actually worked.”<\/p>\n\n\n\n

She checked her execution log. The order had filled at 42.48 units, which was actually above the current market average of 42.45. For the first time in hours, she had gotten a good fill.<\/p>\n\n\n\n

The next random order was scheduled for 1:53 PM, with a size of 12,800 units. Again, the execution was clean, filling at 42.50 units. No manipulation, no front-running, no exploitation.<\/p>\n\n\n\n

Jaya’s excitement grew with each successful order. At 2:01 PM, 15,300 units filled at 42.52. At 2:09 PM, 13,400 units filled at 42.49. Every order executed smoothly, with no sign of the bot’s interference.<\/p>\n\n\n\n

By 3:00 PM, Jaya had executed an additional 400,000 units through the randomization system. Her average fill price was 42.50 units, and the slippage had dropped from 0.7% to 0.3%.<\/p>\n\n\n\n

She was back on track.<\/p>\n\n\n\n

As the afternoon wore on, Jaya continued to monitor her execution with growing confidence. The bot was still active\u2014she could see its footprint in the order book, the occasional small orders that appeared and disappeared\u2014but it was no longer able to exploit her individual trades. The randomization had broken its predictive power.<\/p>\n\n\n\n

Jaya made a note in her execution log: “3:15 PM \u2013 Randomization active for 90 minutes. 580,000 units sold. Average fill price 42.51. Slippage 0.28%. No evidence of front-running. The bot is still present but unable to exploit.”<\/p>\n\n\n\n

She leaned back in her chair, allowing herself a moment of satisfaction. The day had been a rollercoaster of emotions\u2014from confidence to confusion, from despair to determination. But she had found a solution, and she had executed it successfully.<\/p>\n\n\n\n

She looked across the trading floor and saw Kiran at his desk, hunched over his own laptop. He looked up and caught her eye, a small smile playing on his lips. He gave her a thumbs up.<\/p>\n\n\n\n

Jaya returned the gesture, a wide smile spreading across her face. She had done it. With Kiran’s help, she had beaten the Predator Bot.<\/p>\n\n\n\n

But even as she celebrated her victory, Jaya knew the battle wasn’t over. The bot was still out there, watching, learning, adapting. It would find new ways to exploit her, new patterns to detect. The randomization was a powerful tool, but it wasn’t a permanent solution.<\/p>\n\n\n\n

She would need to stay ahead. She would need to keep evolving. The bot was patient, but she could be patient too.<\/p>\n\n\n\n

For now, though, she allowed herself to enjoy the moment. She had faced a formidable adversary and emerged victorious. And that was worth celebrating.<\/p>\n\n\n\n

Jaya turned back to her screens, her fingers flying across the keyboard as she continued her execution. The sun was beginning to set outside the windows, casting long shadows across the trading floor. The market was winding down, the final hours of trading stretching ahead of her.<\/p>\n\n\n\n

She had come a long way since that morning, when she had set up her TWAP with such confidence. The TWAP had been a good tool\u2014simple, elegant, effective\u2014but it had also been predictable, and predictability was a vulnerability.<\/p>\n\n\n\n

The randomization was better. It was more complex, more demanding, but it was also more secure. It forced her to think creatively, to adapt to changing circumstances, to stay one step ahead of the predators.<\/p>\n\n\n\n

Jaya smiled as she placed her next random order. She was ready for whatever the bot threw at her next.<\/p>\n\n\n\n

\n\n\n\n

The market closed at 6:00 PM, and Jaya completed her liquidation with a total slippage of just 0.25%. It was an exceptional result, given the challenges she had faced.<\/p>\n\n\n\n

She stood up, stretched her tired muscles, and walked over to Kiran’s desk. He was packing up his things, preparing to leave for the day.<\/p>\n\n\n\n

“Great work today,” Kiran said as she approached. “You handled that like a pro.”<\/p>\n\n\n\n

Jaya smiled. “I couldn’t have done it without you. Your VRF system was brilliant.”<\/p>\n\n\n\n

Kiran shrugged modestly. “It’s just a tool. You were the one who used it effectively. You recognized the pattern, you asked for help, and you made the right decisions under pressure. That’s what matters.”<\/p>\n\n\n\n

Jaya nodded, grateful for his words. “What happens tomorrow?” she asked. “Will the bot be back?”<\/p>\n\n\n\n

Kiran considered the question. “It will adapt. It’s designed to learn from its failures. It might try to find a new pattern to exploit, or it might use different tactics.”<\/p>\n\n\n\n

“But you’ll be ready for it?” Jaya asked.<\/p>\n\n\n\n

Kiran smiled. “We’ll be ready for it.”<\/p>\n\n\n\n

He paused, studying her with an appraising look. “You know, you handled this better than most experienced traders. You didn’t panic when you saw the pattern. You didn’t ignore it. You faced it head-on.”<\/p>\n\n\n\n

Jaya felt a flush of pride. “I had good help.”<\/p>\n\n\n\n

Kiran nodded. “That’s part of it. But the other part is you. You’re smart, you’re analytical, and you’re not afraid to change course when you need to. Those are the qualities of a great trader.”<\/p>\n\n\n\n

Jaya was quiet for a moment, absorbing his words. Then she said, “I want to learn more about market microstructure. I want to understand how these algorithms work and how to counter them.”<\/p>\n\n\n\n

Kiran’s eyes lit up. “I’d be happy to teach you. We can start tomorrow, if you want.”<\/p>\n\n\n\n

Jaya nodded, a new sense of purpose filling her. The Predator Bot had been a formidable adversary, but she had survived. And now, she was determined to understand the battlefield better\u2014to learn the terrain, to study the enemy, to become a master of the game.<\/p>\n\n\n\n

“Tomorrow it is,” she said.<\/p>\n\n\n\n

Kiran smiled and picked up his laptop. “See you then, Jaya.”<\/p>\n\n\n\n

She watched him walk away, his slight frame disappearing into the elevator. Then she turned back to her own desk, her mind already racing with new questions, new possibilities.<\/p>\n\n\n\n

The day had been a trial by fire, but she had emerged stronger. The TWAP solution had been a wake-up call, a lesson in the dangers of predictability. The randomization had been her salvation, a testament to the power of innovation and collaboration.<\/p>\n\n\n\n

She gathered her things and headed for the door. Tomorrow would bring new challenges, but she was ready. She had learned the most important lesson of all: in the world of algorithmic trading, the only constant was change. And the only way to survive was to keep evolving.<\/p>\n\n\n\n

Table of contents:<\/em><\/strong>
Introduction<\/a>
Chapter 1: The Large Order<\/a>
Chapter 2: A Slippage Problem<\/a>
Chapter 3: The TWAP Solution<\/a>
Chapter 4: The Predictable Pattern<\/a> <<<<<< NEXT<\/strong>
Chapter 5: The Front-Running TWAP<\/a>
Chapter 6: The Chunking Attack<\/a>
Chapter 7: The Randomization Fix<\/a>
Chapter 8: The Volume-Weighted Alternative<\/a>
Chapter 9: The Hidden Liquidity<\/a>
Chapter 10: Trading Smart, Not Predictable<\/a><\/p>\n

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The break room on the eighteenth floor was an oasis of calm in the midst […]<\/p>\n

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